Performance analysis of conventional and AI-based variant callers using short and long reads.

BACKGROUND: The accurate detection of variants is essential for genomics-based studies. Currently, there are various tools designed to detect genomic variants, however, it has always been a challenge to decide which tool to use, especially when various major genome projects have chosen to use different tools. Thus far, most of the existing tools were mainly developed to work on short-read data (i.e., Illumina); however, other sequencing technologies (e.g. PacBio, and Oxford Nanopore) have recently shown that they can also be used for variant calling. In addition, with the emergence of artificial intelligence (AI)-based variant calling tools, there is a pressing need to compare these tools in terms of efficiency, accuracy, computational power, and ease of use. RESULTS: In this study, we evaluated five of the most widely used conventional and AI-based variant calling tools (BCFTools, GATK4, Platypus, DNAscope, and DeepVariant) in terms of accuracy and computational cost using both short-read and long-read data derived from three different sequencing technologies (Illumina, PacBio HiFi, and ONT) for the same set of samples from the Genome In A Bottle project. The analysis showed that AI-based variant calling tools supersede conventional ones for calling SNVs and INDELs using both long and short reads in most aspects. In addition, we demonstrate the advantages and drawbacks of each tool while ranking them in each aspect of these comparisons. CONCLUSION: This study provides best practices for variant calling using AI-based and conventional variant callers with different types of sequencing data.

Use of the Endoleak-to-Aortic Density Ratio to Distinguish Direct Endoleaks from Indirect Endoleaks after Endovascular Aortic Aneurysm Repair.

PURPOSE: To define criteria to distinguish direct (type 1 or 3) from indirect endoleaks (type 2) in the arterial phase of contrast-enhanced computed tomography (CT) scans in patients with abdominal aortic aneurysms treated with endovascular aortic repair. MATERIALS AND METHODS: This retrospective study was conducted from January 2009 to October 2020 and included consecutive patients treated endovascularly for a direct endoleak or an indirect endoleak associated with an enlarging aneurysm. The following characteristics were evaluated using contrast-enhanced CT: location, size, contact with the endograft, density, morphologic criteria, collateral artery enhancement, and endoleak-to-aortic density ratio. Statistical analysis included the Mann-Whitney U test, Pearson χ2 test, Fisher exact test, receiver operating characteristic curve analysis, and multivariable logistic regression. RESULTS: Contrast-enhanced CT scans from 71 patients (87% men), who presented with 87 endoleaks (44 indirect and 43 direct endoleaks), treated by endovascular techniques were analyzed. Using visual criteria, 56% of the endoleaks were not characterizable as direct or indirect. An endoleak-to-aortic density ratio of >0.77 could properly distinguish direct from indirect endoleaks, with a theoretical accuracy of 98% (area under the receiver operating characteristic curve, 0.99), sensitivity of 95%, specificity of 100%, positive predictive value of 100%, and negative predictive value of 96%. CONCLUSION: An endoleak-to-aortic density ratio of >0.77 in the arterial phase of contrast-enhanced CT could be a strong discriminant of a direct-type endoleak.

Combined use of Oxford Nanopore and Illumina sequencing yields insights into soybean structural variation biology.

