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Photoperiod and vernalization gene effects in Southern Australian wheat

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Abstract

Photoperiod and vernalization genes are important for the optimal adaptation of wheat to different environments. Diagnostic markers are now available for Vrn-A1, Vrn-B1, Vrn-D1 and Ppd-D1, with all four genes variable in southern Australian wheat-breeding programs. To estimate the effects of these genes on days to heading we used data from 128 field experiments spanning 24 years. From an analysis of 1085 homozygous cultivars and breeding lines, allelic variation for these four genes accounted for similar to 45% of the genotypic variance for days to heading. In the presence of the photoperiod-insensitive allele of Ppd-D1, differences between the winter genotype and genotypes with a spring allele at one of the genes ranged from 3.5 days for Vrn-B1 to 4.9 days for Vrn-D1. Smaller differences occurred between genotypes with a spring allele at one of the Vrn genes and those with spring alleles at two of the three genes. The shortest time to heading occurred for genotypes with spring alleles at both Vrn-A1 and Vrn-D1. Differences between the photoperiod-sensitive and insensitive alleles of Ppd-D1 depended on the genotype of the vernalization genes, being greatest when three spring alleles were present (11.8 days) and least when the only spring allele was at Vrn-B1 (3.7 days). Because of these epistatic interactions, for the practical purposes of using these genes for cross prediction and marker-assisted selection we concluded that using combinations of alleles of genes simultaneously would be preferable to summing effects of individual genes. The spring alleles of the vernalization genes responded differently to the accumulation of vernalizing temperatures, with the common spring allele of Vrn-A1 showing the least response, and the spring allele of Vrn-D1 showing a response that was similar to, but less than, a winter genotype.

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... More recently, Eagles et al. (2010) have related days to heading to the allelic composition (for Ppd-D1 and Vrn-A1, Vrn-B1 and Vrn-D1 only) of 1085 genotypes across 128 late April to early July sowings at many sites in south-eastern Australia (latitude 34-378S). There were 8524 observations in this unbalanced dataset, from which allelic effects on days to heading were estimated for an early June sowing. ...
... Finally the photoperiod-sensitive allele (Ppd-D1 b) was estimated to delay heading on average 7 days compared to the insensitive one (Ppd-D1 a), an effect which was greatest in fully vernalisation-insensitive genotypes (aaa, 11.8 days). Eagles et al. (2010) has been highlighted because it shows the way forward: the value of more exactly identifying key alleles, and the power of modern statistics for deducing patterns from complex unbalanced data. But the identified alleles explained only 45% of the genetic variance in days to heading (main effect of genotypes), while there was also a genotype  sowing-site variance component equal to 20% of the main effect. ...
... Taking a wider dataset of 24 winter wheat and five spring wheat cultivars grown across 12 years and 82 global locations ranging from latitude 19 to 618 in the International Winter Wheat Performance Nursery, White et al. (2008) had earlier considered the allelic classification at Ppd-D1, Table 1. Alleles of the photoperiod sensitivity gene (Ppd-A1) and the vernalisation genes (Vrn-A1, Vrn-B1, Vrn-D1) in key Australian cultivars (Eagles et al. 2010), as they relate to adaptation to Australia in general, and to Western Australia in particular , and to the Triple Dirk isolines (Pugsley 1968(Pugsley , 1972 Cultivars Genes and alleles Classification Sowing date ...
Article
This review focuses on recent advances in some key areas of wheat physiology, namely phasic development, determination of potential yield and water-limited potential yield, tolerance to some other abiotic stresses (aluminium, salt, heat shock), and simulation modelling. Applications of the new knowledge to breeding and crop agronomy are emphasized. The linking of relatively simple traits like time to flowering, and aluminium and salt tolerance, in each case to a small number of genes, is being greatly facilitated by the development of molecular gene markers, and there is some progress on the functional basis of these links, and likely application in breeding. However with more complex crop features like potential yield, progress at the gene level is negligible, and even that at the level of the physiology of seemingly important component traits (e.g., grain number, grain weight, soil water extraction, sensitivity to water shortage at meiosis) is patchy and generally slow although a few more heritable traits (e.g. carbon isotope discrimination, coleoptile length) are seeing application. This is despite the advent of smart tools for molecular analysis and for phenotyping, and the move to study genetic variation in soundly-constituted populations. Exploring the functional genomics of traits has a poor record of application; while trait validation in breeding appears underinvested. Simulation modeling is helping to unravel G × E interaction for yield, and is beginning to explore genetic variation in traits in this context, but adequate validation is often lacking. Simulation modelling to project agronomic options over time is, however, more successful, and has become an essential tool, probably because less uncertainty surrounds the influence of variable water and climate on the performance of a given cultivar. It is the ever-increasing complexity we are seeing with genetic variation which remains the greatest challenge for modelling, molecular biology, and indeed physiology, as they all seek to progress yield at a rate greater than empirical breeding is achieving.
... Wheat crops are sown in late autumn and early winter and they mature during rising temperatures in late spring and early summer. Vernalisation saturation is usually reached in <50 days and daylength at vernalisation saturation is <12 h (Eagles et al. 2010). Our objective was to assess the effects of Gpc-B1 on grain yield, grain weight and grain protein in this environment, and to determine whether lines containing Gpc-B1 could be developed that were comparable to elite commercial cultivars. ...
... Sowing dates ranged from 4 May to 4 June, which are close to recommended dates for spring cultivars in this part of Australia. Heading dates were recorded at Roseworthy in 2009, 2010 and 2011, and at Horsham and Wagga Wagga in 2010, using methods described in Eagles et al. (2010). Test weights were measured at Roseworthy in 2010 and 2011, and at Arrino, Goomalling and Pinery in 2011. ...
... However, characterisation of alleles of Vrn-B1, as described by Eagles et al. (2009), showed that the line carrying the 'a' allele of Gpc-B1 carried Vrn-B1a, and was the same as VR1128, whereas the line carrying the 'b' allele carried Vrn-B1v, and was the same as Somerset. Hence, this difference was at least partially due to Vrn-B1, a gene known to affect days to heading in southern Australia (Eagles et al. 2010). ...
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The Gpc-B1 gene from wild emmer has been proposed as a potential mechanism for improving grain protein in bread wheat without reducing grain yield. Near-isolines with and without the Gpc-B1 gene in three Australian-adapted genetic backgrounds, Gladius, Wyalkatchem and VR1128, were compared in 14 experiments across the south and west of Australia for grain yield, grain protein content and grain weight. The donor parents of Gpc-B1 were the Canadian cultivars Burnside and Somerset. One of the 14 experiments was discarded because of inadequate rust control and confounding effects of Yr36, a gene closely linked to Gpc-B1. Heading date and test weight were measured in five experiments. Across all comparisons, Gpc-B1 increased grain protein content and reduced grain weight, with a negligible effect on grain yield. Selected lines containing Gpc-B1 in a Wyalkatchem background had comparable grain yields to the elite cultivar Mace, but with significantly higher grain protein contents, slightly higher grain weights, similar heading dates and acceptable test weights. The development of agronomically acceptable lines containing Gpc-B1 was partially attributed to the removal of undesirable genes from wild emmer during the breeding of the Canadian donor parents and the use of Australian recurrent parents with high test weights.
... For photoperiod alleles, primer combinations and amplification conditions as described by Beales et al. (2007) were followed. For multiplexing, PCR was carried out using primers of the dominant and recessive alleles of a gene following Eagles et al. (2010). Amplification products were resolved on 2% Agarose gel using 1 × TBE buffer, stained with Ethidium bromide and visualised on Gel Documentation System (G-Box, SYNGENE Synoptics, USA) under UV transillumination. ...
... Ppd-D1 and Vrn alleles in the cultivars were deduced following multiplex PCR (Figs 1a and 1b) and primer pairs reported by Eagles et al. (2010). The description of individual genotypes possessing a particular allelic combination is depicted in Table S1 and the zonewise distribution of alleles of the six genes is given in Table 2. Majority of the cultivars carried either single or combination of any of the dominant Vrn-A1, Vrn-B1 and Vrn-D1 alleles and having a spring growth habit. ...
... of Vrn-B1 and Vrn-D1 genes were again confirmed by multiplex PCR, following the protocol ofEagles et al. (2010) and are shown inFigures 1c and 1d.The frequency of these Vrn alleles varied across six different agro-ecological zones in India. The Vrn-A1a allele was the most frequent allele present in spring wheat varieties in North-Western Plain Zone (NWPZ) whereas Vrn-B1 allele was mostly identified in North-Eastern Plain Zone (NEPZ) and Peninsular Zone (PZ). ...
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Ninety-nine wheat cultivars from six different agro-climatic zones of India were analyzed for the Vrn-1, Vrn-2, Vrn-B3, Vrn-4 and Ppd-D1 composition with DNA sequenced based allele specific or linked markers for the above-mentioned genes. A majority of the germplasm carried the dominant Vrn-A1a allele alone or in combination with Vrn-B1 and Vrn-D1. The three dominant genes were cumulatively present in 30 cultivars among all the zones, whereas double dominant combination, Vrn-A1/Vrn-B1 was identified in 18 cultivars, Vrn-A1/Vrn-D1 in 6 cvs and Vrn-B1/Vrn-D1 in 16 cvs. The combination of the dominant alleles of all three genes was most frequent in cvs of Northern Western Plains Zone. Northern Hill Zone had vrn-B1 and vrn-D1 alleles in higher proportions compared to the dominant alleles Vrn-B1 and Vrn-D1 indicating successful spring/winter wheat cross breeding. All of the cvs had the recessive Vrn-B3 allele. Most of the cvs had photoperiod insensitive allele in all the zones and only 9% cvs possessed the photoperiod sensitive allele (b) of the Ppd-D1 gene. This information will be useful in selecting parental lines for crossing to maximize diversity at these loci and for future molecular marker assisted breeding for cultivar improvement.
... In order to demonstrate vernalization conditions for each location, cumulative vernalized day degrees were calculated for days from germination employing the method described by Weir et al. (1984) using, however, all available temperature values. Vernalization is best obtained between 3 and 10 • C while temperatures between −4 and 3 • C as well as between 10 and 17 • C result in slower vernalization (Weir et al., 1984;Eagles et al., 2010). For winter wheat, the vernalization requirement can be assumed to be fulfilled when the sum of the accumulated vernalized day degrees has reached 33 vernal days (Weir et al., 1984;Eagles et al., 2010). ...
... Vernalization is best obtained between 3 and 10 • C while temperatures between −4 and 3 • C as well as between 10 and 17 • C result in slower vernalization (Weir et al., 1984;Eagles et al., 2010). For winter wheat, the vernalization requirement can be assumed to be fulfilled when the sum of the accumulated vernalized day degrees has reached 33 vernal days (Weir et al., 1984;Eagles et al., 2010). Days of full vernalization and sum of accumulated vernalized day degrees at January 1st for each location are given in Figure S1B. ...
... Heading date, representing flowering time, was recorded as days after January 1st when 75% of the spikes of an observation plot had emerged to 75% from the flag leaf sheath. Thermal time, often used to more consistently describe the phenological development of plants (Eagles et al., 2010;Rousset et al., 2011;Allard et al., 2012;Cane et al., 2013), was calculated for this time period as the sum of accumulated degree days ( • Cd) which are a function of the daily mean temperature and the base temperature of 0 • C (Weir et al., 1984). ...
Article
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Flowering time is an important trait in wheat breeding as it affects adaptation and yield potential. The aim of this study was to investigate the genetic architecture of flowering time in European winter bread wheat cultivars. To this end a population of 410 winter wheat varieties was evaluated in multi-location field trials and genotyped by a genotyping-by-sequencing approach and candidate gene markers. Our analyses revealed that the photoperiod regulator Ppd-D1 is the major factor affecting flowering time in this germplasm set, explaining 58% of the genotypic variance. Copy number variation at the Ppd-B1 locus was present but explains only 3.2% and thus a comparably small proportion of genotypic variance. By contrast, the plant height loci Rht-B1 and Rht-D1 had no effect on flowering time. The genome-wide scan identified six QTL which each explain only a small proportion of genotypic variance and in addition we identified a number of epistatic QTL, also with small effects. Taken together, our results show that flowering time in European winter bread wheat cultivars is mainly controlled by Ppd-D1 while the fine tuning to local climatic conditions is achieved through Ppd-B1 copy number variation and a larger number of QTL with small effects.
... It was reported that wheat genotypes with all three dominant alleles of Vrn-1 genes (Vrn-A1, Vrn-B1, and Vrn-D1) head quite early compared to mono-or di-dominant gene combinations [28]. Similar information was also reported by various authors [5,9,[57][58][59]. From the results of the above-mentioned studies, it was shown which combinations of alleles perform better than others. ...
... An epistatic interaction between the Vrn-A1 and Vrn-D1 active alleles was demonstrated in a study [9]. The same study confirmed an additive/complementary interaction for flowering time between the photoperiod-insensitive Ppd-D1a allele and the Vrn-1 active alleles [57,60]. Moreover, it was noted that although genotypes carrying Vrn-1 and Ppd-D1a alleles are early flowering under both SD and LD conditions, the flowering time is delayed by low temperatures under SD conditions. ...
... The fact that current wheat germplasm has not been characterized fully in terms of important agronomic traits limits the use of wheat germplasm to a certain extent. Identifying the alleles of these genes and estimating the effects of their combination on growth, heading date, and ultimately grain yield will enhance the selection of cultivars with wide adaptability to a set of environments [57]. This knowledge can help accelerate the introgression of adaptability and yield-contributing genes by predicting the best combinations for enhanced yield potential and adaptation [28]. ...
... The spring (Vrn-D1) and winter (vrn-D1) alleles at the Vrn-D1 locus were distinguished using a single KASP assay (Fu et al. 2005). Spring alleles at the Vrn-A1 locus were not assayed since the dominant Vrn-A1a allele has the most dramatic effect on the development of spring growth habit (Pugsley 1971(Pugsley , 1972Santra et al. 2009;Eagles et al. 2010), and true spring wheat types were not part of the FAWWON collection. ...
... The Mixed Effects model with alleles at Vrn-B1 treated as fixed effects showed slightly reduced prediction accuracy compared to the Random Effects model for Julesburg 2014 (Fig. 2 a), Fort Collins 2015 (Fig. 2b), and Fort Collins 2016 (Fig. 2c). Eagles et al. (2010) reported that spring alleles at the Vrn-1 loci do not reduce heading date equally and that Vrn-B1 confers a smaller effect than Vrn-A1 and Vrn-D1. These results agree with our study, as when treated as a fixed effect, the alleles at Vrn-B1 were not consistently or highly effective in increasing GS prediction accuracy above that observed for the Random Effects model. ...
Article
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Winter survival ability is important for autumn sown winter wheat (Triticum aestivum L.) in regions with cold winters. Wheat vernalization and photoperiod genes influence adaptation by regulating the timing of the transition from vegetative to reproductive growth to protect the floral meristem from cold temperatures. We evaluated winter injury of 287 genotypes from the Facultative and Winter Wheat Observation Nursery (FAWWON) in six field environments over 3 years (2014 to 2016) in Colorado. Entries were genotyped using single-nucleotide polymorphisms (SNPs) obtained by genotyping by sequencing (GBS) and at known vernalization (Vrn-A1, Vrn-B1, and Vrn-D1) and photoperiod (Ppd-B1 and Ppd-D1) loci using Kompetitive Allele Specific PCR (KASP) assays. Winter injury was observed and visually scored in five of the six environments. Mean GS prediction accuracies across the five environments, obtained through ridge regression best linear unbiased prediction (RR-BLUP) using 23,269 SNPs alone as random effects, ranged from 0.26 ± 0.01 to 0.74 ± 0.00. Incorporation of alleles at Vrn-A1, Vrn-B1, and Vrn-D1 loci as fixed effects in the GS models together with GBS markers as random effects provided the highest prediction accuracy with mean GS accuracies ranging from 0.34 ± 0.01 to 0.78 ± 0.00 across the five environments. Genomic selection models incorporating photoperiod alleles as fixed effects rarely improved GS prediction accuracy of winter injury. Genomic selection models that incorporate both major and minor genetic factors that influence low-temperature tolerance improved the model predictions for identifying genotypes that are best adapted to regions where cold winter temperatures are an important production constraint.
