Published by Springer Nature
Online ISSN: 1573-5060
Learn more about this page
Recent publications
Multi-environment trials (MET) are fundamental for assessing genotype-by-environment interaction (GxE) effects, adaptability and stability of genotypes and provide valuable information about target regions. As such, a MET involving grain sorghum hybrid combinations derived from elite inbred lines adapted to diverse sorghum production regions was developed to assess agronomic performance, stability, and genomic-enabled prediction accuracies within mega-environments (ME). Ten females and ten males from the Texas A&M and Kansas State sorghum breeding programs were crossed following a factorial mating scheme to generate 100 hybrids. Grain yield, plant height, and days to anthesis were assessed in a MET consisting of ten environments across Texas and Kansas over two years. Genotype plus Genotype-by-block-of-environment biplot (GGB) assessed ME, while the "mean-vs-stability" view of the biplot and the Bayesian Finlay–Wilkinson regression evaluated hybrid adaptability and stability. A genomic prediction model including the GxE effect was applied within ME to assess prediction accuracy. Results suggest that grain sorghum hybrid combinations involving lines adapted to different target regions can produce superior hybrids. GGB confirmed distinct regions of sorghum adaption in the U.S. Further, genomic predictions within ME reported inconsistent results, suggesting that additional effects rather than the correlations between environments are influencing genomic prediction of grain sorghum hybrids.
Phytic acid (PA) is an important antinutritional component in maize that affects the availability of major micro-nutrients like di- and multi-valent mineral cations like iron (Fe) and zinc (Zn). The long-term consumption of maize as a staple food crop leads to micronutrient malnutrition especially iron and zinc deficiency in the human population. In addition, it also acts as a storehouse of a major part of mineral phosphorous (P), approximately 80% of the total P stored as phytate P is not available to mono-gastric animals like humans and poultry birds, and it gets excreted as such, leading to one of the major environmental pollution called eutrophication. Of the various low phytic acid (lpa) mutants, lpa2-2 generated through mutagenesis reduces PA by 30%. BML 6 and BML 45, the parents of the popular maize hybrid DHM 121 with high PA were selected to introgress lpa2-2 through marker-assisted backcross breeding (MABB). The percent recurrent parental genome (RPG) in the selected BC2F2 plants ranged from 88.68 to 91.04% and 90.09–91.51% in the genetic background of BML 6 and BML 45, respectively. Based on the highest percentage of RPG, best five BC2F2 plants, viz., #3190, #3283, #3230, #3263 and #3292 with RPG 88.68–91.04% in the genetic background of BML 6 and #3720, #3776, #3717, #3828 and #3832 with RPG 90.09–91.51% in the genetic background of BML 45 were advanced to BC2F3. The newly developed near-isogenic lines (NILs) possessed low phytate content (2.37 mg/g in BML 6 and 2.40 mg/g in BML 45) compared to 3.59 mg/g and 3.16 mg/g in recurrent parents BML 6 and BML 45, respectively thereby reducing the phytate by an average of 34 and 24 per cent, respectively. These newly developed progenies were similar to their recurrent parents for various morphological traits. These inbreds assume great significance in alleviating Fe and Zn deficiencies in worldwide.
Relationships between yield components and lint yield are complicated because of interrelationships among them. Traditionally, the exploration of these interrelationships was analyzed by path coefficients which requires a priori knowledge of the cause and effect relationships. Commonality analysis is a method of multiple regression to dissect the total effects of yield components to yield into direct effects and indirect effects. This study was designed to dissect relationships of yield components to yield based on commonality analysis and determine correlated selection responses of yield to selections of different yield components. Selections were made within 300 F3 plants in 2017 for the top seventy-five plants by LP and six within-boll yield components, lint weight per seed, seeds per boll, seed surface area, lint weight per fiber (LWF), lint weight per unit seed surface area, and lint number per unit seed surface area. F4 progenies were evaluated in field with two replicates in 2018. Direct coefficients of the seven single yield components ranged from 0.00 to 0.18 with LP as the largest contributor. Indirect coefficients of multiple components ranged from − 0.04 to 0.08. Five single yield components and five multiple yield components were chosen for selections based on their relatively large coefficients to yield. The correlated selection response (CR) of lint yield, 1684 kg ha⁻¹, in F4 was significantly positive to selections by LP, but the CR of seed size and fiber length was negative to the selection by LP. The CR of lint yield, 1769 kg ha⁻¹, to selections by multiple yield components of LP-LWF, had 5% increase compared with the selection by LP alone. There was no significant CR of seed size and fiber length to these selections. This study was a first application of commonality analysis in crop breeding and results provide evidence for its feasibility in exploration of interrelationships among yield components in breeding.
Crossbreeding within narrow genetic resources increases the homozygosity of the offspring. Resultant inbreeding depression can reduce the yield potential of the offspring. Slow progress in breeding programs because of inbreeding has been suggested in persimmon (Diospyros kaki Thunb.), but quantitative evidence has been limited. Here we assessed how inbreeding affects a population’s yield-related traits by using sequence-based genotyping. To find a reliable inbreeding estimation method that considers persimmon’s hexaploidy, we screened nine marker-based inbreeding estimators (FM) and various read-depth thresholds for genotype calling; the results suggested that the Loiselle–Huang (LH) FM and a read-depth threshold of 10 were optimal. After validating 11,379 variant sites selected under the optimal read-depth threshold, we calculated the LH FM of 97 breeding populations by using the dosage genotypes of 47 cross parents. In these populations, LH FM successfully identified the less inbred populations and confirmed that the inbreeding level was significantly reduced by a pseudo-backcross strategy designed to widen the genetic diversity of the breeding population. In regression analyses using mean phenotypic value and LH FM of the 97 populations as response and explanatory variables, respectively, we detected significant reductions of fruit weight, yield, and tree vigor at the first fruit-bearing age, and delay of the first fruit-bearing age itself as inbreeding progressed; the other eight FM showed similar trends. These results indicate that inbreeding depression occurs in yield-related traits in persimmon and that employing FM would help breeders increase the chance of developing less inbred cultivars with higher yield potential.
Convergence for the genotypic variance of the six characteristics analyzed in the multi-trait model. The numbers on the right refer to the posterior density of the genetic variance estimates. The numbers on the left refer to Markov Chains for genetic variance estimates. GY: grain yields (Kg ha.⁻¹); GL: grain length (mm); GW: grain width (mm); GT: grain thickness (mm); GLW: grain length and width ratio; GWH: 100 grain weight (g)
Genetic selection considering the selection intensity of 60% (15 genotypes). The green dotted line indicates the flood irrigated rice genotypes. Outside the red line are the selected genotypes. E: environments E1, E2, and E3, respectively
The objectives of this study were to use a bayesian multi-trait model, estimate genetic parameters, and select flood-irrigated rice genotypes with better genetic potentials in different evaluation environments. For this, twenty-five rice genotypes and six traits belonging to the flood-irrigated rice improvement program were evaluated. The experimental design used in all experiments was a randomized block design with three replications. The Monte Carlo Markov Chain algorithm estimated genetic parameters and genetic values. The grain thickness trait was considered highly heritable, with a credibility interval ranging from: h2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${h}^{2}$$\end{document}: 0.9480; 0.9440; 0.8610, in environments 1, 2, and 3, respectively. The grain yields showed a weak correlation estimate between grain thickness and 100-grain weight, in all environments, with a credibility interval ranging from (ρ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\rho$$\end{document}= 0.5477; 0.5762; 0.5618 and 0.5973; 0.5247; 0.5632, grain thickness and 100-grain weight, in environments 1, 2, and 3, respectively). The Bayesian multi-trait model proved to be an adequate strategy for the genetic improvement of flood-irrigated.
Nei's diversity index (He) for the all accession, landraces, Moroccan cultivars, and North American cultivars
Combining improved grain yield and end-product quality in durum wheat has become an essential priority for Moroccan breeding programs due to their significant effect on the country's agricultural economy and social system. Landraces and cultivars of distinct germplasm pools constitute an untapped source of genetic variation for durum wheat improvement. To this end, a mixture of genotypes consisting of 35 landraces (LAN), 20 North American cultivars (NAC) and 10 Moroccan cultivars (MC), was evaluated using grain weight and grain size parameters, quality characteristics, and 21 functional molecular markers. Significant genetic variability was revealed between the genotypes. According to observed means across traits, MC showed the best grain characteristics, followed by NAC, and LAN. However, NAC showed overall better physiochemical characteristics. Genetic diversity applying quality trait-based markers increased from LAN to advanced cultivars. Favorable alleles Lpx-B1.1b (Lpx-B1.1), Hap-4A-T (TaCwi-4A), TaGS5-A1b (TaGS5-A1) were predominant in NAC. Unfavorable alleles, namely Psy1-B1a (Psy1-B1), Psy-B1a or b (Psy-B1), Lox-B1a (Lox-B1), Hap- 4A-C (TaCwi-4A), TaGS5-A1a (TaGS5-A1), TaTGW6-b (TGW6-4A), Hap-L (TaSus2), and TaTGW6-A1b (TGW6), were most frequent or even omniprevalent in all genotypes. This work can up open new avenues for the development of new varieties allying yield and grain quality by introducing suitable genotypes and favorable alleles into Moroccan national breeding programs.
Fruits of ‘Whangkeumbae’ (a) and ‘Yali’ (b) collected at 93 days after full bloom. The scale bar indicates 2 cm
Phenotype distribution of fruit length (a), diameter (b), and the ratio of fruit length to diameter (L/D ratio) (c) in ‘Whangkeumbae’ × ‘Yali’ at 93 DAFB. The white and black inverted triangles indicate the phenotype of ‘Whangkeumbae’ and ‘Yali’, respectively
Fruit shape-related QTLs in ‘Whangkeumbae’ × ‘Yali’ genetic linkage map. The scale bar on left is genetic distance (cM). Anchored markers are on the right side of each linkage group (LG). Markers black, green, and red are array-SNPs, pear SSRs, and apple SSRs, respectively. Blue bars represent QTLs associated with L/D ratio and left are logarithm of odds (LOD) values. The LOD graphs on right is for fruit length. The dotted line in LOD graphs implies a threshold (p = 0.05). (Color figure online)
High resolution melting (HRM) results of six SNP markers. a CBp06sn01; b CBp06sn02; c CBp07sn01; d CBp12sn01; e CBp12sn02; f CBp12sn03. Red and blue lines are F1 individuals having genotypes of ‘Whangkeumbae’ and ‘Yali’, respectively. (Color figure online)
Fruit shape is one of the important quantitative traits in pear (Pyrus spp.) breeding program, thus genetic study related to fruit shape could be beneficial to pear breeding. Quantitative trait loci (QTL) analysis was carried out using ‘Whangkeumbae’ (P. pyrifolia, round) × ‘Yali’ (P. bretschneideri, pyriform) and high-resolution melting (HRM) markers were developed. The genetic linkage map of ‘Whangkeumbae’ × ‘Yali’ was constructed using single nucleotide polymorphisms (SNPs) derived from Axiom Pear 70 K Genotyping Array and simple sequence repeats. The integrated genetic linkage map of ‘Whangkeumbae’ × ‘Yali’ showed ~ 90% of genome coverage, a total genetic distance of 998.2 cM, and a marker density of 1.6 cM. F1 progenies of ‘Whangkeumbae’ × ‘Yali’ showed normal distribution of fruit length (L), diameter (D), and L/D ratio. Three QTLs located in linkage group (LG) 6, 7, and 12 were identified with LOD thresholds of 2.8–3.0. Six HRM markers were developed using array-SNPs anchored in the QTLs and predicted fruit shape with 28.6–65.3% accuracy. Notably, accuracy was increased by ~ 90% using an HRM marker combination consisting of CBp06sn02, CBp07sn01, and CBp12sn03. These results could provide a better understanding of the genetic mechanism of fruit shape development and reducing pear breeding period.