BACKGROUND: Structural variants (SVs), including deletions, insertions, duplications, and inversions, are relatively long genomic variations implicated in a diverse range of processes from human disease to ecology and evolution. Given their complex signatures, tendency to occur in repeated regions, and large size, discovering SVs based on short reads is challenging compared to single-nucleotide variants. The increasing availability of long-read technologies has greatly facilitated SV discovery; however, these technologies remain too costly to apply routinely to population-level studies. Here, we combined short-read and long-read sequencing technologies to provide a comprehensive population-scale assessment of structural variation in a panel of Canadian soybean cultivars. RESULTS: We used Oxford Nanopore long-read sequencing data (~12× mean coverage) for 17 samples to both benchmark SV calls made from Illumina short-read data and predict SVs that were subsequently genotyped in a population of 102 samples using Illumina data. Benchmarking results show that variants discovered using Oxford Nanopore can be accurately genotyped from the Illumina data. We first use the genotyped deletions and insertions for population genetics analyses and show that results are comparable to those based on single-nucleotide variants. We observe that the population frequency and distribution within the genome of deletions and insertions are constrained by the location of genes. Gene Ontology and PFAM domain enrichment analyses also confirm previous reports that genes harboring high-frequency deletions and insertions are enriched for functions in defense response. Finally, we discover polymorphic transposable elements from the deletions and insertions and report evidence of the recent activity of a Stowaway MITE. CONCLUSIONS: We show that structural variants discovered using Oxford Nanopore data can be genotyped with high accuracy from Illumina data. Our results demonstrate that long-read and short-read sequencing technologies can be efficiently combined to enhance SV analysis in large populations, providing a reusable framework for their study in a wider range of samples and non-model species.

A high-resolution consensus linkage map for barley based on GBS-derived genotypes.

As genotyping-by-sequencing (GBS) is widely used in barley genetic studies, the translation of the physical position of GBS-derived SNPs into accurate genetic positions has become relevant. The main aim of this study was to develop a high-resolution consensus linkage map based on GBS-derived SNPs. The construction of this integrated map involved 11 bi-parental populations composed of 3743 segregating progenies. We adopted a uniform set of SNP-calling and filtering conditions to identify 50 875 distinct SNPs segregating in at least one population. These SNPs were grouped into 18 580 non-redundant SNPs (bins). The resulting consensus linkage map spanned 1050.1 cM, providing an average density of 17.7 bins and 48.4 SNPs per cM. The consensus map is characterized by the absence of large intervals devoid of marker coverage (significant gaps), the largest interval between bins was only 3.7 cM and the mean distance between adjacent bins was 0.06 cM. This high-resolution linkage map will contribute to several applications in genomic research, such as providing useful information on the recombination landscape for QTLs/genes identified via GWAS or ensuring a uniform distribution of SNPs when developing low-cost genotyping tools offering a limited number of markers.

The construction of a high-density consensus genetic map for soybean based on SNP markers derived from genotyping-by-sequencing.

Genetic linkage maps are used to localize markers on the genome based on the recombination frequency. Most often, these maps are based on the segregation observed within a single biparental population of limited size (n < 300) where relatively few recombination events are sampled and in which some genomic regions are monomorphic because both parents carry the same alleles. Together, these two limitations affect both the resolution and extent of genome coverage of such maps. Consensus genetic maps overcome the limitations of individual genetic maps by merging the information from multiple segregating populations derived from a greater diversity of parental combinations, thus increasing the number of recombination events and reducing the number of monomorphic regions. The aim of this study was to construct a high-density consensus genetic map for single nucleotide polymorphism (SNP) markers obtained through a genotyping-by-sequencing (GBS) approach. Individual genetic maps were generated from six F4:5 mapping populations (n = 278-365), totaling 1857 individuals. The six linkage maps were then merged to produce a consensus map comprising a total of 16 311 mapped SNPs that jointly cover 99.5% of the soybean genome with only two gaps larger than 10 cM. Compared to previous soybean consensus maps, it offers a more extensive and uniform coverage.

The pan-genome of the cultivated soybean (PanSoy) reveals an extraordinarily conserved gene content.

Studies on structural variation in plants have revealed the inadequacy of a single reference genome for an entire species and suggest that it is necessary to build a species-representative genome called a pan-genome to better capture the extent of both structural and nucleotide variation. Here, we present a pan-genome of cultivated soybean (Glycine max), termed PanSoy, constructed using the de novo genome assembly of 204 phylogenetically and geographically representative improved accessions selected from the larger GmHapMap collection. PanSoy uncovers 108 Mb (˜11%) of novel nonreference sequences encompassing 3621 protein-coding genes (including 1659 novel genes) absent from the soybean 'Williams 82' reference genome. Nonetheless, the core genome represents an exceptionally large proportion of the genome, with >90.6% of genes being shared by >99% of the accessions. A majority of PAVs encompassing genes could be confirmed with long-read sequencing on a subset of accessions. The PanSoy is a major step towards capturing the extent of genetic variation in cultivated soybean and provides a resource for soybean genomics research and breeding.

