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Identification and characterization of more than 4 million intervarietal SNPs across the group 7 chromosomes of bread wheat
Plant Biotechnology Journal
Abstract
Despite being a major international crop, our understanding of the wheat genome is relatively poor due to its large size and complexity. To gain a greater understanding of wheat genome diversity, we have identified single nucleotide polymorphisms between 16 Australian bread wheat varieties. Whole-genome shotgun Illumina paired read sequence data were mapped to the draft assemblies of chromosomes 7A, 7B and 7D to identify more than 4 million intervarietal SNPs. SNP density varied between the three genomes, with much greater density observed on the A and B genomes than the D genome. This variation may be a result of substantial gene flow from the tetraploid Triticum turgidum, which possesses A and B genomes, during early co-cultivation of tetraploid and hexaploid wheat. In addition, we examined SNP density variation along the chromosome syntenic builds and identified genes in low-density regions which may have been selected during domestication and breeding. This study highlights the impact of evolution and breeding on the bread wheat genome and provides a substantial resource for trait association and crop improvement. All SNP data are publically available on a generic genome browser GBrowse at www.wheatgenome.info.
... Crop breeding increasingly benefits from the application of molecular tools such as marker-assisted selection (MAS), and more recently genomic selection (GS), and the increasing availability of genomic information supports these advanced breeding tools (Poland et al., 2012;Crossa et al., 2014;Simeao Resende et al., 2014;Cros et al., 2015;Sallam et al., 2015). Modern molecular breeding tools apply single nucleotide polymorphism (SNP) molecular genetic markers, and numerous studies have discovered and validated large numbers of SNP markers across the wheat genome (Lai et al., 2012(Lai et al., , 2015Wang et al., 2014;Winfield et al., 2015). SNPs have been used to find genes that are undergoing selective sweeps and population bottlenecks (Cavanagh et al., 2013), and have also been used to map low-diversity regions which could have been targets of selection (Lai et al., 2015). ...
... Modern molecular breeding tools apply single nucleotide polymorphism (SNP) molecular genetic markers, and numerous studies have discovered and validated large numbers of SNP markers across the wheat genome (Lai et al., 2012(Lai et al., , 2015Wang et al., 2014;Winfield et al., 2015). SNPs have been used to find genes that are undergoing selective sweeps and population bottlenecks (Cavanagh et al., 2013), and have also been used to map low-diversity regions which could have been targets of selection (Lai et al., 2015). ...
... Golicz et al. (2016) characterized the pangenome of Brassica oleracea using nine diverse morphotypes, and assembled an additional 99 Mbp of sequence. The relatively small increase in pangenome assembly size we observe reflects the high degree of relatedness of the cultivars sequenced (Lai et al., 2015). The additional sequence identified in this study is likely to be an underestimate of the total sequence content present in the cultivars, as sequences present in only one or two of the cultivars are unlikely to have sufficient coverage to assemble, as IDBA-UD has 81% assembly efficiency for samples with a sequencing depth of 109 (Peng et al., 2012). ...
... However, this assembly contained only 12.7 Gbp, approximately threequarters of the whole genome. Furthermore, the genome sequences of the chromosomes/chromosome arms were fragmented with many gaps as well as many incomplete, absent, or incorrectly assigned genes making it hard for scientists to find and elucidate specific genes [2,7,8] Despite the incompleteness of this version, it was highly useful for breeders as it provided valuable information at the chromosomal/chromosome arm level. A draft whole genome sequence of wheat was obtained by combining long Pacific Biosciences (PacBio) reads (>10,000 bases long) with short (150-bp) Illumina reads, with 15.34 Gbp and an average contig size of 0.23 Mbp [9]. ...
... Recent investigations have focussed on the optimization of GS in genetic resources in order to harness new diversity from wheat gene banks. Crossa et al. [228] investigated GS models to predict days to heading and days to maturity on a large set of wheat landrace accessions (8,416 Mexican landrace accessions and 2,403 Iranian landrace accessions) from the CIMMYT gene bank using two strategies. The first strategy involved random cross-validation of the data in 20% training (TRN) and 80% testing (TST) (TRN20-TST80). ...
Recent technological advances in next-generation sequencing (NGS) technologies have dramatically reduced the cost of DNA sequencing, allowing species with large and complex genomes to be sequenced. Although bread wheat ( Triticum aestivum L.) is one of the world's most important food crops, until very recently efficient exploitation of molecular marker-assisted breeding approaches has lagged behind that achieved in other crop species due to its large polyploid genome. However, an international public-private effort spanning nine years reported over 65% draft genome of bread wheat in 2014, and finally, after more than a decade culminated in the release of a gold-standard, fully annotated reference wheat genome assembly in 2017. Shortly thereafter, in 2020, the genome of assemblies of additional fifteen global wheat accessions were released. Wheat has now entered into the pan-genomic era where basic resources can be efficiently exploited. Wheat genotyping with a few hundred markers has been replaced by genotyping arrays capable of genotyping hundreds of wheat lines using thousands of markers, providing fast, relatively inexpensive, and reliable data for exploitation in wheat breeding. These advances have opened up a new horizon for marker-assisted selection (MAS) and genomic selection (GS) in wheat. Herein, we review the advances and perspectives in wheat genetics and genomics, with a focus on key traits including grain yield, yield-related traits, end-use quality and resistance to biotic and abiotic stresses. We also enlisted several reported candidate and cloned candidate genes responsible for the aforesaid traits of interest. Furthermore, we report on the improvement in the aforementioned quantitative traits through the use of (i) clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9) mediated gene-editing, (ii) positional cloning methods, and of genomic selection. Finally, we make recommendations on the utilization of genomics for the next-generation wheat breeding and provide a practical example of using the latest, in silico bioinformatics tools that were based on the wheat reference genome sequence.
... In both studies, the number of SNPs was in the range of 200,000 to 300,000. Noticeable exceptions to complexity reduction approaches are the works conducted by Lai et al. [14] and Montenegro et al. [15] who used whole-genome resequencing data from 16 and 18 wheat accessions, respectively, to detect more than four million and 36.4 million SNPs on group 7 chromosomes and at the whole genome level, respectively. However, these two studies included mainly cultivars from Australia, leaving a significant part of the genetic diversity unexplored. ...
... This resource offers the possibility to investigate not only genic but also intergenic regions, including the repetitive fraction that has been shown to be a great source of SNPs for wheat genetics and breeding [18,20]. The overall proportions and distribution of SNPs between homoeologous genomes and chromosomes were quite consistent with previous studies in wheat [10,11,14,41]. However, the proportion of Dgenome SNPs identified in our study was slightly lower than previously reported (10% vs. ...
Because of their abundance and their amenability to high-throughput genotyping techniques, Single Nucleotide Polymorphisms (SNPs) are powerful tools for efficient genetics and genomics studies, including characterization of genetic resources, genome-wide association studies and genomic selection. In wheat, most of the previous SNP discovery initiatives targeted the coding fraction, leaving almost 98% of the wheat genome largely unexploited. Here we report on the use of whole-genome resequencing data from eight wheat lines to mine for SNPs in the genic, the repetitive and non-repetitive intergenic fractions of the wheat genome. Eventually, we identified 3.3 million SNPs, 49% being located on the B-genome, 41% on the A-genome and 10% on the D-genome. We also describe the development of the TaBW280K high-throughput genotyping array containing 280,226 SNPs. Performance of this chip was examined by genotyping a set of 96 wheat accessions representing the worldwide diversity. Sixty-nine percent of the SNPs can be efficiently scored, half of them showing a diploid-like clustering. The TaBW280K was proven to be a very efficient tool for diversity analyses, as well as for breeding as it can discriminate between closely related elite varieties. Finally, the TaBW280K array was used to genotype a population derived from a cross between Chinese Spring and Renan, leading to the construction a dense genetic map comprising 83,721 markers. The results described here will provide the wheat community with powerful tools for both basic and applied research.
... Whole-genome shotgun assembly developed from segregating 90 doubled haploid wheat lines also provided >19 million SNPs (Chapman et al. 2015). About four million intervarietal SNPs were also detected on chromosomes of homoeologous group 7 (7A, 7B, and 7D) using paired read sequences (Lai et al. 2015). In this manner, a vast reservoir of SNPs is already available in wheat. ...
... Freebayes detected more SNPs in comparison to quality-based variant detection because Freebayes was used using less stringent parameters in order to detect low coverage SNPs. Initial output of SnpEff predicted 51,642 total number effects ( Lai et al. 2015). The largest number of SNPs was present in 3′ UTR region followed by intergenic, downstream, and upstream regions (Table S5). ...
Single nucleotide polymorphisms (SNPs) are becoming the most amenable form of DNA-based molecular markers for genetic analysis. In hexaploid bread wheat (Triticum aestivum L.), it is difficult to discern true polymorphic SNPs due to homoeologous and paralogous genes. Two serial analysis of gene expression (SAGE) libraries were developed utilizing leaves from resistant plants carrying leaf rust resistance gene Lr28; one library was derived from leaves that were mock inoculated and the other was derived from leaves inoculated with the urediniospores of the leaf rust pathogen Puccinia triticina. Next-generation sequencing reads, after quality trimming and removal of fungal sequences, were mapped to wheat reference sequences at Ensembl Plants. CLC Genomics Workbench and Freebayes softwares were employed for SNP calling. A total of 611 SNPs were predicted to be common by both softwares, of which 207 varietal SNPs were identified by ConservedPrimer software. A subset of 100 SNPs was used for validation across 47 wheat genotypes using Kompetitive Allele Specific PCR (KASP) assay; 83 SNPs could be successfully validated. These SNPs were positioned on wheat subgenomes and chromosome arms. When functionally annotated, many sequences harboring SNPs showed homology to resistance and resistance-like genes listed in Plant Resistance Gene database (PRGdb) as well as pathogenesis-related (PR) and stress-responsive genes. The results of the present study involving discovery of SNPs associated with resistance to leaf rust, a major threat to wheat production worldwide, will be valuable for molecular breeding for rust resistance.
... Over the past few years, tremendous efforts in SNP discovery have been made in wheat, mainly targeting the coding fraction of the genome. Various approaches have been used, including cDNA sequencing (Allen et al., 2011), targeted resequencing of the wheat exome (Allen et al., 2013;Winfield et al., 2012), transcriptome sequencing (Lai et al., 2012), and whole-genome resequencing (Lai et al., 2015;International Wheat Genome Sequencing Consortium, 2014). These projects have led to the discovery of several millions of SNPs. ...
... Based on these proportions, one can extrapolate that this approach would lead to the discovery of more than 400,000 ISBP-SNPs in the whole wheat genome. As this number is relatively low compared to whole-genome resequencing approaches (Lai et al., 2015; International Wheat Genome Sequencing Consortium, 2014), this complexity reduction approach allows for SNPs to be mined in a larger set of lines, thus reducing ascertainment bias. ...
Transposable elements (TEs) account for more than 80% of the wheat genome. Although they represent a major obstacle for genomic studies, TEs are also a source of polymorphism and consequently of molecular markers such as insertion site-based polymorphism (ISBP) markers. Insertion site-based polymorphisms have been found to be a great source of genome-specific singlenucleotide polymorphism (SNPs) in the hexaploid wheat (Triticum aestivumL.) genome. Here, we report on the development of a high-throughput SNP discovery approach based on sequence capture of ISBP markers. By applying this approach to the reference sequence of chromosome 3B from hexaploid wheat, we designed 39,077 SNPs that are evenly distributed along the chromosome. We demonstrate that these SNPs can be efficiently scored with the KASPar (Kompetitive allele-specific polymerase chain reaction) genotyping technology. Finally, through genetic diversity and genome-wide association studies, we also demonstrate that ISBP-derived SNPs can be used in marker-assisted breeding programs.
... Our own experience of Next Generation Sequencing (NGS) with 9 K Illumina Infinium SNP array in wheat [10] confirmed the supreme effectiveness of this technology in crops [11]. In wheat, the numbers of available SNP markers is growing rapidly jumping from 90 K as recorded by the new Infinium [12,13] to 500 K and 4 M in Illumina shortgun WGS array [14,15]. ...
... In durum wheat, the range of applied SNP markers is even wider including: 2.6K [24], 26K [25] and 90K [12]. Most recently, a 9M SNP array in a single homeologous group of chromosome 7 in bread wheat has been reported [15]. Clearly, SNP markers continue to be of great value to plant genetic research and the true extent of their worth may not yet be apparent. ...