... The relative maturities among the varieties were assessed by measuring the days to flower in the plants remaining in the plots used to measure CID. It is recognised that time to flower is strongly influenced by environment, but the main interest for the analysis was the relative rankings of maturities among varieties across experiments, which is quite consistent across sites (Eagles et al. 2010). The ranking of several commonly-grown varieties was also checked against published maturity ratings and these were found to be consistent with the rankings from the field assessment. ...
... The use of genetic information, either in the form of molecular markers, near-isogenic lines, or genotypes that are well characterised for specific traits, is a valuable tool to analyse the importance of different environmental constraints, or the importance of physiological characteristics to yield and adaptation (Brancourt-Hulmel 1999;Mathews et al. 2006Mathews et al. , 2011Eagles et al. 2010). Ideally, perfect markers or isogenic lines would be most useful, but in the absence of such genetic material we based our analysis on the grain yields of genotypes screened for a range of traits that have been associated with yield or adaptation on soils that have some form of subsoil constraint. ...
Article
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Many of the soils in the Australian cereal belt have subsoils with chemical and physical properties that restrict root growth, which limits water use and yield. On alkaline sodic soils salinity, high pH, high available boron (B), deficiencies of zinc (Zn) and manganese (Mn) and high soil strength occur commonly and aluminium (Al) toxicity restricts root growth on acid soils. While the effects of individual subsoil constraints have been studied there is some debate about the relative importance to yield of the different soil stresses across the region. To address this issue yield variation among a set of 52 varieties of bread wheat was analysed using yield data from 233 trials conducted over 12 years. The trials were conducted in all mainland States but the majority were in South Australia and Western Australia. Each variety was characterised for its response to high B, high pH, Al toxicity, salinity, deficiencies in Zn and Mn and resistance to root lesion nematode (Pratylenchus neglectus), root growth through strong soil, seminal root angle, carbon isotope discrimination (CID) and maturity. This data was then used to examine the contribution of each trait to the genetic variation in yield at each of the 233 trials. The contribution of a specific trait to the genetic variation in yield at each site was used to infer the importance of a particular constraint to yield at that site. Of the traits linked to soil constraints, salinity tolerance, (measured by Na+ exclusion) was most often associated with genetic variation in grain yield (34% of all experiments), followed by tolerance to high Al (26%) and B tolerance (21%). Tolerance to low Zn and Mn were not consistently associated with yield variation. However, maturity was the trait that was most frequently associated with yield variation (51% of experiments), although the relative importance of early and late flowering varied among the States. Yield variation was largely associated with early flowering in Western Australia and the relative importance of late flowering increased as trials moved eastward into South Australia, Victoria and New South Wales. Narrow, rather than wide, seminal root angle was more commonly associated with high yield (25% of sites) and there was little evidence of any regional pattern in the importance of root angle. CID was important in 18% of trials with a low CID being most commonly associated with high yields. The yield advantage at sites where a trait contributed significantly to yield variation ranged from similar to 15% for Na+ exclusion and B tolerance to 4% for tolerance to high pH. The analysis has provided an assessment of the relative importance of a range of traits associated with adaptation to environments where subsoil constraints are likely to affect yield and has indicated patterns in the importance and effects of these traits that may be linked to regional variation in rainfall and soils.
... A significant relation has recently been observed between the duration of preanthesis growth phases and the tillering and dry matter accumulation [126]. A detailed study of Australian wheat cultivars over several years and a wide range of locations has revealed that cultivars with one spring allele in any of the three Vrn1 loci are the earliest in heading when compared with cultivars having two spring alleles [127]. Again, spring alleles in all three Vrn1 loci have very small effects in forwarding the heading date, which suggests the presence of epistatic or overdose effects. ...
... In addition, the haplotypes variation identified in other studies for these genes was found to affect several yield-contributing parameters, and thus adaptation to different environments [51,55]. As a result, several attempts have been made to determine the value of the alleles of Vrn1 and Ppd1 genes over the past few years in the local environments of different countries [52,55,68,73,83,84,86,127,128,141]. In most cases, the plant material did not cover all the available alleles present in nature, or even the same allele in different genetic backgrounds. ...
Article
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Wheat grown under rain-fed conditions is often affected by drought worldwide. Future projections from a climate simulation model predict that the combined effects of increasing temperature and changing rainfall patterns will aggravate this drought scenario and may significantly reduce wheat yields unless appropriate varieties are adopted. Wheat is adapted to a wide range of environments due to the diversity in its phenology genes. Wheat phenology offers the opportunity to fight against drought by modifying crop developmental phases according to water availability in target environments. This review summarizes recent advances in wheat phenology research, including vernalization (Vrn), photoperiod (Ppd), and also dwarfing (Rht) genes. The alleles, haplotypes, and copy number variation identified for Vrn and Ppd genes respond differently in different climatic conditions, and thus could alter not only the development phases but also the yield. Compared with the model plant Arabidopsis, more phenology genes have not yet been identified in wheat; quantifying their effects in target environments would benefit the breeding of wheat for improved drought tolerance. Hence, there is scope to maximize yields in water-limited environments by deploying appropriate phenology gene combinations along with Rht genes and other important physiological traits that are associated with drought resistance.
... There is uncertainty in the amount of variation in TTF that can be explained by alleles of the five major development genes described in Table 1, and thus the potential accuracy of GDPE models. In field trials, Eagles et al. (2010) found that cultivars with matching multi-locus genotypes (MLGs) based on alleles at the major gene loci, with the exclusion of Ppd-B1, accounted for 45% of variation in time to heading from an unbalanced dataset. Cane et al. (2013), with the inclusion of Ppd-B1 and additional alleles of Ppd-D1, found 53% of the variation was accounted for with the same dataset. ...
... The proportion of variation explained by allelic variation in the five major development genes in this study is consistent with previous studies conducted in the field (as cited earlier: Eagles et al. 2010;Cane et al. 2013). These data were obtained from 128 field trials across seven sites and 24 years with multiple sowing dates; however, crops were sown much later (30 May-13 June) than farmers would typically sow (Flohr et al. 2017b), which, as described above, would reduce the predictive ability of alleles. ...
Article
Flowering time of wheat (Triticum aestivum L.) is a critical determinant of grain yield. Frost, drought and heat stresses from either overly early or overly late flowering can inflict significant yield penalties. The ability to predict time of flowering from different sowing dates for diverse cultivars across environments in Australia is important for maintaining yield as autumn rainfall events become less reliable. However, currently there are no models that can accurately do this when new cultivars are released. Two major Photoperiod1 and three Vernalisation1 development genes, with alleles identified by molecular markers, are known to be important in regulating phasic development and therefore time to anthesis, in response to the environmental factors of temperature and photoperiod. Allelic information from molecular markers has been used to parameterise models that could predict flowering time, but it is uncertain how much variation in flowering time can be explained by different alleles of the five major genes. This experiment used 13 elite commercial cultivars of wheat, selected for their variation in phenology and in turn allelic variation at the major development genes, and 13 near-isogenic lines (NILs) with matching multi-locus genotypes for the major development genes, to quantify how much response in time to flowering could be explained by alleles of the major genes. Genotypes were grown in four controlled environments at constant temperature of 22°C with factorial photoperiod (long or short day) and vernalisation (±) treatments applied. NILs were able to explain a large proportion of the variation of thermal time to flowering in elite cultivars in the long-day environment with no vernalisation (97%), a moderate amount in the short-day environment with no vernalisation (62%), and less in the short-day (51%) and long-day (47%) environments with vernalisation. Photoperiod was found to accelerate development, as observed in a reduction in phyllochron, thermal time to heading, thermal time to flowering, and decreased final leaf numbers. Vernalisation response was not as great, and rates of development in most genotypes were not significantly increased. The results indicate that the alleles of the five major development genes alone cannot explain enough variation in flowering time to be used to parameterise gene-based models that will be accurate in simulating flowering time under field conditions. Further understanding of the genetics of wheat development, particularly photoperiod response, is required before a model with genetically based parameter estimates can be deployed to assist growers to make sowing-time decisions for new cultivars.
... In APSIM, wheat flowering time is predicted based on temperature, photoperiod and vernalisation, and parameters accounting for these effects seem to have been optimised in those environments. For example, model parameters of the popular cultivar Enterprise Grains Australia (EGA) Gregory, which is less photo-period sensitive 36 , are such that the original APSIM predicts flowering reasonably well for New South Wales sites/sowings, but not so well for Queensland sites/sowings resulting in a poor (0.81) Lin's CCC (Fig. 6a). The default value of photoperiod sensitivity factor for this cultivar in the model is set to 3.2 and vernalisation sensitivity to 2.7. ...
... To predict flowering time, the daily thermal time in the model was reduced by multiplying it with the vernalisation and photoperiod sensitivity factors for a given cultivar (www.apsim.info). Cultivar Gregory released in 2004 for cultivation in Queensland and New South Wales was considered to be relatively photoperiod insensitive 36 , but it has high a photoperiod factor of 3.2 (for 0 to 5 scale) in the model. We hypothesized that if Gregory cultivar is indeed photoperiod insensitive, the high photoperiod sensitivity for this cultivar in the APSIM model could be to account for the effect of soil water on flowering. ...
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Matching crop phenology to environment is essential to improve yield and reduce risk of losses due to extreme temperatures, hence the importance of accurate prediction of flowering time. Empirical evidence suggests that soil water can influence flowering time in chickpea and wheat, but simulation models rarely account for this effect. Adjusting daily thermal time accumulation with fractional available soil water in the 0–60 cm soil layer improved the prediction of flowering time for both chickpea and wheat in comparison to the model simulating flowering time with only temperature and photoperiod. The number of post-flowering frost events accounted for 24% of the variation in observed chickpea yield using a temperature-photoperiod model, and 66% of the variation in yield with a model accounting for top-soil water content. Integrating the effect of soil water content in crop simulation models could improve prediction of flowering time and abiotic stress risk assessment.
... Regions, genotypes and locations contributed to the random part of the mixed model. Due to the large epistatic effects of the photoperiod and vernalisation genes (Eagles et al., 2010;Harris et al., 2017), phenological analysis was performed on combinations of the alleles (genotype code) rather than individual genes. Genotypes with either four (Ppd-D1, Vrn-A1, Vrn-B1 and Vrn-D1) or five (Ppd-B1, Ppd-D1, Vrn-A1, Vrn-B1 and Vrn-D1) allelic combinations were included in the fixed part of the mixed model. ...
... Across all experiments, the 5-allele model improved predictive ability over the 4allele model for determining timing for Sow-TS (1.8 days improvement) and Sow-AN (1.3 days improvement). Eagles et al. (2010) showed that allelic variation for the four genes accounted for 45% of the genotypic variance to heading in a large unbalanced population from wheat breeding programs (Latitude 33.34°S to 36.67°S). With a more precise resolution of Ppd-D1 and the inclusion of Ppd-B1 genotypes, Cane et al. (2013) increased the proportion of variance to 53%. ...
Article
We developed a photoperiod-corrected thermal model that can predict wheat phenology based solely on the combination of photoperiod (Ppd) and vernalisation (Vrn) alleles to identify the phenological suitability of germplasm across the cropping region in southern Australia. More than 200 wheat genotypes that vary in combinations of Ppd and Vrn alleles were grown at 17 locations spanning 11° Latitude, thus providing a wide range in temperature and daylength gradients. The phenological sensitivities of a genotype to varying basic temperature, photoperiod and vernalisation requirement was adjusted via optimisation to minimise the least square difference between the measured and predicted dates of both terminal spike (TS) and flowering (AN). The model predicted dates of TS and AN to within 5 days of the field values. Information was used to identify the alleles required to achieve a wheat ideotype defined in a previous study. The optimum allelic combinations required to target the optimum flowering period for different locations when sown on different dates were also identified. The use of allelic based phenological models has the potential to reduce the costs to breeding programs and accelerate the release of better adapted germplasm to new and changing environments.
... Allelic variation at Ppd-A1 also affects photoperiod sensitivity, however the allelic effects of Ppd-A1 are weaker than Ppd-D1 or Ppd-B1 [17]. The photoperiod and vernalization pathways are integrated and epistatic interactions between photoperiod loci and Vrn1 loci are well characterized [18]. ...
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Heading date in wheat (Triticum aestivum L.) and other small grain cereals is affected by the vernalization and photoperiod pathways. The reduced-height loci also have an effect on growth and development. Heading date, which occurs just prior to anthesis, was evaluated in a population of 299 hard winter wheat entries representative of the U.S. Great Plains region, grown in nine environments during 2011-2012 and 2012-2013. The germplasm was evaluated for candidate genes at vernalization (Vrn-A1, Vrn-B1, and Vrn-D1), photoperiod (Ppd-A1, Ppd-B1 and Ppd-D1), and reduced-height (Rht-B1 and Rht-D1) loci using polymerase chain reaction (PCR) and Kompetitive Allele Specific PCR (KASP) assays. Our objectives were to determine allelic variants known to affect flowering time, assess the effect of allelic variants on heading date, and investigate changes in the geographic and temporal distribution of alleles and haplotypes. Our analyses enhanced understanding of the roles developmental genes have on the timing of heading date in wheat under varying environmental conditions, which could be used by breeding programs to improve breeding strategies under current and future climate scenarios. The significant main effects and two-way interactions between the candidate genes explained an average of 44% of variability in heading date at each environment. Among the loci we evaluated, most of the variation in heading date was explained by Ppd-D1, Ppd-B1, and their interaction. The prevalence of the photoperiod sensitive alleles Ppd-A1b, Ppd-B1b, and Ppd-D1b has gradually decreased in U.S. Great Plains germplasm over the past century. There is also geographic variation for photoperiod sensitive and reduced-height alleles, with germplasm from breeding programs in the northern Great Plains having greater incidences of the photoperiod sensitive alleles and lower incidence of the semi-dwarf alleles than germplasm from breeding programs in the central or southern plains.
... Addison et al. (2016) reported epistasis for GY between Ppd-B1 and vrn-B1 in the same population, with a winter allele at vrn-B1 for reduced vernalization requirement (Guedira et al., 2014) and the Ppd-B1b allele for photoperiod sensitivity favorable for higher GY across southern US environments. Previous studies have also reported epistatic interactions between Ppd loci (Bennett et al., 2012a;Le Gouis et al., 2012) and Ppd and Vrn loci (Eagles et al., 2010;Kumar et al., 2012;Le Gouis et al., 2012) for developmental traits. ...
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The objective of this study was to identify quantitative trait loci (QTL) associated with normalized difference vegetation index (NDVI) measured across different growth stages in a wheat (Triticum aestivum L.) recombinant inbred line (RIL) population and to determine the predictability of NDVI and grain yield (GY) using a genomic selection (GS) approach. The RILs were grown over three seasons in 12 total site-years and NDVI was measured in seven site-years. Measurements of NDVI from tillering to physiological maturity showed low to moderate heritability (h² = 0.06-0.68). Positive correlations were observed among NDVI, GY, and biomass, particularly in low-yielding site-years. Quantitative trait loci analysis found 18 genomic regions associated with NDVI, with most pleiotropic across multiple growth stages. The QTL were detected near markers for Ppd-B1, Ppd- D1, vrn-A1, and vrn-B1, with Ppd-D1 having the largest effect. Multiple QTL models showed that epistatic interactions between Ppd and Vrn loci also significantly influenced NDVI. Genomic selection accuracy ranged from r = -0.10 to 0.54 for NDVI across growth stages. However, the inclusion of Vrn and Ppd loci as fixed effect covariates increased GS accuracy for NDVI and GY in site-year groupings with the lowest heritability. The highest accuracy for GY (r = 0.58- 0.59) was observed in the site-year grouping with the highest heritability (h² = 0.85). Overall, these results will aid in future selection of optimal plant growth for target environments using both phenotypic and GS approaches.