Soybean (Glycine max) Haplotype Map (GmHapMap): a universal resource for soybean translational and functional genomics.

Here, we describe a worldwide haplotype map for soybean (GmHapMap) constructed using whole-genome sequence data for 1007 Glycine max accessions and yielding 14.9 million variants as well as 4.3 M tag single-nucleotide polymorphisms (SNPs). When sampling random subsets of these accessions, the number of variants and tag SNPs plateaued beyond approximately 800 and 600 accessions, respectively. This suggests extensive coverage of diversity within the cultivated soybean. GmHapMap variants were imputed onto 21 618 previously genotyped accessions with up to 96% success for common alleles. A local association analysis was performed with the imputed data using markers located in a 1-Mb region known to contribute to seed oil content and enabled us to identify a candidate causal SNP residing in the NPC1 gene. We determined gene-centric haplotypes (407 867 GCHs) for the 55 589 genes and showed that such haplotypes can help to identify alleles that differ in the resulting phenotype. Finally, we predicted 18 031 putative loss-of-function (LOF) mutations in 10 662 genes and illustrated how such a resource can be used to explore gene function. The GmHapMap provides a unique worldwide resource for applied soybean genomics and breeding.

DepthFinder: a tool to determine the optimal read depth for reduced-representation sequencing.

MOTIVATION: Identification of DNA sequence variations such as single nucleotide polymorphisms (SNPs) is a fundamental step toward genetic studies. Reduced-representation sequencing methods have been developed as alternatives to whole genome sequencing to reduce costs and enable the analysis of many more individual. Amongst these methods, restriction site associated sequencing (RSAS) methodologies have been widely used for rapid and cost-effective discovery of SNPs and for high-throughput genotyping in a wide range of species. Despite the extensive improvements of the RSAS methods in the last decade, the estimation of the number of reads (i.e. read depth) required per sample for an efficient and effective genotyping remains mostly based on trial and error. RESULTS: Herein we describe a bioinformatics tool, DepthFinder, designed to estimate the required read counts for RSAS methods. To illustrate its performance, we estimated required read counts in six different species (human, cattle, spruce budworm, salmon, barley and soybean) that cover a range of different biological (genome size, level of genome complexity, level of DNA methylation and ploidy) and technical (library preparation protocol and sequencing platform) factors. To assess the prediction accuracy of DepthFinder, we compared DepthFinder-derived results with independent datasets obtained from an RSAS experiment. This analysis yielded estimated accuracies of nearly 94%. Moreover, we present DepthFinder as a powerful tool to predict the most effective size selection interval in RSAS work. We conclude that DepthFinder constitutes an efficient, reliable and useful tool for a broad array of users in different research communities. AVAILABILITY AND IMPLEMENTATION: https://bitbucket.org/jerlar73/DepthFinder. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genome-wide association study for resistance to the Meloidogyne javanica causing root-knot nematode in soybean.