Background
Barley and bread wheat show large differences in frequencies of Single Nucleotide Polymorphism (SNP) as determined from genome-wide studies. These frequencies have been estimated as 2.4-3 times higher in the entire barley genome than within each diploid genomes of wheat (A, B or D). However, barley SNPs within individual genes occur significantly more frequently than quoted. Differences between wheat and barley are based on the origin and evolutionary history of the species. Bread wheat contains rarer SNPs due to the double genetic ‘bottle-neck’ created by natural hybridisation and spontaneous polyploidisation. Furthermore, wheat has the lowest level of useful SNP-derived markers while barley is estimated to have the highest level of polymorphism.
Results
Different strategies are required for the development of suitable molecular markers in these cereal species. For example, SNP markers based on high-throughput technology (Infinium or KASP) are very effective and useful in both barley and bread wheat. In contrast, Cleaved Amplified Polymorphic Sequences (CAPS) are more widely and successfully employed in small-scale experiments with highly polymorphic genetic regions containing multiple SNPs in barley, but not in wheat. However, preliminary ‘in silico’ search databases for assessing the potential value of SNPs have yet to be developed.
Conclusions
This mini-review summarises results supporting the development of different strategies for the application of effective SNP and CAPS markers in wheat and barley.
... Here, we present the application of a skim-based genotyping by sequencing (skimGBS) method in B. napus and C. arietinum to assess the frequency and distribution of recombination. SGSautoSNP has been previously used to successfully predict SNPs in B. napus with an accuracy of >95 % (Hayward et al. 2012a) and in wheat with an accuracy of 93 % (Lai et al. 2014). By combining this SNP discovery method with skimGBS, we can assess the segregation of SNPs in a population. ...
... We used only non-repetitively aligning reads to minimise the number of SNPs from homeologous regions (Lai et al. 2014;Lorenc et al. 2012). As we require two adjacent SNPs to call a gene conversion and need both SNPs to be at least 20 bp apart, we estimate the frequency of miscalled gene conversions due to sequence error to be negligible. ...
Key message
We characterise the distribution of crossover and non-crossover recombination in
Brassica napus
and
Cicer arietinum
using a low-coverage genotyping by sequencing pipeline SkimGBS.
Abstract
The growth of next-generation DNA sequencing technologies has led to a rapid increase in sequence-based genotyping for applications including diversity assessment, genome structure validation and gene–trait association. We have established a skim-based genotyping by sequencing method for crop plants and applied this approach to genotype-segregating populations of Brassica napus and Cicer arietinum. Comparison of progeny genotypes with those of the parental individuals allowed the identification of crossover and non-crossover (gene conversion) events. Our results identify the positions of recombination events with high resolution, permitting the mapping and frequency assessment of recombination in segregating populations.
... However, this assembly contained only approximately threequarters of the whole wheat genome. Furthermore, the genome sequences of the chromosomes/chromosome arms were fragmented with many gaps as well as many incomplete, absent, or incorrectly assigned genes, making it hard for scientists to find and elucidate specific genes (Berkman et al., 2013;IWGSC, 2014;Lai et al., 2015). Despite the incompleteness of this version, it was highly useful for breeders, as it provided valuable information at the chromosomal/chromosome-arm level. ...
Recent technological advances in next-generation sequencing (NGS) technologies have dramatically reduced the cost of DNA sequencing, allowing species with large and complex genomes to be sequenced. Although bread wheat (Triticum aestivum L.) is one of the world’s most important food crops, efficient exploitation of molecular marker-assisted breeding approaches has lagged behind that achieved in other crop species, due to its large polyploid genome. However, an international public–private effort spanning 9 years reported over 65% draft genome of bread wheat in 2014, and finally, after more than a decade culminated in the release of a gold-standard, fully annotated reference wheat-genome assembly in 2018. Shortly thereafter, in 2020, the genome of assemblies of additional 15 global wheat accessions was released. As a result, wheat has now entered into the pan-genomic era, where basic resources can be efficiently exploited. Wheat genotyping with a few hundred markers has been replaced by genotyping arrays, capable of characterizing hundreds of wheat lines, using thousands of markers, providing fast, relatively inexpensive, and reliable data for exploitation in wheat breeding. These advances have opened up new opportunities for marker-assisted selection (MAS) and genomic selection (GS) in wheat. Herein, we review the advances and perspectives in wheat genetics and genomics, with a focus on key traits, including grain yield, yield-related traits, end-use quality, and resistance to biotic and abiotic stresses. We also focus on reported candidate genes cloned and linked to traits of interest. Furthermore, we report on the improvement in the aforementioned quantitative traits, through the use of (i) clustered regularly interspaced short-palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-mediated gene-editing and (ii) positional cloning methods, and of genomic selection. Finally, we examine the utilization of genomics for the next-generation wheat breeding, providing a practical example of using in silico bioinformatics tools that are based on the wheat reference-genome sequence.
... Wheat genomics has made rapid advances in recent years with the first draft genome assembly produced in 2014 (The International Wheat Genome Sequencing Consortium [IWGSC], 2014) based on the shotgun sequencing of isolated chromosome arms (Berkman et al., 2011(Berkman et al., , 2012Lai et al., 2015). A first near-complete assembly of the 'Chinese Spring' was produced in 2017 (Zimin et al., 2017) with a final reference genome assembly available in 2018 (IWGSC, 2018). ...
Bread wheat (Triticum aestivum L.) is one of humanity's most important staple crops, characterized by a large and complex genome with a high level of gene presence–absence variation (PAV) between cultivars, hampering genomic approaches for crop improvement. With the growing global population and the increasing impact of climate change on crop yield, there is an urgent need to apply genomic approaches to accelerate wheat breeding. With recent advances in DNA sequencing technology, a growing number of high‐quality reference genomes are becoming available, reflecting the genetic content of a diverse range of cultivars. However, information on the presence or absence of genomic regions has been hard to visualize and interrogate because of the size of these genomes and the lack of suitable bioinformatics tools. To address this limitation, we have produced a wheat pangenome graph maintained within an online database to facilitate interrogation and comparison of wheat cultivar genomes. The database allows users to visualize regions of the pangenome to assess PAV between bread wheat genomes. Graph pangenomes represent more genomic variants than reference genomes. We present a wheat graph pangenome based on 16 public assemblies. We present Wheat Panache, an online visual representation of this graph. Wheat Panache lets users search the graph for presence–absence variants. We also distribute the graph preindexed for Giraffe utilization.
... While SNP discovery using whole genome sequence data is currently limited to a relatively small number of wheat and barley accessions, this situation is expected to rapidly change as sequencing costs continue to decrease. For example, 4M group 7 chromosome SNPs from 16 bread wheat accessions (Lai et al., 2015) and 36M whole genome SNPs from 18 bread wheat accessions (Montenegro et al., 2017) have previously been reported. The more recent publication of the whole genome 1 https://www.earthbiogenome.org/ ...
Array-based single nucleotide polymorphism (SNP) genotyping platforms have low genotype error and missing data rates compared to genotyping-by-sequencing technologies. However, design decisions used to create array-based SNP genotyping assays for both research and breeding applications are critical to their success. We describe a novel approach applicable to any animal or plant species for the design of cost-effective imputation-enabled SNP genotyping arrays with broad utility and demonstrate its application through the development of the Illumina Infinium Wheat Barley 40K SNP array Version 1.0. We show that the approach delivers high quality and high resolution data for wheat and barley, including when samples are jointly hybridised. The new array aims to maximally capture haplotypic diversity in globally diverse wheat and barley germplasm while minimizing ascertainment bias. Comprising mostly biallelic markers that were designed to be species-specific and single-copy, the array permits highly accurate imputation in diverse germplasm to improve the statistical power of genome-wide association studies (GWAS) and genomic selection. The SNP content captures tetraploid wheat (A- and B-genome) and Aegilops tauschii Coss. (D-genome) diversity and delineates synthetic and tetraploid wheat from other wheat, as well as tetraploid species and subgroups. The content includes SNP tagging key trait loci in wheat and barley, as well as direct connections to other genotyping platforms and legacy datasets. The utility of the array is enhanced through the web-based tool, Pretzel ( https://plantinformatics.io/ ) which enables the content of the array to be visualized and interrogated interactively in the context of numerous genetic and genomic resources to be connected more seamlessly to research and breeding. The array is available for use by the international wheat and barley community.
... With the advent of nextgeneration sequencing (NGS) technologies, the focus of researchers has shifted from single-genome analysis to multiple-genome analysis and population studies (Redon et al., 2006). Ever since the first plant genome sequence became available (The Arabidopsis Genome Initiative, 2000), comparative genomic studies have largely focused on single nucleotide polymorphisms (SNPs) in different plant species (Gore et al., 2009;Lai et al., 2015;McNally et al., 2009). A general consensus of the current research is that a single reference genome does not adequately represent the complete genetic content and diversity of a species because of the presence of structural variations (SVs) and TEs, which significantly modify the genetic makeup of different individuals within a species (Saxena, Edwards, & Varshney, 2014). ...
Proteomics is rapidly expanding with the advent of high throughput
technologies and offers a greater understanding of the complexity of life and the
process of evolution. Protein profile comparison between genetically heterogeneous
individuals may provide important insights into physiological diversity and function. A
new term, pan-proteomics, has also been introduced that permits the qualitative and
quantitative comparison of proteomes of genetically heterogeneous organisms. Here in
this chapter, various aspects of pan-proteomics along with its basic methodology and
applications have been discussed.
... costs continue to decrease. For example, Lai et al. (2015) and Montenegro et al. (2017) used whole 79 genome sequence data from 16 and 18 bread wheat accessions to identify more than 4M and 36M 80 SNP on group 7 chromosomes and at the whole genome level, respectively. The more recent 81 publication of whole genome sequence assemblies for 14 modern bread wheat varieties from global 82 breeding programs (Walkowiak et al. 2020) provides additional new resources for de novo whole 83 genome SNP discovery and to investigate structural variation within the wheat genome. ...
Array-based SNP genotyping platforms have low genotype error and missing data rates compared to genotyping-by-sequencing technologies. However, design decisions used to create array-based SNP genotyping assays for both research and breeding applications are critical to their success. We describe a novel approach applicable to any animal or plant species for the design of cost-effective imputation-enabled SNP genotyping arrays with broad utility and demonstrate its application through the development of the Infinium Wheat Barley 40K SNP array. We show the approach delivers high-quality and high-resolution data for wheat and barley, including when samples are jointly hybridised. The new array aims to maximally capture haplotypic diversity in globally diverse wheat and barley germplasm while minimising ascertainment bias. Comprising mostly biallelic markers designed to be species-specific and single-copy, it permits highly accurate imputation in diverse germplasm to improve statistical power for GWAS and genomic selection. The SNP content captures tetraploid wheat (A- and B-genome) and Ae. tauschii (D-genome) diversity and delineates synthetic and tetraploid wheat from other wheats, as well as tetraploid species and subgroups. The content includes SNP tagging key trait loci in wheat and barley and that directly connect to other genotyping platforms and legacy datasets. The utility of the array is enhanced through the web-based tool Pretzel ( https://plantinformatics.io/ ) which enables the array’s content to be visualised and interrogated interactively in the context of numerous genetic and genomic resources to more seamlessly connect research and breeding. The array is available for use by the international wheat and barley community.
Short summary
Designing SNP genotyping arrays for closely related species with broad applicability in both research and breeding is challenging. Here we describe a novel generic approach to select SNP content for such arrays and demonstrate its utility in wheat and barley to: capture haplotypic diversity while minimising ascertainment bias;
accurately impute to high SNP density in diverse germplasm;
generate high-quality high-resolution genotypic data; and
jointly hybridise samples to the same bead chip array.
... These traits are quantitative, determined by multigenic control, and strongly influenced by the environment [21]. The "dissection" of complex traits has been enhanced by the development of analysis technologies focused on identifying quantitative trait loci (QTL) underlying phenotypic variation [22][23][24][25]. Analysis of candidate genes and genome-wide association studies (GWASs) have been performed in bread wheat to identify SNP markers controlling traits such as dehydration tolerance [26,27], leaf rust resistance [28], grain yield [29], carbon isotope discrimination [30], kernel and root morphology [31,32], resistance to low nitrogen [33], and leaf traits [34], among others. ...