... Vernalization (Vrn), photoperiod response (Ppd) and semi-dwarfing (Rht) gene marker assays Vrn and Rht8 PCR-marker amplicons were visualized by agarose gel electrophoresis. Vrn polymorphisms assayed are considered diagnostic of winter/spring alleles conditioning vernalization sensitivity/insensitivity. For Vrn-A1, primer pair BT468/BT486 located in the promoter-region [48] was used. For Vrn-B1 and Vrn-D1, three-primer mixtures identifying insertion/deletion polymorphisms in intron-1 of these genes were used: (Intr1/B/F, Intr1/B/R3 and Intr1/B/R4), and (Intr1/D/F, Intr1/D//R3 and Intr1/ D/R4), respectively [49]. ...
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Background Molecular markers and knowledge of traits associated with heat tolerance are likely to provide breeders with a more efficient means of selecting wheat varieties able to maintain grain size after heat waves during early grain filling. Results A population of 144 doubled haploids derived from a cross between the Australian wheat varieties Drysdale and Waagan was mapped using the wheat Illumina iSelect 9,000 feature single nucleotide polymorphism marker array and used to detect quantitative trait loci for heat tolerance of final single grain weight and related traits. Plants were subjected to a 3 d heat treatment (37 °C/27 °C day/night) in a growth chamber at 10 d after anthesis and trait responses calculated by comparison to untreated control plants. A locus for single grain weight stability was detected on the short arm of chromosome 3B in both winter- and autumn-sown experiments, determining up to 2.5 mg difference in heat-induced single grain weight loss. In one of the experiments, a locus with a weaker effect on grain weight stability was detected on chromosome 6B. Among the traits measured, the rate of flag leaf chlorophyll loss over the course of the heat treatment and reduction in shoot weight due to heat were indicators of loci with significant grain weight tolerance effects, with alleles for grain weight stability also conferring stability of chlorophyll (‘stay-green’) and shoot weight. Chlorophyll loss during the treatment, requiring only two non-destructive readings to be taken, directly before and after a heat event, may prove convenient for identifying heat tolerant germplasm. These results were consistent with grain filling being limited by assimilate supply from the heat-damaged photosynthetic apparatus, or alternatively, accelerated maturation in the grains that was correlated with leaf senescence responses merely due to common genetic control of senescence responses in the two organs. There was no evidence for a role of mobilized stem reserves (water soluble carbohydrates) in determining grain weight responses. Conclusions Molecular markers for the 3B or 6B loci, or the facile measurement of chlorophyll loss over the heat treatment, could be used to assist identification of heat tolerant genotypes for breeding. Electronic supplementary material The online version of this article (doi:10.1186/s12870-016-0784-6) contains supplementary material, which is available to authorized users.
... Assumptions about the covariance structure of cultivars and environment at particular locations can also be explored using either compound symmetry, diagonal or factor analytic models (Smith et al., 2001). On occasions, environmental covariates such as rainfall can be introduced into such a model to further define environment (Eagles et al., 2010). The attempt to define cultivar performance for specific environments is partly driven by the need to communicate to farmers which cultivars will be suited to their farm. ...
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Farmers must choose which cultivar to grow based on the phenology of the cultivar and anticipated season length. The current study investigated the established doctrine of sowing fast maturing cultivars late, and slow maturing cultivars early. This was explored by quantifying the genotype (G) × environment (E) × management (M) available to farmers using commercially released cultivars, where management relates to the time of sowing. Nineteen cultivars of spring wheat (Triticum aestivum) were sown at 3 times of sowing (early, conventional and late) at 13 sites in 2011 and 2012. Sites were located throughout the Australian grain growing region in Queensland, New South Wales, Victoria, South Australia and Western Australia from latitudes 27°34′S to 35°09′S where annual rainfall ranged from 237 mm to 747 mm. In general, the three way interaction between G, E and M for yield was small and cultivar could not overcome the yield penalty associated with a late time of sowing. At 11 of the 13 sites, fast to moderately fast maturing cultivars sown early generated the highest yields. Fast maturing cultivars sown late could not compensate for a late time of sowing. Commercial cultivars were broadly adapted to environment and management, and with these cultivars, the Australian grain growing region could be split into just two environments, south and north. Even then, season appears to be the main arbiter of environment, rather than location per se as individual sites moved from one group to the other, depending on season. There was no evidence to suggest farmers could exploit a cultivar by management interaction for time of sowing with commercial cultivars, as the outcome of the season is unpredictable, and with current technology farmers should simply choose the best performing cultivar for their region and sow it as early as possible.
... It was found mainly in southern regions where it is usually combined with PPD-D1a (see above). As shown previously, VRN-D1a is the predominant allele in spring wheat genotypes adapted to tropical and subtropical regions (Iwaki et al. 2001, Zhang et al. 2008, Eagles et al. 2010). Thus, the combination of photoperiod sensitive PPD-D1b allele with two dominant alleles at VRN-A1 and VRN-B1 represents the most common genotype of spring wheat for most of Europe except southern region where monogenically dominant at VRN-B1 (VRN-D1) genotypes may get an advantage providing later heading in environments with longer growing season. ...
Article
The variation of the vernalization (VRN-1) and photoperiod (PPD-1) genes offers opportunities to adjust heading time and to maximize yield in crop species. The effect of these genes on heading time was studied based on a set of 245 predominantly spring cultivars of bread wheat from the main eco-geographical regions of Europe. The genotypes were screened using previously published diagnostic molecular markers for detecting the dominant or recessive alleles of the major VRN-1 loci such as: VRN-A1, VRN-B1, VRN-D1 as well as PPD-D1. We found that 91% of spring wheat cultivars contain the photoperiod sensitive PPD-D1b allele. Photoperiod insensitive PPD-D1a allele has been found mainly in southern region of Europe. For this region the monogenic control of vernalization by VRN-B1 or VRN-D1 dominant alleles is common, whereas in the remaining part of Europe, the combination of photoperiod sensitive PPD-D1b allele with dominant VRN-A1, VRN-B1 and recessive vrn-D1 alleles represents the most frequent genotype. Also, we revealed a significantly later (5–8 days) heading of the monogenically dominant genotypes at VRN-B1 as compared to the digenic VRN-A1 VRN-B1 genotypes.
... Previous studies indicated that increased expression of the Vrn-D1 gene contributes to early flowering and maturity (Yan et al., 2004a;Chen and Dubcovsky, 2012). The dominant Vrn-D1a allele was found to result in early heading in a large set of Australian wheat genotypes (Eagles et al., 2010;Cane et al., 2013). Fu et al. (2005) suggested that the promoter and intron 1 regulatory sequences both affected the vernalization response, and mutations in the regulatory sequences reduced the expression of this gene. ...
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A total of 205 wheat cultivars from the Yellow and Huai valley of China were used to identify allelic variations of vernalization and photoperiod response genes, as well as the copy number variations (CNVs) of Ppd-B1 and Vrn-A1 genes. A novel Vrn-D1 allele with 174-bp insertion in the promoter region of the recessive allele vrn-D1 was discovered in three Chinese wheat cultivars and designated as Vrn-D1c. Quantitative real-time polymerase chain reaction showed that cultivars with the Vrn-D1c allele exhibited significantly higher expression of the Vrn-D1 gene than that in cultivars with the recessive allele vrn-D1, indicating that the 174-bp insertion of Vrn-D1c contributed to the increase in Vrn-D1 gene expression and caused early heading and flowering. The five new cis-elements (Box II-like, 3-AF1 binding site, TC-rich repeats, Box-W1 and CAT-box) in the 174-bp insertion possibly promoted the basal activity level of Vrn-D1 gene. Two new polymorphism combinations of photoperiod genes were identified and designated as Ppd-D1_Hapl-IX and Ppd-D1_Hapl-X. Association of the CNV of Ppd-B1 gene with the heading and flowering days showed that the cultivars with Ppd-B1_Hapl-VI demonstrated the earliest heading and flowering times, and those with Ppd-B1_Hapl-IV presented the latest heading and flowering times in three cropping seasons. Distribution of the vernalization and photoperiod response genes indicated that all recessive alleles at the four vernalization response loci, Ppd-B1_Hapl-I at Ppd-B1 locus, and Ppd-D1_Hapl-I at the Ppd-D1 locus were predominant in Chinese winter wheat cultivars. This study can provide useful information for wheat breeding programs to screen wheat cultivars with relatively superior adaptability and maturity.
... In eastern Australia, where it is cooler and where rainfall in summer and autumn is more common, early sowing opportunities are frequent; in fact, the unavailability of suitable new varieties may currently be holding back a shift to earlier planting. The vernalisation and photoperiod genes that regulate crop development and determine time of floral initiation, and therefore flowering, are well understood and very good diagnostic molecular markers are available for breeders (Eagles et al. 2010;Cane et al. 2013). These markers provide breeders with the opportunity to identify parents and progeny that range from being completely insensitive to being extremely sensitive to vernalisation and photoperiod. ...
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The improvement in grain yield of wheat throughout Australia through both breeding and management has been impressive. Averaged across all farms, there has been an approximate doubling of yield per unit area since similar to 1940. This has occurred across a broad range of environments with different rainfall patterns. Interestingly, the gain in the driest years (9 kg ha(-1) year(-1) or 0.81% year(-1)) has been proportionally greater than in the most favourable years (13.2 kg ha(-1) year(-1) or 0.61% per year) when expressed as yield relative to 2012. These data from all farms suggest that further yield progress is likely, and evidence is presented that improved management practices alone could double this rate of progress. The yield increases achieved have been without any known compromise in grain quality or disease resistance. As expected, improvements have come from both changed management and from better genetics, as well as from the synergy between them. Yield improvements due to changed management have been dramatic and are easiest to quantify, whereas those from breeding have been important but more subtle. The management practices responsible have largely been driven by advances in mechanisation that enable direct seeding, more timely and flexible sowing and nutrient management, and improved weed and pest control, many of which have been facilitated by improved crop sequences with grain legumes and oilseeds that improve water-and nutrient-use efficiency. Most of the yield improvements from breeding in Australia have come from conventional breeding approaches where selection is almost solely for grain yield (together with grain quality and disease resistance). Improvements have primarily been through increased harvest index (HI), although aboveground biomass has also been important. We discuss future opportunities to further increase Australian rainfed wheat yields. An important one is earlier planting, which increases resource capture. This will require knowledge of the genes regulating phenological development so that flowering still occurs at the optimum time; appropriate modifications to sowing arrangements and nutrient management will also be required. To improve yield potential, we propose a focus on physiological traits that increase biomass and HI and suggest that there may be more scope to improve biomass than HI. In addition, there are likely to be important opportunities to combine novel management practices with new breeding traits to capture the synergy possible from variety x management interactions. Finally, we comment on research aimed at adapting agriculture to climate change.
... For two out of three spring wheat cultivars the presence of the dominant Vrn-B1 allele caused acceleration of heading time (Table 2). This result is convergent with observations described previously for flowering time (Eagles et al., 2010;Kumar et al., 2012;Kamran et al., 2013). We did not show heading acceleration for triticale containing the dominant Vrn-B1 allele, however this result needs to be verified using a greater number of genotypes. ...
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In cereals, the transition from the vegetative stage to flowering is controlled in the main by the set of vernalization genes. Within these genes the most important role is played by VRN1, which encodes a MADS-box transcription factor, regulating the transition of shoot apical meristem to the reproductive phase. The level of vernalization requirement is strongly linked to the molecular structure of this gene. In this study we analyzed molecular mechanisms regulating the vernalization requirement in triticale on the basis of comparative analysis of the VRN1 locus between triticale (×Triticosecale Witt.) and common wheat (Triticum aestivum L.) genotypes. We also estimated the influence of VRN genotype on heading time and the winter hardiness of these two species. Molecular markers developed for VRN genotype detection in common wheat were successfully applied to an analysis of triticale genomic DNA. Subsequent analysis of the ampli-cons nucleotide sequence confirmed full similarity of the products obtained between triticale and common wheat. All winter triticale cultivars tested contained the recessive vrn-A1 allele, whereas all spring genotypes carried the dominant Vrn-A1a allele. Molecular analysis of the Vrn-B1 gene revealed the presence of the dominant Vrn-B1b allele in only one of the triticale genotypes analyzed (Legalo). The major system of determination of the vernalization requirement in triticale was transferred from common wheat without changes and is based on an alteration in the VRN1 gene promoter sequence within the A genome.
... Spring wheat sown in the winter is generally thought to show little response to vernalization and to be photoperiod insensitive. Although qualitatively true, especially for vernalization, these spring wheat crops do respond to vernalization and photoperiod treatments (Eagles et al., 2010). What remains unclear is whether the levels of response are large enough to affect prediction of anthesis dates for a spring wheat sown in the winter. ...
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Accurate prediction of phenology is required to guide crop management decisions and to predict crop growth and yield. However, the relative importance of photoperiod and vernalization in predicting anthesis dates for spring bread and durum wheat (Triticum aestivum L. and T. durum Desf.) sown in the winter has not been reported. The purpose of this research is to determine the improvement in predicting anthesis dates of spring wheat sown in the winter when photoperiod and vernalization are considered. Observed dates of anthesis were obtained from University of Arizona wheat variety trials conducted at Maricopa, Wellton, and Yuma, AZ. The Cropping Systems Model CROPSIM-CERES as released in DSSAT 4.5 was used to simulate days to anthesis based on temperature, daylength, and vernalization. For 12 bread and durum wheat cultivars, the model predicted days to anthesis with a root mean square error (RMSE) of 7.6 d if all cultivar differences were ignored, 6.4 d considering only differences in thermal time (TT), 6.1 d with differences in TT and daylength response, 6.4 d with TT and vernalization, and 6.2 d with TT, daylength, and vernalization. Consideration of cultivar differences in TT and photoperiod response improved the prediction of days to anthesis for winter-sown spring wheat, but there was no benefit from considering effects of vernalization in CROPSIM-CERES.
... In contrast, spring types generally do not require vernalisation to progress developmentally, though can vary in their responses, whereby exposure to vernalising temperatures can hasten their development (facultative vernalisation requirement), or have no effect on development (vernalisation insensitive) (Pugsley 1983, Hunt 2017. Vernalisation and photoperiod (day length) sensitivity interact and as such there is genotypic variation among winter and spring types in their flowering responses across environments (Davidson et al. 1985, Eagles et al. 2010. ...
... The dominant VRN-D1a allele was first isolated from spring near-isogenic line TDE (Table 1). As shown, VRN-D1a is the predominant allele in spring wheat genotypes adapted to tropical and subtropical regions [59][60][61][62]. The VRN-D1b allele has been originated from the previous allele due to SNP in the CArG-box at the promoter region [63]. ...
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Background The key gene in genetic system controlling the duration of the vegetative period in cereals is the VRN1 gene, whose product under the influence of low temperature (vernalization) promotes the transition of the apical meristem cells into a competent state for the development of generative tissues of spike. As early genetic studies shown, the dominant alleles of this gene underlie the spring forms of plants that do not require vernalization for this transition. In wheat allopolyploids various combinations of alleles of the VRN1 homoeologous loci (VRN1 homoeoalleles) provide diversity in such important traits as the time to heading, height of plants and yield. Due to genetical mapping of VRN1 loci it became possible to isolate the dominant VRN1 alleles and to study their molecular structure compared with the recessive alleles defining the winter type of plants. Of special interest is the process of divergence of VRN1 loci in the course of evolution from diploid ancestors to wheat allopolyploids of different levels of ploidy. Results Molecular analysis of VRN1 loci allowed to establish that various dominant alleles of these loci appeared as a result of mutations in two main regulatory regions: the promoter and the first intron. In the diploid ancestors of wheat, especially, in those of A- genome (T. boeoticum, T. urartu), the dominant VRN1 alleles are rare in accordance with a limited distribution of spring forms in these species. In the first allotetraploid wheat species including T. dicoccoides, T. araraticum (T. timopheevii), the spring forms were associated with a new dominant alleles, mainly, within the VRN-A1 locus. The process of accumulation of new dominant alleles at all VRN1 loci was significantly accelerated in cultivated wheat species, especially in common, hexaploid wheat T. aestivum, as a result of artificial selection of spring forms adapted to different climatic conditions and containing various combinations of VRN1 homoeoalleles. Conclusions This mini-review summarizes data on the molecular structure and distribution of various VRN1 homoeoalleles in wheat allopolyploids and their diploid predecessors.