KEY MESSAGE: A locus on chromosome 13, containing multiple TIR-NB-LRR genes and SNPs associated with M. javanica resistance, was identified using a combination of GWAS, resequencing, genetic mapping and expression profiling. Meloidogyne javanica, a root-knot nematode, is an important problem in soybean-growing areas, leading to severe yield losses. Some accessions have been identified carrying resistance loci to this nematode. In this study, a set of 317 soybean accessions was characterized for resistance to M. javanica. A genome-wide association study was performed using SNPs from genotyping-by-sequencing, and a region of 29.2 kb on chromosome 13 was identified. An analysis of haplotypes showed that SNPs were able to discriminate between susceptible and resistant accessions, with 25 accessions sharing the haplotype associated with resistance. Furthermore, five accessions that exhibited resistance without carrying this haplotype may carry different loci conferring resistance to M. javanica. We also conducted the screening of the SNPs in the USDA soybean germplasm, revealing that several soybean accessions previously reported as resistant to other nematodes also shared the resistance haplotype on chromosome 13. Two SNP-based TaqMan® assays were developed and validated in two panels of soybean cultivars and in biparental populations. In silico analysis of the region associated with resistance identified the occurrence of genes with structural similarity with classical major resistance genes (NBS-LRR genes). Specifically, several nonsynonymous SNPs were observed in Glyma.13g194800 and Glyma.13g194900. The expression profile of these candidate genes demonstrated that the two gene models were up-regulated in the resistance source PI 505,099 after nematode infection. Overall, the SNPs associated with resistance and the genes identified constitute an important tool for introgression of resistance to the root-knot nematode by marker-assisted selection in soybean breeding programs.

Genome-wide association mapping of Sclerotinia sclerotiorum resistance in soybean using whole-genome resequencing data.

BACKGROUND: Sclerotinia stem rot (SSR), caused by Sclerotinia sclerotiorum (Lib.) de Bary, is an important cause of yield loss in soybean. Although many papers have reported different loci contributing to partial resistance, few of these were proved to reproduce the same phenotypic impact in different populations. RESULTS: In this study, we identified a major quantitative trait loci (QTL) associated with resistance to SSR progression on the main stem by using a genome-wide association mapping (GWAM). A population of 127 soybean accessions was genotyped with 1.5 M SNPs derived from genotyping-by-sequencing (GBS) and whole-genome sequencing (WGS) ensuring an extensive genome coverage and phenotyped for SSR resistance. SNP-trait association led to discovery of a new QTL on chromosome 1 (Chr01) where resistant lines had shorter lesions on the stem by 29 mm. A single gene (Glyma.01 g048000) resided in the same LD block as the peak SNP, but it is of unknown function. The impact of this QTL was even more significant in the descendants of a cross between two lines carrying contrasted alleles for Chr01. Individuals carrying the resistance allele developed lesions almost 50% shorter than those bearing the sensitivity allele. CONCLUSION: These results suggest that the new region on chromosome 1 harbors a promising resistance QTL to SSR that can be used in soybean breeding program.

Identification of loci controlling mineral element concentration in soybean seeds.

BACKGROUND: Mineral nutrients play a crucial role in the biochemical and physiological functions of biological systems. The enhancement of seed mineral content via genetic improvement is considered as the most promising and cost-effective approach compared alternative means for meeting the dietary needs. The overall objective of this study was to perform a GWAS of mineral content (Ca, K, P and S) in seeds of a core set of 137 soybean lines that are representative of the diversity of early maturing soybeans cultivated in Canada (maturity groups 000-II). RESULTS: This panel of 137 soybean lines was grown in five environments (in total) and the seed mineral content was measured using a portable x-ray fluorescence (XRF) spectrometer. The association analyses were carried out using three statistical models and a set of 2.2 million SNPs obtained from a combined dataset of genotyping-by-sequencing and whole-genome sequencing. Eight QTLs significantly associated with the Ca, K, P and S content were identified by at least two of the three statistical models used (in two environments) contributing each from 17 to 31% of the phenotypic variation. A strong reproducibility of the effect of seven out these eight QTLs was observed in three other environments. In total, three candidate genes were identified involved in transport and assimilation of these mineral elements. CONCLUSIONS: There have been very few GWAS studies to identify QTLs associated with the mineral element content of soybean seeds. In addition to being new, the QTLs identified in this study and candidate genes will be useful for the genetic improvement of soybean nutritional quality through marker-assisted selection. Moreover, this study also provides details on the range of phenotypic variation encountered within the Canadian soybean germplasm.

Population structure of Nepali spring wheat (Triticum aestivum L.) germplasm.