... These traits are quantitative, determined by multigenic control, and strongly influenced by the environment [21]. The "dissection" of complex traits has been enhanced by the development of analysis technologies focused on identifying quantitative trait loci (QTL) underlying phenotypic variation [22][23][24][25]. Analysis of candidate genes and genome-wide association studies (GWASs) have been performed in bread wheat to identify SNP markers controlling traits such as dehydration tolerance [26,27], leaf rust resistance [28], grain yield [29], carbon isotope discrimination [30], kernel and root morphology [31,32], resistance to low nitrogen [33], and leaf traits [34], among others. ...
Water deficit represents an important challenge for wheat production in many regions of the world. Accumulation and remobilization of water-soluble carbohydrates (WSCs) in stems are part of the physiological responses regulated by plants to cope with water stress and, in turn, determine grain yield (GY). The genetic mechanisms underlying the variation in WSC are only partially understood. In this study, we aimed to identify Single Nucleotide Polymorphism (SNP) markers that account for variation in a suite of WSC and GY, evaluated in 225 cultivars and advanced lines of spring wheat. These genotypes were established in two sites in the Mediterranean region of Central Chile, under water-limited and full irrigation conditions, and assessed in two growing seasons, namely anthesis and maturity growth periods. A genome-wide association study (GWAS) was performed by using 3243 SNP markers. Genetic variance accounted for 5 to 52% of phenotypic variation of the assessed traits. A rapid linkage disequilibrium decay was observed across chromosomes (r2 ≤ 0.2 at 2.52 kbp). Marker-trait association tests identified 96 SNPs related to stem weight (SW), WSCs, and GY, among other traits, at the different sites, growing seasons, and growth periods. The percentage of SNPs that were part of the gene-coding regions was 34%. Most of these genes are involved in the defensive response to drought and biotic stress. A complimentary analysis detected significant effects of different haplotypes on WSC and SW, in anthesis and maturity. Our results evidence both genetic and environmental influence on WSC dynamics in spring wheat. At the same time, they provide a series of markers suitable for supporting assisted selection approaches and functional characterization of genes.
... Molecular markers are highly useful for genetic and genomic studies, such as linkage map construction, map-based cloning, marker-trait associated analysis, genetic diversity analysis and marker-assisted breeding for crop improvement [8][9][10][11][12][13]. Single nucleotide polymorphisms (SNPs) are the most abundant type of genetic variation in both animal and plant genomes, and have become the marker of choice in large-scale genotyping applications [14][15][16]. With the reduced cost of next-generation sequencing (NGS) technologies, an increasing number of SNP loci have been detected in many crops [17][18][19]. ...
Kompetitive allele-specific PCR (KASP) is a cost-effective single-step SNP genotyping technology, With an objective to enhance the marker repertoire and develop high efficient KASP-SNP markers in Chinese cabbage, we re-sequenced four Chinese cabbage doubled haploid (DH) lines, Y177-47, Y635-10, Y510-1 and Y510-9, and generated a total of more than 38.5 billion clean base pairs. A total of 827,720 SNP loci were identified with an estimated density of 3,217 SNPs/Mb. Further, a total of 387,354 SNPs with at least 30 bp to the next most adjacent SNPs on either side were selected as resource for KASP markers. From this resource, 258 (96.27%) of 268 SNP loci were successfully transformed into KASP-SNP markers using a Roche LightCycler 480-II instrument. Among these markers, 221 (85.66%) were co-dominant markers, 220 (85.27%) were non-synonymous SNPs, and 257 (99.6%) were newly developed markers. In addition, 53 markers were applied for genotyping of 34 Brassica rapa accessions. Cluster analysis separated these 34 accessions into three clusters based on heading types. The millions of SNP loci, a large set of resource for KASP markers, as well as the newly developed KASP markers in this study may facilitate further genetic and molecular breeding studies in Brassica rapa.
... With the advent of nextgeneration sequencing (NGS) technologies, the focus of researchers has shifted from single-genome analysis to multiple-genome analysis and population studies (Redon et al., 2006). Ever since the first plant genome sequence became available (The Arabidopsis Genome Initiative, 2000), comparative genomic studies have largely focused on single nucleotide polymorphisms (SNPs) in different plant species (Gore et al., 2009;Lai et al., 2015;McNally et al., 2009). A general consensus of the current research is that a single reference genome does not adequately represent the complete genetic content and diversity of a species because of the presence of structural variations (SVs) and TEs, which significantly modify the genetic makeup of different individuals within a species (Saxena, Edwards, & Varshney, 2014). ...
Plant genomes contain both protein‐coding and noncoding sequences including transposable elements (TEs) and noncoding RNAs (ncRNAs). The ncRNAs are recognized as important elements that play fundamental roles in the structural organization and function of plant genomes. Despite various hypotheses, TEs are believed to be a major precursor of ncRNAs. Transposable elements are also prime factors that cause genomic variation among members of a species. Hence, TEs pose a major challenge in the discovery and analysis of ncRNAs. With the increase in the number of sequenced plant genomes, it is now accepted that a single reference genome is insufficient to represent the complete genomic diversity and contents of a species, and exploring the pan‐genome of a species is critical. In this review, we summarize the recent progress in the field of plant pan‐genomes. We also discuss TEs and their roles in ncRNA biogenesis and present our perspectives on the application of pan‐genomes for the discovery of ncRNAs to fully explore and exploit their biological roles in plants.
... Dubcovsky and Dvorak (2007) reported the hexaploid wheat was found to have a larger portion of the natural gene diversity from its tetraploid ancestor (AABB) than the diversity found in the Aegilops tauschii (DD). Similarly, the identification of a relatively higher frequency of SNPs showing transition substitutions (62.3%) than transversions is consistent with previous genome-wide SNP discovery studies in crop plants, including wheat (Parida et al., 2012;Lai et al., 2015;Rimbert et al., 2018;Alipour et al., 2019). The present study showed that the GBS-derived SNPs hold potential variation among genomes, which has to be explored further by analyzing the genomic variation of Triticum genotypes. ...
Wheat (Triticum spp.) has been an important staple food crop for mankind since the beginning of agriculture. The genus Triticum L. is composed of diploid, tetraploid, and hexaploid species, majority of which have not yet been discriminated clearly, and hence their phylogeny and classification remain unresolved. Genotyping-by-sequencing (GBS) is an easy and affordable method that allows us to generate genome-wide single nucleotide polymorphism (SNP) markers. In this study, we used GBS to obtain SNPs covering all seven chromosomes from 283 accessions of Triticum-related genera. After filtering low-quality and redundant SNPs based on haplotype information, the GBS assay provided 14,188 high-quality SNPs that were distributed across the A (71%), B (26%), and D (2.4%) genomes. Cluster analysis and discriminant analysis of principal components (DAPC) allowed us to distinguish six distinct groups that matched well with Triticum species complexity. We constructed a Bayesian phylogenetic tree using 14,188 SNPs, in which 17 Triticum species and subspecies were discriminated. Dendrogram analysis revealed that the polyploid wheat species could be divided into groups according to the presence of A, B, D, and G genomes with strong nodal support and provided new insight into the evolution of spelt wheat. A total of 2,692 species-specific SNPs were identified to discriminate the common (T. aestivum) and durum (T. turgidum) wheat cultivar and landraces. In principal component analysis grouping, the two wheat species formed individual clusters and the SNPs were able to distinguish up to nine groups of 10 subspecies. This study demonstrated that GBS-derived SNPs could be used efficiently in genebank management to classify Triticum species and subspecies that are very difficult to distinguish by their morphological characters.
... The results in the present study may help users to make informed decisions when choosing genotyping platforms. In addition to the platforms used in the present study, platforms with higher density-for example, the wheat 500K (Butcher, Davis, Craig, & Plomin, 2008), 660K (Zhang et al., 2017), 820K (Winfield et al., 2016), and 4 M (Lai et al., 2015) arrays-are available. Perhaps only those programs that have Crop Science the objective of pure gene discovery warrant the use of very high-density platforms, due to the higher cost and the fact that medium-density platforms like I90K and DArTseq probably have enough power to detect MTAs from GWAS and for genomic selection. ...
Notwithstanding the rapid development of high‐throughput genotyping platforms in recent years, several plant research programs find themselves in a dilemma of which marker system to use while conducting genome‐wide association studies (GWAS) and genomic selection. To gain insight into this, we genotyped an elite spring wheat (Triticum aestivum L.) association mapping initiative (WAMI, 287 lines) panel with various array‐based platforms—(i) Diversity Arrays Technology (DArT), (ii) Illumina Infinium BeadChip wheat 9K iSelect (I9K), and (iii) wheat 90K iSelect (I90K)—and sequencing‐based platform DArTseq. The raw markers refined using a common set of protocols after the bioinformatics analysis were compared by performing a series of genetic analyses: estimates of genetic diversity through nucleotide diversity (π), population structure and familial relatedness, marker‐trait associations (MTAs), and genomic prediction. Results indicated that genetic data from DArTseq consisted of a high proportion of rare allele markers (1% < minor allele frequency < 5%). The nucleotide diversity statistic (π) was higher for the array‐based single nucleotide polymorphisms (SNPs) than sequencing‐based SNPs. The I9K detected population structure caused by the variety ‘Kauz’ and grouped the population into two subgroups, whereas I90K, DArT, and DArTseq detected five subgroups driven by key pedigrees. The I90K with the highest marker density identified a high number of significant MTAs. Genomic prediction accuracy varied among traits; DArTseq and I90K produced similar prediction accuracies. Among the marker platforms compared, I90K was the best genotyping platform for GWAS, and DArTseq—given the low cost per SNP—was the best platform for genomic prediction in spring wheat.
... Cloning and sequencing of EPSPS in wheat cv. Fielder A vast number of intervarietal SNPs are known to exist in hexaploid wheat [44]. Therefore, for the purpose of designing effective gRNAs, we first obtained sequence information for the three homoeoalleles of EPSPS in our target wheat cv. ...
Background:
The CRISPR-Cas9 system is a powerful and versatile tool for crop genome editing. However, achieving highly efficient and specific editing in polyploid species can be a challenge. The efficiency and specificity of the CRISPR-Cas9 system depends critically on the gRNA used. Here, we assessed the activities and specificities of seven gRNAs targeting 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) in hexaploid wheat protoplasts. EPSPS is the biological target of the widely used herbicide glyphosate.
Results:
The seven gRNAs differed substantially in their on-target activities, with mean indel frequencies ranging from 0% to approximately 20%. There was no obvious correlation between experimentally determined and in silico predicted on-target gRNA activity. The presence of a single mismatch within the seed region of the guide sequence greatly reduced but did not abolish gRNA activity, whereas the presence of an additional mismatch, or the absence of a PAM, all but abolished gRNA activity. Large insertions (≥20 bp) of DNA vector-derived sequence were detected at frequencies up to 8.5% of total indels. One of the gRNAs exhibited several properties that make it potentially suitable for the development of non-transgenic glyphosate resistant wheat.
Conclusions:
We have established a rapid and reliable method for gRNA validation in hexaploid wheat protoplasts. The method can be used to identify gRNAs that have favourable properties. Our approach is particularly suited to polyploid species, but should be applicable to any plant species amenable to protoplast transformation.
... Prevailing next-generation sequencing (NGS) technologies make available the opportunity of large-scale SNP detection by evaluating whole-genome shotgun sequences of datasets from crop plants with high-quality reference genome sequences. Recently Lai et al., (2015) identified around 4 million intervarietal SNPs in bread wheat. This study also provided insight into the molecular consequences of the evolution and selection that resulted in modern hexaploid wheat. ...
... During the evolution of modern bread wheat, there has been extensive gene flow between hexaploid T. aestivum and tetraploid emmer wheat (AABB), while gene flow between the hexaploid and Ae. tauschii (DD) might have not occurred [44][45][46][47], which might explain higher polymorphism on the A and B genomes than on the D genome [31,48]. The greatest number of SNPs was mapped to the chromosome 3B and the least number of SNPs was mapped to the chromosome 4D, which agrees with Edae et al. [4] using W7984 and CSSS assemblies. ...