... Nevertheless, recent studies indicate that they exhibit temperature sensitivity in wheat (Ochagavía et al. 2019;Prieto et al. 2020). Numerous strategies have been adopted to decipher the genetic control of flowering time in wheat, such as the candidate gene approach (Eagles et al. 2010;Rousset et al. 2011;Bentley et al. 2013), and the meta-QTL (quantitative trait locus) analysis, which includes individual and separate QTL studies. The last was used firstly in maize and was conducted in wheat as well using either biparental populations or collections of association panels (Hanocq et al. 2007;Griffiths et al. 2009;Kamran et al. 2014). ...
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Key message The genetic response to changing climatic factors selects consistent across the tested environments and location-specific thermo-sensitive and photoperiod susceptible alleles in lower and higher altitudes, respectively, for starting flowering in winter wheat. Abstract Wheat breeders select heading date to match the most favorable conditions for their target environments and this is favored by the extensive genetic variation for this trait that has the potential to be further explored. In this study, we used a germplasm with broad geographic distribution and tested it in multi-location field trials across Germany over three years. The genotypic response to the variation in the climatic parameters depending on location and year uncovered the effect of photoperiod and spring temperatures in accelerating heading date in higher and lower latitudes, respectively. Spring temperature dominates other factors in inducing heading, whereas the higher amount of solar radiation delays it. A genome-wide scan of marker-trait associations with heading date detected two QTL: an adapted allele at locus TaHd102 on chromosome 5A that has a consistent effect on HD in German cultivars in multiple environments and a non-adapted allele at locus TaHd044 on chromosome 3A that accelerates flowering by 5.6 days. TaHd102 and TaHd044 explain 13.8% and 33% of the genetic variance, respectively. The interplay of the climatic variables led to the detection of environment specific association responding to temperature in lower latitudes and photoperiod in higher ones. Another locus TaHd098 on chromosome 5A showed epistatic interactions with 15 known regulators of flowering time when non-adapted cultivars from outside Germany were included in the analysis.
... The TKW was evaluated by weighing 1000 kernels with a precision of 0.01 g. Flowering time was recorded as days starting by 10th of January (the vernalization requirement can be assumed to be fulfilled with 33 accumulated vernalized day degrees) when 50% of the spikes of an observation plot come into flower (Weir et al. 1984;Eagles et al. 2010;Langer et al. 2014). ...
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Key message Coincident regions on chromosome 4B for GW, on 5A for SD and TSS, and on 3A for SL and GNS were detected through an integration of a linkage analysis and a genome-wide association study (GWAS). In addition, six stable QTL clusters on chromosomes 2D, 3A, 4B, 5A and 6A were identified with high PVE% on a composite map. Abstract The panicle traits of wheat, such as grain number per spike and 1000-grain weight, are closely correlated with grain yield. Superior and effective alleles at loci related to panicles developments play a crucial role in the progress of molecular improvement in wheat yield breeding. Here, we revealed several notable allelic variations of seven panicle-related traits through an integration of genome-wide association mapping and a linkage analysis. The linkage analysis was performed using a recombinant inbred line (RIL) population (173 lines of F8:9) with a high-density genetic map constructed with 90K SNP arrays, Diversity Arrays Technology (DArT) and simple sequence repeat (SSR) markers in five environments. Thirty-five additive quantitative trait loci (QTL) were discovered, including eleven stable QTLs on chromosomes 1A, 2D, 4B, 5B, 6B, and 6D. The marker interval between EX_C101685 and RAC875_C27536 on chromosome 4B exhibited pleiotropic effects for GW, SL, GNS, FSN, SSN, and TSS, with the phenotypic variation explained (PVE) ranging from 5.40 to 37.70%. In addition, an association analysis was conducted using a diverse panel of 205 elite wheat lines with a composite map (24,355 SNPs) based on the Illumina Infinium assay in four environments. A total of 73 significant marker-trait associations (MTAs) were detected for panicle traits, which were distributed across all wheat chromosomes except for 4D, 5D, and 6D. Consensus regions between RAC875_C27536_611 and Tdurum_contig4974_355 on chromosome 4B for GW in multiple environments, between QTSS5A.7-43 and BS00021805_51 on 5A for SD and TSS, and between QSD3A.2-164 and RAC875_c17479_359 on 3A for SL and GNS in multiple environments were detected through linkage analysis and a genome-wide association study (GWAS). In addition, six stable QTL clusters on chromosomes 2D, 3A, 4B, 5A, and 6A were identified with high PVE% on a composite map. This study provides potentially valuable information on the dissection of yield-component traits and valuable genetic alleles for molecular-design breeding or functional gene exploration.
... (Salomé et al., 2011), sorghum (Mace et al., 2013, and maize (Zea mays L.) (Buckler et al., 2009) have provided insights into the genetic architecture of flowering time in these species. Contrary to maize and sorghum, which have large numbers of small-effect loci, the genetic architecture of heading date in the Australian wheat germplasm appeared controlled by a small number of major genes and numerous small-effect loci (Eagles et al., 2010;Eagles, Cane, & Vallance, 2009). Effects on PS and VR were mainly determined by Ppd-D1 and Vrn-A1, respectively, with additional large and stable effect loci for PS (5B-8) and EPS (6B-10). ...
Article
In Australian wheat (Triticum aestivum L.) production, optimizing wheat phenology is essential for yield potential and to avoid stress, especially around flowering. Breeding could be accelerated by identifying key loci and developing models to predict genotype flowering times under different pedoclimatic scenarios. Here, association genetics for heading date, earliness components (photoperiod sensitivity [PS]; vernalization requirement [VR]; earliness per se [EPS]) and simulation model (APSIM) phenology parameters from a panel of Australian cultivars and breeding lines identified loci with stable, repeatable effects. Major chromosomal regions with stable effects included the Ppd‐D1 region on chromosome 2D for PS and EPS, one region on 5B for PS, one region on 6B for EPS, and the Vrn‐A1 region on 5A for VR. Regions with stable, smaller effects were detected on 1A and 2D for PS, on 5A and 6B for EPS, and on 1A and 5D for VR. Other regions with stable effects on heading date and earliness components were located on 1A, 2B, 4B, 5B, 6B and 7B (PS and EPS), 2A, 3A and 7A (EPS and VR). Quantitative trait loci (QTL)–based model parameters were used to simulate heading dates across the Australian wheat belt for set of independent genotypes. Comparisons of average observed and predicted heading dates for four main regions of the Australian wheat belt showed good performance in prediction of independent lines from QTL information alone (r2 = .61–.83). The model allows testing of putative genotypes under various pedoclimatic scenarios including for adaptation to anticipated climate changes.
... The diversity of photoperiod and vernalization allelic combinations is the key component to controlling phenology, which regulates the anthesis date [47][48][49]. The effect of the photoperiod allele and vernalization allele on the anthesis date is summarized from literature in Table 5. Eagles [50] combined the photoperiod and vernalization alleles to study the effect of gene combinations on heading date. Their results showed that compared with a single gene, the combined genotype more comprehensively explains the variation of heading date among different varieties. ...
Article
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Quantitative studies on the effects of growing season, genotype (including photoperiod genes and vernalization genes), and their interaction (GGI) on the anthesis date of winter wheat (Triticum aestivum L.) are helpful to provide a scientific reference for selecting or developing adaptive varieties in target environments. In this study, we collected 100 winter wheat varieties with ecological adaptability in North China and identified the anthesis date under field conditions for three consecutive years from 2016 to 2019 with mapped photoperiod and vernalization alleles. Our results showed that the number of the photoperiod-insensitive Ppd-D1a allele increased with variety replacement, while the haplotype Ppd-A1b + Ppd-D1b + vrn-D1 (A4B2) decreased from the 1940s to 2000s. The anthesis date of A4B2 was significantly delayed due to the photoperiod-insensitive alleles Ppd-A1b and Ppd-D1b. The additive main effect and multiplicative interaction (AMMI) model and GGI biplot analysis were used for data analysis. A large portion of the total variation was explained by growing seasons (66.3%), while genotypes and GGIs explained 21.9% and 10.1% of the anthesis dates, respectively. The varieties from the 1940s and before had a great influence on the anthesis date, suggesting these germplasms tend to avoid premature anthesis and could facilitate the development of phenological resilient varieties.
... Also, in addition to Ppd and Vrn genes, Eps genes can also influence phenological processes (Ochagavía et al. 2019). More Ppd-D1 potency than Ppd-B1 has already been shown (Díaz et al. 2012;Eagles et al. 2010). Vrn-A1 and Vrn-B1 genes have been reported to have a dominant effect on the Vrn-D1 gene (Likhenko et al. 2015). ...
Article
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Phenological stages and allelic variation of vernalization and photoperiod response genes play an important role in wheat environmental adaptation and grain yield. In the present study, phenological stages of 260 Iranian wheat landraces and cultivars were studied during two cropping years. In addition, allelic variation of vernalization and photoperiod markers were also investigated to identify the genetic basis of different phenological stages. Ppd-D1 and then Ppd-B1 were highly variable in cultivars and landraces, while Ppd-A1 showed lower variation. Distribution patterns of allele frequency in Vrn-B1b, Ppd-D1b-D001, and Ppd-D1 markers were remarkably different in cultivars and landraces. About 98% and 96% of landraces showed photoperiod-sensitive allele of Ppd-D1b-D001 and Ppd-D1 markers, respectively, while most of cultivars had photoperiod-insensitive alleles. The frequency of Vrn-B1a was 82.2% in cultivars and 100% in landraces. However, Vrn-A1a-E4 was 43% and 79% in cultivar and landraces, respectively. We have found that Ppd-D1, Ppd-B1, and Vrn-A1 have a decisive effect on phenological stages and the combination of Ppd-B1a, Ppd-D1b, and Vrn-A1b is the most abundant allelic compound. The combination of aaa, bbb, and aab alleles for these three loci led to increased yield, thousand kernel weight (TKW), and grain filling period and shortening of phenological stages. Cluster analysis based on phenological stages and growing degree-days (GDD) of phenological stages clearly separated cultivars from landraces. This clustering pattern was consistent with marker data. The findings of this study provide a comprehensive insight into the basis of genetic control of the phenological stages of Iranian wheat landraces and cultivars. Therefore, this information can be used to select desirable genotypes in future breeding programs.
... Spanish germplasm has also been widely used in the Edstar wheat breeding program ( Table 2) by one of the authors, and a number of crosses to these lines have provided varieties of early maturity and good dryland adaptability (personal observation: Ian Edwards) [36]. Although Vrn-A1a has a stronger effect on vernalization requirement than Vrn-B1a [37,38], the reduction in days to heading in lines containing Vrn-B1a likely contributed to this, being the most frequently observed spring allele among the varieties, regardless of the genetic background, thereby indicating its broad adaptive value. Earlier maturity has been found to have a positive impact on grain yield in water-limited environments, and previous work has suggested that this may be a key reason for the higher frequency of this gene among lines that perform well under moisture stress [39,40]. ...
... Spanish germplasm has also been widely used in the Edstar wheat breeding program ( Table 2) by one of the authors, and a number of crosses to these lines have provided varieties of early maturity and good dryland adaptability (personal observation: Ian Edwards) [36]. Although Vrn-A1a has a stronger effect on vernalization requirement than Vrn-B1a [37,38], the reduction in days to heading in lines containing Vrn-B1a likely contributed to this, being the most frequently observed spring allele among the varieties, regardless of the genetic background, thereby indicating its broad adaptive value. Earlier maturity has been found to have a positive impact on grain yield in water-limited environments, and previous work has suggested that this may be a key reason for the higher frequency of this gene among lines that perform well under moisture stress [39,40]. ...
Article
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Photoperiod, vernalization, and plant height controlling genes are major developmental genes in wheat that govern environmental adaptation and hence, knowledge on the interaction effects among different alleles of these genes is crucial in breeding cultivars for target environments. The interaction effects among these genes were studied in nineteen Australian advanced lines from diverse germplasm pools and four commercial checks. Diagnostic markers for the Vrn-A1 locus revealed the presence of the spring allele Vrn-A1a in 10 lines and Vrn-A1c in one line. The dominant alleles of Vrn-B1a and Vrn-D1a were identified in 19 and 8 lines, respectively. The most common photoperiod-insensitive allele of Ppd-D1a was identified in 19 lines and three and four copy photoperiod-insensitive alleles (Ppd-B1a and Ppd-B1c) were present in five and one lines, respectively. All the lines were photoperiod-sensitive for the Ppd-A1 locus. All lines were semi-dwarf, having either of the two dwarfing alleles; 14 lines had the Rht-B1b (Rht-1) and the remaining had the Rht-D1b (Rht-2) dwarfing allele. The presence of the photoperiod-insensitive allele Ppd-D1a along with one or two spring alleles at the Vrn1 loci resulted in an earlier heading and better yield. Dwarfing genes were found to modify the heading time-the Rht-D1b allele advanced heading by three days and also showed superior effects on yield-contributing traits, indicating its beneficial role in yield under rain-fed conditions along with an appropriate combination of photoperiod and vernalization alleles. This study also identified the adaptability value of these allelic combinations for higher grain yield and protein content across the different the water-limited environments.
... Mbp). Notably, the different Vrn and Ppd genes are known for their epistatic interactions [22]. Thus, while all genotypes in this panel carry the Vrn-B1 winter allele, the QTL might be caused by allelic variation at the Vrn-B1 locus, in line with the observed effect of developmental differences on cereal leaf beetle infestation. ...
Article
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Wheat production can be severely damaged by endemic and invasive insect pests. Here, we investigated resistance to cereal leaf beetle in a panel of 876 winter wheat cultivars, and dissected the genetic architecture underlying this insect resistance by association mapping. We observed an effect of heading date on cereal leaf beetle infestation, with earlier heading cultivars being more heavily infested. Flag leaf glaucousness was also found to be correlated with resistance. In line with the strong effect of heading time, we identified Ppd-D1 as a major quantitative trait locus (QTL), explaining 35% of the genotypic variance of cereal leaf beetle resistance. The other identified putative QTL explained much less of the genotypic variance, suggesting a genetic architecture with many small-effect QTL, which was corroborated by a genomic prediction approach. Collectively, our results add to our understanding of the genetic control underlying insect resistances in small-grain cereals.
... Although the value of this enterprise has been recognized (Fischer, 2011;He et al., 2012;Yin et al., 2018), prediction of the phenology has been rather poor (White et al., 2008) if compared with the performance of the model calibrated through phenological trials. Better results were obtained by mixing both traditional and genetic approaches, but only a limited number of alleles were assessed (Ppd-D1a versus Ppd-D1b in Eagles et al. (2010) and Zheng et al. (2013)), limiting the combinations to which inference can be extended. Understanding how Ppd-1 allelic variants affect the response to photoperiod of timing of anthesis has been pointed out as a solution to the lack of accuracy (He et al., 2012;Bloomfield et al., 2018). ...
Article
Coupling anthesis date to the best environment is critical for wheat (Triticum aestivum L.) adaptation and yield potential. Development to anthesis is controlled by temperature and photoperiod. Response to photoperiod is chiefly modulated by Ppd-1 genes, but their effect on the quantitative response of i) time to anthesis, and ii) pre-anthesis phases to photoperiod remains largely unknown. A photoperiod-sensitive spring cultivar, Paragon, and near-isogenic lines of it carrying different combinations of Ppd-1a insensitivity alleles were tested under a wide range of photoperiods, including switches in photoperiod at the onset of stem elongation. Using multimodel inference we found that Ppd-1a alleles reduced photoperiod sensitivity from a) emergence to anthesis and b) emergence to onset of stem elongation, both in a less than additive manner, while threshold photoperiod and intrinsic earliness were unaffected. Sensitivity to current photoperiod from onset of stem elongation to flag leaf and from then to anthesis was milder than for previous phases and was not related to variability in Ppd-1. But ‘memory’ effects of previously experienced photoperiod on the duration from onset of stem elongation to flag leaf, was. The characterisation and quantification provided here of Ppd-1 allelic combinations’ effects on development should help increase genotype-to-phenotype models’ accuracy for predicting wheat phenology.