Violin plots of color-related traits of flour and its end-use products
Genetic linkage map of QTLs for the investigated color-related traits on chromosomes 4B and 7B based on the RIL population. Bold indicates a major QTL with more than 10.0% PVE value; red indicates a QTL with positive allele from cv. Shannong 01–35; blue indicates a QTL with negative allele from cv. Gaocheng 9411
The color of flour and its end-use products is an important quality trait of wheat. Understanding the genetic basis of this trait is essential for improving wheat quality. In this study, quantitative trait locus (QTL) mapping for 27 color-related traits of flour, starch, gluten, dough sheet, steamed bread, and baked bread was performed using a population of recombinant inbred lines (RILs) with 173 lines of F9:10, tested in four environments. For this purpose, a high-density genetic map constructed using a 90 K SNP array, Diversity Arrays Technology (DArT) and simple sequence repeat (SSR) markers was used. A total of 43 additive QTLs were detected, including 25 large-effect QTLs, located on chromosomes 1A, 1B, 2A, 4B, 5B, and 7B. Four of these major QTLs, namely QFa7B.7-1, QFb7B.7-2, QFb7B.7-1 and QGb4B.4, made the highest contribution and accounted for 29.60, 29.02, 27.45, and 22.24% of the phenotypic variation, respectively. Six stable QTLs (QSa4B.4, QSl4B.4-1, QFa7B.7-2, QFb7B.7-1, QFb7B.7-2, and QBca7B.7) were detected in more than one environment with high PVE values. In addition, two robust QTL clusters contribution to 13 evaluated traits were identified on chromosomes 4B (RAC875_c27536_611-wsnp_Ku_c28756_38667953) and 7B (wPt-1196-Kukri_c2348_2340). A locus within the interval Ex_c101685_705-RAC875_c27536_611 of 4B also harbored many genes previously reported to affect wheat quality and yield. These detected QTLs may be used for further study and be used to improve wheat quality in wheat-breeding programs.
A SCAR marker, SCAR3007RS, showing polymorphisms in the F2 plants from the cross ‘CGN17397 (resistant)’ × ‘Patriot (susceptible)’. Lane 1: ‘CGN17397’, Lane 2: ‘Patriot’, Lanes 3–6: homozygous for resistance, Lanes 7–10: heterozygous, Lanes 11–14: homozygous for susceptible, M: 100 bp ladder marker
Genetic map of FW2-LG7 (Fusarium Wilt resistance to race 2 on LG7) using an F2 population derived from a cross between ‘CGN17397’ and ‘Patriot’ by AFLP analysis (a), and using an F2 population derived from a cross between ‘CGN17397’ and ‘Salinas’ by fine-mapping with PCR-based markers (b). “FW2-LG7” indicates the position of the causal gene for resistance to Fusarium wilt race 2. Genetic distances (cM) were shown between the markers
The influence of Fusarium wilt in lettuce (Lactuca sativa L.) is becoming increasingly severe under the influence of global warming in tropical and subtropical regions. Previously, we reported on the development of a PCR-based marker, LG1_v8_116.506Mbp, on LG1 for the resistance to Fusarium wilt race 2. This study investigated genetic resources with novel resistance to race 2 using molecular markers for stable lettuce production. Comparing genotypes and phenotypes of the 48 cultivars/lines, it was found that ‘CGN17397’ and ‘2008–11’, which were at first considered to possess the same resistance genes, showed resistant phenotypes but had susceptible genotypes in the marker on LG1. Allelism tests using ten resistant cultivars/lines showed that the resistance derived from ‘CGN17397’ was not located on LG1. Using the two F2 populations derived from ‘CGN17397’, it was clarified that the resistance was controlled by a single semi-dominant gene located at the region between 63.476 Mbp and 66.012 Mbp on LG7, defined by AFLP analysis and fine mapping with PCR-based markers. Of the four markers which showed complete co-segregation with the resistance phenotype, only LG7_v8_65.645Mbp allowed us to identify the resistance genotype by genotyping the 48 cultivars/lines. According to the annotation of the reference genome sequence of ‘Salinas’, the locus for resistance on LG7 had twelve disease resistance gene candidates. The elucidation of underlying resistance mechanisms in the two loci on LG1 and LG7 is of future concern. These results may contribute to accelerating the breeding of Fusarium wilt-resistant cultivars and add understanding to the fundamental mechanisms for resistance to race 2 in lettuce.
Backcrossing scheme for the incorporation of xa13 gene into the CO43 (Gm1, Gm4). * No. of plants selected, # No. of plants genotyped
Genotyping for xa13, Gm1 and Gm4 genes in the selected BC3F3 lines (C39-24–11 and C39-24–127)
Bacterial blight reactions recorded in the parents and selected BC3F3 lines. a susceptible check ADT38, b CO43 (Gm1, Gm4), c B95-1 X Abhaya, d–f BC3F3 lines
Graphical genotypes of the selected BC3F3 lines covering the 12 rice chromosomes
Biotic stresses cause severe yield reductions in rice and are a threat to global food security. Developing resistant cultivars is the most affordable and sustainable approach to handling different biotic stresses. CO43 is an elite rice variety of Tamil Nadu susceptible to gall midge (GM) and bacterial blight (BB). In this regard, the current research was carried out to pyramid a major BB resistance gene xa13 into the background of the improved CO43 carrying two major genes for GM resistance Gm1 and Gm4. The improved CO43 was crossed with the donor line B95-1 X Abhaya, carrying the BB resistance gene xa13 and GM resistance gene Gm4. Marker-assisted backcross breeding was employed to develop three gene-pyramided homozygous BC3F3 lines (Gm1Gm1 + Gm4Gm4 + xa13xa13). Foreground selection was done at every generation using the functional marker xa13-prom for selecting the xa13 gene and the SSR markers RM1328 and RM22550 for targeting the Gm1 and Gm4 genes, respectively. The selected BC3F3 lines were highly resistant to GM and BB. Agronomical and grain quality evaluation of the selected lines led to the identification of two lines, C39-24-11 and C39-24-127 having yield on par with the improved CO43. The selected lines will be further pyramided with additional BB and blast resistance genes to develop improved lines with durable resistance against multiple biotic stresses of rice.
Internode length (IL) is an important characteristic of plant architecture of watermelon (Citrullus lanatus L.). A dwarf type plant phenotype can support the greater planting density and land utilization for well growth of crop plants. In this study, two watermelon lines "W1-1 (standard vine) and ZXG01061 (dwarf vine)” were used as parental lines and F1, F2, BC1P1 and BC1P2 generations were developed for dwarf trait inheritance analysis and candidate gene identification. Genetic analysis of two year's collected phenotypic data indicated that watermelon dwarfism was regulated by a single recessive gene (cladw). Bulked segregant analysis sequencing (BSA-seq) total of 1.24-Mb genomic region harbouring the candidate dwarfism gene on chromosome 9. Fine genetic with 1,097 F2 plants signified that the cladw locus was finally delimited to a 203-kb region containing 10 candidate genes (including five genes annotated as GID1L2 gibberellin (GA) receptors). Endogenous hormone quantification analysis also showed that the internode GA content of ZXG01061 was higher than that of W1-1. When ZXG01061 plants were treated with exogenous application of GA3, then original plant height was not recovered, indicating that ZXG01061 is GA insensitive. Further, Cla010254 and Cla010256 (annotated as gibberellin receptor GID1L2) exhibted base deletions in ZXG01061 compared with W1-1. The expression of Cla010254 in W1-1 was significantly higher than that of ZXG01061. In conclusion, our results indicated that Cla010254 is a candidate gene for regulating the watermelon dwarfism trait.
a Fruit phenotype of two wax gourd (Benincasa hispida) parental lines (XDJQ-1, P1; SL-7, P2). b Cross-section of the fruits of two wax gourd (B. hispida) parental lines (XDJQ-1, P1; SL-7, P2)
High-density genetic map of wax gourd (Benincasa hispida)
Collinearity between the genetic map and GX-19 wax gourd reference genome. The main categorical x-axis represents each of the linkage groups (illustrated using different colours) and main categorical y-axis represents the genome of the 12 chromosomes. Furthermore, within each smaller grey plot, the x-axis represents genetic distance and y-axis represents physical distance. (Color figure online)
Logarithm of odds map of quantitative trait loci for fruit-related traits of wax gourd detected using a composite interval mapping model. Each panel corresponds to a specific fruit-related trait (a, fruit flesh colour; b, fruit length; c, fruit width). (Color figure online)
Wax gourd (Benincasa hispida [Thunb] Cogn.) is an important horticultural crop in the Cucurbitaceae family that has high nutritive and medicinal value. We analysed quantitative trait loci (QTLs) related to the fruit-related traits of wax gourd by constructing a high-density genetic map through whole-genome resequencing. We obtained an F2 population of 195 individuals by crossing two inbred wax gourd lines: XDJQ-1 and SL-7. A high-density genetic map was constructed after generating a sequencing library and identifying and genotyping single-nucleotide polymorphisms (SNPs). Finally, we used QTL mapping to analyse the fruit-related traits of wax gourd. The high-density genetic map showed sufficient coverage to detect recombination breakpoints and contained 323,107 SNP markers, spanned 1243.87 cM, and had an average distance between adjacent markers of 0.33 cM. Furthermore, 3,720 bin markers (including SNP markers) were mapped to 12 linkage groups. Based on the high-density genetic map, one major QTL for fruit flesh colour (fc5.1) was mapped on the 3.379 Mb region of chromosome 5, and two major QTLs for fruit length (fl2.1) and fruit width (fw2.1) were mapped on the (0.345 Mb) and (0.602 Mb) regions of chromosome 2 respectively. The QTLs for fc5.1, fl2.1, and fw2.1 accounted for 28.684%, 63.562%, and 59.979% of wax gourd phenotypic variation, respectively. To our knowledge, ours is the first high-density genetic map of wax gourd constructed using whole-genome resequencing and is the highest density genetic map available for wax gourd. Our results provide a foundation for future map-based cloning, candidate gene identification, and marker-assisted breeding.
Representative images for nineteen wheat varieties 21 days post spray inoculation with Fusarium graminearum isolate A121
Representative images for nineteen wheat varieties 21 days post point inoculation with Fusarium graminearum isolate A121
Spearman’s rank correlation results for different methods used to screen for Fusarium head blight (FHB) resistance 21 days after spray and point inoculation of wheat varieties with Fusarium graminearum isolate A121
Fusarium head blight (FHB) infections do not only result in a decline in wheat production but contribute to mycotoxin contaminated grain. Different FHB resistance sources, both major and minor genes/quantitative trait loci (QTL), are available for deployment. However, FHB resistance breeding is complicated by the quantitative nature of the resistance sources and multiple gene combinations are required for efficient field resistance. In this study three major FHB resistance genes/QTL (Fhb1, Qfhs.ifa-5AS and Qfhs.ifa-5Ac) present in the wheat variety CM82036 were used in a backcross breeding programme and transferred to Krokodil, a South African irrigation spring wheat variety. Experimental wheat lines with different combinations of the three resistance genes/QTL were phenotypically and genotypically characterised. After phenotypic evaluation at 21 days post inoculation, inoculated wheat spikes were subjected to quantitative polymerase chain reaction analysis to quantify the β-tubulin and Tri5 genes relative to the reference translation elongation factor EF-G wheat gene. Phenotypic data revealed lower FHB infection levels for developed wheat lines containing resistance genes/QTL compared to their negative controls. Expected higher β-tubulin:EF-G ratios were obtained for lines containing no resistance genes/QTL. However, low variation between the Tri5:EF-G ratios was observed between wheat varieties. Over entries, the β-tubulin:EF-G ratios were positively correlated with percentage FHB spikelet infection, indicating the usefulness of these methods. Wheat experimental lines with high levels of FHB resistance were identified and can be used as parents in future breeding programmes and for evaluation in field trials.