Genotyping-by-sequencing (GBS) provides high SNP coverage and has recently emerged as a popular technology for genetic and breeding applications in bread wheat (Triticum aes-tivum L.) and many other plant species. Although GBS can discover millions of SNPs, a high rate of missing data is a major concern for many applications. Accurate imputation of those missing data can significantly improve the utility of GBS data. This study compared imputa-tion accuracies among four genome references including three wheat references (Chinese Spring survey sequence, W7984, and IWGSC RefSeq v1.0) and one barley reference genome by comparing imputed data derived from low-depth sequencing to actual data from high-depth sequencing. After imputation, the average number of imputed data points was the highest in the B genome (~48.99%). The D genome had the lowest imputed data points (~15.02%) but the highest imputation accuracy. Among the four reference genomes, IWGSC RefSeq v1.0 reference provided the most imputed data points, but the lowest impu-tation accuracy for the SNPs with < 10% minor allele frequency (MAF). The W7984 reference , however, provided the highest imputation accuracy for the SNPs with < 10% MAF.
... The polyploidy of bread wheat and several Brassica genomes makes them particularly challenging to assemble, and recent advances for Brassica crops ( Bayer et al., 2017;Yang et al., 2016;Zhang et al., 2018) and bread wheat ( Appels et al., 2018;Montenegro et al., 2017) aim to improve reference genome assembly quality. Further studies have identified genome-wide single nucleotide polymorphisms (SNPs) for B. napus (Bancroft et al., 2011;Bayer et al., 2015;Bus et al., 2012;Dalton-Morgan et al., 2014;Delourme et al., 2013;Schmutzer et al., 2015) and wheat Lai et al., 2012;Lai et al., 2015;Lopes et al., 2015;Rimbert et al., 2018;Winfield et al., 2017). SNPs are the most common form of genomic variation and contribute to crop improvement by enabling marker assisted selection and genomic selection ( Jannink et al., 2010;Varshney et al., 2009). ...
Advances in sequencing technology have led to a rapid rise in the genomic data available for plants, driving new insights into the evolution, domestication and improvement of crops. Single nucleotide polymorphisms (SNPs) are a major component of crop genomic diversity and are invaluable as genetic markers in research and breeding programs. High‐throughput SNP arrays, or ‘SNP chips’, can generate reproducible sets of informative SNP markers and have been broadly adopted. Although there are many public repositories for sequencing data, which is routinely uploaded, there are no formal repositories for crop SNP array data. To make SNP array data more easily accessible, we have developed CropSNPdb (http://snpdb.appliedbioinformatics.com.au), a database for SNP array data produced by the Illumina Infinium™ hexaploid bread wheat (Triticum aestivum) 90K and Brassica 60K arrays. We currently host SNPs from datasets covering 526 Brassica lines and 309 bread wheat lines, and provide search, download and upload utilities for users. CropSNPdb provides a useful repository for these data which can be applied for a range of genomics and molecular crop breeding activities.
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... The genomic distribution of SNPs across tef's pseudomolecules was uneven, with moderate SNP density per Mb (Figure 1), and was largely in agreement with results reported for various crop species, including rice [47,48], wheat [15,49], common bean [27], soybean [50,51], barley [15], cabbage [52], chickpea [53], and cotton [46]. As part of an ongoing investigation, examining the relationship between the patterns of SNP distribution and/or density and the presumed functional consequences on genes in the different parts of the tef genome is suggested. ...
The genus Eragrostis consists of 350 species, including tef (Eragrostis tef (Zucc.) Trotter), the only cultivated species in this genus. Very little is known about the genetic potential of these species for tef improvement and genomics research. Here, we investigated a germplasm panel consisting of 40 Eragrostis species and 42 tef lines with single nucleotide polymorphism (SNP) data generated using the genotyping by sequencing (GBS) protocol. Thousands of SNPs were identified genome-wide from the germplasm panel. High-quality SNPs were used to assess sequence similarity and/or divergence, genetic diversity, population structure, and phylogenetic relationships. Mapping individual reads to the tef reference genome revealed that of the 40 wild Eragrostis species included in this study, E. pilosa, E. aethiopica, E. obtusa, E. ferruginea, E. lugens, and E. lehmanniana had 92% of their sequences represented in the tef reference genome. In the maximum likelihood phylogenetic analysis, these wild species clearly showed grouping in the clade consisting of the entire tef germplasm. Population structure analysis showed two major clusters consistent with the germplasm class information and the inferred phylogenetic relationships. The wild Eragrostis species were more diverse than the tef cultivars and could therefore potentially be used to enrich the tef gene pool. The SNP dataset and the results documented here are taxonomically the most inclusive to date and could be a useful informational tool for the design of genomics-informed tef breeding and research.
... Currently, TAGdb hosts around 20 TB of Illumina raw read data of different species, including wheat, barley and rye. Wheat data comprises sequences from 16 Australian bread wheat cultivars [18] and Chinese Spring. The Chinese Spring data includes sequence data for each chromosome arm. ...
The genomics revolution brought on by advances in high-throughput sequencing has led to the production of vast amounts of data. Databases play an essential role in storing and managing this information to make it available to researchers and crop breeders. This chapter provides an outline of how to use databases and tools for wheat genome research.
... These are available in a generic genome browser, GBrowse, at www.wheatgenome.info (Lai et al., 2015). SNP identification is challenging in complex polyploid and/or outcrossing heterozygous genomes due to mis-assembly and false positive SNP identification (Mason, 2015). ...
Most important food and feed crops in the world belong to the C3 grass family. The future of food security is highly reliant on achieving genetic gains of those grasses. Conventional breeding methods have already reached a plateau for improving major crops. Genomics tools and resources have opened an avenue to explore genome-wide variability and make use of the variation for enhancing genetic gains in breeding programs. Major C3 annual cereal breeding programs are well equipped with genomic tools; however, genomic research of C3 cool-season perennial grasses is lagging behind. In this review, we discuss the currently available genomics tools and approaches useful for C3 cool-season perennial grass breeding. Along with a general review, we emphasize the discussion focusing on forage grasses that were considered orphan and have little or no genetic information available. Transcriptome sequencing and genotype-by-sequencing technology for genome-wide marker detection using next-generation sequencing (NGS) are very promising as genomics tools. Most C3 cool-season perennial grass members have no prior genetic information; thus NGS technology will enhance collinear study with other C3 model grasses like Brachypodium and rice. Transcriptomics data can be used for identification of functional genes and molecular markers, i.e., polymorphism markers and simple sequence repeats (SSRs). Genome-wide association study with NGS-based markers will facilitate marker identification for marker-assisted selection. With limited genetic information, genomic selection holds great promise to breeders for attaining maximum genetic gain of the cool-season C3 perennial grasses. Application of all these tools can ensure better genetic gains, reduce length of selection cycles, and facilitate cultivar development to meet the future demand for food and fodder.
... Le modèle (simplifié) est le suivant : , et des changements de variances génétiques dans le temps (Lawlor et al., 2002). Kolmodin et al., (2002) (Lai et al., 2015). Avec l'accroissement considérable de l'information moléculaire, la sélection commence à avoir accès aux polymorphismes causaux expliquant la variation de caractères d'intérêt, ou à des polymorphismes en déséquilibre de liaison très fort avec ces derniers. ...
Un des principaux enjeux de l’amélioration des plantes consiste aujourd’hui à faire face au changement climatique, en assurant un rendement élevé et plus stable dans des systèmes agricoles économes en intrants (eau, fertilisants) et respectueux de l’environnement. Les nouvelles variétés de blé devront non seulement être tolérantes aux stress hydriques et aux fortes températures, mais aussi continuer à être productives avec des apports limités en fertilisation, tout en maintenant une qualité du grain adaptés aux différents usages. De nouvelles méthodes de prédiction des réponses des blés à ces stress sont indispensables pour avancer dans cette direction.Dans ce travail, nous avons tout d’abord identifié les stress qui régissaient les interactions entre génotypes et les environnements (GxE) dans les essais considérés, puis développé un modèle génomique de l’adaptation à un stress environnemental (Factorial Regression genomic Best Linear Unbiased Prediction ou FR-gBLUP), en particulier pour le stress hydrique. En émettant l’hypothèse que plus des variétés de blés sont génétiquement proches, plus elles répondront de façon similaire à un stress environnemental donné, nous avons mesuré par validation croisée des gains de précision de prédiction par rapport à un modèle additif variant entre 3.5% et 15.4%. Des simulations complètent l’étude en démontrant que plus la part de variance expliquée par les réponses au stress considéré est importante, plus le modèle FR-gBLUP apporte un gain de précision. Pour prédire les réponses variétales à un stress particulier, les environnements doivent être finement caractérisés pour les stress limitant le développement des plantes. En nous intéressant plus particulièrement au stress azoté en France, nous avons établi des indicateurs de stress à partir d’un modèle de culture, et les avons comparés à des indicateurs classiques, tels que le type de conduite azotée ou l’azote disponible. Nous avons ainsi mis en évidence l’intérêt des modèles de culture pour caractériser les interactions GxE et pour prédire la réponse génomique au stress azoté, à condition que le signal d’interaction soit assez fort.Au-delà de l’application potentielle de ces méthodes pour la sélection ou la recommandation de variétés de blés plus adaptées ou plus résistantes au changement climatique, les résultats de ce travail démontrent aussi l’intérêt de la complémentarité des approches éco-physiologiques et génétiques.
... In regarding to work related to genome sequencing, we need to be cautious in ordering and orientating sequence contigs based on comparative approaches as different individuals may have different translocations and inversions. We also need to be aware that the widely used method of whole genome resequencing based on a single reference genome [16][17][18][19] would not only miss large-sized variants but also other types of dispensable elements which could be important and account for large portions of various genomes including microbes 20-24 and plants [25][26][27][28][29][30][31][32] . ...
The hexaploid wheat genotype Chinese Spring (CS) has been used worldwide as the reference base for wheat genetics and genomics, and significant resources have been used by the international community to generate a reference wheat genome based on this genotype. By sequencing flow-sorted 3B chromosome from a hexaploid wheat genotype CRNIL1A and comparing the obtained sequences with those available for CS, we detected that a large number of sequences in the former were missing in the latter. If the distribution of such sequences in the hexaploid wheat genome is random, CRNILA sequences missing in CS could be as much as 159.3 Mb even if only fragments of 50 bp or longer were considered. Analysing RNA sequences available in the public domains also revealed that dispensable genes are common in hexaploid wheat. Together with those extensive intra- and interchromosomal rearrangements in CS, the existence of such dispensable genes is another factor highlighting potential issues with the use of reference genomes in various studies. Strong deviation in distributions of these dispensable sequences among genotypes with different geographical origins provided the first evidence indicating that they could be associated with adaptation in wheat.
... The polyploidization history of wheat provides some explanation for the predominant role of B and D subgenomes in biotic stress responses (Marcussen et al., 2014). The predominance of the B subgenome over the A subgenome may have resulted through changes to genetic regulation during the period where the progenitor genomes existed in a tetraploid state (Lai et al., 2015) driving genome asymmetry in a function-specific manner. In tetraploid wheat, global transcriptomic analysis revealed the A subgenome to be dominant over the B subgenome in terms of genomic stability (Pont et al., 2011). ...
Bread wheat (Triticum aestivum L.) is an allopolyploid species containing three ancestral genomes. Therefore, three homoeologous copies exist for the majority of genes in the wheat genome. Whether different homoeologs are differentially expressed (homoeolog expression bias) in response to biotic and abiotic stresses is poorly understood. In this study, we applied a RNA-seq approach to analyze homoeolog-specific global gene expression patterns in wheat during infection by the fungal pathogen Fusarium pseudograminearum, which causes crown rot disease in cereals. To ensure specific detection of homoeologs, we first optimized read alignment methods and validated the results experimentally on genes with known patterns of subgenome specific expression. Our global analysis identified widespread patterns of differential expression among homoeologs, indicating homoeolog expression bias underpins a large proportion of the wheat transcriptome. In particular, genes differentially expressed in response to Fusarium infection were found to be disproportionately contributed from B and D subgenomes. In addition, we found differences in the degree of responsiveness to pathogen infection among homoeologous genes with B and D homoeologs exhibiting stronger responses to pathogen infection than A genome copies. We call this latter phenomenon as “homoeolog induction bias”. Understanding how homoeolog expression and induction biases operate may assist the improvement of biotic stress tolerance in wheat and other polyploid crop species. This article is protected by copyright. All rights reserved.
... et al. have aligned these paired reads to the draft assemblies of chromosomes 7A, 7B, and 7D. A total of over 4,018,311 intervarietal SNPs have been identifi ed between these 16 Australian wheat varieties[ 13 ]. ...