... These approaches are mainly developed and applied in cold regions and at high latitudes. [11][12][13][14][15] McMaster and Smika 16 analyzed three temporal scales [number of calendar days, growing degree-days (GDD), and photothermal units] based on a variety of base temperatures for the determination of the phenological stages of wheat. These authors found that any of the approaches analyzed can be considered more precise for every analyzed condition, although the approaches based on GDDs and photothermal units were demonstrated to be more precise in some conditions. ...
Article
We propose the use of temporal series of remote-sensing images (RS) for the characterization of the dynamics of the crop canopy throughout the growing and development cycle. Crop phenology, meteorological data, and normalized difference vegetation index (NDVI) were obtained during the period 2008 to 2016 for commercial fields planted with wheat. Three temporal scales based on the number of days, the growing degree-days (GDD), and the reference evapotranspiration (ETo) were analyzed for the intercomparison of the growing cycles. The use of the accumulated value of ETo as the reference scale for the temporal evolution of NDVI allowed for a better analysis of the differences among the fields. This scale also improves the estimation of the duration of the cycles and the prediction of flowering and physiological maturity. The analysis of the accumulated NDVI indicated that flowering occurs during the middle of the growing cycle and that the accumulated NDVI in the vegetative and reproductive phases is similar if the growing cycle is analyzed in terms of ETo or GDD. In addition, the estimation of the green-up based on RS data allows for the definition of the beginning of the growing period for this crop even in the absence of planting dates data.
... For example, the semidwarf alleles Rht-B1b and Rht-D1b became the main target for selection after the Green Revolution (Rebetzke & Richards, 2000). Different allele combinations for the photoperiod (Ppd) and vernalization (Vrn) genes that control flowering time have been selected for wheat grown in different agriproduction zones across Australia (Cane et al., 2013;Eagles et al., 2010;Eagles, Cane, & Vallance, 2009). Multiple quality genes have been also subject to selection across Australia depending on industrial end-use requirements (Cane et al., 2008;Crawford et al., 2011;Eagles et al., 2006). ...
Article
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Australia has one of the oldest modern wheat breeding programs worldwide although the crop was first introduced to the country in 1788. Breeders selected wheat with high adaptation to different Australian climates, while ensuring satisfactory yield and quality. This artificial selection left distinct genomic signatures that can be used to retrospectively understand breeding targets, and to detect economically important alleles. To study the effect of artificial selection on modern cultivars and cultivars released in different Australian states, we genotyped 482 Australian cultivars representing the history of wheat breeding in Australia since 1840. Computer simulation showed that 86 genomic regions were significantly affected by artificial selection. Characterization of 18 major genes known to affect wheat adaptation, yield and quality revealed that many were affected by artificial selection and contained within regions under selection. Similarly, many reported QTL and genes for yield, quality and adaptation were also contained in regions affected by artificial selection. These included TaCwi‐A1, TaGW2‐6A, Sus‐2B, Ta‐Sus1‐7A, TaSAP1‐7A, Glu‐A1, Glu‐B1, Glu‐B3, PinA, PinB, Ppo‐D1, Psy‐A1, Psy‐A2, Rht‐A1, Rht‐B1, Ppd‐D1, Vrn‐A1, Vrn‐B1 and Cre8. Interestingly, 17 regions affected by artificial selection were in moderate to high linkage disequilibrium with each other with an average r² value of 0.35 indicating strong simultaneous selection on specific alleles. These regions included Glu‐B1, TaGw2‐6A, Cre8, Ppd‐D1, Rht‐B1, Vrn‐B1, TaSus1‐7A, TaSAP1‐7A and Psy‐A1 plus multiple QTL affecting wheat yield and yield components. These results highlighted the effects of the long‐term artificial selection on Australian wheat germplasm and identified putative regions underlying important traits in wheat. This article is protected by copyright. All rights reserved.
... The Cranbrook × Halberd DH population consists of 166 DH lines (Kammholz et al. 2001), all of which were genotyped using a 90K SNP chip containing gene-associated SNPs that provide dense coverage of the wheat genome (Wang et al. 2014). The SNP markers were complemented with the genotypes of the photoperiod gene PPD-D1, vernalisation gene VRN-7 A1 and the semi-dwarf locus Rht1; these genes are polymorphic between the Cranbrook and Halberd population parents (Eagles et al. 2010(Eagles et al. , 2014(Eagles et al. , 2009). The linkage map was constructed using ASMap (Taylor and Butler 2014), a program which wraps MSTMap (Wu et al. 2008) in R (R-Development-Core-Team 2014). ...
Article
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Water stress during reproductive growth is a major yield constraint for wheat (Triticum aestivum L). We previously established a controlled environment drought tolerance phenotyping method targeting the young microspore stage of pollen development. This method eliminates stress avoidance based on flowering time. We substituted soil drought treatments by a reproducible osmotic stress treatment using hydroponics and NaCl as osmolyte. Salt exclusion in hexaploid wheat avoids salt toxicity, causing osmotic stress. A Cranbrook x Halberd doubled haploid (DH) population was phenotyped by scoring spike grain numbers of unstressed (SGNCon) and osmotically stressed (SGNTrt) plants. Grain number data were analyzed using a linear mixed model (LMM) that included genetic correlations between the SGNCon and SGNTrt traits. Viewing this as a genetic regression of SGNTrt on SGNCon allowed derivation of a stress tolerance trait (SGNTol). Importantly, and by definition of the trait, the genetic effects for SGNTol are statistically independent of those for SGNCon. Thus they represent non-pleiotropic effects associated with the stress treatment that are independent of the control treatment. QTL mapping was conducted using a whole genome approach in which the LMM included all traits and all markers simultaneously. The marker effects within chromosomes were assumed to follow a spatial correlation model. This resulted in smooth marker profiles that could be used to identify positions of putative QTL. The most influential QTL were located on chromosome 5A for SGNTol (126cM; contributed by Halberd), 5A for SGNCon (141cM; Cranbrook) and 2A for SGNTrt (116cM; Cranbrook). Sensitive and tolerant population tail lines all showed matching soil drought tolerance phenotypes, confirming that osmotic stress is a valid surrogate screening method.
... The truly-physiological contribution from this group at Wagga Wagga, NSW, actually came from seeking to understand the genetics underlying daylength and vernalization sensitivities which controlled flowering. This at last flowed into all Australian wheat breeding with the advent of DNA markers for the key controlling alleles, as exemplified by the accurate prediction of their effects on heading date across the wheat belt (Eagles et al 2010), but whether it is useful for breeders is not so clear. ...
Conference Paper
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The challenges for global agriculture are unprecedented and urgent; the next two decades are critical. In a context of declining investment to tackle these challenges, here we identify inefficiencies, and outline avenues to improve the returns on the investment of scarce R&D resources in agriculture.
... Cultivars with the Vrn-A1a allele flowered earlier than cultivars with the Vrn-B1 or Vrn-D1 alleles in non-vernalizing conditions in Pakistani wheat (Iqbal et al. 2012), wherein Vrn-A1a is the predominant allele in CIMMYT wheat (Yan et al. 2004) and vrn-A1 is the predominant allele in Chinese winter wheat (Chen et al. 2013a). Cultivars with the Vrn-D1a allele 1 3 headed and flowered earlier than the cultivars with other Vrn-D1 alleles in Australian wheat (Eagles et al. 2010;Cane et al. 2013) and Chinese wheat (Zhang et al. 2015a). Cultivars with the recessive vrn-B3 headed and flowered later than cultivars with the dominant Vrn-B3 in Chinese winter wheat (Chen et al. 2013a). ...
Article
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Heading date is one of the most important traits in wheat breeding as it affects adaptation and yield potential. A genome-wide association study (GWAS) using the 90 K iSelect SNP genotyping assay indicated that a total of 306 loci were significantly associated with heading and flowering dates in 13 environments in Chinese common wheat from the Yellow and Huai wheat region. Of these, 105 loci were significantly correlated with both heading and flowering dates and were found in clusters on chromosomes 2, 5, 6, and 7. Based on differences in distribution of the vernalization and photoperiod genes among chromosomes, arms, or block regions, 13 novel, environmentally stable genetic loci were associated with heading and flowering dates, including RAC875_c41145_189 on 1DS, RAC875_c50422_299 on 2BL, and RAC875_c48703_148 on 2DS, that accounted for more than 20% phenotypic variance explained (PVE) of the heading/flowering date in at least four environments. GWAS and t test of a combination of SNPs and vernalization and photoperiod alleles indicated that the Vrn-B1, Vrn-D1, and Ppd-D1 genes significantly affect heading and flowering dates in Chinese common wheat. Based on the association of heading and flowering dates with the vernalization and photoperiod alleles at seven loci and three significant SNPs, optimal linear regression equations were established, which show that of the seven loci, the Ppd-D1 gene plays the most important role in modulating heading and flowering dates in Chinese wheat, followed by Vrn-B1 and Vrn-D1. Additionally, three novel genetic loci (RAC875_c41145_189, Excalibur_c60164_137, and RAC875_c50422_299) also show important effect on heading and flowering dates. Therefore, Ppd-D1, Vrn-B1, Vrn-D1, and the novel genetic loci should be further investigated in terms of improving heading and flowering dates in Chinese wheat. Further quantitative analysis of an F10 recombinant inbred lines population identified a major QTL that controls heading and flowering dates within the Ppd-D1 locus with PVEs of 28.4% and 34.0%, respectively; this QTL was also significantly associated with spike length, peduncle length, fertile spikelets number, cold resistance, and tiller number.
... In bread wheat, Eps genes have been estimated to be responsible for 5% of the genetic variability for heading time, whenever vernalization and photoperiod genes were also acting (Kamran et al., 2014). In other reports, when vernalization requirements were fulfilled and their effects accounted for, around 50% of genetic variation was attributed to intrinsic earliness (Eagles et al., 2010;Cane et al., 2013). In the case of the genotypes and the environments used in the present study, the percentage of variation attributable to genetic factors unrelated to Vrn/Ppd was over 50% for thermal time to flowering. ...
Article
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The main yield components in durum wheat are grain number per unit area (GN) and thousand kernel weight (TKW), both of which are affected by environmental conditions. The most critical developmental stage for their determination is flowering time, which partly depends on photoperiod sensitivity genes at Ppd-1 loci. Fifteen field experiments, involving 23 spring durum wheat genotypes containing all known allelic variants at the PHOTOPERIOD RESPONSE LOCUS (Ppd-A1 and Ppd-B1) were carried out at three sites at latitudes ranging from 41∘ to 27∘ N (Spain, Mexico-north, and Mexico-south, the latter in spring planting). Allele GS100 at Ppd-A1, which causes photoperiod insensitivity and results in early-flowering genotypes, tended to increase TKW and yield, albeit not substantially. Allele Ppd-B1a, also causing photoperiod insensitivity, did not affect flowering time or grain yield. Genotypes carrying the Ppd-B1b allele conferring photoperiod sensitivity had consistently higher GN, which did not translate into higher yield due to under-compensation in TKW. This increased GN was due to a greater number of grains spike-1 as a result of a higher number of spikelets spike-1. Daylength from double ridge to terminal spikelet stage was strongly and positively associated with the number of spikelets spike-1 in Spain. This association was not found in the Mexico sites, thereby indicating that Ppd-B1b had an intrinsic effect on spikelets spike-1 independently of environmental cues. Our results suggest that, in environments where yield is limited by the incapacity to produce a high GN, selecting for Ppd-B1b may be advisable.
... It was found mainly in southern regions where it is usually combined with PPD-D1a (see above). As shown previously, VRN-D1a is the predominant allele in spring wheat genotypes adapted to tropical and subtropical regions (Iwaki et al. 2001, Zhang et al. 2008, Eagles et al. 2010). Thus, the combination of photoperiod sensitive PPD-D1b allele with two dominant alleles at VRN-A1 and VRN-B1 represents the most common genotype of spring wheat for most of Europe except southern region where monogenically dominant at VRN-B1 (VRN-D1) genotypes may get an advantage providing later heading in environments with longer growing season. ...
Article
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We characterized a representative set of 42 spring wheat cultivars from Russia and adjacent regions for 3 Vrn loci. The 42 genotypes were screened, along with 3 genotypes of known Vrn genes, using previously published genome-specific polymerase chain reaction (PCR) primers designed for detecting the presence or absence of dominant or recessive alleles of the major Vrn loci: Vrn-A1, Vrn-B1 and Vrn-D1. The dominant promoter duplication allele Vrn-A1a was present in 28 of 42 cultivars, whereas the promoter deletion allele Vrn-A1b was present in only 1 of the Russian cultivars (Triticum aestivum L. 'Pyrothrix 28'). The intron deletion allele Vrn-A1c was not present in any tested cultivar. The dominant Vrn-D1 allele was found in 1 of the cultivars. Thirteen of the spring wheat cultivars tested here carry the recessive vrn-A1 allele. However, for 6 cultivars, there were inconsistencies between PCR data and genetic segregation analysis, showing the presence of the dominant Vrn-A1 gene. No inconsistencies were found in the case of Vrn-B1 locus. A new combination of specific primers allowed amplification of the common Vrn-B1a allele along with the novel Vrn-B1c allele, which was present in 17 of the studied cultivars (40%). Twenty-five cultivars (59%) had dominant alleles of Vrn-A1a and Vrn-B1 in combination. We showed the predominance of the Vrn-B1c allele among cultivars with monogenic control of vernalization in West Siberia and Kazakhstan. In the absence of epistatic effects of Vrn-A1, this allele causes an earlier heading time compared to Vrn-B1a, thereby avoiding early fall frosts. Suggestions are made concerning the origin and distribution of the Vrn-B1c allele among Russian spring wheats.
Article
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Key message: Genetic analysis of the yield and physical quality of wheat revealed complex genetic control, including strong effects of photoperiod-sensitivity loci. Environmental conditions such as moisture deficit and high temperatures during the growing period affect the grain yield and grain characteristics of bread wheat (Triticum aestivum L.). The aim of this study was to map quantitative trait loci (QTL) for grain yield and grain quality traits using a Drysdale/Gladius bread wheat mapping population grown under a range of environmental conditions in Australia and Mexico. In general, yield and grain quality were reduced in environments exposed to drought and/or heat stress. Despite large effects of known photoperiod-sensitivity loci (Ppd-B1 and Ppd-D1) on crop development, grain yield and grain quality traits, it was possible to detect QTL elsewhere in the genome. Some of these QTL were detected consistently across environments. A locus on chromosome 6A (TaGW2) that is known to be associated with grain development was associated with grain width, thickness and roundness. The grain hardness (Ha) locus on chromosome 5D was associated with particle size index and flour extraction and a region on chromosome 3B was associated with grain width, thickness, thousand grain weight and yield. The genetic control of grain length appeared to be largely independent of the genetic control of the other grain dimensions. As expected, effects on grain yield were detected at loci that also affected yield components. Some QTL displayed QTL-by-environment interactions, with some having effects only in environments subject to water limitation and/or heat stress.
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Grain quality is an important determinant of market value of wheat in southern Australia and in many other parts of the world. Identification of the genes that influence grain quality traits and estimation of effects of alleles of these genes can improve the effectiveness of wheat breeding. An efficient method for estimating the effects of alleles of recently discovered genes is to use mixed-model analyses in large plant breeding datasets that have already been characterised for previously known genes. We used this method to estimate the effects of two alleles of Spa-B1, a storage protein activator gene that is linked to Glu-B1, on grain quality traits. Alleles of the two genes tracked together as haplotypes for generations, but recombination events were identified. These recombination events were used to enhance confidence in identification of the alleles. The effects of the alleles of Spa-B1 were small and statistically not significant for all of the grain quality traits in our population.