Backcrossing scheme for the hybridization between Brassica rapa and Eruca vesicaria. Structure of each genome, including progenies and the number of hybrid lines obtained are shown in parenthesis and at the figure bottom
Morphological traits of flowers, buds, petals, habitus, leaves, pods, and chromosomes of intergeneric hybrid BC1F1 and BC2F1 plants obtained from backcrossing with Brassica rapa and Eruca vesicaria. Inflorescences of B. rapa (a), Komeru BC1-2 hybrid (b), and E. vesicaria (c); habitus of Komeru BC1-1 hybrid (d); corolla (e), petal (f), leaf shape (g), placenta (h), and proximal end of a cauline leaf (i) of B. rapa (left), four intergeneric BC1F1 hybrids (center), and E. vesicaria (right) (note that the second plant from left of four intergeneric BC1F1 hybrid plants has an unrolled cauline leaf); pollen tube growth toward ovules of an intergeneric hybrid BC1F1 (j); corollas of B. rapa (left), four BC2F1 hybrids (k), and of another BC2F1 plant (l); determinate inflorescence of a BC2F1 plant (m); leaf shapes of six BC2F1 hybrids (n); and chromosome behavior in metaphase I of a BC2F1 hybrid (o)
Cladogram of totally 89 plants of Brassica rapa, Eruca vesicaria, and their intergeneric hybrid progenies based on taste and morphological traits and constructed using the maximum parsimony algorithm. Each morphological trait was classified into two to four grades, according to its presence/absence, type, or level and was replaced with nucleobase letters A, G, T or C to mimic nucleotide sequences (Kumar et al. 2018). Recurrent parent, B. rapa; nonrecurrent parent, E. vesicaria; F1, Komeru F1 (red); BC1F1, Komeru BC1 (purple); straight cross BC2F1, Komeru BC2 (green); reciprocal cross BC2F1, MKBC1 (blue)
Breeding at both interspecific and intergeneric levels is an effective method for expanding genetic variation of cruciferous crops; however, few commercially accepted varieties have been released because of difficulties in generating fertile progenies. We employed backcross strategy to introduce Eruca vesicaria-specific characteristics into Brassica rapa and successfully obtained four BC1F1 lines that showed a wide range of diversity of morphological traits and glucosinolate (GSL) composition. Thus, leaf shape, anthocyanin coloration, glucoraphanin content, and red petal veins were found to be inherited mainly from E. vesicaria, though most of the morphological characteristics and GSL composition were inherited from intergeneric F1 plants. Since all BC1F1 lines showed post-fertilization barriers, backcrossing with B. rapa was performed and BC2F1 progenies were successfully obtained, which showed diverse morphological characteristics and GSL composition as well as higher regeneration potential. These results suggest that widening of genetic diversity of B. rapa can be achieved through successive reciprocal backcrossing of B. rapa × E. vesicaria hybrids with B. rapa.
French bean is one of the most important staple foods in many parts of the world. Among several bacterial, fungal and viral diseases, anthracnose caused by Colletotrichum lindemuthianum is the most widespread and severe disease of French bean. Therefore, the present study was undertaken as prebreeding effort with the objective of introgression of important bean anthracnose resistance gene Co-4 in elite cultivar. Hybridization between resistant genotype, TO having bean anthracnose resistance gene Co-4 and elite cultivar Arka Komal was done. Cross Arka Komal × TO was further advanced to generate, F1, BC1F1, BC2F1 and BC2F2 plants. Testing of hybridity of the resultant F1, BC1F1, BC2F1 and BC2F2 plants/pods using gene linked SCAR marker SY20 resulted in identification of 46 gene-positive BC2F2. Further foreground selection revealed lack of segregation for the target gene Co-4 in 16 progenies. Screening of these 16 homozygous progenies (Co-4 gene) following detached pod and germinated seed dip methods using race 3 of C. lindemuthianum validated Co-4 imparted resistance in all the 16 BC2F3 progenies. Agronomic evaluation of 16 Co-4 gene-positive BC2F4 progenies for 8 qualitative traits and 9 quantitative traits led to identification of AKTO 4, AKTO 5, AKTO 7 and AKTO 43 progenies as having better elite background. These can either be used as donors of resistance gene for further introgression and gene pyramiding or can further be advanced following backcrossing to develop essentially derived variety of elite parent, Arka Komal.
Kinship, LD decay of the whole population, principal components (PC). (a) Heatmap of kinship matrix of 220 rice accessions using SNPs data. Red indicates the highest correlation between pairs of individuals and yellow indicates the lowest correlation. A hierarchical clustering tree based on the pairwise kinship values for all accessions is displayed along the top and left axes. (b) LD decay of genome-wide association study (GWAS) population, each dot represents LD (r2) between a pair of SNPs, as a function of the distance (in bp). The red line shows the regression used to describe the relationship between the pairwise distance and r2. Significant LD decay was observed in population. (c) population structure of rice germplasm collection as reflected by PCs. 3D Scree plot from GAPIT showing the selection of PC3 against PC1 for association study and results showed three main groups. (d) principal components first two PCs explain 8.5% and 7.4% of the variations, respectively. The third PC explains 2.6% of the variation
Manhattan plots of germination data from GWAS using the MLM model. The-log10 (p values) from the GWAS were plotted according to genomic position on each of the 12 rice chromosome at left side of each Manhattan plot. (a) NDG; (b) RDW; (c) SDW; (d) GP; (e) SL; (f) RL; (g) SFW; (h) RFW
Genome-wide association study (GWAS) has become an accepted and powerful method for understanding the associations between phenotypes and genotypes. In agricultural production, uniform and rapid germination is an important prerequisite in crop production. Here, the genetic diversity of rice (Oryza sativa L.) genotypes was put under scrutiny for germination and post-germination related seedling traits, and a rice GWAS analysis with 33,934 SNPs for eight traits including germination percentage (GP), shoot (SL) and root length (RL), root (RFW) and shoot fresh weight (SFW), root (RDW) and shoot (SDW) dry weight, and number of days to germinate (NDG) was performed to define genomic regions influencing seed germination and post-germination related seedling traits. By GWAS, 52 QTLs tagged to 93 significant trait-associated markers were detected across all rice chromosomes. The detected QTLs explained 5 to 58% of variation of different traits. More important candidate associated genes in the vicinity of the detected QTL regions were: LOC_Os01g26210 (OsWAK6) co-located with a seed vigor QTL, a gene with α-glucosidases/starch lyase activity (GH31, LOC_Os07g23944) associated with shoot length, UDP-glucuronic acid 4-epimerase 1 (LOC_Os03g14540) associated with root length, chloroplast outer envelope protein 86 (LOC_Os12g09570) associated with root fresh mass, vacuolar sorting receptor 7 (LOC_Os04g52190) and a gene cluster on chromosome 7 including LOC_Os07g07320 (glutathione S-transferase), LOC_Os07g07340 (glucan endo-1,3-beta-glucosidase) and LOC_Os08g42720 (solute carrier 35) affecting root dry mass, and LOC_Os06g47640 (calmodulin-related calcium sensor protein 29) involveing in the inhibition of ABA during seed germination, associated with germination rate. The associated genes for the studied traits can be generally classified as hydrolytic enzymes, kinases and transferases or transcription factors that can directly or indirectly influence germination and post-germination related seedling traits. Our GWAS results identified several putative candidate genes for germination and seedling traits that will greatly contribute to our understanding of the genetic complexity underlying the corresponding traits.
The aim of this study was to analyse the effects of different date of insecticidal treatment against Noctuinae caterpillars on the technological yield from sugar beet using the additive main effect and multiplicative interaction (AMMI) model. The AMMI model is one of the most widely used statistical tools in the analysis of multiple-environment trials. The results of the analysis of the dependence of the components of the sugar beet yield, carried out separately in individual years (2011–2018) of the experiment, indicate a significant and directly proportional impact of the root mass on the technological yield of sugar in all years. The average sugar content per years also varied from 16.22% (2014) to 19.68% (2015). Potassium molasses from the base of the tested protective treatments varied from 27.27 to 61.43 mmol kg⁻¹. The average sodium molasses per years also varied from 1.196 mmol kg⁻¹ (2015) to 6.692 mmol kg⁻¹ (2018). α-amine-nitrogen of the tested protective treatments varied from 6.03 (for phenological criterion in 2011) to 37.95 mmol kg⁻¹ (for intervention criterion in 2018). Technological yield of sugar beet tested protective treatments varied from 171.4 (for phenological criterion in 2015) to 360.0 t ha⁻¹ (for soil spraying of plants—in 2012) throughout the 8 years, with an average of 280.47 t ha⁻¹. The use of the AMMI model to estimate the interaction of conducted insecticidal treatments based on environmental conditions showed the additivity of the effects of the applied treatments on the effectiveness of the obtained quality features of the technological yield of sugar beet.
Principal coordinates analysis on the three datasets. Axis.1 and Axis.2 are the two first components, explaining 9.5 and 3.7% of the variations, respectively. Black squares correspond to the core collection CC196. Black triangles correspond to the core collection BW186. Orange and blue circles indicate elite genotypes from BDul dataset from Agri-Obtentions and Florimond Desprez (two breeding companies), respectively
Predictive ability (PA, A), root means square error (RMSE, B) and mean values of optimization criteria (C) over 60 repetitions of the G-BLUP model with different TP sizes. The vertical bars on figures A and B represent the standard deviations. The genotypes in the TP were selected by different methods. Genotypes were selected randomly with RDM (black). The genotypes the most related on average to the genotypes of the VP were selected with OPT_MEAN (purple). The genotypes with the highest maximum relatedness to the genotypes of the VP were selected with OPT_MAX (green). The genotypes with the highest minimum relatedness to the genotypes of the VP were selected with OPT_MIN (brown). The selection of genotypes by the CD_MEAN (orange) method was based on the maximization of the CDmean criterion. OPT_IND (blue) selected an optimized TP for each of the genotypes of the VP. The optimization criterium for RDM and OPT_MEAN is Kmean. For OPT_MAX, OPT_MIN, CDMEAN and OPT_IND, it is Kmax\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Kmax$$\end{document}, Kmin\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Kmin$$\end{document}, CDmean and the average relatedness between genotypes of the VP and their associated genotypes, respectively
PCoA representation of genotypes of the three datasets. Axis.1 and Axis.2 are the two first components, explaining 9.5 and 3.7% of the variations, respectively. For 20 genotypes and 80 genotypes in the TP, 100 random distributions of the BDul genotypes in 3 folds were produced. Genotypes in the optimized TP were then selected according to the four optimization methods (OPT_MIN, OPT_MAX, OPT_MEAN and CD_MEAN). The colors indicate the frequency of selection of a genotype (100%: a genotype is always selected when it is not in the VP (in red); 0%: the genotype is never selected (in dark blue)). Genotypes the most related on average to the genotypes of the VP were selected with OPT_MEAN; genotypes with the highest maximum relatedness to the genotypes of the VP were selected with OPT_MAX; genotypes with the highest minimum relatedness to the genotypes of the VP were selected with OPT_MIN; selection of genotypes by the CD_MEAN method was based on the maximization of the CDmean criterion (Rincent et al. 2012)
End-use value of wheat flour depends strongly on the concentration and composition of storage proteins, namely the gliadins and glutenins. As protein concentration in wheat grain is negatively correlated with grain yield, monitoring the gliadin to glutenin ratio is a mean to maintain end-use quality in modern varieties. However, the measurement of this ratio is expensive and time consuming. As genomic selection (GS) has proved very successful for traits controlled by many Quantitative Trait Loci and is already used for breeding, we decided to apply it to the gliadin to glutenin ratio. Therefore, we phenotyped for this trait and genotyped with a 420,000 SNP (Single Nucleotide Polymorphism) array a set of 88 modern varieties and 325 core-collection varieties. A GS model taking into account the genotypic, environmental and genotype x environment interaction effects was tested. Its predictive ability depends on the composition of the training population (TP). Adding significant SNPs as fixed effects did not improve the predictive ability. However, we observed improvements by optimizing the TP with five methods based on relatedness between genotypes and obtained a maximum predictive ability of 0.62 and a minimum Root Mean Square Error of 0.056 for the gliadin to glutenin ratio. To conclude, our results are promising and strongly suggested that GS can be efficiently applied to the gliadin to glutenin ratio. In addition, genotypes phenotyped and genotyped in previous breeding generations could be useful to train the model.