An integrated database with a variety of Web-based systems named WheatGenome.info hosting wheat genome and genomic data has been developed to support wheat research and crop improvement. The resource includes multiple Web-based applications, which are implemented as a variety of Web-based systems. These include a GBrowse2-based wheat genome viewer with BLAST search portal, TAGdb for searching wheat second generation genome sequence data, wheat autoSNPdb, links to wheat genetic maps using CMap and CMap3D, and a wheat genome Wiki to allow interaction between diverse wheat genome sequencing activities. This portal provides links to a variety of wheat genome resources hosted at other research organizations. This integrated database aims to accelerate wheat genome research and is freely accessible via the web interface at http://www.wheatgenome.info/.
... Since the sequencing of the first plant genome (Initiative, 2000), comparative genomic studies of plants often focus on single nucleotide polymorphisms (SNPs) between individuals as these can be relatively easily identified and assayed across populations (Gore et al., 2009;Lai et al., 2015;McNally et al., 2009). However, there has been an increasing awareness that a single reference genome is insufficient to capture the genomic diversity we observe in nature due to a considerable amount of structural variation including copy number variants (CNVs) and presence/ absence variants (PAVs), which alter the total amount of genomic sequence found in individuals (Saxena et al., 2014). ...
As an increasing number of genome sequences become available for a wide range of species, there is a growing understanding that the genome of a single individual is insufficient to represent the gene diversity within a whole species. Many studies examine the sequence diversity within genes, and this allelic variation is an important source of phenotypic variation which can be selected for by man or nature. However, the significant gene presence/absence variation that has been observed within species and the impact of this variation on traits is only now being studied in detail. The sum of the genes for a species is termed the pangenome, and the determination and characterization of the pangenome is a requirement to understand variation within a species. In this review, we explore the current progress in pangenomics as well as methods and approaches for the characterization of pangenomes for a wide range of plant species.
... The overall transitions/transversions ratio (Ts:Tv) was 1.44 which is slightly lower than that observed in maize nuclear SNPs (1.48) and grass chloroplast (1.3) (14,16,23,(29)(30)(31). Using SnpEff, the impact of variations on the protein coding sequences was classified into low, moderate and high effect variations. ...
Molecular markers are valuable tools for breeders to help accelerate crop improvement. High throughput sequencing technologies facilitate the discovery of large-scale variations such as single nucleotide polymorphisms (SNPs) and simple sequence repeats (SSRs). Sequencing of chickpea genome along with re-sequencing of several chickpea lines has enabled the discovery of 4.4 million variations including SNPs and InDels. Here we report a repository of 1.9 million variations (SNPs and InDels) anchored on eight pseudomolecules in a custom database, referred as CicArVarDB that can be accessed at http://cicarvardb.icrisat.org/. It includes an easy interface for users to select variations around specific regions associated with quantitative trait loci, with embedded webBLAST search and JBrowse visualisation. We hope that this database will be immensely useful for the chickpea research community for both advancing genetics research as well as breeding applications for crop improvement.
Database URL:
http://cicarvardb.icrisat.org.
... More recently, the advent of next-generation sequencing (NGS) is revolutionizing molecular breeding either through genomic selection approaches (Collard and Mackill, 2008;Gupta et al., 2008) or through the identification of large numbers of SNPs which can be converted into MAS assays (Allen et al., 2013). Despite this potential, identifying SNPs in bread wheat (Triticum aestivum L.) is challenging due to its hexaploid nature (6n = 42; AABBDD) and large genome size~17 Gbp (Gupta et al., 2008;Shewry, 2009), although large-scale efforts to identify intervarietal SNP are becoming more common (Lai et al., 2014;Wang et al., 2014). The three genomes (A, B and D) are referred to as homoeologues and are related, and yet distinct, sharing a complementary set of genes which have between 96% and 98% sequence identity across coding regions (Krasileva et al., 2013). ...
The identification of genetic markers linked to genes of agronomic importance is a major aim of crop research and breeding programmes. Here, we identify markers for Yr15, a major disease resistance gene for wheat yellow rust, using a segregating F2 population. After phenotyping, we implemented RNA sequencing (RNA-Seq) of bulked pools to identify single-nucleotide polymorphisms (SNP) associated with Yr15. Over 27 000 genes with SNPs were identified between the parents, and then classified based on the results from the sequenced bulks. We calculated the bulk frequency ratio (BFR) of SNPs between resistant and susceptible bulks, selecting those showing sixfold enrichment/depletion in the corresponding bulks (BFR > 6). Using additional filtering criteria, we reduced the number of genes with a putative SNP to 175. The 35 SNPs with the highest BFR values were converted into genome-specific KASP assays using an automated bioinformatics pipeline (PolyMarker) which circumvents the limitations associated with the polyploid wheat genome. Twenty-eight assays were polymorphic of which 22 (63%) mapped in the same linkage group as Yr15. Using these markers, we mapped Yr15 to a 0.77-cM interval. The three most closely linked SNPs were tested across varieties and breeding lines representing UK elite germplasm. Two flanking markers were diagnostic in over 99% of lines tested, thus providing a reliable haplotype for marker-assisted selection in these breeding programmes. Our results demonstrate that the proposed methodology can be applied in polyploid F2 populations to generate high-resolution genetic maps across target intervals.
Improving the crop traits is highly required for the development of superior crop varieties to deal with climate change and the associated abiotic and biotic stress challenges. Climate change-driven global warming can trigger higher insect pest pressures and plant diseases thus affecting crop production sternly. The traits controlling genes for stress or disease tolerance are economically imperative in crop plants. In this scenario, the extensive exploration of available wild, resistant or susceptible germplasms and unraveling the genetic diversity remains vital for breeding programs. The dawn of next-generation sequencing technologies and omics approaches has accelerated plant breeding by providing the genome sequences and transcriptomes of several plants. The availability of decoded plant genomes offers an opportunity at a glance to identify candidate genes, quantitative trait loci (QTLs), molecular markers, and genome-wide association studies that can potentially aid in high throughput marker-assisted breeding. In recent years genomics is coupled with marker-assisted breeding to unravel the mechanisms to harness better better crop yield and quality. In this review, we discuss the aspects of marker-assisted breeding and recent perspectives of breeding approaches in the era of genomics, bioinformatics, high-tech phonemics, genome editing, and new plant breeding technologies for crop improvement. In nutshell, the smart breeding toolkit in the post-genomics era can steadily help in developing climate-smart future food crops.
Single-nucleotide polymorphisms (SNPs) have become the primary type of molecular genetic marker used in a diverse range of genetic and genomic studies. SNPs can be used to identify genomic regions linked to traits such as disease in genome-wide association studies, to understand population structure and diversity, or to understand mechanisms of genome evolution. One of the first steps of any SNP-based workflow, following SNP discovery, is quality control of SNP data. The protocol described here details how to perform quality control on SNP data to minimise errors in downstream analysis.
Plant breeding leads to the genetic improvement of target traits by selecting a small number of genotypes from among typically large numbers of candidate genotypes after careful evaluation. In this study, we first investigated how mutations at conserved nucleotide sites normally viewed as deleterious, such as nonsynonymous sites, accumulated in a wheat, Triticum aestivum, breeding lineage. By comparing a 150 year old ancestral and modern cultivar, we found recent nucleotide polymorphisms altered amino acids and occurred within conserved genes at frequencies expected in the absence of purifying selection. Mutations that are deleterious in other contexts likely had very small or no effects on target traits within the breeding lineage. Second, we investigated if breeders selected alleles with favorable effects on some traits and unfavorable effects on others and used different alleles to compensate for the latter. An analysis of a segregating population derived from the ancestral and modern parents provided one example of this phenomenon. The recent cultivar contains the Rht-B1b green revolution semi-dwarfing allele and compensatory alleles that reduce its negative effects. However, improvements in traits other than plant height were due to pleiotropic loci with favorable effects on traits and to favorable loci with no detectable pleiotropic effects. Wheat breeding appears to tolerate mutations at conserved nucleotide sites and to only select for alleles with both favorable and unfavorable effects on traits in exceptional situations.
Controlled pedigrees and multi-decade timescale of national crop plant breeding programs offer a unique experimental context for examining how selection affects plant genomes. More than 3,000 wheat cultivars have been registered, released and documented since 1949 in China. Here, a set of 145 elite cultivars from the historical series of wheat breeding in China were re-sequenced. A total of 43.75 Tb of sequence data was generated with an average read depth of 17.94× for each cultivar, and more than 60.92 million SNPs and 2.54 million InDels were captured, based on the Chinese Spring RefSeq v1.0. Seventy years of breeder driven selection led to dramatic changes in grain yield and related phenotypes, with distinct genomic regions and phenotypes targeted by different breeders across the decades. There are very clear instances of how the introduced Italian and other foreign germplasm was integrated into Chinese wheat programs and reshaped the genome landscape of local modern cultivars. Importantly, the resequencing data also highlighted significant asymmetric breeding selection amongst the three sub-genomes: this was evident in both the collinear blocks for homeologous chromosomes and among sets of three homeologous genes. Accumulation of more newly assembled genes in newer cultivars implied potential values of these genes in breeding. Conserved and extended sharing of LD-blocks were highlighted among pedigree-related cultivars, in which fewer haplotypes differences were detected. Fixation or replacement of haplotypes from founder genotypes after generations of breeding was related to their breeding value. Based on the haplotype frequency changes in LD-blocks of pedigree-related cultivars, we propose a strategy for evaluating the breeding value of any given line on the basis of the accumulation (pyramiding) of beneficial haplotypes. This research also demonstrates the impact of "founder genotypes" on the output of breeding efforts over multiple decades, and suggests "founder genotype" perspectives are in fact more dynamic when applied in the context of modern genomics-informed breeding.
There is a need to accelerate crop improvement by introducing alleles conferring host plant resistance, abiotic stress adaptation, and high yield potential. Elite cultivars, landraces and wild relatives harbor useful genetic variation that needs to be more easily utilized in plant breeding. We review genome-wide approaches for assessing and identifying alleles associated with desirable agronomic traits in diverse germplasm pools of cereals and legumes. Major quantitative trait loci and single nucleotide polymorphisms (SNPs) associated with desirable agronomic traits have been deployed to enhance crop productivity and resilience. These include alleles associated with variation conferring enhanced photoperiod and flowering traits. Genetic variants in the florigen pathway can provide both environmental flexibility and improved yields. SNPs associated with length of growing season and tolerance to abiotic stresses (precipitation, high temperature) are valuable resources for accelerating breeding for drought-prone environments. Both genomic selection and genome editing can also harness allelic diversity and increase productivity by improving multiple traits, including phenology, plant architecture, yield potential and adaptation to abiotic stresses. Discovering rare alleles and useful haplotypes also provides opportunities to enhance abiotic stress adaptation, while epigenetic variation has potential to enhance abiotic stress adaptation and productivity in crops. By reviewing current knowledge on specific traits and their genetic basis, we highlight recent developments in the understanding of crop functional diversity and identify potential candidate genes for future use. The storage and integration of genetic, genomic and phenotypic information will play an important role in ensuring broad and rapid application of novel genetic discoveries by the plant breeding community. Exploiting alleles for yield-related traits would allow improvement of selection efficiency and overall genetic gain of multigenic traits. An integrated approach involving multiple stakeholders specializing in management and utilization of genetic resources, crop breeding, molecular biology and genomics, agronomy, stress tolerance, and reproductive/seed biology will help to address the global challenge of ensuring food security in the face of growing resource demands and climate change induced stresses.
Plant germplasm underpins much of crop genetic improvement. Millions of germplasm accessions have been collected and conserved ex situ and/or in situ, and the major challenge is now how to exploit and utilize this abundant resource. Genomics-based plant germplasm research (GPGR) or “Genoplasmics” is a novel cross-disciplinary research field that seeks to apply the principles and techniques of genomics to germplasm research. We describe in this paper the concept, strategy, and approach behind GPGR, and summarize current progress in the areas of the definition and construction of core collections, enhancement of germplasm with core collections, and gene discovery from core collections. GPGR is opening a new era in germplasm research. The contribution, progress and achievements of GPGR in the future are predicted.