Chapter
Climatic stresses have been affecting agricultural productivity and thereby present a major challenge for the food and nutritional security. The frequency and magnitude of these stresses are projected to increase and impact the crop yields at global level as well as in India. Genetic adaptation is identified as the most crucial factor for improving productivity in future climates. Contextualization of genetic improvement for changing climates is essential to improve the crop productivity as well as to conserve the natural resources. Serious reorientation of breeding efforts is required for a comprehensive genetic improvement programme that should address the challenges of changing climates and growing demand for food and nutritional quality. The approaches to be deployed for crop improvement should include characterization of projected climatic stresses, entire germplasm with projected climatic variability as background, utilization of entire genetic diversity and deploying multipronged approaches for genetic improvement. This chapter is aimed to contextualize the issues and approaches for breeding climate resilient varieties.
Article
Photoperiod and vernalisation genes are important for the adaptation of wheat to variable environments. Previously, using diagnostic markers and a large, unbalanced dataset from southern Australia, we estimated the effects on days to heading of frequent alleles of Vrn-A1, Vrn-B1, and Vrn-D1, and also two allelic classes of Ppd-D1. These genes accounted for similar to 45% of the genotypic variance for that trait. We now extend these analyses to further alleles of Ppd-D1, and four alleles of Ppd-B1 associated with copy number. Variation in copy number of Ppd-B1 occurred in our population, with one to four linked copies present. Additionally, in rare instances, the Ppd-B1gene was absent (a null allele). The one-copy allele, which we labelled Ppd-B1b, and the three-copy allele, which we labelled Ppd-B1a, occurred through a century of wheat breeding, and are still frequent. With several distinct progenitors, the one-copy allele might not be homogenous. The two-copy allele, which we labelled Ppd-B1d, was generally introduced from WW15 (syn. Anza), and the four-copy allele, which we labelled Ppd-B1c, came from Chinese Spring. In paired comparisons, Ppd-B1a and Ppd-B1c reduced days to heading, but Ppd-B1d increased days to heading. Ppd-D1a, with a promoter deletion, Ppd-D1d, with a deletion in Exon 7, and Ppd-D1b, the intact allele, were frequent in modern Australian germplasm. Differences between Ppd-D1a and Ppd-D1d for days to heading under our field conditions depended on alleles of the vernalisation genes, confirming our previous report of large epistatic interactions between these classes of genes. The Ppd-D1b allele conferred a photoperiod response that might be useful for developing cultivars with closer to optimal heading dates from variable sowing dates. Inclusion of Ppd-B1 genotypes, and more precise resolution of Ppd-D1, increased the proportion of the genotypic variance attributed to these vernalisation and photoperiod genes to similar to 53%.
Article
Allele-specific markers for important genes can improve the efficiency of plant breeding. Their value can be enhanced if effects of the alleles for important traits can be estimated in identifiable types of environment. Provided potential bias can be minimised, large, unbalanced, datasets from previous plant-breeding and agronomic research can be used. Reliable, allele-specific markers are now available for the phenology genes Ppd-D1, Vrn-A1, Vrn-B1 and Vrn-D1, the aluminium-tolerance gene TaALMT1, and the plant-stature genes Rht-B1 and Rht-D1. We used a set of 208 experiments with growing-season rainfall of <347 mm from southern Australia to estimate the effects of seven frequent combinations of the phenology genes, an intolerant and a tolerant allele of TaALMT1, and two semi-dwarf combinations Rht-B1b + Rht-D1a (Rht-ba) and Rht-B1a + Rht-D1b (Rht-ab) on grain yield in lower rainfall, Mediterranean-type environments in southern Australia. There were 775 lines in our analyses and a relationship matrix was used to minimise bias. Differences among the phenology genes were small, but the spring allele Vrn-B1a might be desirable. The tolerant allele, TaALMT1-V, was advantageous in locations with alkaline soils, possibly because of toxic levels of aluminium ions in subsoils. The advantage of TaALMT1-V is likely to be highest when mean maximum temperatures in spring are high. Rht-ab (Rht2 semi-dwarf) was also advantageous in environments with high mean maximum temperatures in spring, suggesting that for these stress environments, the combination of Vrn-B1a plus TaALMT1-V plus Rht-ab should be desirable. Many successful cultivars carry this combination.
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In the Mallee region of north-western Victoria, Australia, there is very little grazing of crops that are intended for grain production. The success of dual-purpose crops in other regions in south-eastern Australia with higher and more evenly distributed rainfall has driven interest in assessing the performance of dual-purpose cereals in the region. Five experiments were established in five consecutive years (2009-13) in the southern Mallee to measure the forage production and grain yield and quality response in wheat and barley to grazing by sheep or mechanical defoliation. The first three experiments focused on spring cultivars sown from late April to June, and the last two on winter cultivars planted from late February to early March. Cereal crops provided early and nutritious feed for livestock, with earlier sowing increasing the amount of dry matter available for winter grazing, and barley consistently produced more dry matter at the time of grazing or defoliation than wheat. However, the grain-production response of cereals to grazing or defoliation was variable and unpredictable. Effects on yield varied from-0.7 to +0.6t/ha, with most site×year×cultivar combinations neutral (23) or negative (14), and few positive (2). Changes in grain protein were generally consistent with yield dilution effects. Defoliation increased the percentage of screenings (grains passing a 2-mm sieve) in three of five experiments. Given the risk of reduced grain yield and quality found in this study, and the importance of grain income in determining farm profitability in the region, it is unlikely that dual-purpose use of current cereal cultivars will become widespread under existing grazing management guidelines for dual-purpose crops (i.e. that cereal crops can be safely grazed once anchored, until Zadoks growth stage Z30, without grain yield penalty). It was demonstrated that early-sown winter wheat cultivars could produce more dry matter for grazing (0.4-0.5t/ha) than later sown spring wheat and barley cultivars popular in the region (0.03-0.21t/ha), and development of regionally adapted winter cultivars may facilitate adoption of dual-purpose cereals on mixed farms.
Article
In order to study the effect of duration of the vegetative period (sowing to floral initiation) on potential yield, sister spring wheat semi-dwarf cultivars, Yecora and Cajeme, the latter having an extra vernalization sensitive allele (Vrn-A1v) and a photoperiod sensitive one (Ppd-D1b), were grown at 4–5 sowing dates over 5 years under irrigation and high fertility in northwest Mexico (latitude 27°N). In the earliest sowings (late Oct-early Nov) Cajeme had a 20 day longer vegetative period; this delay decreased steadily to 8 days in the latest sowings (mid-late January); anthesis date for Cajeme was, respectively, 17 and 6 days later. Relationships to minimum temperature levels in the vegetative phase strongly suggest that this sowing date by cultivar interaction arises largely because of the difference in vernalization alleles in an environment where there is limited vernalizing cold. Cajeme produced a greater maximum number of shoots, more spikelet nodes per spike, greater green area index, and greater above ground dry matter at anthesis and at physiological maturity. However Cajeme yielded no more than Yecora, even when yield was plotted against anthesis date, tending to have fewer grains/m². A similar conclusion was reached when grains/m² were related to preanthesis photothermal quotient, and grain weight to grain filling mean temperature: both cultivars responded similarly although Cajeme had slightly fewer grains/m² and heavier kernels, thus weather around flowering dominated determination of these yield components. Some other yield components were also slightly, but significantly, affected by cultivar in a manner independent of flowering date and weather. Thus Cajeme had a significantly higher spike dry matter at anthesis and a significantly lower fruiting efficiency of Cajeme (73.8 versus 84.2 grains/g spike dry matter). It is suggested that the latter was a consequence of the longer vegetative period leading to greater tillering, poorer tiller survival and a more competitive preanthesis canopy, causing poorer floret survival in grain-bearing spikes. The excessive tillering may have been exaggerated by supplying all nitrogen fertilizer at sowing.
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Improving water-use efficiency by incorporating drought avoidance traits into new wheat varieties is an important objective for wheat breeding in water-limited environments. This study uses genome wide association studies (GWAS) to identify candidate loci for water-soluble carbohydrate accumulation, an important drought-avoidance characteristic in wheat. Phenotypes from a multi-environment trial with experiments differing in water availability and separate single nucleotide polymorphism (SNP) and diversity arrays technology (DArT) marker sets were used to perform the analyses. Significant associations for water-soluble carbohydrate accumulation were identified on chromosomes 1A, 1B, 1D, 2D and 4A. Notably, these loci did not collocate with the major loci identified for relative maturity. Loci on chromosome 1D collocated with markers previously associated with the high molecular weight glutenin Glu-D1 locus. Genetic × environmental interactions impacted the results strongly, with significant associations for carbohydrate accumulation only identified in the water-deficit experiments. The markers associated with carbohydrate accumulation may be useful for marker assisted selection of drought tolerance in wheat.
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Winter wheat cultivars are defined as those that have an obligate vernalisation requirement that must be met before they will progress from the vegetative to reproductive phase of development i.e. they must experience a true winter before they will flower. Historically, very little breeding effort has been applied to the selection of winter cultivars suited to southern Australia, with the notable exception of the New South Wales Agriculture breeding program based in Wagga and Temora that ran from the 1960s until 2002. A shift by growers to earlier sowing, increased usage of dual-purpose cereals, and research highlighting the whole-farm benefits of winter cultivars to average farm wheat yield has increased grower interest and demand for winter cultivars. Three major wheat breeding companies operating in southern Australia have responded by commencing selection for milling quality winter cultivars, the first of which was released in 2017. Existing research relating to winter wheats in southern Australian farming systems is reviewed here, including interactions with agronomic management, environment and weeds and disease. It is concluded that winter wheats can offer significant production and farming system benefits to growers by allowing earlier establishment, which increases water-limited potential yield (PYw) by ∼15% relative to later sown spring wheats, and makes forage available for dual-purpose grazing during vegetative development. Winter wheats sown early require agronomic management different to that of later sown spring wheats, including greater attention to control of grass weeds and certain diseases. There are significant research gaps that will prevent growers from maximising the opportunities from new winter cultivars once they are released. The first of these is a well-defined establishment window for winter cultivars, particularly in medium-low rainfall environments of South Australia, Victoria and Western Australia that have not historically grown them. There is circumstantial evidence that the yield advantage of early established winter wheats over later sown spring wheats is greatest when stored soil water is present at establishment, or the soil profile fills during the growing season. Explicit confirmation of this would allow growers to identify situations where the yield advantage of winter wheats will be maximised. Given the imminent release of several new winter wheat cultivars and the increases in PYw that they embody, it is critical to experimentally define the management and environmental conditions under which performance of these new genotypes are optimised, before their release and availability to growers. Optimising the genotype×environmental×management interactions possible with these cultivars will empower growers to make the best use of the technology and better realise the gains in water limited potential yield possible with these genotypes.
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Genetic improvement in phosphorus (P) use efficiency (i.e. the ratio of biomass or yield at nil P to that at a given rate of application) is an important goal to improve P recovery and P efficiency of farming systems. Experiments were conducted at three sites in South Australia between 2009 and 2011 to characterise genetic variation in yield with no applied P and in the response to P fertiliser among a diverse range of barley (Hordeum vulgare L.) genotypes. In each experiment, 39-54 genotypes were grown at 0 or 30 kg P/ha. Responses to P were measured near the beginning of stem elongation by using normalised difference vegetation index (NDVI) and by harvesting the grain. Rhizosheath size was also measured on seedlings. Consistent differences in growth and yield at 0 kg P/ha were measured among the genotypes. By contrast, there were large environmental effects on responses to P, but some genotypes showed consistent responses. Measurements of growth, yield and P uptake on a subset of genotypes showed that most of the variation in biomass and yield could be attributed to variation in P-uptake efficiency (net total P uptake per unit available P) rather than to P-utilisation efficiency (biomass or yield per unit total P uptake). The size of the rhizosheath made a small contribution to variation in NDVI but not grain yield, suggesting that rhizosheath size may be of some benefit to early growth but that this does not persist through to yield. Genetic correlations between NDVI and yield were often weak but were generally positive at 0 kg P/ha. Correlations between responses in NDVI and responses in grain yield were low and often negative. The study identified several barley genotypes that showed consistent differences in yield at low P and responses to P however, selection for P efficiency based solely on responses in vegetative growth may not be appropriate. Variation in P uptake appeared to be more important than P-utilisation efficiency for P efficiency in barley.
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Spring bread wheat is the most important cereal crop, cultivated under various climatic conditions and on different latitudes. Modern molecular genetic studies of wheat are aimed at investigating the crop’s genetic potential. By now, molecular markers have been developed to identify alleles of the Vrn (vernalization response) and Ppd (photoperiod response) genes. Vrn genes are responsible for crop development rate regulation and crop yield structure. Ppd genes determine the response of plants to the length of the day, that is, the timing of flowering and the beginning of heading in plants under different cultivation conditions. The use of diagnostic DNA markers made it possible to analyze the presence of allelic combinations of the Vrn and Ppd genes in local and commercial wheat varieties from Europe, Asia, North and South Americas, Africa and Australia. This review summarizes the results of studies on the distribution of alleles of Vrn and Ppd genes in wheat breeding material over different geographical areas of its cultivation. For example, the dominant Vrn-A1a allele was found in 62% of European varieties; 52% of the studied Turkish wheat varieties carried dominant Vrn-B1 alleles. A dominant Vrn-D1 was found in 61% of Pakistani wheat accessions. Vrn-D1 is present in 41.9% of the studied varieties of Chinese wheat. Higher incidence of Ppd-D1A is typical for West European varieties. A Ppd-D1a allele was found in 58.6% of varieties preserved in the Turkish wheat collection, with a 60% frequency of this allele in commercial cultivars. Among local Afghan varieties, 97% are sensitive to photoperiod (carriers of Ppd-D1b); they are distributed throughout the country without much dependence on agroecological zones. All Pakistani varieties are insensitive to photoperiod (carriers of Ppd-D1a). In China, the highest incidence of the Ppd-D1a allele was observed in zone VII (87.5% of varieties).
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While plant breeders traditionally base selection on phenotype, the development of genetic ideotypes can help focus the selection process. This chapter provides a road map for the establishment of a refined genetic ideotype. The first step is an accurate definition of the target environment including the underlying constraints, their probability of occurrence, and impact on phenotype. Once the environmental constraints are established, the wealth of information on plant physiological responses to stresses, known gene information, and knowledge of genotype ×environment and gene × environment interaction help refine the target ideotype and form a basis for cross prediction. Once a genetic ideotype is defined the challenge remains to build the ideotype in a plant breeding program. A number of strategies including marker-assisted recurrent selection and genomic selection can be used that also provide valuable information for the optimization of genetic ideotype. However, the informatics required to underpin the realization of the genetic ideotype then becomes crucial. The reduced cost of genotyping and the need to combine pedigree, phenotypic, and genetic data in a structured way for analysis and interpretation often become the rate-limiting steps, thus reducing genetic gain. Systems for managing these data and an example of ideotype construction for a defined environment type are discussed.