Truncation selection is often used to rapidly achieve short-term genetic gain within a breeding program. Unfortunately, it is also associated with the loss of favorable QTL alleles in the breeding population, causing a premature convergence to sub-optimal genetic values. Parental selection strategies such as the scoping method, the population merit method, and optimal cross selection have been proposed to preserve genetic variation in the breeding population and thus maximize genetic gain in the long term. Nevertheless, for economic reasons, breeders are often interested to maximize the genetic gain in a shorter time frame. We propose a new selection strategy, named the adaptive scoping method, that aims at maximizing the genetic gain within a specific, predefined time frame. Throughout this time frame, the adaptive scoping method progressively changes its selection strategy: during the initial breeding cycles, it attempts to maximally preserve genetic variation, whereas in later breeding cycles, it prioritizes the increase of the genetic value. We demonstrate through simulation studies that the adaptive scoping method is able to maximize the genetic gain for a wide range of time frames and that it outperforms the original scoping method, both in the short and in the long term.
Experiment setup A. Locomotory behaviour of R. padi, B. Host preference behaviour of R. padi, C. Aphid developmental assay, D. Nymphiposition of R. padi, E. Tolerance (Created with
Star shaped arena used to study host preference studies
Clip cage: To confine the individual aphid on leaves. The clip cage was made from two acrylic rings (25 mm diameter) attached with hair clip and foam to avoid the damage to leave
Locomotory behaviour of R. padi on Ae. tauschii acc. pau14232, Ae. tauschii acc. pau14576 and HD 2967 during 2019 and 2020
Host preference of R. padi for Ae. tauschii acc. pau14232, Ae. tauschii acc. pau14576, HD 2967, control during 2019 and 2020
Host plant resistance (HPR) is the most promising alternative to aphidicides used to control bird cherry-oat aphid, Rhopalosiphum padi L. infestation in wheat. A variety of experiments including locomotory, olfactometry (antixenosis), nymphiposition, relative growth and development bioassay (antibiosis), and tolerance studies were conducted to underpin the category of HPR for R. padi resistance in diploid Aegilops tauschii Coss. accessions pau 14232 and 14576 along with susceptible hexaploid Triticum aestivum L. variety HD 2967. R. padi nymphs showed a lower intrinsic rate of increase (0.192), weight gain (46.41–49.50 µg), mean relative growth rate (0.026–0.029), nymphal survival (43–48%), adult longevity (10.7–11.17 days), total development period (25.45–25.65 days) with a prolonged nymphal duration (13.4 days) on Ae. tauschii accessions as compared to susceptible check (HD 2967). Bird cherry-oat aphid also showed reduced locomotory and nymphiposition behaviour on Ae. tauschii. In the olfactometry assay, R. padi indicated less preference for diploid Ae. tauschii accessions. However, no significant difference observed in tolerance parameters viz. percentage proportional fresh plant loss index and percentage proportional dry plant loss index between Ae. tauschii accessions and HD 2967. Results showed that the R. padi resistance in Ae. tauschii pau accessions are governed by a combination of antixenosis and antibiosis.
Identification of stable and high-yielding genotypes is a real challenge in peach breeding, since genotype-by-environment interaction (GE) masks the performance of the materials. The aim of this work was to evaluate the effectiveness of parameter estimation and genotype selection solving the linear mixed models (LMM) under frequentist and Bayesian approaches. Fruit yield of 308 peach genotypes were assessed under different seasons and replication numbers arranged in a completely randomized design. Under the frequentist framework the restricted maximum likelihood method to estimate variance component and genotypic prediction was used. Different models considering environment, genotype and GE effects according to the likelihood ratio test and Akaike information criteria were compared. In the Bayesian approach, the mean and the variance components were assumed to be random variables having a priori non-informative distributions with known parameters. According the deviance information criteria the most suitable Bayesian model was selected. The full model was the most appropriate to calculate parameters and genotypic predictions, which were very similar in both approaches. Due to imbalance data, Cullis’s method was the most appropriate to estimate heritability. It was calculated at 0.80, and selecting above 5% of the genotypes, the realized gain of 14.80 kg tree¹ was attained. Genotypic frequentist and Bayesian predictions showed a positive correlation (r = 0.9991; P = 0.0001). Since the Bayesian method incorporates the credible interval for genetic parameters, genotypic Bayesian prediction would be a more useful tool than the frequentist approach and allowed the selection of 17 high-yielding and stable genotypes.
Representative fruits of the parental lines N29 (A), N317 (B), F1 hybrid (C), and some F2 individuals (D)
Histogram and density plots of pumpkin fruit traits and their correlation matrix. FL represents fruit length. FD represents fruit diameter. FSI represents fruit shape index. FTH represents flesh thickness. SCS represents seed cavity size. FW represents fruit weight. TSS represents total soluble solids
The synteny between linkage map and physical map
Locations of the identified fruit traits related QTLs on pumpkin chromosomes
Pumpkin is a popular vegetable crop and exhibits a broad diversity in fruit shape and size. Fruit-related traits are the decisive factors determining consumer acceptance and market value of pumpkin cultivar. As a result, deciphering the genetic basis of fruit-related traits is of great importance for pumpkin breeding. To address this problem, a F2 population was generated by two Cucurbita moschata inbred lines with contrasting fruit shapes, and genotyping by sequencing approach was used to construct a genetic map and localize the QTLs underlying the fruit-related traits in this study. The results showed that a high-quality genetic map was constructed for pumpkin, which comprised of 2413 bins and spanned a total length of 2252.10 cM with an average genetic distance of 0.94 cM. Thirty significant QTLs with moderate or small effects were identified for seven fruit-related traits, including fruit length, fruit diameter, fruit shape index, fruit weight, fruit flesh thickness, seed cavity size, and total soluble solids content. Co-locations were observed between the QTLs underlying different traits, demonstrating that pleiotropic effect plays an important role in genetic control of fruit-related traits. The identified QTLs provide valuable information for further fine mapping of the related genes and pumpkin breeding programs with the aim of improving fruit quality.
Awns on A panicles and B spikelets. Top (in A) and left (in B): HRCP 26 (Norin No. 34); middle: HRCP 34 (Kitakoganne); bottom and right: HRCP 10 (Norin No. 9). Scale bars 20 mm in A and B
Variation in awn length among the HRCP population. The dashed vertical line separates landraces (LR) before breeding programs began and breeding lines after they began. Dates indicate the year of registration of each variety
Variation in awn length by genotype at two chromosomal regions among the F2 population (n = 181) derived from ‘Kitaibuki’ (KT) × ‘Akage’ (AG). A Frequency distributions of awn length; vertical and horizontal bars show the mean and range, respectively, of awn length in the parents. B Awn length in nine genotypic classes; A, ‘Kitaibuki’; B, ‘Akage’; H, heterozygous; Kitaibuki is AA and Akage is BB. Bars with the same letters are not significantly different at p < 0.05
Selection based on phenotype during rice breeding programs in Hokkaido. RAE1 and RAE2 are genes controlling awn length
Understanding genetic diversity among local populations may facilitate the development of new crop varieties and is a primary goal of the molecular evolution of genes. Awn length is a well-documented phenotype among domestication traits in rice (Oryza sativa L.), from long to short awns. Short awned or awnless varieties have been selected in rice breeding programs. Awnlessness is favored by rice farmers in the current agriculture system. Here, we identified the genetic basis of awn length during rice breeding programs in Hokkaido, Japan. We found variation in awn length ranging from 0.0 to 37.6 mm among a local population consisted of breeding lines. Genetic analysis of awn length identified that RAE1 and RAE2 on chromosomes 4 and 8, respectively, accounted for awn presence. These genes are well known to be significant during Asian rice domestication. Sequence variations in these genes may clarify the molecular evolution of the genes for awn length in rice breeding programs. Firstly, a loss-of-function allele in RAE1, rae1, was selected for short awn length. Then, alleles of RAE2, RAE2-H01 to RAE2-H04, were targeted for the selection of short awns or awnlessness. The selections of an awnlessness phenotype can diversify these alleles in the genes RAE1 and RAE2 exhibiting variation in awn length.
Schematic representation of genomic selection breeding program in pearl millet (based on Heffner et al. 2009)
Integration of OMICS for enhancing drought tolerance in pearl millet
Globally pearl millet production is severely hampered by low moisture stress during crop season affecting economic yield drastically especially in the dry ecologies. Though conventional genetic interventions have delivered drought tolerant varieties/hybrids but achieved limited success in drought prone ecologies. Next-generation breeding techniques have revolutionized improvement of genetically complex traits like drought. An efficient strategy is to integrate conventional breeding methodologies with ‘OMICS’ techniques for fast track identification and transfer of genes improving drought tolerance in pearl millet at critical growth stages. Recently published draft genome sequence of pearl millet have made available a large wealth of genomic information and resources which could speed up breeding programmes for enhancing drought tolerance. The review highlights the multifarious effects of low moisture stress at different phases in pearl millet and mechanisms to cope with it. Progress made so far in tackling drought stress through conventional and next generation enabled breeding techniques has been discussed highlighting on an integrated OMICS approach to address drought stress effectively.
Phenotypic plasticity (PP) is the ability of an organism to produce multiple phenotypes in response to environmental changes. In cultivated species, such as maize (Zea mays L.), the PP of plant architecture traits will play an important role in the adaptation of genotypes to unpredictable scenarios given by climate change, marginal areas, and seeding with variable plant density (D). We bring information to improve the understanding of the environmental modulation of PPs of plant architecture traits of maize, untangling their genetic bases, and testing the hypothesis of independent genetic control of the traits per se and their PPs. The PP of traits related to leaf area, spatial distribution of leaf area and stem architecture [(leaf area, maximum leaf width, maximum leaf length (LL), leaf orientation value, vertical leaf angle, leaf length to the flagging point (LF), LF/LL relationship (LFLL), azimuthal leaf orientation, ear height (EH), plant eight (PH), EH/PH relatioship (EHPH) and stem diameter] were estimated using 160 RILs from the IBM B73 × Mo17 Syn4 population, cultivated under two contrasting D (5 and 10 pl m⁻²) during two growing seasons that determined different environmental conditions. Data were phenotypically analyzed and quantitative traits loci (QTLs) were mapped. For leaf area and stem architecture related traits, high mean values of traits per se were related with high PPs values at low intraspecific competition while low mean values were observed at high intraspecific competition. The opposite response was found on leaf orientation related traits, with the exception of AZ. Forty-eight QTLs were detected for PP of plant architecture related traits on all chromosomes with exception of chromosome 7. There was no phenotypic correlation and no co-located QTLs for traits per se and their PPs. This independent genetic control for traits per se and their PPs would allow breeders to develop genotypes adapted to specific environments selecting for high or low PP in combination with high or low values for relevant agronomic traits.