Genetic structure can be altered by chemical mutagenesis, which is a common method applied in molecular biology and genetics. Second generation sequencing provides a platform to reveal base alterations occurring in the whole genome due to mutagenesis. A model legume, Lotus japonicus ecotype Miyakojima, was chemically mutated with alkylating ethyl methanesulphonate for the scanning of DNA lesions throughout the genome. Using second generation sequencing, two individually mutated third generation progeny (M3, named AM and AS) were sequenced and analysed to identify single nucleotide polymorphisms and reveal ethyl methanesulphonate effects on nucleotide sequences in these mutant genomes. Single nucleotide polymorphisms were found in every 208 kb (AS) and 202 kb (AM) with a bias mutation of G/C-to-A/T changes at low percentage. Most mutations were intergenic. The mutation spectrum of the genomes was comparable in their individual chromosomes however; each mutated genome has unique alterations, which are useful to identify causal mutations for their phenotypic changes. The data obtained demonstrate that whole genomic sequencing is applicable as a high throughput tool to investigate genomic changes due to mutagenesis. The identification of these single point mutations will facilitate the identification of phenotypically causative mutations in EMS mutated germplasm.
Copyright © 2015 Author et al.
Cereal crops form the bulk of the world's food sources, and thus their importance cannot be understated. Crop breeding programs increasingly rely on high-resolution molecular genetic markers to accelerate the breeding process. The development of these markers is hampered by the complexity of some of the major cereal crop genomes, as well as the time and cost required. In this review, we address current and future methods available for the characterisation of cereal genomes, with an emphasis on faster and more cost effective approaches for genome sequencing and the development of markers for trait association and marker assisted selection (MAS) in crop breeding programs.
Single nucleotide polymorphisms (SNPs) are becoming the dominant form of molecular marker for genetic and genomic analysis. The advances in second generation DNA sequencing provide opportunities to identify very large numbers of SNPs in a range of species. However, SNP identification remains a challenge for large and polyploid genomes due to their size and complexity. We have developed a pipeline for the robust identification of SNPs in large and complex genomes using Illumina second generation DNA sequence data and demonstrated this by the discovery of SNPs in the hexaploid wheat genome. We have developed a SNP discovery pipeline called SGSautoSNP (Second-Generation Sequencing AutoSNP) and applied this to discover more than 800,000 SNPs between four hexaploid wheat cultivars across chromosomes 7A, 7B and 7D. All SNPs are presented for download and viewing within a public GBrowse database. Validation suggests an accuracy of greater than 93% of SNPs represent polymorphisms between wheat cultivars and hence are valuable for detailed diversity analysis, marker assisted selection and genotyping by sequencing. The pipeline produces output in GFF3, VCF, Flapjack or Illumina Infinium design format for further genotyping diverse populations. As well as providing an unprecedented resource for wheat diversity analysis, the method establishes a foundation for high resolution SNP discovery in other large and complex genomes.
High-density single nucleotide polymorphism (SNP) genotyping arrays are a powerful tool for studying genomic patterns of diversity, inferring ancestral relationships between individuals in populations and studying marker-trait associations in mapping experiments. We developed a genotyping array including about 90 000 gene-associated SNPs and used it to characterize genetic variation in allohexaploid and allotetraploid wheat populations. The array includes a significant fraction of common genome-wide distributed SNPs that are represented in populations of diverse geographical origin. We used density-based spatial clustering algorithms to enable high-throughput genotype calling in complex data sets obtained for polyploid wheat. We show that these model-free clustering algorithms provide accurate genotype calling in the presence of multiple clusters including clusters with low signal intensity resulting from significant sequence divergence at the target SNP site or gene deletions. Assays that detect low-intensity clusters can provide insight into the distribution of presence-absence variation (PAV) in wheat populations. A total of 46 977 SNPs from the wheat 90K array were genetically mapped using a combination of eight mapping populations. The developed array and cluster identification algorithms provide an opportunity to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat.
Genomic selection (GS) uses genomewide molecular markers to predict breeding values and make selections of individuals or breeding lines prior to phenotyping. Here we show that genotyping-by-sequencing (GBS) can be used for de novo genotyping of breeding panels and to develop accurate GS models, even for the large, complex, and polyploid wheat (Triticum aestivum L.) genome. With GBS we discovered 41,371 single nucleotide polymorphisms (SNPs) in a set of 254 advanced breeding lines from CIMMYT's semiarid wheat breeding program. Four different methods were evaluated for imputing missing marker scores in this set of unmapped markers, including random forest regression and a newly developed multivariate-normal expectation-maximization algorithm, which gave more accurate imputation than heterozygous or mean imputation at the marker level, although no signifi cant differences were observed in the accuracy of genomic-estimated breeding values (GEBVs) among imputation methods. Genomic-estimated breeding value prediction accuracies with GBS were 0.28 to 0.45 for grain yield, an improvement of 0.1 to 0.2 over an established marker platform for wheat. Genotyping-by-sequencing combines marker discovery and genotyping of large populations, making it an excellent marker platform for breeding applications even in the absence of a reference genome sequence or previous polymorphism discovery. In addition, the fl exibility and low cost of GBS make this an ideal approach for genomics-assisted breeding.
Domesticated crops experience strong human-mediated selection aimed at developing high-yielding varieties adapted to local conditions. To detect regions of the wheat genome subject to selection during improvement, we developed a high-throughput array to interrogate 9,000 gene-associated single-nucleotide polymorphisms (SNP) in a worldwide sample of 2,994 accessions of hexaploid wheat including landraces and modern cultivars. Using a SNP-based diversity map we characterized the impact of crop improvement on genomic and geographic patterns of genetic diversity. We found evidence of a small population bottleneck and extensive use of ancestral variation often traceable to founders of cultivars from diverse geographic regions. Analyzing genetic differentiation among populations and the extent of haplotype sharing, we identified allelic variants subjected to selection during improvement. Selective sweeps were found around genes involved in the regulation of flowering time and phenology. An introgression of a wild relative-derived gene conferring resistance to a fungal pathogen was detected by haplotype-based analysis. Comparing selective sweeps identified in different populations, we show that selection likely acts on distinct targets or multiple functionally equivalent alleles in different portions of the geographic range of wheat. The majority of the selected alleles were present at low frequency in local populations, suggesting either weak selection pressure or temporal variation in the targets of directional selection during breeding probably associated with changing agricultural practices or environmental conditions. The developed SNP chip and map of genetic variation provide a resource for advancing wheat breeding and supporting future population genomic and genome-wide association studies in wheat.
Globally, wheat is the most widely grown crop and one of the three most important crops for human and livestock feed. However, the complex nature of the wheat genome has, until recently, resulted in a lack of single nucleotide polymorphism (SNP)-based molecular markers of practical use to wheat breeders. Recently, large numbers of SNP-based wheat markers have been made available via the use of next-generation sequencing combined with a variety of genotyping platforms. However, many of these markers and platforms have difficulty distinguishing between heterozygote and homozygote individuals and are therefore of limited use to wheat breeders carrying out commercial-scale breeding programmes. To identify exome-based co-dominant SNP-based assays, which are capable of distinguishing between heterozygotes and homozygotes, we have used targeted re-sequencing of the wheat exome to generate large amounts of genomic sequences from eight varieties. Using a bioinformatics approach, these sequences have been used to identify 95 266 putative single nucleotide polymorphisms, of which 10 251 were classified as being putatively co-dominant. Validation of a subset of these putative co-dominant markers confirmed that 96% were true polymorphisms and 65% were co-dominant SNP assays. The new co-dominant markers described here are capable of genotypic classification of a segregating locus in polyploid wheat and can be used on a variety of genotyping platforms; as such, they represent a powerful tool for wheat breeders. These markers and related information have been made publically available on an interactive web-based database to facilitate their use on genotyping programmes worldwide.
Genetic evidence of Manfred Heun et al. (Reports, 14 Nov, [p. 1312][1]) for einkorn wheat domestication in southeast Turkey has been countered by Martin K. Jones et al. (Letters, 16 Jan., [p. 302][2]). Jones et al. cite evidence that agriculture began earlier in the southern Levant and that einkorn
Many important crop species have genomes originating from ancestral or recent polyploidisation events. Multiple homoeologous gene copies, chromosomal rearrangements and amplification of repetitive DNA within large and complex crop genomes can considerably complicate genome analysis and gene discovery by conventional, forward genetics approaches. On the other hand, ongoing technological advances in molecular genetics and genomics today offer unprecedented opportunities to analyse and access even more recalcitrant genomes. In this review, we describe next-generation sequencing and data analysis techniques that vastly improve our ability to dissect and mine genomes for causal genes underlying key traits and allelic variation of interest to breeders. We focus primarily on wheat and oilseed rape, two leading examples of major polyploid crop genomes whose size or complexity present different, significant challenges. In both cases, the latest DNA sequencing technologies, applied using quite different approaches, have enabled considerable progress towards unravelling the respective genomes. Our ability to discover the extent and distribution of genetic diversity in crop gene pools, and its relationship to yield and quality-related traits, is swiftly gathering momentum as DNA sequencing and the bioinformatic tools to deal with growing quantities of genomic data continue to develop. In the coming decade, genomic and transcriptomic sequencing, discovery and high-throughput screening of single nucleotide polymorphisms, presence-absence variations and other structural chromosomal variants in diverse germplasm collections will give detailed insight into the origins, domestication and available trait-relevant variation of polyploid crops, in the process facilitating novel approaches and possibilities for genomics-assisted breeding.
The large and complex genome of wheat makes genetic and genomic analysis in this important species both expensive and resource intensive. The application of next-generation sequencing technologies is particularly resource intensive, with at least 17 Gbp of sequence data required to obtain minimal (1×) coverage of the genome. A similar volume of data would represent almost 40× coverage of the rice genome. Progress can be made through the establishment of consortia to produce shared genomic resources. Australian wheat genome researchers, working with Bioplatforms Australia, have collaborated in a national initiative to establish a genetic diversity dataset representing Australian wheat germplasm based on whole genome next-generation sequencing data. Here, we describe the establishment and validation of this resource which can provide a model for broader international initiatives for the analysis of large and complex genomes.
The neighbour-joining method reconstructs phylogenies by iteratively joining pairs of nodes until a single node remains. The
criterion for which pair of nodes to merge is based on both the distance between the pair and the average distance to the
rest of the nodes. In this paper, we present a new search strategy for the optimisation criteria used for selecting the next
pair to merge and we show empirically that the new search strategy is superior to other state-of-the-art neighbour-joining
implementations.
Bread wheat (Triticum aestivum) is one of the most important crop plants, globally providing staple food for a large proportion of the human population. However, improvement of this crop has been limited due to its large and complex genome. Advances in genomics are supporting wheat crop improvement. We provide a variety of web-based systems hosting wheat genome and genomic data to support wheat research and crop improvement. WheatGenome.info is an integrated database resource which includes multiple web-based applications. These include a GBrowse2-based wheat genome viewer with BLAST search portal, TAGdb for searching wheat second-generation genome sequence data, wheat autoSNPdb, links to wheat genetic maps using CMap and CMap3D, and a wheat genome Wiki to allow interaction between diverse wheat genome sequencing activities. This system includes links to a variety of wheat genome resources hosted at other research organizations. This integrated database aims to accelerate wheat genome research and is freely accessible via the web interface at http://www.wheatgenome.info/.
Complex Triticeae genomes pose a challenge to genome sequencing efforts due to their size and repetitive nature. Genome sequencing can reveal details of conservation and rearrangements between related genomes. We have applied Illumina second generation sequencing technology to sequence and assemble the low copy and unique regions of Triticum aestivum chromosome arm 7BS, followed by the construction of a syntenic build based on gene order in Brachypodium. We have delimited the position of a previously reported translocation between 7BS and 4AL with a resolution of one or a few genes and report approximately 13% genes from 7BS having been translocated to 4AL. An additional 13 genes are found on 7BS which appear to have originated from 4AL. The gene content of the 7DS and 7BS syntenic builds indicate a total of ~77,000 genes in wheat. Within wheat syntenic regions, 7BS and 7DS share 740 genes and a common gene conservation rate of ~39% of the genes from the corresponding regions in Brachypodium, as well as a common rate of colinearity with Brachypodium of ~60%. Comparison of wheat homoeologues revealed ~84% of genes previously identified in 7DS have a homoeologue on 7BS or 4AL. The conservation rates we have identified among wheat homoeologues and with Brachypodium provide a benchmark of homoeologous gene conservation levels for future comparative genomic analysis. The syntenic build of 7BS is publicly available at http://www.wheatgenome.info.
The variant call format (VCF) is a generic format for storing DNA polymorphism data such as SNPs, insertions, deletions and structural variants, together with rich annotations. VCF is usually stored in a compressed manner and can be indexed for fast data retrieval of variants from a range of positions on the reference genome. The format was developed for the 1000 Genomes Project, and has also been adopted by other projects such as UK10K, dbSNP and the NHLBI Exome Project. VCFtools is a software suite that implements various utilities for processing VCF files, including validation, merging, comparing and also provides a general Perl API.