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Eight spring bread wheat cultivars (Triticum aestivum L.), differing widely in their nominal yield component characteristics, were tested under rain-fed conditions for three years at sowing densities ranging from 50 to 800 seeds m-2. The objectives of the experiments were to estimate the relationship between grain yield and particular yield components, the expression of plant type (yield components) in relation to plant density, and the plant population x cultivar interaction for grain yield over a range of seasons in a given environment. The 'optimum' plant population (at maximum grain yield) varied over 30-220 plants m-2, depending on season and cultivar. In general, variation in the 'optimum' population was greater between seasons for a given cultivar than between cultivars within seasons. The relationship between grain yield and yield components was examined at the 'optimum' population rather than at an arbitrary population at which grain yield may have been suboptimal for some cultivars or seasons. Grain yields at the optimum populations for the various cultivar x season combinations were positively related to culms m-2, spikes m-2 and seeds m-2. They were not clearly related to culm mortality (%). When averaged across seasons, cultivar grain yields were positively related to harvest index, but the general relationship was not so clear when seasons and cultivars were examined individually. Spike size (seeds spike-I or spike weight) and seed size were also not clearly related to grain yield at the 'optimum' population, and it was thus postulated that the production and survival of large numbers of culms, which in turn led to large numbers of seeds per unit area, were the source of large grain yields. Some interactions were found between yield components and plant population for some cultivars that could have implications for plant breeders selecting at low plant densities. The implications for crop ideotypes of the individual plant characters at the 'optimum' population are also discussed. Interactions between cultivars and plant populations implied that some cultivars required different populations to achieve maximum yields in some seasons. There was a tendency for larger yields to be achieved from cultivar x season combinations where the optimum population was larger, which suggested that commercial seed rates should be re-examined when changes to plant types or yield levels are made.
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The orderly development of winter wheat through its life cycle can be marked at three stages: stem elongation, heading date, and physiological maturity. The duration of a developmental phase between two stages is important in yield component generation. In this study the three developmental stages were characterized and 350 markers were mapped in a population of recombinant inbred lines (RILs) generated from a cross between two winter wheat cultivars (‘Jagger’ and ‘2174’). Three major QTLs were found to control variation in developmental process, and each of them was tightly associated with a known flowering gene, VRN-A1 on chromosome 5A, PPD-D1 on chromosome 2D, and VRN-D3 on chromosome 7D. The average contribution of the gene marker for each QTL to the total phenotypic variation (R 2) was evaluated over 3 years. The effect of VRN-A1 ranged from 21.5% at stem elongation to 17.4% at physiological maturity. The effect of PPD-D1 was minor (6.7%) at stem elongation but increased to 29.7% at heading and 20.1% at physiological maturity. The effect of VRN-D3 was not detected at stem elongation but increased to 14.6% at heading and to 20.5% at physiological maturity. Hence, the VRN-A1 locus, the PPD-D1 locus, and the VRN-D3 locus had greatest impact on development at stem elongation, heading date, and physiological maturity, respectively. Whereas the Jagger VRN-A1 and VRN-D3 alleles accelerated development, the Jagger PPD-D1 allele delayed the developmental process due to its sensitivity to photoperiod. Our findings suggest that through the appropriate combination of alleles at these three loci one would be able to regulate the various developmental phases to accommodate different agricultural needs.
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A model that calculates the length of the day for a flat surface for a given latitude and day of the year is described. Calculated daylengths are within 1 minute of values published in Smithsonian Meteorological Tables and the Astronomical Almanac for latitudes between 40-degrees North and South with a maximum error of 7 minutes occurring at 60-degrees latitude. The model allows the use of different definitions of sunrise/sunset and the incorporation of twilight. Comparisons with other daylength models indicate that this model is more accurate and that variation in accumulated hours of daylight of up to one week over the course of the growing season can be accounted for by how sunrise/sunset are defined.
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Rising research costs, broadening goals, intellectual property rights, and other concerns increase the need for robust management of crop improvement data. The data model of the International Crop Information System (ICIS) allows breeding processes to be recorded unambiguously in a relational database. This paper describes this model, which underlies the Genealogical Management System (GMS) of ICIS. The model recognizes three classes of methods by which genetic material is advanced. Generative methods such as crossing or mutagenesis increase variation. Derivative methods usually involve selection, and maintenance methods conserve the genetic makeup of germplasm, such as in seed multiplications. Unlike systems that only track pedigrees, the model describes steps of selection. Applications are illustrated for self-pollinating, outcrossing, and clonally propagated crops. The ICIS GMS is in use for species including rice (Oryza sativa L.), wheat (Triticum aestivum L.), maize (Zea mays L.), potato (Solanum tuberosum L.), common bean (Phaseolus vulgaris L.), lesquerella [Lesquerella fendleri (Gray) S. Wats.], and witloof chicory (Cichorium intybus L.). The International Rice Information System, based on ICIS, holds more than 2.6 million unique identifiers for germplasm accessions, crosses, populations, and lines, requiring about 900 megabytes of storage space, which can easily be managed on a personal computer. The GMS model appears suited for widespread use in managing data on crop improvement.
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The study of the phenotypic responses of a set of genotypes in their dependence on the environment has always been an important area of research in plant breeding. Non-parallelism of those responses is called genotype by environment interaction (GEI). GEI especially affects plant breeding strategies, when the phenotypic superiority of genotypes changes in relation to the environment. The study of the genetic basis of GEI involves the modelling of quantitative trait locus (QTL) expression in its dependence on environmental factors. We present a modelling framework for studying the interaction between QTL and environment, using regression models in a mixed model context. We integrate regression models for QTL main effect expression with factorial regression models for genotype by environment interaction, and, in addition, take care to model adequately the residual genetic variation. Factorial regression models describe GEI as differential genotypic sensitivity to one or more environmental covariables. We show how factorial regression models can be generalized to make also QTL expression dependent on environmental covariables. As an illustrative example, we reanalyzed yield data from the North American Barley Genome Project. QTL by environment interaction for yield, as identified at the 2H chromosome could be described as QTL expression in relation to the magnitude of the temperature range during heading.
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Studies involving the effects of single genes on quantitative traits may involve closed populations, selection may be practiced, and the quantitative trait of concern may also be influenced by background genes that are inherited in a polygenic manner. It is shown analytically that analysis of such data by ordinary least squares, the usual method of analysis, can lead to finding an excess of spurious significant effects of single genes, when no effect exists, for both randomly and directionally selected populations and can lead to bias in estimates of single-gene effects when selection has been practiced. The bias depends on heritability of the polygenic effects on the trait, selection intensity, mode of inheritance, magnitude of gene effect, gene frequency, and data structure. It is argued that when genotypes of individuals can be identified for all individuals with observations on the trait, use of mixed-model procedures under an animal model treating single-gene effects as fixed effects can provide unbiased estimates of single-gene effects and exact tests of associated hypotheses for pedigreed populations, even when selection is practiced. Results are illustrated through computer simulation.
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Although using hourly weather data offers the greatest accuracy for estimating growing degree-day values, daily maximum and minimum temperature data are often used to estimate these values by approximating the diurnal temperature trends. This paper presents a new empirical model for estimating the hourly mean temperature. The model describes the diurnal variation using a sine function from the minimum temperature at sunrise until the maximum temperature is reached, another sine function from the maximum temperature until sunset, and a square-root function from then until sunrise the next morning. The model was developed and calibrated using several years of hourly data obtained from five automated weather stations located in California and representing a wide range of climate conditions. The model was tested against an additional data-set at each location. The temperature model gave good results, the rootmean-square error being less than 2.0 degrees C for most years and locations. The comparison with published models from the literature showed that the model was superior to the other methods. Hourly temperatures from the model were used to calculate degree-day values. A comparison between degree-day estimates determined from the model and those obtained other selected methods is presented. The results showed that the model had the best accuracy in general regardless of the season.
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Four major genes in wheat (Triticum aestivum L.), with the dominant alleles designated Vrn-A1, Vrn-B1, Vrn-D1, and Vrn4, are known to have large effects on the vernalization response, but the effects on cold hardiness are ambiguous. Near-isogenic experimental lines (NILs) in a Triple Dirk (TD) genetic background with different vernalization alleles were evaluated for cold hardiness. Although TD is homozygous dominant for Vrn-A1 (formerly Vrn1) and Vrn-B1 (formerly Vrn2), four of the lines are each homozygous dominant for a different vernalization gene, and one line is homozygous recessive for all four vernalization genes. Following establishment, the plants were initially acclimated for 6 weeks in a growth chamber and then stressed in a low temperature freezer from which they were removed over a range of temperatures as the chamber temperature was lowered 1.3 degrees C h(-1). Temperatures resulting in no regrowth from 50% of the plants (LT(50)) were determined by estimating the inflection point of the sigmoidal response curve by nonlinear regression. The LT(50) values were -6.7 degrees C for cv. TD, -6.6 degrees C for the Vrn-A1 and Vrn4 lines, -8.1 degrees C for the Vrn-D1 (formerly Vrn3) line, -9.4 degrees C for the Vrn-B1 line, and -11.7 degrees C for the homozygous recessive winter line. The LT(50) of the true winter line was significantly lower than those of all the other lines. Significant differences were also observed between some, but not all, of the lines possessing dominant vernalization alleles. The presence of dominant vernalization alleles at one of the four loci studied significantly reduced cold hardiness following acclimation.
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Vernalization, the requirement of a long exposure to low temperatures to induce flowering, is an essential adaptation of plants to cold winters. We have shown recently that the vernalization gene VRN-1 from diploid wheat Triticum monococcum is the meristem identity gene APETALA1, and that deletions in its promoter were associated with spring growth habit. In this study, we characterized the allelic variation at the VRN-1 promoter region in polyploid wheat. The Vrn-A1a allele has a duplication including the promoter region. Each copy has similar foldback elements inserted at the same location and is flanked by identical host direct duplications (HDD). This allele was found in more than half of the hexaploid varieties but not among the tetraploid lines analyzed here. The Vrn-A1b allele has two mutations in the HDD region and a 20-bp deletion in the 5' UTR compared with the winter allele. The Vrn-A1b allele was found in both tetraploid and hexaploid accessions but at a relatively low frequency. Among the tetraploid wheat accessions, we found two additional alleles with 32 bp and 54 bp deletions that included the HDD region. We found no size polymorphisms in the promoter region among the winter wheat varieties. The dominant Vrn-A1 allele from two spring varieties from Afghanistan and Egypt ( Vrn-A1c allele) and all the dominant Vrn-B1 and Vrn-D1 alleles included in this study showed no differences from their respective recessive alleles in promoter sequences. Based on these results, we concluded that the VRN-1 genes should have additional regulatory sites outside the promoter region studied here.
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The broad adaptability of wheat and barley is in part attributable to their flexible growth habit, in that spring forms have recurrently evolved from the ancestral winter growth habit. In diploid wheat and barley growth habit is determined by allelic variation at the VRN-1 and/or VRN-2 loci, whereas in the polyploid wheat species it is determined primarily by allelic variation at VRN-1. Dominant Vrn-A1 alleles for spring growth habit are frequently associated with mutations in the promoter region in diploid wheat and in the A genome of common wheat. However, several dominant Vrn-A1, Vrn-B1, Vrn-D1 (common wheat) and Vrn-H1 (barley) alleles show no polymorphisms in the promoter region relative to their respective recessive alleles. In this study, we sequenced the complete VRN-1 gene from these accessions and found that all of them have large deletions within the first intron, which overlap in a 4-kb region. Furthermore, a 2.8-kb segment within the 4-kb region showed high sequence conservation among the different recessive alleles. PCR markers for these deletions showed that similar deletions were present in all the accessions with known Vrn-B1 and Vrn-D1 alleles, and in 51 hexaploid spring wheat accessions previously shown to have no polymorphisms in the VRN-A1 promoter region. Twenty-four tetraploid wheat accessions had a similar deletion in VRN-A1 intron 1. We hypothesize that the 2.8-kb conserved region includes regulatory elements important for the vernalization requirement. Epistatic interactions between VRN-H2 and the VRN-H1 allele with the intron 1 deletion suggest that the deleted region may include a recognition site for the flowering repression mediated by the product of the VRN-H2 gene of barley.
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Ambiguous germplasm identification; difficulty in tracing pedigree information; and lack of integration between genetic resources, characterization, breeding, evaluation, and utilization data are constraints in developing knowledge-intensive crop improvement programs. To address these constraints, the International Crop Information System (www.icis.cgiar.org), a database system for the management and integration of global information on genetic resources and crop improvement for any crop, was developed by genetic resource specialists, crop scientists, and information technicians associated with the Consultative Group for International Agricultural Research and collaborative partners. The International Rice Information System (www.iris.irri.org) is the rice (Oryza species) implementation of the International Crop Information System. New components are now being added to the International Rice Information System to handle the diversity of rice functional genomics data including genomic sequence data, molecular genetic data, expression data, and proteomic information. Users access information in the database through stand-alone programs and Web interfaces, which offer specialized applications and customized views to researchers with different interests.
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A doubled haploid population constructed from a cross between the South Australian wheat cultivars 'Trident' and 'Molineux' was grown under winter field conditions, under field conditions over summer and under artificial light both with and without vernalisation. The duration from planting to ear-emergence was recorded and QTL associated with heading date were detected using a previously constructed genetic linkage map. Associations were shown with chromosomal regions syntenous to previously identified photoperiod (Ppd-B1) and vernalisation (Vrn-A1) sensitive loci. Additional QTL associated with time to heading were also identified on chromosomes 1A, 2A, 2B, 6D, 7A and 7B. Comparisons between the genetic associations observed under the different growing conditions allowed the majority of these loci to be classified as having either photoperiod-sensitive, vernalisation-sensitive or earliness per se actions. The identification of a photoperiod-sensitive QTL on chromosome 1A provides evidence for a wheat gene possibly homoeologous to Ppd-H2 previously identified on chromosome 1H of barley. The occurrence of a putative major gene for photoperiod sensitivity observed on chromosome 7A is presented. The combined additive effects at these loci accounted for more than half the phenotypic variance in the duration from planting to ear-emergence in this population. The possible role of these loci on the adaptation of wheat in Australia is discussed.
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Ppd-D1 on chromosome 2D is the major photoperiod response locus in hexaploid wheat (Triticum aestivum). A semi-dominant mutation widely used in the "green revolution" converts wheat from a long day (LD) to a photoperiod insensitive (day neutral) plant, providing adaptation to a broad range of environments. Comparative mapping shows Ppd-D1 to be colinear with the Ppd-H1 gene of barley (Hordeum vulgare) which is a member of the pseudo-response regulator (PRR) gene family. To investigate the relationship between wheat and barley photoperiod genes we isolated homologues of Ppd-H1 from a 'Chinese Spring' wheat BAC library and compared them to sequences from other wheat varieties with known Ppd alleles. Varieties with the photoperiod insensitive Ppd-D1a allele which causes early flowering in short (SD) or LDs had a 2 kb deletion upstream of the coding region. This was associated with misexpression of the 2D PRR gene and expression of the key floral regulator FT in SDs, showing that photoperiod insensitivity is due to activation of a known photoperiod pathway irrespective of day length. Five Ppd-D1 alleles were found but only the 2 kb deletion was associated with photoperiod insensitivity. Photoperiod insensitivity can also be conferred by mutation at a homoeologous locus on chromosome 2B (Ppd-B1). No candidate mutation was found in the 2B PRR gene but polymorphism within the 2B PRR gene cosegregated with the Ppd-B1 locus in a doubled haploid population, suggesting that insensitivity on 2B is due to a mutation outside the sequenced region or to a closely linked gene.
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Early maturity has been one of the important breeding objectives in wheat (Triticum aestivum L.) in the southwestern part of Japan, because this trait is suitable for double cropping with summer crops such as rice, and for avoiding pre-harvest sprouting which often occurs in the rainy season. However, early maturing cultivars are usually spring type cultivars which are prone to sustain frost damage in early spring because of their earliness in ear primordia initiation and stem elongation. To develop early maturing wheat cultivars with tillers that can avoid frost damage, winter type near-isogenic lines were bred for the extremely earlJ maturing spring cultivars Asakazekomugi and Salkal l07 (latel reg Istered as "Abukumawase") by backcrosslng to a winter type cultivar Ebisukomugi (Fig. l).