Geometric diagram of the shape traits analyzed with Tomato Analyzer and their abbreviation. Full explanation of the traits and their derivation is found in the Tomato Analyzer 4.0 manual
Heritability estimates for the nut shape traits with mid-parent offspring regression and variance component analysis
Nut shape corresponds to the maximum and minimum values for first three principal components (PC) obtained from elliptical Fourier transform (Left). Nut images represent extremes for nut roundness (PC1), proximal end angle (PC2) and distal end angle (PC3). PCA plot showing distribution of parents and progeny from all full-sib families (Right)
Correlation (scale: −1 to 1) between the PCs from EFT and shape trait values obtained from tomato analyzer. Size of the square represents the P-value (larger the square smaller the P-value and vice versa). Box with no color indicates P-value ≥ 0.05 (MW: maximum width, MH: maximum height, FSIEI: fruit shape index (external I), DFB: distal fruit blockiness, PFB: proximal fruit blockiness, cir: circularity, rect: rectangularity, DisAMa: distal angle (macro), ProAma: proximal angle (macro), ovo: ovoidness)
Nut shape is an important trait in determining the value of a pecan (Carya illinoensis) nut crop. Nut shape influences attractiveness to consumers, nut filling, ease of mechanical cracking, and is distinctive enough that it is the primary means of cultivar identification. Narrow sense heritability (h²) of a trait is the fraction of phenotypic variance attributed to variation in genes with additive effect. Estimation of h² is key to breeding programs as it determines the method of selection and amount of genetic gain in each breeding cycle. In the present study, we estimated the heritability of pecan nut shape characters following two different approaches. First, image-based phenotypes of pecan nuts from 34 full-sib families generated from random crosses between 31 different parents were generated and analyzed for 10 different morphometric traits using the computer program Tomato Analyzer. The narrow-sense heritability for each trait was estimated using the mid-parent offspring regression method. Second, a separate set of 19 pecan genotypes were phenotyped for the same shape traits for two years and heritabilities were estimated by variance component analysis. Heritability estimates ranged from 0.41 to 0.83 for the mid-parent offspring regression method and from 0.26 to 0.78 for variance component method. Additionally, elliptical Fourier transform was performed to study the overall variation in nut shape. The first three principal components obtained from Elliptical Fourier transform explained 65.9% of the total variation in shape attributed to the nut’s roundness and angularity of proximal and distal ends. The use of the image-based high-throughput method of phenotyping and the heritability estimates obtained in this study directly benefit pecan breeding programs focusing on nut shape traits.
QTL controlling resistance to late wilt disease of maize detected on chromosome 1, 3 and 5 in mapping population derived from CV138811 × CV143587 (MP 1)
QTL controlling resistance to late wilt disease of maize detected on chromosome 1, 5, 6 and 10 in mapping population derived from CV138811 × CV136745 (MP 2)
Frequency distributions of mean disease scores of late wilt disease of F2:3 progeny families of the a Mapping Population 1 (CV138811 × CV143587), b Mapping Population 2 (CV138811 × CV136745)
Maize (Zea mays L.) is the third largest globally cultivated cereal after wheat and rice contrib- uting chiefly to global food and nutritional security. It is known to be affected by various diseases. Among the diseases, post flowering stalk rots (PFSR) are complex, most serious, destructive and widespread. Harpophora maydis causing late wilt disease (LWD) is one of major component pathogens causing PFSR. In this study, we identified two major and six minor QTLs controlling resistance to LWD in two F2:3 popu- lations developed involving one LWD resistant inbred line and two susceptible inbred lines. Among the two major QTLs detected one each on chromosome 3 and 5 explained 14.62 and 12.54% phenotypic variation respectively. Among the six minor QTLs detected, three on chromosome 1; one each on 3, 5 and 6; all explained < 10% phenotypic variation. Of these QTLs detected one QTL exhibited additive effect while six showed partially dominant effects and remaining one showed dominant effects.
Analysis of 365 independent research articles on heat and drought adaptation between 1970 and June 2020 sourced from Scopus. (a) Pie chart of the 365 articles showing the percentage of research articles focusing on drought alone, heat alone and combination of drought and heat. The blue colour represents the drought articles, red represents the heat articles, while the yellow represents the articles focusing on the combined effects of drought and heat (b) Text analysis result from Leximancer version 4.5 showing the number of times a specific word is used and ranked them according to the number of times they appeared in the titles, abstracts, and keywords
Aboveground biomass associated with water use a) Profligate water use leading to yield penalty b) Conservative water use leading to yield benefit
Schematic diagram of how genetic variation in gene bank material may be exploited using pre-breeding approaches
Chickpea (Cicer arietinum L.) is one of the most important grain legumes in the world, but its current and future production is threatened due to the increased incidence of drought and heat stress. To address this challenge, an integrated crop improvement strategy encompassing breeding, genomics, physiology and agronomy is required. Here, we review the physiological traits known to confer drought and heat adaptation in chickpea and identify areas of drought and heat adaptation research that may be prioritised in the future. Furthermore, we underscore approaches to efficiently phenotype chickpea adaptation traits and highlight the significant challenges and importance of understanding the nexus between canopy and root development. Finally, we present the opportunity to adopt multi-trait genomic prediction approaches to efficiently utilise key physiological traits, that can be assayed using high-throughput phenotyping platforms, to accelerate genetic gain in drought and heat prone environments.
Nutritional composition of soybean seed
Soybean is an excellent source of high quality protein and vegetable oil for human and animals. The diverse and increasing demands for soybean have created enough opportunities for breeders to improve the soybean seed composition traits influencing nutritional parameters. Protein and oil content, protein subunit composition, fatty acid composition, anti-nutritional factors etc. are some of the important seed traits that need to be improved to enhance the nutritional value of soybean as food and feed. Many studies have been carried out to modify the seed composition traits to enhance the nutritional quality of soybean. The extensive screening of worldwide soybean germplasm collections has led to the identification of many genotypes with significant variation for seed composition traits. In addition, induced mutagenesis has contributed immensely in improving the quality of soybean seeds by creating novel mutant genotypes for various seed quality traits. Gene/QTL mapping and molecular characterization of these mutants had led to elucidation of gene function and significantly increased the knowledge on molecular basis of seed composition traits. The emergence of modern biotechnological tools like siRNA and targeted mutagenesis techniques like CRISPR/Cas9 has further opened new opportunities in modifying the nutritional value of soybean. This review article provides comprehensive and up-to-date knowledge about the genetic improvement of important seed composition traits in soybean by conventional and biotechnological approaches. The article also discusses the major challenges and limitations in genetic enhancement and utilization of quality related traits in soybean.
Three of the red clover sub-populations used in the study, one year after sowing (top) and one month before collecting survivors. Survivors were crossed within sub-population to make a new generation, which was phenotyped under controlled conditions. MS 3, mixed stand and 3 cuts per year; PS 3, pure stand and 3 cuts per year; PS 5, pure stand and five cuts per year. Note that PS 5 was photographed almost a month earlier than MS 3 and PS 3 in May 2011
Characteristics of the studied red clover survivor populations during early growth. Plants were grown under “normal” light conditions in controlled conditions, and half the plants were transferred to a simulated shade treatment after 6 weeks (w). After 6 weeks the averages of the two light treatments are shown. Original, the original population sown at Ås; PS 3, pure stand harvested 3 times a year; PS 5, pure stand harvested 5 times a year (Ås only); MS 3, mixed stand harvested 3 times a year. See Table 1a and b for statistical analysis
Characteristics of the studied red clover populations during stem elongation in the studied survivor populations. Averages across two light treatments are shown. Original, the original population sown at Ås; PS 3, pure stand harvested 3 times a year; PS 5, pure stand harvested 5 times a year (Ås only); MS 3, mixed stand harvested 3 times a year. See Table 1b for statistical analysis
Timing of stem elongation and characteristics measured at harvest and after regrowth in the studied red clover survivor populations from Ås and Stjørdal. Averages of 2 (Ås) or 3 (Stjørdal) replicate survivor populations per population type are shown together with standard errors. Original, the original population sown at Ås; PS 3, pure stand harvested 3 times a year; PS 5, pure stand harvested 5 times a year (Ås only); MS 3, mixed stand harvested 3 times a year. See Table 1b for statistical analysis
Mortality of the studied red clover survivor populations after freezing, expressed as the proportion of tested plants that survived. Averages of 2 (Ås) or 3 (Stjørdal) replicate survivor populations per population type are shown together with standard errors. Original, the original population sown at Ås; PS 3, pure stand harvested 3 times a year; PS 5, pure stand harvested 5 times a year (Ås only); MS 3, mixed stand harvested 3 times a year. See Table 1c for statistical analysis
Legumes are important in sustainable agriculture and particularly so when they are intercropped with other species. In breeding programs, little attention is paid to their agronomic performance in species mixtures. In red clover, improved persistence is an important breeding goal. We identified traits associated with survival of red clover cultivated in pure stands (PS 3) or in mixtures with grasses (MS 3) and managed under a 3-cut system (two locations), as well as in pure stands in a 5-cut system (PS 5, one location). Survivors from replicate plots were collected and a new generation made from each plot. The new generations were characterized in a growth experiment with light or simulated shade, and in a freezing experiment. We show that the traits related to red clover persistence depend on both plant community composition and cutting frequency. MS 3 had more leaves with larger leaf blades and longer petioles during the vegetative stage, followed by earlier stem elongation, higher number of elongating stems, higher biomass (also when accounting for earlier stem elongation) and more leaves in the regrowth after cutting than PS 3. MS 3 also had better freezing tolerance. PS 5 was similar to MS 3 and different from PS 3 in the number of leaves, leaf blade size, petiole length and number of elongating stems. These results show that breeding and cultivar evaluation, which is currently almost exclusively considering performance in pure stands, may miss some variation which provides persistence of red clover in mixtures with grasses.