BACKGROUND: Appropriate information about genetic diversity and population structure of germplasm improves the efficiency of plant breeding. The low productivity of Nepali bread wheat (Triticum aestivum L.) is a major concern particularly since Nepal is ranked the 4th most vulnerable nation globally to climate change. The genetic diversity and population structure of Nepali spring wheat have not been reported. This study aims to improve the exploitation of more diverse and under-utilized genetic resources to contribute to current and future breeding efforts for global food security. RESULTS: We used genotyping-by-sequencing (GBS) to characterize a panel of 318 spring wheat accessions from Nepal including 166 landraces, 115 CIMMYT advanced lines, and 34 Nepali released varieties. We identified 95 K high-quality SNPs. The greatest genetic diversity was observed among the landraces, followed by CIMMYT lines, and released varieties. Though we expected only 3 groupings corresponding to these 3 seed origins, the population structure revealed two large, distinct subpopulations along with two smaller and scattered subpopulations in between, with significant admixture. This result was confirmed by principal component analysis (PCA) and UPGMA distance-based clustering. The pattern of LD decay differed between subpopulations, ranging from 60 to 150 Kb. We discuss the possibility that germplasm explorations during the 1970s-1990s may have mistakenly collected exotic germplasm instead of local landraces and/or collected materials that had already cross-hybridized since exotic germplasm was introduced starting in the 1950s. CONCLUSION: We suggest that only a subset of wheat "landraces" in Nepal are authentic which this study has identified. Targeting these authentic landraces may accelerate local breeding programs to improve the food security of this climate-vulnerable nation. Overall, this study provides a novel understanding of the genetic diversity of wheat in Nepal and this may contribute to global wheat breeding initiatives.

SRG extractor: a skinny reference genome approach for reduced-representation sequencing.

MOTIVATION: Reduced-representation sequencing is a genome-wide scanning method for simultaneous discovery and genotyping of thousands to millions of single nucleotide polymorphisms that is used across a wide range of species. However, in this method a reproducible but very small fraction of the genome is captured for sequencing, while the resulting reads are typically aligned against the entire reference genome. RESULTS: Here we present a skinny reference genome approach in which a simplified reference genome is used to decrease computing time for data processing and to increase single nucleotide polymorphism counts and accuracy. A skinny reference genome can be integrated into any reduced-representation sequencing analytical pipeline. AVAILABILITY AND IMPLEMENTATION: https://bitbucket.org/jerlar73/SRG-Extractor. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Haplotype diversity underlying quantitative traits in Canadian soybean breeding germplasm.

KEY MESSAGE: Identification of marker-trait associations and trait-associated haplotypes in breeding germplasm identifies regions under selection and highlights changes in haplotype diversity over decades of soybean improvement in Canada. Understanding marker-trait associations using genome-wide association in soybean is typically carried out in diverse germplasm groups where identified loci are often not applicable to soybean breeding efforts. To address this challenge, this study focuses on defining marker-trait associations in breeding germplasm and studying the underlying haplotypes in these regions to assess genetic change through decades of selection. Phenotype data were generated for 175 accessions across multiple environments in Ontario, Canada. A set of 76,549 SNPs were used in the association analysis. A total of 23 genomic regions were identified as significantly associated with yield (5), days to maturity (5), seed oil (3), seed protein (5) and 100-seed weight (5), of which 14 are novel. Each significant region was haplotyped to assess haplotype diversity of the underlying genomic region, identifying ten regions with trait-associated haplotypes in the breeding germplasm. The range of genomic length for these regions (7.2 kb to 6.8 Mb) indicates variation in regional LD for the trait-associated regions. Six of these regions showed changes between eras of breeding, from historical to modern and experimental soybean accessions. Continued selection on these regions may necessitate introgression of novel parental genetic diversity as some haplotypes were fixed within the breeding germplasm. This finding highlights the importance of studying associations and haplotype diversity at a breeding program scale to understand breeders' selections and trends in soybean improvement over time. The haplotypes may also be used as a tool for selection of parental germplasm to inform breeder's decisions on further soybean improvement.