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Cereal production is strongly influenced by flowering date. Wheat (Triticum aestivum L.) models simulate days to flower by assuming that development is modified by vernalization and photoperiodism. Cultivar differences are parameterized by vernalization requirement, photoperiod sensitivity, and earliness per se. The parameters are usually estimated by comparing simulations with field observations but appear estimable from genetic information. For wheat, the Vrn and Ppd loci, which affect vernalization and photoperiodism, were logical candidates for estimating parameters in the model CSM-Cropsim-CERES. Two parameters were estimated conventionally and then re-estimated with linear effects of Vrn and Ppd. Flowering data were obtained for 29 cultivars from international nurseries and divided into calibration (14 locations) and evaluation (34 locations) sets. Simulations with a generic cultivar explained 95% of variation in flowering for calibration data (10 d RMSE) and 89% for evaluation data (10 d RMSE), indicating the large effect of environment. Nonetheless, for the calibration data, the gene-based model explained 29% of remaining variation, and the conventional model, 54%. For the evaluation data, the gene-based model explained 17% of remaining variation, and the conventional model, 27%. Gene-based prediction of wheat phenology appears feasible, but more extensive genetic characterization of cultivars is needed.
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The photoperiod sensitivity gene Ppd-D1 and the vernalisation genes Vrn-A1, Vrn-B1, and Vrn-D1 are known to contribute to optimal adaptation to specific environments. Diagnostic molecular markers for detecting important alleles of these genes are now available, including for 2 distinct spring alleles of Vrn-A1 (a and b). As a first step for determining the relative importance of these alleles, they were characterised in Australian cultivars released from the late 19th until the early 21st Century. The photoperiod-insensitive Ppd-D1a allele did not occur in the Australian cultivars we assessed until after the release of cultivars containing CIMMYT germplasm in 1973. Thereafter, this allele became common; however, cultivars with an alternative, presumably photoperiod- sensitive, allele have continued to be released for all parts of the Australian wheatbelt, including for latitudes less than 28S. In contrast to other parts of the world, Vrn-A1b was frequent in cultivars released during the first 70 years of the 20th Century and is still present in modern cultivars. Before the use of CIMMYT germplasm, the spring allele of Vrn-B1 and the winter allele of Vrn-D1 were common. Four major combinations of alleles of these major genes were identified in modern cultivars: first, those similar to WW15 (Anza), with the Ppd-D1a allele, the spring Vrn-A1a allele, and winter alleles at Vrn-B1 and Vrn-D1; second, those similar to Spear or Kite, with the alternative, photoperiod-sensitive allele at Ppd-D1, the spring Vrn-A1a allele, the spring Vrn-B1a allele, and the winter allele at Vrn-D1; third, those similar to Pavon F 76, with the Ppd-D1a allele, the winter allele at Vrn-A1, and the spring alleles at Vrn-B1 and Vrn-D1; fourthly, those similar to Gabo, with the winter allele at Vrn-A1, the spring allele at Vrn-B1, the winter allele at Vrn-D1, but the Ppd-D1a allele. Other combinations were found, including those for winter cultivars and those for early heading cultivars. A hypothesis was suggested for the facultative cv. Oxley. Evidence was presented to suggest that modern full-season cultivars head ∼1 week earlier in a Mallee environment than cultivars from the late 19th Century.
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Production of wheat of sufficient quality to meet market demands is an ongoing agricultural challenge. Identification and evaluation of alleles of genes affecting quality parameters enables breeders to improve their germplasm by active selection towards specific allele combinations. Using a large dataset obtained from southern Australian wheat breeding programs, and including a relationship matrix in the analysis to minimise bias, we re-evaluated the effects of high- and low-molecular-weight glutenin alleles and puroindoline alleles on the grain quality parameters Rmax, dough extensibility, dough development time, flour water absorption, and milling yield and found that estimated effects were in close agreement with those from earlier analyses without a relationship matrix. We also evaluated, for the first time, the effects on the same quality parameters of 2 alleles (wild-type and null) of a defence grain protein, a serpin located on chromosome 5B. In addition, we assessed the effect of the VPM1 alien segment. The serpin null allele significantly reduced milling yield by ∼0.4g of flour per 100g of grain milled across different germplasm sources and flour protein levels. In Australian germplasm, the origin of this allele was traced to a 19th Century introduction from India by William Farrer; however other sources, of significance in international breeding programs, were also identified. Our analysis of the effect of the VPM1 segment on quality traits revealed no detrimental effects of its presence on the traits we measured.
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Milling yield, maximum dough resistance (Rmax), dough extensibility, flour protein concentration (flour protein), particle size index (PSI), water absorption, and dough development time are important determinants of grain quality and are routinely evaluated in Australian wheat breeding programs. Information on allelic variation at the 6 loci determining glutenin proteins is also regularly obtained and used to predict Rmax and extensibility. For each character, except dough development time, 4029 observations on 2377 lines and 94 environments were analysed to estimate genotypic and environmental variances, heritabilities, genotypic and environmental correlations, and the effects of glutenin genes. A subset was analysed for dough development time. Milling yield, Rmax, extensibility, PSI, water absorption, and dough development time had intra-class correlation coefficients, or broad-sense heritabilities, between 0.66 and 0.76, and extensibility had a value of 0.52, with flour protein at 0.36. Genotypic and environmental correlations between extensibility and flour protein were high at +0.78 and +0.85, respectively. Rmax had a genotypic correlation with dough development time of +0.67, which was substantially due to pleiotropic effects of glutenin genes. Rmax, extensibility, PSI, and dough development time were influenced by glutenin genes. For Rmax about 50% of the genotypic variance could be explained by glutenin genes. For extensibility about 50% could be explained by flour protein, with 50% of the remainder by the inclusion of glutenin genes. For dough development time about 15% could be explained by flour protein, with a further 30% by glutenin genes. For PSI, about 40% of the genotypic variation could be accounted for by glutenin genes after the removal of the effects of flour protein and milling yield. We concluded that dough development time could be added to Rmax and extensibility as a trait that can be usefully predicted by the glutenin genes, but more work is required for PSI.
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The effects of genes in self-pollinated crops are usually estimated from designed experiments where selection is minimised. In this study, we used a large, but unbalanced, dataset from a barley breeding program to estimate the effects of the Ha2, Ha4, and sdw1 genes on grain yield, grain weight, grain protein, malt extract, and diastatic power. The Ha2 and Ha4 genes for resistance to cereal cyst nematode were under intense selection pressure, whereas the sdw1 gene, which reduces plant height, was under mild selection pressure.From a mixed-model analysis of mainly F5-derived lines over 5 years, resistance due to the Ha2 gene was found to increase grain yields at 2 sites where the nematode was expected to be present, but not at 3 other sites. There was no significant effect of Ha4 on grain yield. Because of selection, data from later stages of evaluation were not useable for Ha2 or Ha4. From analyses of both early stage and later stages of evaluation, the semi-dwarf allele of the sdw1 gene increased grain yields at high-yielding sites, but decreased yields at low-yielding sites. The semi-dwarf allele reduced grain weight. The effects of Ha2 or Ha4 on malt extract and diastatic power were not significant, but the semi-dwarf allele at sdw1 reduced grain protein.We concluded that plant breeding data can be used to successfully estimate the effects of important genes, with bias due to selection minimised by the use of data from appropriate stages of selection and the use of appropriate statistical models.
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Relations between the growth intervals in wheat and meteorological variables were defined from time-of-sowing field experiments. The major factors affecting the duration of each interval were the date of sowing, the day-degrees of maximum air temperature and daylength. Equations to predict the number of days in a growth interval were tested against measurements made in other wheat growing districts. The relations between day-degrees of maximum air temperature and sowing date gave best predictions of the growth intervals in various districts. The data have application for estimating flowering dates and potential yield, and for estimating harvest dates.
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Seven Australian wheat varieties were compared with six Mexican and four European spring wheats for the influence of sowing date on time to ear emergence in the field. Their sensitivities to daylength and vernalization were compared in a glasshouse experiment. The Australian varieties were intermediate in their response to daylength. Those suited to early autumn sowing depended on their vernalization sensitivity to delay ear emergence past the frost-liable period in the spring. The European varieties, with no vernalization response, were also suited to early sowing, the delay of ear emergence depending entirely on their high sensitivity to daylength. The Mexican varieties, with nil or small vernalization response and a low sensitivity to daylength developed too rapidly for early sowing, but were more suited to late sowing than the Australian varieties.
Article
Many varieties of wheat (Triticum spp.) and barley (Hordeum vulgare L.) require prolonged exposure to cold during winter in order to flower (vernalization). In these cereals, vernalization-induced flowering is controlled by the VERNALIZATION1 (VRN1) gene. VRN1 is a promoter of flowering that is activated by low temperatures. VRN1 transcript levelsincreasegraduallyduringvernalization,withlongercoldtreatmentsinducinghigherexpressionlevels.ElevatedVRN1 expression is maintained in the shoot apex and leaves after vernalization, and the level of VRN1 expression in these organs determineshowrapidlyvernalizedplants flower.SomeallelesofVRN1areexpressedwithoutvernalizationduetodeletions or insertions within the promoter or first intron of the VRN1 gene. Varieties of wheat and barley with these alleles flower without vernalization and are grown where vernalization does not occur. The first intron of the VRN1 locus has histone modificationstypically associated withthe maintenance of aninactive chromatin state, suggesting this region is targeted by epigeneticmechanismsthatcontributetorepressionofVRN1beforewinter.Othermechanismsarelikelytoactelsewherein the VRN1 gene to mediate low-temperature induction. This review examines how understanding the mechanisms that regulateVRN1providesinsightsintothebiologyofvernalization-induced floweringincerealsandhowthiswillcontributeto future cereal breeding strategies.
Article
Grain hardness is a major determinant of the classification and end-use of wheat. Two genes, Pina-D1 and Pinb-D1, have a major effect on this trait, so for wheat breeding programs it is important to identify the alleles of these genes present in elite germplasm. This study was conducted to identify the alleles present in southern Australian germplasm, and to determine if they affected quality characteristics other than grain hardness.Only 3 genotypes were identified. These were Pina-D1a/Pinb-D1a producing soft grain, Pina-D1a/Pinb-D1b producing moderately hard grain, and Pina-D1b/Pinb-D1a producing very hard grain. WW15 was the probable source of Pina-D1a/Pinb-D1b in most cultivars; however, Halberd represented another source. An important source of Pina-D1b/Pinb-D1a was the CIMMYT line Pavon, with sources from the old Australian cultivars Gabo and Falcon probably still present in modern germplasm.In an analysis of grain quality data from the Victorian Institute for Dryland Agriculture breeding program, the Pina-D1b/Pinb-D1a genotype had a significantly higher water absorption and significantly lower milling yield than the Pina-D1a/Pinb-D1b genotype, which indicates that these genes will impede the development of hard-grained cultivars that combine high water absorption and high milling yield.
Article
Sowing date, sowing rate and row spacing effects were studied on high input crops at Griffith, N.S.W., between 1983 and 1985 using 25 bread wheats (Triticum aestivum L.) and 3 triticales (X Triticosecale Wittmack). The aim was to identify improved management practices and genotypes through a better understanding of development and growth of irrigated wheat grown under high-yielding conditions. The genotypes were chosen to represent a wide range in genetic background, maturity and stature. Growing period durations were between 208 days and 100 days for early April and mid-August sowings, respectively, with differences in anthesis dates within sowing dates of up to 45 days. Genotypes were classified into six major maturity groups. There was no maturity type that could flower close to 1 October from a wide range of sowing dates since anthesis was delayed by 0.3 to 0.5 days per 1-day delay in sowing. Increased daylength sensitivity tended to delay anthesis relative to the timing of floral initiation and terminal spikelet formation. The end of tillering was generally associated with the attainment of 50-60% light interception rather than a given development stage of the inflorescence. Spike density was not closely related to maximum tiller number but depended on genotype, environment and plant density. Leaf appearance rate was influenced by environment and genotype, but was independent of spike development. For a given final leaf number, internode elongation started at a later leaf number for later sowing dates, resulting in reductions in both node number and height. Crop height decreased by up to 5 cm per 1-week delay in anthesis date. The period of full light interception decreased from 133 days to 43 days between April and August sowings, respectively. The timing of reproductive development determined the green area duration, but the initial development and size of the canopy was less affected by it, because of adjustments in number and type of tillers, and size and thickness of leaves. The development and maintenance of an adequate canopy was not restricted by earliness, shortness or low sowing rates (50 kg seed/ha) for April-July sowing dates.
Article
A whole crop computer simulation model of winter wheat has been written in FORTRAN and used to simulate the growth of September- and October-sown crops of Hustler wheat at Rothamsted for the years 1978–9, 1979–80 and 1980–1. Results of the simulations, which are for crops with adequate water and nutrients, are compared with observations from experiments at Rothamsted. The model uses daily maximum and minimum temperatures and daylength to calculate the dates of emergence, double ridge, anthesis and maturity of the crops and the growth and senescence of tillers and leaves. In the simulations, the canopy intercepts daily radiation and produces dry matter that is partitioned between roots, shoots, leaves, ears and grain. Partial simulations, using observed LAI values, produced dry matter in close agreement with observations of late-sown crops, but consistently overestimated the total dry-matter production of the early-sown crops. Full simulation described satisfactorily the average difference in dry-matter production to be expected with changes in time of sowing, but did not give as close correspondence for individual crops. A grain growth submodel, that linked maximum grain weight to average temperatures during the grain growth period, correctly simulated the observed growth of individual grains in the 1981 crop. The benefits to be obtained by combining whole crop modelling with detailed crop observations are discussed.
Article
This chapter describes the genetics and physiology of vernalization response in wheat. Vernalization is generally considered to be affected by temperatures of 10°C or less, although the upper limit has not been critically established. It is generally considered that the weaker the vernalization response, the higher the vernalizing temperature necessary for maximum rate of vernalization. The vernalization process in partially devernalized seeds has been shown to be more rapid than in plants receiving just an original vernalization treatment. An important aspect of the vernalization process in wheat is the change in response of plants as they age. It is found that wheat was responsive to vernalization in 2- to 44-day-old plants, but the older the plant was, the shorter was the period of cold treatment necessary for vernalization to be satisfied. It is observed that spring wheat has little or no vernalization response and a winter wheat has a strong response. The use of intervarietal chromosome substitution lines in hexaploid wheat has facilitated the location to specific chromosome of genes that influence vernalization response. The interactions between genes for growth habit or vernalization response are also elaborated.
Article
Geographical variation of growth habit was studied for 749 landraces from various parts of the world, with special reference to their adaptation and ecogeographical differentiation. The total frequency of spring-type landraces was 49.9%, and varied between localities. Spring-type landraces were frequent in two distinct areas where the average January temperature was either below -7°C or above 4°C, with winter-type landraces in areas from -7°C to 4°C. These results indicated that geographical variation of growth habit is closely related to the degree of winter coldness. An analysis of the Vrn genotype for 216 spring-type landraces demonstrated the uneven distribution of four Vrn genes, with Vrn4 being the least frequent. The adaptive Vrn genotype was different between localities. Genotypes carrying Vrn-A1 and additional Vrn gene(s) were frequent in two distinct areas where the average January temperature was either below -7°C or over 10°C, while genotypes with any of three Vrn genes, except Vrn-A1, adapted to areas with temperatures from 4°C to 10°C. Therefore, it was concluded that the adaptability of wheat landraces differed depending on their growth habit and Vrn genotype, and that ecotypes with different Vrn genotypes were allopatrically distributed as a result of adaptation to different winter temperature. However, the differential distribution of Vrn-B1, Vrn-D1 and Vrn4 could not be explained by their adaptability, and might reflect the polyphyletic origin of common wheat.
Article
The Vrn1, Vrn2 and Vrn3 genes have different values of effects on heading date and related yield components. The genetic background and environment do not affect the ranking of Vrn genotypes according to earliness within near-isogenic line sets; however, they do influence the level of differences between heading dates of particular genotypes and between effect values, respectively. The frequencies of defined Vrn genotypes in the global set of spring bread wheat cultivars are associated with grain weight per plant predicted on the basis of Vrn gene effects averaged over backgrounds and over environments. Peculiarities of backgrounds and environments alter the grain yield ranges of Vrn genotypes. For early photoperiod-insensitive wheats, planted in stress conditions at grain filling, the highest yield was predicted for double dominant Vrn genotypes with Vrn3. This gene is rarely used by the breeders in middle latitudes and its wider adoption is encouraged.