Average number of CBB (in all stages ± SE) in coffee beans of F2 plants of five populations of the crossing of lines of registered variety Castillo with Ethiopian introductions in two trials (A and B) conducted under controlled conditions. Black dots bars correspond to F2 plants of the population CX.2170 × CC534; white dots bars to F2 plants of the population CX.2178 × CCC470; white bars to F2 plants of the population CX.2848 × CCC477; vertical line bars to F2 plants of the population CX.2391 × CCC477; gray bars to F2 plants of the population CU.1812 × CCC534; black bars to male parents (CCC470, CCC477, CCC534); and diagonal line bars to susceptible controls (Caturra variety and female parents CU.1812, CX.2178, CX .2391, CX.2710, CX.2848) (SE = Standard Error)
Average number of CBB (in all stages ± SE) in berries of F2 plants of five populations of the crossing of lines of registered variety Castillo with Ethiopian introductions in two field trials (A and B). (SE = Standard Error). Black dots bars correspond to F2 plants of the population CX.2170 × CC534; white dots bars to F2 plants of the population CX.2178 × CCC470; white bars to F2 plants of the population CX.2848 × CCC477; vertical line bars to F2 plants of the population CX.2391 × CCC477; gray bars to F2 plants of the population CU.1812 × CCC534; black bars to male parents (CCC470, CCC477, CCC534); and diagonal bars to susceptible controls (Caturra variety and female parents CU.1812, CX.2178, CX .2391, CX.2710, CX.2848)
Percentage distribution of CBB stages in F2 plants of the five populations resulting from the crossing of lines of variety Castillo with Ethiopian introductions in relation to female parents: a CX.2710 × CCC534, b CX.2178 × CCC470, c CX.2848 × CCC477, d CX.2391 × CCC477, and e CU1812 x CCC534. The arrows indicate the location of the male parents (Ethiopian introductions that carry the antibiosis character against the CBB) and Caturra variety (CBB-susceptible control)
Hypothenemus hampei Ferrari, commonly known as the coffee berry borer (CBB), causes the greatest economic losses to coffee crops worldwide. Five lines of the registered coffee variety Castillo with resistance to coffee leaf rust (CX.2710, CX.2178, CX.2848, CX.2391, CU.1812) were crossed with three Ethiopian introductions (CCC534, CCC470, CCC477) presenting an antibiosis effect against the CBB. The F1 hybrids were advanced to the F2 generation, and the number of CBB stages in 714 plants was evaluated in both field and controlled conditions. Results indicated that under controlled conditions only 68 F2 plants presented a significantly lower average number of stages (18.67–37.7%) regarding susceptible controls. In the field, the lower average of CBB stages of the 68 F2 plants was also confirmed, ranging between 29.05 and 73.10%. Study results demonstrated the presence of antibiosis in F2 plants due to low reproductive fitness of CBB. The distribution of the percentage of CBB stages on F2 plants in relation to susceptible controls was found to have a normal distribution, indicating a segregation that is typical of a quantitative trait involving several genes. Populations will be advanced and selected until a coffee variety presenting antibiosis against CBB and desirable agronomic characteristics is obtained. These new plants would be used in coffee-growing areas highly vulnerable to CBB in Colombia as a component of an integrated pest management (IPM) strategy.
As one of the important spike components, spikelet number is closely related to wheat yield. In the present study, a major stable QTL for spikelet number per spike (SNPS), qSnps-7D, was identified using a recombinant inbred line mapping population derived from the cross between Kenong 9204 (KN9204) and Jing 411 (J411) (KJ-RILs). To decipher its genetic effects on yield-related traits and selection effects in wheat breeding process, phenotype data together with genotype data from KJ-RILs and a natural mapping population were collected. qSnps-7D was mapped to the interval of 1.63 Mb on chromosome 7D in the KN9204 genome assembly in 4 of the 6 datasets. The favored alleles from KN9204 could significantly increase SNPS, kernel number per spike (KNPS). The diagnostic markers for SNPS were further developed and validated. The selection utilization rate of the favored haplotype in foreign varieties was lower than that in China, and it showed an increasing trend with time passage, with the ratio reaching more than 50% since the 1990s. In addition, loci for yield-related traits co-located with qSnps-7D were sorted out. Meanwhile, the relationship between SNPS and its components as well as other important yield-related traits were also discussed. Taken together, the studies will lay foundation for gene cloning and molecular breeding utilization of qSnps-7D.
AMMI biplot presenting cane yield for 15 sugarcane genotypes
AMMI biplot presenting sugar yield for 15 sugarcane genotypes
Which-won-where polygon view of the GGE biplot for cane yield of 15 sugarcane genotypes (G) in 7 different environments (E) to show that genotype performed superlative in which environment and significant mega environment
Which-won-where polygon view of the GGE biplot for sugar yield of 15 sugarcane genotypes (G) in 7 different environments (E) to show that genotype performed superlative in which environment and significant mega environment
Genotype main effect plus genotype-by-environment (GGE) biplots of sugarcane genotypes based on cane yield (a) and sugar yield (b) in seven studied environments. , GGE biplot showing a polygon view of a scatter plot of which genotype won where
Seven field experiments were conducted at three experiment stations representing major sugarcane producing regions in Egypt. Each experiment comprised a randomized complete block design with three replications. Fourteen elite breeding lines typical of those routinely generated in the three final selection stages of sugarcane breeding programs in Egypt, along with one check variety (GT54-9) were evaluated for cane and sugar yield in this study during the 2018/2019, 2019/2020 and 2020/2021 seasons. Stability parameters including cultivar stability rank and superiority index were determined. The data was also investigated using GGE-biplots, the additive main effects and multiplicative interaction model (AMMI), and the AMMI stability value (ASV). The genotype main effect was used to visualize the G x E interaction. The results of these trials are of significance in guiding the selection and recommendation of superior sugarcane varieties and more stable in sugarcane production zones. The clone G.2016–129 had a mean sugar yield and cultivar superiority index for sugar yield exceeding that of GT54-9, and hence was recommended for commercial planting. Because of local conditions in Egypt, an elite sugarcane variety would have high and stable yield and would adapt to a wide range of environments. In the present study, only one clone G.2016–129 fit that definition by producing higher and more stable sugar yield than the commercial variety GT 54–9.. At the side of multivariate analyses, the ASV (AMMI stability value) supports selection of stable varieties in the AMMI Method. Varieties with lowest ASV are stable. Therefore, the results of this study exposed that G.2016–95, F-150 and G.2016–129 with lowest ASV for cane yield by contrast, G.2009–11, G.2016–128, F-150 and G.2016–95 with lowest ASV for sugar yield, were stable clones for cane and sugar yields, respectively.
Daily maximum (MaxT, °C) and minimum temperature (MinT, °C) in December 2019 and January 2021
OW rice cultivar evaluated from spring 2019 to spring 2020. a Field performance of 1034 rice cultivars transplanted in May 2019; b Field performance of 1034 rice culticars in December 2019; c, d OW rice cultivars germinated in March and April 2020
Geographic deistribution of OW rice cultivars with cold tolerance of 4 °C in December 2019
OW rice cultivar evaluated from spring 2020 to spring 2021. a Field performance of 1034 rice cultivars transplanted in April 2020; b–f OW rice sprouted from tillering node March and Aptil 2021
Geographic deistribution of OW rice cultivars with cold tolerance of 0 °C in January 2021
Overwintering rice can survive through the natural cold-winter field environment, sprout from rice tillering node in the following spring, tiller, flower, seed, and being harvested in the following autumn, which is a type of an extreme case of cold tolerance of rice. The successful utilization of cold tolerance rice is the most economical strategy for the cold tolerance rice cultivar breeding project. This work aims to identify the OW rice for the future development of cold tolerance cultivars. Altogether 1034 Chinese existing rice cultivars including 735 (71.08%) conventional Japonica rice cultivars and 299 (28.92%) conventional Indica rice cultivars were collected and evaluated for their responses to low temperatures under the natural field cold-winter environment. Among them, altogether 262 (25.34%) conventional Japonica rice cultivars could withstand cold tolerance to 4 °C of the daily minimum temperatures in December 2019 throughout the cold-winter season and distributed in 13 provinces of China, survive through the natural cold-winter field environment, and sprout from rice tillering node in March 2020. Only 24 (2.32%) conventional japonica rice cultivars could withstand cold tolerance to 0 °C of the daily minimum temperatures in January 2021 throughout the cold-winter season, which could also sprout from rice tillering node in March 2021 and distributed in seven provinces of China. The present cold tolerance rice cultivars will provide beneficial breeding germplasm for the future cold tolerance rice breeding project and new strategies involved in elucidating the molecular mechanism of the cold tolerance of rice.
Manhattan plots for height (A), and Cercosporiosis (B). Dashed lines show Bonferroni adjusted thresholds of 5.55 for alpha equal to 5%. The X-axis indicates the chromosomes and the Y-axis the P-values
Manhattan plots for rust (A), diameter of the canopy projection (B), and vegetative vigor (C). Dashed lines show Bonferroni adjusted thresholds of 5.55 for alpha equal to 5%. The X-axis indicates the chromosomes and the Y-axis the P-values
Genome wide association studies (GWAS) have been traditionally used for the identification and comprehension of loci associate with phenotypic variation and identification of markers useful in genetic breeding programs. The GWAS was used in this work to identify chromosomal regions with significant associations with the main agronomic trait of Coffea canephora. The studied population comprised 165 clones of the two varietal groups Conilon and Robusta and intervarietal hybrids from crosses between these groups. Coffee trees were genotyped using 17 885 single nucleotide polymorphisms (SNP) markers distributed throughout the genome and phenotyped with eight morpho agronomic traits. Significant SNPs were found associated with plant height, diameter of the canopy projection, vegetative vigor, rust incidence, and cercosporiosis incidence. SNP marker distribution was quite uniform, with few gaps in the centromeric regions, with 27.72% and 9.09% present in intergenic and coding regions, respectively; the latter led to 70% amino acid exchanges and 30% silent mutations. Candidate genes, in which SNP markers were inserted, were identified and their function was related to traits of plant architecture and coffee diseases resistance. SNPs with significant associations were found in all chromosomes of the species, especially in chromosomes 0, 2, 6, 9, and 11. This methodology was efficient in C. canephora populations and helped identify several SNPs in candidate genes involved in important biological processes of coffee. Therefore, these SNPs can be used as strategies to accelerate the coffee breeding program through molecular marker assisted selection.
Correlation of yield, its attributing and fiber quality traits in the G. hirsutum cv DS-28 × G. barbadense cv SBYF-425 RIL mapping population at 0.05 level of significance
Details of 26 linkage groups (LGs), assigned 26 chromosomes with identified QTLs in the RILs of cross between G. hirsutum cv DS-28 and G. barbadense cv SBYF-425
Collinearity of genetic map (LG = Linkage group) with physical map (the nomenclature of chromosomes in physical map is shortened from AD_chr. to A for convenience)
The recombinant inbred lines of inter-specific cross, Gossypium hirsutum cv. DS-28 × G. barbadense cv. SBYF-425 was evaluated in three consecutive rainy seasons of 2017–18 (F13), 2018–19 (F14) and 2019–20 (F15) in an augmented design. The preponderance of huge continuous variability for both productivity and fiber quality traits was recorded. The principal component analysis revealed that the mapping population was well suited for mapping of productivity and fiber quality traits. On the basis the Z-scores for skewness and kurtosis, 178 RILs with normal distribution were selected for genetic linkage mapping. A high-density saturated linkage map was constructed using SNP arrays of CottonSNP63K, an Illumina’s infinium array and CottonSNP50K, CSIR-National Botanical Research Institute’s Axiom array with a total spanned length of 2402.65 cM, an average marker density of 1.54 and with map coverage of 96.99% of the reference genome. The developed genetic map of inter specific cross of Indian cotton varieties is a highly saturated in terms of coverage and highly comparable to the published maps. In QTL analysis, altogether 99 QTLs were identified for productivity and fiber quality traits. Among those, eight were stable and 38 were major QTLs. Cluster 1, 4 and 6 respectively on chromosome AD_chr.03, AD_chr.14 and AD_chr.18 were the biggest QTL clusters each with four QTLs and cluster 4 and 6 were QTL hotspots for fiber quality traits.