Genome-wide association analyses reveal the genetic basis of biomass accumulation under symbiotic nitrogen fixation in African soybean.

KEY MESSAGE: We explored the genetic basis of SNF-related traits through GWAS and identified 40 candidate genes. This study provides fundamental insights into SNF-related traits and will accelerate efforts for SNF breeding. Symbiotic nitrogen fixation (SNF) increases sustainability by supplying biological nitrogen for crops to enhance yields without damaging the ecosystem. A better understanding of this complex biological process is critical for addressing the triple challenges of food security, environmental degradation, and climate change. Soybean plants, the most important legume worldwide, can form a mutualistic interaction with specialized soil bacteria, bradyrhizobia, to fix atmospheric nitrogen. Here we report a comprehensive genome-wide association study of 11 SNF-related traits using 79K GBS-derived SNPs in 297 African soybeans. We identified 25 QTL regions encompassing 40 putative candidate genes for SNF-related traits including 20 genes with no prior known role in SNF. A line with a large deletion (164 kb), encompassing a QTL region containing a strong candidate gene (CASTOR), exhibited a marked decrease in SNF. This study performed on African soybean lines provides fundamental insights into SNF-related traits and yielded a rich catalog of candidate genes for SNF-related traits that might accelerate future efforts aimed at sustainable agriculture.

Fast-GBS v2.0: an analysis toolkit for genotyping-by-sequencing data.

Genotyping-by-sequencing (GBS) is a rapid, flexible, low-cost, and robust genotyping method that simultaneously discovers variants and calls genotypes within a broad range of samples. These characteristics make GBS an excellent tool for many applications and research questions from conservation biology to functional genomics in both model and non-model species. Continued improvement of GBS relies on a more comprehensive understanding of data analysis, development of fast and efficient bioinformatics pipelines, accurate missing data imputation, and active post-release support. Here, we present the second generation of Fast-GBS (v2.0) that offers several new options (e.g., processing paired-end reads and imputation of missing data) and features (e.g., summary statistics of genotypes) to improve the GBS data analysis process. The performance assessment analysis showed that Fast-GBS v2.0 outperformed other available analytical pipelines, such as GBS-SNP-CROP and Gb-eaSy. Fast-GBS v2.0 provides an analysis platform that can be run with different types of sequencing data, modest computational resources, and allows for missing-data imputation for various species in different contexts.

Time for a paradigm shift in the use of plant genetic resources.

For all major crops, sizeable genebanks are maintained across the world and serve as repositories of genetic diversity and key sources of novel traits used in breeding. Although molecular markers have been used to characterize diversity in a broad sense, the most common approach to exploring these resources has been through phenotypic characterization of subsets of these large collections. With the advent of affordable large-scale genotyping technologies and the increasing body of candidate genes for traits of interest, we argue here that it is time for a paradigm shift in the way that we explore and exploit these considerable and highly useful resources. By combining dense genotypic information in and around candidate genes, it is possible to classify accessions based on their haplotype, something approximating the actual alleles at these genes of interest.

Identification of candidate domestication-related genes with a systematic survey of loss-of-function mutations.

Domestication is an important key co-evolutionary process through which humans have extensively altered the genomic make-up and appearance of both plants and animals. The identification of domestication-related genes remains very arduous. In this study, we present a systematic analytical approach that harnesses two recent advances in genomics, whole-genome sequencing (WGS) and prediction of loss-of-function (LOF) mutations, to greatly facilitate the assembly of an enriched catalogue of domestication-related candidate genes. Using WGS data for 296 cultivated (Glycine max) and 64 wild soybean accessions, we identified 8699 LOF variants, and 116 genes that are uniquely fixed for one or more LOF allele(s) in domesticated soybeans. Existing soybean transcriptomic data led us to overcome analytical challenges associated with whole-genome duplications and to identify neo- or subfunctionalized genes. This systematic approach allowed us to identify 110 candidate domestication-related genes in an efficient and rapid way. This catalogue contains previously well characterized domestication genes in soybean, as well as some orthologs from other domesticated crop species. In addition, it comprises many promising candidate domestication genes. Overall, this collection of candidate domestication-related genes in soybean is almost twice as large as the sum of all previously reported candidate genes in all other crops. We believe this systematic approach could readily be used in wide range of species.