Availability: http://vcftools.sourceforge.net
Contact: rd@sanger.ac.uk
Many plants have large and complex genomes with an abundance of repeated sequences. Many plants are also polyploid. Both of these attributes typify the genome architecture in the tribe Triticeae, whose members include economically important wheat, rye and barley. Large genome sizes, an abundance of repeated sequences, and polyploidy present challenges to genome-wide SNP discovery using next-generation sequencing (NGS) of total genomic DNA by making alignment and clustering of short reads generated by the NGS platforms difficult, particularly in the absence of a reference genome sequence.
An annotation-based, genome-wide SNP discovery pipeline is reported using NGS data for large and complex genomes without a reference genome sequence. Roche 454 shotgun reads with low genome coverage of one genotype are annotated in order to distinguish single-copy sequences and repeat junctions from repetitive sequences and sequences shared by paralogous genes. Multiple genome equivalents of shotgun reads of another genotype generated with SOLiD or Solexa are then mapped to the annotated Roche 454 reads to identify putative SNPs. A pipeline program package, AGSNP, was developed and used for genome-wide SNP discovery in Aegilops tauschii-the diploid source of the wheat D genome, and with a genome size of 4.02 Gb, of which 90% is repetitive sequences. Genomic DNA of Ae. tauschii accession AL8/78 was sequenced with the Roche 454 NGS platform. Genomic DNA and cDNA of Ae. tauschii accession AS75 was sequenced primarily with SOLiD, although some Solexa and Roche 454 genomic sequences were also generated. A total of 195,631 putative SNPs were discovered in gene sequences, 155,580 putative SNPs were discovered in uncharacterized single-copy regions, and another 145,907 putative SNPs were discovered in repeat junctions. These SNPs were dispersed across the entire Ae. tauschii genome. To assess the false positive SNP discovery rate, DNA containing putative SNPs was amplified by PCR from AL8/78 and AS75 and resequenced with the ABI 3730 xl. In a sample of 302 randomly selected putative SNPs, 84.0% in gene regions, 88.0% in repeat junctions, and 81.3% in uncharacterized regions were validated.
An annotation-based genome-wide SNP discovery pipeline for NGS platforms was developed. The pipeline is suitable for SNP discovery in genomic libraries of complex genomes and does not require a reference genome sequence. The pipeline is applicable to all current NGS platforms, provided that at least one such platform generates relatively long reads. The pipeline package, AGSNP, and the discovered 497,118 Ae. tauschii SNPs can be accessed at (http://avena.pw.usda.gov/wheatD/agsnp.shtml).
US maize yield has increased eight-fold in the past 80 years, with half of the gain attributed to selection by breeders. During this time, changes in maize leaf angle and size have altered plant architecture, allowing more efficient light capture as planting density has increased. Through a genome-wide association study (GWAS) of the maize nested association mapping panel, we determined the genetic basis of important leaf architecture traits and identified some of the key genes. Overall, we demonstrate that the genetic architecture of the leaf traits is dominated by small effects, with little epistasis, environmental interaction or pleiotropy. In particular, GWAS results show that variations at the liguleless genes have contributed to more upright leaves. These results demonstrate that the use of GWAS with specially designed mapping populations is effective in uncovering the basis of key agronomic traits.
We have resequenced a group of six elite maize inbred lines, including the parents of the most productive commercial hybrid in China. This effort uncovered more than 1,000,000 SNPs, 30,000 indel polymorphisms and 101 low-sequence-diversity chromosomal intervals in the maize genome. We also identified several hundred complete genes that show presence/absence variation among these resequenced lines. We discuss the potential roles of complementation of presence/absence variations and other deleterious mutations in contributing to heterosis. High-density SNP and indel polymorphism markers reported here are expected to be a valuable resource for future genetic studies and the molecular breeding of this important crop.
The large bread wheat genome (1C approximately 17 Gbp) contains a preponderance of repetitive DNA and the species is polyploid. These characteristics together serve to hamper the molecular analysis of the wheat genome. Its complexity can, however, be reduced by using flow cytometry to isolate individual chromosomes, and these can be exploited to construct chromosome-specific BAC libraries. Such libraries simplify the task of physical map construction, positional cloning and the targeted development of genetic markers. Rapid improvements in the efficiency and cost of DNA sequencing provide an opportunity to contemplate sequencing the wheat genome by preparing sequence-ready physical maps for each chromosome or chromosome arm in turn. The quality of the chromosome-specific libraries depends on their chromosome coverage and the mean insert size. First-generation libraries suffered from a relatively low mean insert size, but improvements to the protocol have generated a second wave of libraries with a significantly increased mean insert size and better chromosome coverage. Each chromosome (arm)-specific library is composed of a manageable number of clones, and so represents a practical tool in the area of wheat genomics.
Molecular genetic markers represent one of the most powerful tools for the analysis of genomes and enable the association of heritable traits with underlying genomic variation. Molecular marker technology has developed rapidly over the last decade and two forms of sequence based marker, Simple Sequence Repeats (SSRs), also known as microsatellites, and Single Nucleotide Polymorphisms (SNPs) now predominate applications in modern genetic analysis. The reducing cost of DNA sequencing has led to the availability of large sequence data sets derived from whole genome sequencing and large scale Expressed Sequence Tag (EST) discovery that enable the mining of SSRs and SNPs, which may then be applied to diversity analysis, genetic trait mapping, association studies, and marker assisted selection. These markers are inexpensive, require minimal labour to produce and can frequently be associated with annotated genes. Here we review automated methods for the discovery of SSRs and SNPs and provide an overview of the diverse applications of these markers.
Despite important strides in marker technologies, the use of marker-assisted selection has stagnated for the improvement of quantitative traits. Biparental mating designs for the detection of loci affecting these traits (quantitative trait loci [QTL]) impede their application, and the statistical methods used are ill-suited to the traits' polygenic nature. Genomic selection (GS) has been proposed to address these deficiencies. Genomic selection predicts the breeding values of lines in a population by analyzing their phenotypes and high-density marker scores. A key to the success of GS is that it incorporates all marker information in the prediction model, thereby avoiding biased marker effect estimates and capturing more of the variation due to small-effect QTL. In simulations, the correlation between true breeding value and the genomic estimated breeding value has reached levels of 0.85 even for polygenic low heritability traits. This level of accuracy is sufficient to consider selecting for agronomic performance using marker information alone. Such selection would substantially accelerate the breeding cycle, enhancing gains per unit time. It would dramatically change the role of phenotyping, which would then serve to update prediction models and no longer to select lines. While research to date shows the exceptional promise of GS, work remains to be done to validate it empirically and to incorporate it into breeding schemes.
In this study, we developed 359 detection primers for single nucleotide polymorphisms (SNPs) previously discovered within intron sequences of wheat genes and used them to evaluate SNP polymorphism in common wheat (Triticum aestivum L.). These SNPs showed an average polymorphism information content (PIC) of 0.18 among 20 US elite wheat cultivars, representing seven market classes. This value increased to 0.23 when SNPs were pre-selected for polymorphisms among a diverse set of 13 hexaploid wheat accessions (excluding synthetic wheats) used in the wheat SNP discovery project (http://wheat.pw.usda.gov/SNP). PIC values for SNP markers in the D genome were approximately half of those for the A and B genomes. D genome SNPs also showed a larger PIC reduction relative to the other genomes (P < 0.05) when US cultivars were compared with the more diverse set of 13 wheat accessions. Within those accessions, D genome SNPs show a higher proportion of alleles with low minor allele frequencies (<0.125) than found in the other two genomes. These data suggest that the reduction of PIC values in the D genome was caused by differential loss of low frequency alleles during the population size bottleneck that accompanied the development of modern commercial cultivars. Additional SNP discovery efforts targeted to the D genome in elite wheat germplasm will likely be required to offset the lower diversity of this genome. With increasing SNP discovery projects and the development of high-throughput SNP assay technologies, it is anticipated that SNP markers will play an increasingly important role in wheat genetics and breeding applications.
Genome-wide association (GWA) studies have identified a large number of SNPs associated
with disease phenotypes. As most GWA studies have been performed in populations of European
descent, this Review examines the issues involved in extending the consideration of GWA
studies to diverse worldwide populations. Although challenges exist with issues such as
imputation, admixture and replication, investigation of a greater diversity of populations
could make substantial contributions to the goal of mapping the genetic determinants of
complex diseases for the human population as a whole.
Grain morphology in wheat (Triticum aestivum) has been selected and manipulated even in very early agrarian societies and remains a major breeding target. We undertook a large-scale quantitative analysis to determine the genetic basis of the phenotypic diversity in wheat grain morphology. A high-throughput method was used to capture grain size and shape variation in multiple mapping populations, elite varieties, and a broad collection of ancestral wheat species. This analysis reveals that grain size and shape are largely independent traits in both primitive wheat and in modern varieties. This phenotypic structure was retained across the mapping populations studied, suggesting that these traits are under the control of a limited number of discrete genetic components. We identified the underlying genes as quantitative trait loci that are distinct for grain size and shape and are largely shared between the different mapping populations. Moreover, our results show a significant reduction of phenotypic variation in grain shape in the modern germplasm pool compared with the ancestral wheat species, probably as a result of a relatively recent bottleneck. Therefore, this study provides the genetic underpinnings of an emerging phenotypic model where wheat domestication has transformed a long thin primitive grain to a wider and shorter modern grain.
The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments.
Availability: http://samtools.sourceforge.net
Contact: rd@sanger.ac.uk
SOAP2 is a significantly improved version of the short oligonucleotide alignment program that both reduces computer memory usage and increases alignment speed at an unprecedented rate. We used a Burrows Wheeler Transformation (BWT) compression index to substitute the seed strategy for indexing the reference sequence in the main memory. We tested it on the whole human genome and found that this new algorithm reduced memory usage from 14.7 to 5.4 GB and improved alignment speed by 20-30 times. SOAP2 is compatible with both single- and paired-end reads. Additionally, this tool now supports multiple text and compressed file formats. A consensus builder has also been developed for consensus assembly and SNP detection from alignment of short reads on a reference genome.
Availability:
http://soap.genomics.org.cn.
In hexaploid wheat (Triticum aestivum L.) (AABBDD, C=17 000 Mb), repeat DNA accounts for approximately 90% of the genome, of which transposable elements (TEs) constitute 60%-80%. Despite the dynamic evolution of TEs, our previous study indicated that the majority of TEs are conserved and collinear between the homologous wheat genomes, based on identical insertion patterns. In this study, we exploited the unique and abundant TE insertion junction regions identified from diploid Aegilops tauschii to develop genome-specific repeat DNA junction markers (RJM) for use in hexaploid wheat. In this study, both BAC end and random shotgun sequences were used to search for RJM. Of the 300 RJM primer pairs tested, 269 (90%) amplified single bands from diploid Ae. tauschii. Of these 269 primer pairs, 260 (97%) amplified hexaploid wheat and 9 (3%) amplified Ae. tauschii only. Among the RJM primers that amplified hexaploid wheat, 88% were successfully assigned to individual chromosomes of the hexaploid D genome. Among the 38 RJM primers mapped on chromosome 6D, 31 (82%) were unambiguously mapped to delineated bins of the chromosome using various wheat deletion lines. Our results suggest that the unique RJM derived from the diploid D genome could facilitate genetic, physical, and radiation mapping of the hexaploid wheat D genome.
Wheat is the third most important crop for human nutrition in the world. The availability of high-resolution genetic and physical maps and ultimately a complete genome sequence holds great promise for breeding improved varieties to cope with increasing food demand under the conditions of changing global climate. However, the large size of the bread wheat (Triticum aestivum) genome (approximately 17 Gb/1C) and the triplication of genic sequence resulting from its hexaploid status have impeded genome sequencing of this important crop species. Here we describe the use of mitotic chromosome flow sorting to separately purify and then shotgun-sequence a pair of telocentric chromosomes that together form chromosome 4A (856 Mb/1C) of wheat. The isolation of this much reduced template and the consequent avoidance of the problem of sequence duplication, in conjunction with synteny-based comparisons with other grass genomes, have facilitated construction of an ordered gene map of chromosome 4A, embracing ‡85% of its total gene content, and have enabled precise localization of the various translocation and inversion breakpoints on chromosome 4A that differentiate it from its progenitor chromosome in the A genome diploid donor. The gene map of chromosome 4A, together with the emerging sequences of homoeologous wheat chromosome groups 4, 5 and 7, represent unique resources that will allow us to obtain new insights into the evolutionary dynamics between homoeologous chromosomes and syntenic chromosomal regions.