The fruits and husks of YQ1 and Rice-Tartary; a fruits of YQ1, b fruits of Rice-Tartary, c husks of YQ1, d husks of Rice-Tartary
Association analysis of SNP; a the ED value of each SNP site, b the calculated SNP-index value of R04(easily shelled pool), c the calculated SNP-index value of R03(hard-shelled pool), d the calculated ΔSNP-index value of R04-R03
Correlation analysis of InDel; a the ED value of each InDel site, b the calculated InDel-index value of R04 (easily shelled pool), c the calculated InDel-index value of R03(hard-shelled pool), d the calculated ΔInDel-index value of R04-R03
Construction of chromosome genetic map within the initial mapping interval of Tartary buckwheat
qRT-PCR analysis of candidate genes
The hard-shelled character of ordinary cultivated Tartary buckwheat has become a factor influencing its taste and nutritional efficacy. However, the local variety, Rice-Tartary, can dehull easily. The genetic mechanism regulating easily-shelled Fagopyrum tataricum is unknown. In this study, the F2 generation segregating population was constructed by crossing Yunqiao No.1 (hard-shelled) and Rice-Tartary (easily-shelled) as parents, and the bulked segregant analysis sequencing (BSA-seq) strategy was used to initial mapping. The gene locus controlling the easily-shelled trait of Tartary buckwheat was preliminarily located in the 4.07 Mb region of the first chromosome. To further narrow the range, the Kompetitive allele-specific PCR primers based on the single nucleotide polymorphisms in the initial location range were designed and tested in 335 individual plants in the hybrid F2 population. The candidate gene Ftes1 was located between Ft6,705,225 and Ft7,041,921, according to the genetic linkage map constructed based on typing data. Combined with the location of candidate genes, the RNA-Seq data, and qRT-PCR results, the results indicate that 3 genes, FtPinG0001427400.01, FtPinG0001428600.01, and FtPinG0002492200.01 may regulate the easily-shelled Tartary buckwheat. The results of this study provide vital candidate genes for the cloning and functional analysis of genes related to easily-shelled traits, as well as prominent molecular markers for breeding of new varieties of Tartary buckwheat.
Improving tomatoes keeping quality is crucial for reducing post-harvest losses. Knowledge of heterosis, and combining ability is a prerequisite for breeding high yielding and good shelf life heterotic hybrids. An investigation was undertaken with each of 3 lines, testers, and 9 hybrids to identify desirable parents and crosses for 20 fruit biochemical, morpho-physiological, and yield traits and to elucidate the nature of gene action for shelf life and its contributing traits through line × tester analysis. The lines contributed to most of hybrids variability than testers and fruit quality traits had a higher degree of SCA variance as compared to GCA variance. pH, ascorbic acid, fruit firmness, and plant height governed by additive gene action. Lycopene, titratable acidity, TSS, calcium, magnesium, pericarp thickness, pulp content, locule number, fruit length, diameter, weight, shelf life, number of branches, number of clusters, number of fruit/cluster, and yield/plant were under the control of non-additive gene action. All the lines and Arka Saurabh were the best general combiners and IIHR 2349 × Arka Vikas, IIHR 2349 × Arka Saurabh, IIHR 2358 × Arka Ahuti and IIHR 2357 × Arka Ahuti were the best specific combiner in producing heterotic hybrids. IIHR 2349 × Arka Vikas and IIHR 2349 × Arka Saurabh were promising hybrids for high yield and shelf life. The crosses involved both parents with high, one parent with high and other with low and both parents with low good overall general combining ability status respectively indicated the additive, non-additive and epistatic gene action in fruit quality and yield traits inheritance.
Dendrograms and cophenetic correlation coefficient (CCC) of the unweighted pair group method with arithmetic mean (UPGMA), from Mahalanobis´ generalized distance, obtained in 17 common bean genotypes evaluated in the 2016 rainy (I), 2017 dry (II), 2017 rainy (III) and 2018 dry (IV) season crops
Dendrograms and cophenetic correlation coefficient (CCC) of the unweighted pair group method with arithmetic mean (UPGMA), from Mahalanobis´ generalized distance, obtained in 17 common bean genotypes evaluated in the combined experiments I and II (2016 rainy and 2017 dry season crops), I, II and III (2016 rainy, 2017 dry and 2017 rainy season crops) and I, II, III and IV (2016 rainy, 2017 dry, 2017 rainy and 2018 dry season crops)
The number of experiments that allows the choice of parents to be used in controlled crossings in a more assertive way in cluster analysis is unknown for plant architecture and grain yield traits in common bean. Therefore, the objective of this work was to determine the number of experiments that should be considered in Tocher's and the unweighted pair group method with arithmetic mean (UPGMA) cluster analyses to identify promising common bean parents for several plant architecture and grain yield traits. Four experiments were carried out in different years and growing seasons, in the same site. The randomized block design was used and 17 common bean genotypes with carioca (beige seed coat with brown streaks) and black grains were evaluated in relation to 12 traits related to plant architecture and five traits related to grain yield. Statistical analyses were performed with data obtained from individual and combined experiments. Significant genotype × experiment interaction was observed for most of the evaluated traits. When Tocher's and UPGMA cluster analyses was performed from data obtained in individual experiments different groups were formed. The use from data obtained in two, three or four experiments allowed greather reliability in the formation of groups. Three and two experiments are sufficient in the Tocher's and the UPGMA cluster analyses, respectively, to identify promising carioca and black common bean parents for several plant architecture and grain yield traits in a more assertive way.
AMMI biplot of grain yield and the first interaction principal component axis (IPCA 1) of 29 QPM, non-QPM and check hybrids evaluated at 13 locations in South Africa and Zimbabwe during the 2017/2018 and 2018/2019 cropping seasons
Despite the development of quality protein maize (QPM) genotypes with increased lysine and tryptophan levels, there is still a controversy on the yield potential of QPM genotypes compared to non-QPM genotypes. The objective of this study was to compare the QPM hybrids with non-QPM hybrids for grain yield and related traits and to determine if the QPM trait caused yield reduction in tested environments. A total of 126 hybrids were developed by crossing 32 inbred lines (22 QPM and 10 non-QPM) with two QPM and two non-QPM testers, using a line x tester design, and these were evaluated with four hybrid checks (two QPM and two non-QPM) at 13 locations in South Africa and Zimbabwe. Significant differences were observed among the hybrids for almost all the traits, indicating that superior hybrids could be identified and selected. Significant genotype by environment interaction effect was detected for almost all the traits which indicated that hybrids performed differently across the tested environments. When average yield for QPM and non-QPM was compared across the 13 sites, the yield reduction was 9.34% due to the QPM trait. Decreased ear placement and increased ear aspect could have contributed to this reduction. Yield reduction was 13% for the two QPM testers crossed with lines compared with means of crosses with two non-QPM testers. The best performing hybrid was a QPM genotype (entry 41), but only four of the top 20 hybrids were QPM. Though most crosses indicated a substantial yield loss due to the QPM trait, the top performing hybrid being a QPM indicates the possibility of yield potential improvement in QPM genotypes.
Physical map positions of SNP markers, of QTL confidence intervals (CI, red bar) for SFA and other seed quality traits, and positions of candidate genes (Loci names in red) for ASG Population. The SNP markers in green were also identified within the same region for erucic acid (on C03) and ADL (on C05) contents by Behnke et al. (2018). (Color figure online)
Physical map positions of SNP markers, QTL confidence intervals (CI, red bar) for SFA and other seed quality traits, and positions of candidate genes (Loci names in red) for AZH Population. The SNP markers in green were also identified within the same region for ADL content by Behnke et al. (2018). (Color figure online)
Consumption of foodstuff with low contents of saturated fatty acids is considered beneficial for human health. Reducing saturated fatty acid content in oilseed rape (canola) and other oil and protein crops is a relevant breeding aim. The objective of this work was to study the genetic variation and inheritance of saturated fatty acids in two DH populations of oilseed rape, to map QTL and to identify candidate genes. In addition, the correlation to other seed quality traits was studied. To this end, two half-sib DH populations were tested in up to five field environments in north-western Europe and seeds harvested from open-pollinated seeds were analyzed. Genotyping was performed using Illumina Brassica 15 K SNP chip. In both populations, significant effects for the genotypes and for the environments were detected, and heritability ranged from 68 to 89% for the predominant palmitic acid and stearic acid content. Up to 48 QTL for different fatty acids, oil and acid detergent lignin (ADL) content were mapped in the two populations. Co-locating QTL for palmitic acid, stearic acid, the C16/18 fatty acid ratio, the FATB/A ratio, oil and ADL content were identified on different chromosomes. A large number of candidate genes were identified within the vicinity of QTL flanking markers. Identification of several co-locating QTL positions, of associated candidate genes and SNP markers should facilitate oilseed rape breeding for low saturated fatty acid content.
BLUP of the selection index for 60 sweet potato genotypes selectable within the aptitudes for ethanol production (A), animal feed (B), and human consumption (C) in 1606 genotypes evaluated in Lavras, MG, Brazil
The objective of this study was to identify the aptitude of sweet potato genotypes derived from botanical seeds and select them for the aptitudes human consumption, ethanol production, and animal feed through separate indices. A row–column incomplete block design was used, restricting relatedness in the draw. A total of 1604 half-sib genotypes resulting from recombination of 55 clones from the germplasm collection of the Federal University of Lavras were evaluated. The accessions UFVJM 58 and UFVJM 61 were used as controls, for a total of 1606 treatments. The aptitude indices corresponded to the mean values of the 10 traits evaluated, with weights assigned to each trait according to the aptitude of interest. The data of all three aptitudes were transformed and standardized. Then, using the Zi index and with 2.5% selection pressure, the most promising genotypes were selected through the best linear unbiased predictor according to the traits evaluated and the aptitude of interest. Sixty genotypes were selected (out of 1604 tested) based on one or more of the three reported aptitudes: 25 showed a single aptitude, whereas 20 showed dual aptitude and 15 showed triple. The data obtained will provide information for breeding programmes of the sweet potato crop. There is great genetic variability for the traits evaluated, facilitating the selection of new genotypes, with the possibility of obtaining new cultivars important for national food sovereignty and making a significant social contribution.
Schematic diagram of the layout of the dominant pineapple areas. Dark green areas represent Western Yunnan dominant pineapple cultivation areas, yellow areas represent Southern Guangxi dominant pineapple cultivation areas, light green areas represent Hainan–Leizhou Peninsula dominant pineapple cultivation areas, and purple areas represent Eastern Guangdong-Southern Fujian dominant pineapple cultivation areas.
Pineapple is the most important economic plant in the family Bromeliaceae and the third-most economically important tropical fruit in the world. It has become an important tropical fruit in Guangdong, Hainan, and Guangxi, which are suitable areas for its cultivation. However, modern and well-organized breeding systems have not yet been established for pineapple. In this review, we describe the current status of the geographical distribution, industrial development, and breeding of pineapple in China. The current status of pineapple breeding is introduced, including traditional breeding methods, such as crossbreeding, mutagenesis breeding, and biotechnology breeding, combining cell engineering and gene engineering. In addition, the research progress on assisted breeding technology based on genetic map construction and molecular marker development is presented. New challenges and perspectives for obtaining high fruit quality are discussed in the context of breeding programs for pineapple.