Screening populations for copy number variation using genotyping-by-sequencing: a proof of concept using soybean fast neutron mutants.

BACKGROUND: The effective use of mutant populations for reverse genetic screens relies on the population-wide characterization of the induced mutations. Genome- and population-wide characterization of the mutations found in fast neutron populations has been hindered, however, by the wide range of mutations generated and the lack of affordable technologies to detect DNA sequence changes. In this study, we therefore aimed to test whether genotyping-by-sequencing (GBS) technology could be used to characterize copy number variation (CNV) induced by fast neutrons in a soybean mutant population. RESULTS: We called CNVs from GBS data in 79 soybean mutants and assessed the sensitivity and precision of this approach by validating our results against array comparative genomic hybridization (aCGH) data for 19 of these mutants as well as targeted PCR and ddPCR assays for a representative subset of the smallest events detected by GBS. Our GBS pipeline detected 55 of the 96 events found by aCGH, with approximate detection thresholds of 60 kb, 500 kb and 1 Mb for homozygous deletions, hemizygous deletions and duplications, respectively. Among the whole set of 79 mutants, the GBS data revealed 105 homozygous deletions, 32 hemizygous deletions and 19 duplications. This included several extremely large events, exhibiting maximum sizes of ~ 11.2 Mb for a homozygous deletion, ~ 11.6 Mb for a hemizygous deletion, and ~ 50 Mb for a duplication. CONCLUSIONS: This study provides a proof of concept that GBS can be used as an affordable high-throughput method for assessing CNVs in fast neutron mutants. The modularity of this GBS approach allows combining as many different libraries or sequencing runs as is necessary for reaching the goals of a particular study. This method should enable the low-cost genome-wide characterization of hundreds to thousands of individuals in fast neutron mutant populations or any population with large genomic deletions and duplications.

Association mapping of a locus that confers southern stem canker resistance in soybean and SNP marker development.

BACKGROUND: Southern stem canker (SSC), caused by Diaporthe aspalathi (E. Jansen, Castl. & Crous), is an important soybean disease that has been responsible for severe losses in the past. The main strategy for controlling this fungus involves the introgression of resistance genes. Thus far, five main loci have been associated with resistance to SSC. However, there is a lack of information about useful allelic variation at these loci. In this work, a genome-wide association study (GWAS) was performed to identify allelic variation associated with resistance against Diaporthe aspalathi and to provide molecular markers that will be useful in breeding programs. RESULTS: We characterized the response to SSC infection in a panel of 295 accessions from different regions of the world, including important Brazilian elite cultivars. Using a GBS approach, the panel was genotyped, and we identified marker loci associated with Diaporthe aspalathi resistance through GWAS. We identified 19 SNPs associated with southern stem canker resistance, all on chromosome 14. The peak SNP showed an extremely high degree of association (p-value = 6.35E-27) and explained a large amount of the observed phenotypic variance (R2 = 70%). This strongly suggests that a single major gene is responsible for resistance to D. aspalathi in most of the lines constituting this panel. In resequenced soybean materials, we identified other SNPs in the region identified through GWAS in the same LD block that clearly differentiate resistant and susceptible accessions. The peak SNP was selected and used to develop a cost-effective molecular marker assay, which was validated in a subset of the initial panel. In an accuracy test, this SNP assay demonstrated 98% selection efficiency. CONCLUSIONS: Our results suggest relevance of this locus to SSC resistance in soybean cultivars and accessions from different countries, and the SNP marker assay developed in this study can be directly applied in MAS studies in breeding programs to select materials that are resistant against this pathogen and support its introgression.