Molecular genetic markers represent one of the most powerful tools for the analysis of genomes and enable the association of heritable traits with underlying genomic variation. Molecular marker technology has developed rapidly over the last decade and two forms of sequence based marker, Simple Sequence Repeats (SSRs), also known as microsatellites, and Single Nucleotide Polymorphisms (SNPs) now predominate applications in modern genetic analysis. The reducing cost of DNA sequencing has led to the availability of large sequence data sets derived from whole genome sequencing and large scale Expressed Sequence Tag (EST) discovery that enable the mining of SSRs and SNPs, which may then be applied to diversity analysis, genetic trait mapping, association studies, and marker assisted selection. These markers are inexpensive, require minimal labour to produce and can frequently be associated with annotated genes. Here we review automated methods for the discovery of SSRs and SNPs and provide an overview of the diverse applications of these markers.
Bread wheat derives from a grass ancestor structured in 7 protochromosomes followed by a paleotetraploidization to reach a 12 chromosomes intermediate and a neohexaploidization (involving subgenomes A, B and D) event that finally shaped the 21 modern chromosomes. Insights into wheat syntenome in sequencing COS (Conserved Orthologous Set) genes unravelled differences in genomic structure (such as gene conservation and diversity) and genetical landscape (such as recombination pattern) between ancestral as well as recent duplicated blocks. Contrasted evolutionary plasticity is observed where the B subgenome appears more sensitive (i.e. plastic) in contrast to A as dominant (i.e. stable) in response to the neotetraploidization and D subgenome as supradominant (i.e. pivotal) in response to the neohexaploidization event. Finally, the wheat syntenome, delivered through a public web interface PlantSyntenyViewer at http://urgi.versailles.inra.fr/synteny-wheat, can be considered as a guide for accelerated dissection of major agronomical traits in wheat. This article is protected by copyright. All rights reserved.
Allohexaploid bread wheat is grown on more acreage than any other cereal crop, yet variation at the DNA level seems to be less than that observed in many diploid crop species. A common explanation for the small amount of DNA-level variation is that a severe bottleneck event resulted from the polyploidization events that gave rise to hexaploid wheat, whereby wheat was genetically separated from its progenitors. In this report, we test the extent of the bottleneck separating wheat from its D-genome progenitor, Triticum tauschii, by comparative DNA sequence analysis. Restriction site variation of low-copy DNA sequences amplified by PCR showed an average of 2.9 and 2.4 alleles per primer set in T. tauschii and wheat, respectively. Two different restriction patterns were present in T. tauschii for DNA amplified with a primer set for the A1 locus. Both alleles were also present in wheat. Alleles at the A1 locus were cloned and 527 bp of sequence obtained from 12 and 13 diverse accessions of wheat and T. tauschii, respectively. Average genetic distance among the wheat alleles was similar to that among the T. tauschii alleles (0.0127 and 0.0133, respectively). Nucleotide differences indicated that two distinct alleles existed in T. tauschii, both of which were present in wheat. These data suggest that hexaploid wheat formed at least twice, and that the bottleneck separating wheat from T. tauschii may be less constrictive than previously supposed.Key words: wheat, evolution, DNA.
Modern genomics approaches rely on the availability of high-throughput and high-density genotyping platforms. A major breakthrough in wheat genotyping was the development of an SNP array. In this study, we used a diverse panel of 172 elite European winter wheat lines to evaluate the utility of the SNP array for genomic analyses in wheat germplasm derived from breeding programs. We investigated population structure and genetic relatedness and found that the results obtained with SNP and SSR markers differ. This suggests that additional research is required to determine the optimum approach for the investigation of population structure and kinship. Our analysis of linkage disequilibrium (LD) showed that LD decays within approximately 5-10 cM. Moreover, we found that LD is variable along chromosomes. Our results suggest that the number of SNPs needs to be increased further to obtain a higher coverage of the chromosomes. Taken together, SNPs can be a valuable tool for genomics approaches and for a knowledge-based improvement of wheat.
Despite the international significance of wheat, its large and complex genome hinders genome sequencing efforts. To assess the impact of selection on this genome, we have assembled genomic regions representing genes for chromosomes 7A, 7B and 7D. We demonstrate that the dispersion of wheat to new environments has shaped the modern wheat genome. Most genes are conserved between the three homoeologous chromosomes. We found differential gene loss that supports current theories on the evolution of wheat, with greater loss observed in the A and B genomes compared with the D. Analysis of intervarietal polymorphisms identified fewer polymorphisms in the D genome, supporting the hypothesis of early gene flow between the tetraploid and hexaploid. The enrichment for genes on the D genome that confer environmental adaptation may be associated with dispersion following wheat domestication. Our results demonstrate the value of applying next-generation sequencing technologies to assemble gene-rich regions of complex genomes and investigate polyploid genome evolution. We anticipate the genome-wide application of this reduced-complexity syntenic assembly approach will accelerate crop improvement efforts not only in wheat, but also in other polyploid crops of significance.
The volume of publications on the development and to a lesser extent the application of molecular markers in plant breeding has increased dramatically during the last decade. However, most of the publications result from investments from donors with a strategic science quality or biotech advocacy mandate leading to insufficient emphasis on applied value in plant breeding. Converting promising publications into practical applications requires the resolution of many logistical and genetical constraints that are I rarely addressed in journal publications. This results in a high proportion of published markers failing at one or more of the translation steps i from research arena to application domain. The rate of success is likely to increase due to developments in gene-based marker development, More efficient quantitative trait locus (QTL) mapping procedures, and lower cost genotyping systems. However, some fundamental remain to be resolved, particularly regarding complex traits, before marker-assisted selection realizes its full potential in public sector breed ing programs. These include the development of high throughput precision phenotyping systems for QTL mapping, improved understanding of genotype by environment interaftion and epistasis, and development of publicly available computational tools tailored to the needs of molecular breeding programs.
Food security is a global concern and substantial yield increases in cereal crops are required to feed the growing world population. Wheat is one of the three most important crops for human and livestock feed. However, the complexity of the genome coupled with a decline in genetic diversity within modern elite cultivars has hindered the application of marker-assisted selection (MAS) in breeding programmes. A crucial step in the successful application of MAS in breeding programmes is the development of cheap and easy to use molecular markers, such as single-nucleotide polymorphisms. To mine selected elite wheat germplasm for interva-rietal single-nucleotide polymorphisms, we have used expressed sequence tags derived from public sequencing programmes and next-generation sequencing of normalized wheat comple-mentary DNA libraries, in combination with a novel sequence alignment and assembly approach. Here, we describe the development and validation of a panel of 1114 single-nucle-otide polymorphisms in hexaploid bread wheat using competitive allele-specific polymerase chain reaction genotyping technology. We report the genotyping results of these markers on 23 wheat varieties, selected to represent a broad cross-section of wheat germplasm including a number of elite UK varieties. Finally, we show that, using relatively simple technology, it is possible to rapidly generate a linkage map containing several hundred single-nucleotide poly-morphism markers in the doubled haploid mapping population of Avalon · Cadenza.
Single nucleotide polymorphisms (SNPs) are the most abundant type of molecular genetic marker and can be used for producing high-resolution genetic maps, marker-trait association studies and marker-assisted breeding. Large polyploid genomes such as wheat present a challenge for SNP discovery because of the potential presence of multiple homoeologs for each gene. AutoSNPdb has been successfully applied to identify SNPs from Sanger sequence data for several species, including barley, rice and Brassica, but the volume of data required to accurately call SNPs in the complex genome of wheat has prevented its application to this important crop. DNA sequencing technology has been revolutionized by the introduction of next-generation sequencing, and it is now possible to generate several million sequence reads in a timely and cost-effective manner. We have produced wheat transcriptome sequence data using 454 sequencing technology and applied this for SNP discovery using a modified autoSNPdb method, which integrates SNP and gene annotation information with a graphical viewer. A total of 4,694,141 sequence reads from three bread wheat varieties were assembled to identify a total of 38 928 candidate SNPs. Each SNP is within an assembly complete with annotation, enabling the selection of polymorphism within genes of interest.
Wheat is the third most important crop for human nutrition in the world. The availability of high-resolution genetic and physical maps and ultimately a complete genome sequence holds great promise for breeding improved varieties to cope with increasing food demand under the conditions of changing global climate. However, the large size of the bread wheat (Triticum aestivum) genome (approximately 17 Gb/1C) and the triplication of genic sequence resulting from its hexaploid status have impeded genome sequencing of this important crop species. Here we describe the use of mitotic chromosome flow sorting to separately purify and then shotgun-sequence a pair of telocentric chromosomes that together form chromosome 4A (856 Mb/1C) of wheat. The isolation of this much reduced template and the consequent avoidance of the problem of sequence duplication, in conjunction with synteny-based comparisons with other grass genomes, have facilitated construction of an ordered gene map of chromosome 4A, embracing ≥85% of its total gene content, and have enabled precise localization of the various translocation and inversion breakpoints on chromosome 4A that differentiate it from its progenitor chromosome in the A genome diploid donor. The gene map of chromosome 4A, together with the emerging sequences of homoeologous wheat chromosome groups 4, 5 and 7, represent unique resources that will allow us to obtain new insights into the evolutionary dynamics between homoeologous chromosomes and syntenic chromosomal regions.
Michael Balter's recent article about French AIDS research (News & Comment, 16 Jan., [p. 312][1]) describes a feudal system with barons, czars, big bosses, and 35-year-old scientists considered as only young wolves. Unfortunately, this is not restricted to the AIDS research field, but is a general
Wheat was one of the first crops to be domesticated more than 10,000 years ago in the Middle East. Molecular genetics and archaeological data have allowed the reconstruction of plausible domestication scenarios leading to modern cultivars. For diploid einkorn and tetraploid durum wheat, a single domestication event has likely occurred in the Karacadag Mountains, Turkey. Following a cross between tetraploid durum and diploid T. tauschii, the resultant hexaploid bread wheat was domesticated and disseminated around the Caucasian region. These polyploidisation events facilitated wheat domestication and created genetic bottlenecks, which excluded potentially adaptive alleles. With the urgent need to accelerate genetic progress to confront the challenges of climate change and sustainable agriculture, wild ancestors and old landraces represent a reservoir of underexploited genetic diversity that may be utilized through modern breeding methods. Understanding domestication processes may thus help identifying new strategies.
The genome of bread wheat (Triticum aestivum) is predicted to be greater than 16 Gbp in size and consist predominantly of repetitive elements, making the sequencing and assembly of this genome a major challenge. We have reduced genome sequence complexity by isolating chromosome arm 7DS and applied second-generation technology and appropriate algorithmic analysis to sequence and assemble low copy and genic regions of this chromosome arm. The assembly represents approximately 40% of the chromosome arm and all known 7DS genes. Comparison of the 7DS assembly with the sequenced genomes of rice (Oryza sativa) and Brachypodium distachyon identified large regions of conservation. The syntenic relationship between wheat, B. distachyon and O. sativa, along with available genetic mapping data, has been used to produce an annotated draft 7DS syntenic build, which is publicly available at http://www.wheatgenome.info. Our results suggest that the sequencing of isolated chromosome arms can provide valuable information of the gene content of wheat and is a step towards whole-genome sequencing and variation discovery in this important crop.
Allopolyploidy accelerates genome evolution in wheat in two ways: 1) allopolyploidization triggers rapid genome alterations (revolutionary changes) through the instantaneous generation of a variety of cardinal genetic and epigenetic changes, and 2) the allopolyploid condition facilitates sporadic genomic changes during the life of the species (evolutionary changes) that are not attainable at the diploid level. The revolutionary alterations, occurring during the formation of the allopolyploid and leading to rapid cytological and genetic diploidization, facilitate the successful establishment of the newly formed allopolyploid in nature. On the other hand, the evolutionary changes, occurring during the life of the allopolyploids, increase the intra-specific genetic diversity, and consequently, increased fitness, adaptability and competitiveness. These phenomena, emphasizing the dynamic plasticity of the allopolyploid wheat genome with regards to both structure and function, are described and discussed in this review.