Symptoms on plants inoculated with H. brassicae isolate R10 at seedling stage. Resistance: no host reaction and no sporulation, or small necrosis on the adaxial cotyledon/leaf surface and root. Susceptibility: sporulation dispersed over whole abaxial cotyledon/leaf surface and root, or abundant and dense sporulation dispersed over the whole cotyledon/leaf/root. a Drop inoculation of cotyledons with 6 days. b Resistant cotyledons of the accession Rd004 (class 1) 7dpi (days post-inoculation). c Susceptible cotyledons of the accession Rd197 (class 6) 7dpi. d Spraying inoculation of leaves with 14 days. e Adaxial and abaxial surface of a resistant leaf of the accession Rd198 with dark necrosis and no sporulation (class 1) 12dpi. f Adaxial and abaxial surface of a susceptible leaf of the accession Rd197 with dense sporulation (class 6) 12dpi. g Daikon long-red radish root of resistant accession Rd004 (class 1) 12dpi. h Long-red radish root of susceptible accession Rd201 (class 4) 12dpi. i. Round-red radish root of susceptible accession Rd197 (class 4) 12dpi
Correlation between Disease Index (DI) values of thirty-six radish accessions inoculated with H. brassicae isolates R10 and R6 on the roots (r = 0.805, P = 0.000)
a Correlation between Disease Index (DI) values of cotyledon and true-leaf inoculation (r = 0.443, P = 0.003, N = 44). b Correlation between DI values of cotyledon and root inoculation (r = 0.187, P = 0.224, N = 44). 3c. Correlation between DI values of true-leaf and root inoculation (r = 0.354, P = 0.018, N = 44) inoculated with H. brassicae isolate R10
Radish downy mildew (DM) caused by the oomycete Hyaloperonospora brassicae f. sp. raphani is a serious problem in radish crop, an edible root vegetable of the Brassicaceae family. The objective of this research was to assess radish germplasm for DM resistance and to evaluate the response of different radish organs to the disease under controlled conditions. Forty-four radish accessions were inoculated at cotyledons and true-leaves with H. brassicae isolate R10, collected in cotyledons of field plants. The roots were tested with isolates R10 and R6, this last one collected in roots of field radish. DM symptoms varied with the radish genotype and plant organ analysed. Twenty-seven resistant and partially resistant accessions were identified in all plant stages and are promising sources of resistance to DM, namely 16 commercial varieties, 10 breeding lines, and one landrace. A significant correlation was observed between cotyledon and leaf (1st and 2nd leaves) DM resistance, but low and no correlation was found between the resistance of true-leaves or cotyledons and roots, respectively. Cotyledon and leaf evaluation cannot be used to predict root resistance response in radish. However, cotyledon resistance has its own value because non-infected cotyledons will act as a barrier to slow disease progression to true-leaves and roots. Interesting sources of DM resistance were identified that can be used in radish breeding programs.
Frequency distributions of pushing resistances in 44 CSSLs at 7 weeks after heading and correlations between pushing resistance and days to heading. a, b Show the histogram of PRL; d, e show the histogram of PRL/TN. c, f show the correlation. Black arrows indicate the mean values for “Koshihikari”
Map locations of QTLs for pushing resistance, tiller number, and days to heading. Simple sequence repeat (SSR) markers were defined by McCouch et al. (2002). Mapped QTLs indicate the locus detected at the same position in two years. K and N in parentheses indicate that “Koshihikari” and “Nona Bokra” alleles have a positive effect, respectively
Graphical genotypes on chromosome 4 in CSSL-PRL4 and IL-PRL4 (a) and pushing resistances of “Koshihikari” and IL-PRL4 (b). LPW4 locus is the QTL for low panicle weight reported by Ujiie et al. (2012). Vertical bars on pushing resistances indicate standard errors. ***, **, and * indicate significant differences at 0.001, 0.01, and 0.05 probability levels, respectively
Resistance to lodging, an important problem in rice production, has three types: low plant height, strong culm, and high strength of the lower part of the plant. The determinants of strength of the lower part remains unclear, compared with plant height and culm strength. This study identified a new genetic factor involved in the strength of the lower part, as assessed by pushing resistance, using chromosomal segment substitution lines (CSSLs) to clarify the determinants of strength of the lower part by functional analysis of the CSSL and the introgression line (IL) harboring the identified quantitative trait locus (QTL). QTL analysis identified the QTL for increasing pushing resistance on chromosome 4, PRL4, which was not related to days to heading. The CSSL with PRL4 showed increased pushing resistance and physical strength of the basal culm, but decreased filled grain ratio and grain weight. The IL with PRL4, developed by backcrossing this CSSL, improved pushing resistance and the strain of culm until breaking under compression, and did not decrease yield traits. These lines with PRL4 increased the accumulation of non-structural carbohydrate (NSC) in the basal culm at the fully ripe stage. Thus, the genetic control of NSC accumulation in culms by PRL4 may improve the strength of the lower part by enhancing culm toughness with strength and ductility.
Phelipanche ramosa infestation in a tomato cultivation
Schematic representation of strigolactones (SLs) biosynthesis (modified from Al-Babili and Bouwmeester 2015) and P. ramosa germination in tomato. It is hypothesized that SLs released in root exudates diffuses in the rhizosphere establishing a concentration gradient that allows P. ramosa seed germination and growth of parasite roots toward host roots (figure not in scale)
Soilless infection assay in different tomato genotype produced by genome editing. A large number of Phelipanche ramosa tubercles (red arrows) are produced in the wild type cv. Ailsa Craig a, while they are substantially reduced or totally absent in ccd7b and ccd8c knock-out genotypes, respectively
Broomrapes (Orobanche and Phelipanche spp.) are root holoparasites deriving their nourishment from the parasitic interaction they establish with the host plant. Vegetable crops are severely affected worldwide from broomrapes infestations, which are hard-to-manage through the conventional agronomical practices and determines relevant production losses. The identification of resistant varieties represents the ideal solution to face with this noxious threat, and several efforts were spent along decades in this perspective. In this review, we give an update about genetic and molecular mechanisms underlying the host-parasite interactions and a comprehensive overview on breeding for resistance to Orobanche and Phelipanche spp. in vegetables. Natural sources of resistance were discovered from germplasm exploration in some species, and artificial mutagenesis provided additional variability. Recent advancements in the genomics of parasitic and host plants, and the availability of new breeding technologies will pave the way for future developments, and valuable results have already been achieved in the last few years. The integration of different genetic resistance mechanisms, preferably interfering with different parasite’s developmental stages, with innovative agronomical management practices will probably provide a more effective and durable containment strategy.
Phylogenetic tree of advanced lines derived from different recurrent parents. HAAS1 denoted breeding lines derived from Yuhua15 × Kainong1715 (in red). HAAS2 denoted breeding lines derived from Yuanza9102 × DF12 (in blue). Bootstrap values were indicated on the branches. (Color figure online)
The peanut rich in oleic acid in seed oil, also known as high oleic peanut, renders its products superior in human healthy diet, long shelf life and high oxidative stability in food and oil processing. High oleic peanut varieties in China are derived from a handful of high oleic donors with limited genetic background. Improvement of high oleic peanut cultivars by integrating key target traits is crucial for both food security and germplasm enhancement. Several superior high oleic peanut lines have been developed by marker assisted backcrossing in our breeding program. The objective of present study is to characterize bacterial wilt disease resistance and yield related traits in these novel peanut lines. The two-year disease nursery survival rates were used as an indicator for bacterial wilt resistance, and the diagnostic markers identified by QTL mapping were used for molecular verification. Genetic background of high oleic peanut lines was estimated by 40 K genotyping by target sequencing (GBTS) SNP panel. Preliminary and regional yield tests were performed for selected breeding lines in 2021. As a result, an elite high oleic peanut accession Yuhua183 was identified, inheriting the superior characteristics of its recurrent parent such as resistance to bacterial wilt, high shelling percentage and early maturity. The development of Yuhua183 broadened the genetic background of high oleic peanut germplasm, providing valuable genetic resources for peanut breeding and further utilization.
Photomicrograph of metaphase chromosome from root tip cell of H. syriacus ‘Saejamyung’ (2n = 88). Viewed at 1000× Size bar 5 μm. (Color figure online)
Chromosomes counts in a H. syriacus ‘Saejamyung’ 2n = 88; b H. sinosyriacus ‘Seobong’ 2n = 80; c H. moscheutos ‘Luna Red’ 2n = 38; and d H. paramutabilis 2n = 82.
Viewed at 1000× Size bar 5 μm. (Color figure online)
FISH results of a H. syriacus ‘Saejamyung’ 2n = 88; b H. sinosyriacus ‘Seobong’ 2n = 80; c H. moscheutos ‘Luna Red’ 2n = 38; and d H. paramutabilis 2n = 82, 5S rDNA and 18S rDNA loci are indicated by green and red fluorescence respectively. Viewed at 1000× Size bar 5 μm. (Color figure online)
FISH karyotype detail of 5S rDNA and 18S rDNA loci on chromosomes of a H. syriacus ‘Saejamyung’; b H. sino syriacus ‘Seobong’; c H. moscheutos ‘Luna Red’; and d H. paramutabilis, where green fluorescence indicate 5S rDNA and red fluorescence indicates 18S rDNA. (Color figure online)
Histogram of nuclear DNA content of a H. syriacus ‘Saejamyung’, b H. sinosyriacus ‘Seobong’, c H. moscheutos ‘Luna Red’ and d H. paramutabilis. (Color figure online)
Determination of nuclear DNA content, genome size, and ploidy level and, information on cytogenetic characteristics are all prerequisite of modern plant breeding. However, identification of individual chromosomes of Hibiscus species is extremely difficult due to high number, small size and similar shape of mitotic chromosomes. The goal of the study was to ascertain the chromosome number, karyomorphology, distribution of 5S and 18S rDNA signals, chromosome length, and centromere positions as well as the ploidy level, genome sizes, 2C - DNA content of winter-hardy Hibiscus (H. syriacus ‘Saejamyung’, H. sinosyriacus ‘Seobong’, H. moscheutos ‘Luna Red’ and, H. paramutabilis). 5S rDNA and 18S rDNA signals were detected by fluorescence in situ hybridization (FISH). According to the FISH results, there are two 5S rDNA signals (green) in H. syriacus, H. sinosyriacus, and H. moscheutos, and four 5S rDNA signals in H. paramutabilis. The range in length of somatic chromosomes in H. syriacus, H. sinosyriacus, H. moscheutos, and H. paramutabilis is 2.66–7.06, 3.18–7.31, 2.91–5.23, and 4.75–7.60, respectively. The 2C - DNA content of H. syriacus, H. sinosyriacus, and H. paramutabilis are very similar, the amount was 4.06, 4.11, and 4.18 pg, respectively whereas, H. moscheutos has nearly half and that amount was 2.06 pg. These findings will contribute to the detailed cytogenetic assessment of Hibiscus and thus benefit plant breeding in this genus.
Trisomic cauliflower plants ( Brassica oleracea L. var. botrytis ) display abnormal curd phenotypes that seriously decrease commercial value of the crop. Despite extensive breeding efforts, selection of genotypes producing euploid gametes remains unsuccessful due to unknown genetic and environmental factors. To reveal an eventual role of an-euploid gametes, we analyzed chromosome pairing, chiasma formation and chromosome segregation in pollen mother cells of selected cauliflower genotypes. To this end we compared three genotypes exhibiting Low with < 5%, Moderate with 5–10% and High with > 10% aberrant offspring, respectively. Although chromosome pairing at pachytene was regular, cells at diakinesis and metaphase I showed variable numbers of univalents, suggesting partial desynapsis. Cells at anaphase I–telophase II exhibit various degrees of unbalanced chromosome numbers, that may explain the aneuploid offspring. Immunofluorescence probed with an MLH1 antibody demonstrated fluorescent foci in all genotypes, but their lower numbers do not correspond to the number of putative chiasmata. Interchromosomal connections between chromosomes and bivalents are common at diakinesis and metaphase I, and they contain centromeric and 45S rDNA tandem repeats, but such chromatin connections seem not to affect proper disjoin of the half bivalents at anaphase I. Moreover, male meiosis in the Arabidopsis APETALA 1/ CAULIFLOWER double mutant with the typical cauliflower phenotype does show interchromosomal connections, but there are no indications for partial desynapsis. The causality of the curd development on the desynapsis in cauliflower is still a matter of debate.
Top-cited authors
Rajeev K Varshney
  • Murdoch University
Pushpendra Gupta
  • Chaudhary Charan Singh University
Ravi Singh
  • International Maize and Wheat Improvement Center
S.C. Bhardwaj
  • ICAR-Indian Institute of Wheat and Barley Research, Karnal, Haryana, India
Julio Huerta-Espino
  • INIFAP Instituto Nacional de Investigaciones Forestales Agricolas y Pecuarias