Bridging the genotyping gap: using genotyping by sequencing (GBS) to add high-density SNP markers and new value to traditional bi-parental mapping and breeding populations

SorGSD: a sorghum genome SNP database

BACKGROUND

Sorghum (Sorghum bicolor) is one of the most important cereal crops globally and a potential energy plant for biofuel production. In order to explore genetic gain for a range of important quantitative traits, such as drought and heat tolerance, grain yield, stem sugar accumulation, and biomass production, via the use of molecular breeding and genomic selection strategies, knowledge of the available genetic variation and the underlying sequence polymorphisms, is required.

RESULTS

Based on the assembled and annotated genome sequences of Sorghum bicolor (v2.1) and the recently published sorghum re-sequencing data, ~62.9 M SNPs were identified among 48 sorghum accessions and included in a newly developed sorghum genome SNP database SorGSD (http://sorgsd.big.ac.cn). The diverse panel of 48 sorghum lines can be classified into four groups, improved varieties, landraces, wild and weedy sorghums, and a wild relative Sorghum propinquum. SorGSD has a web-based query interface to search or browse SNPs from individual accessions, or to compare SNPs among several lines. The query results can be visualized as text format in tables, or rendered as graphics in a genome browser. Users may find useful annotation from query results including type of SNPs such as synonymous or non-synonymous SNPs, start, stop of splice variants, chromosome locations, and links to the annotation on Phytozome (www.phytozome.net) sorghum genome database. In addition, general information related to sorghum research such as online sorghum resources and literature references can also be found on the website. All the SNP data and annotations can be freely download from the website.

CONCLUSIONS

SorGSD is a comprehensive web-portal providing a database of large-scale genome variation across all racial types of cultivated sorghum and wild relatives. It can serve as a bioinformatics platform for a range of genomics and molecular breeding activities for sorghum and for other C4 grasses.

High-density linkage map construction and mapping of seed trait QTLs in chickpea (Cicer arietinum L.) using Genotyping-by-Sequencing (GBS)

This study reports the use of Genotyping-by-Sequencing (GBS) for large-scale SNP discovery and simultaneous genotyping of recombinant inbred lines (RILs) of an intra-specific mapping population of chickpea contrasting for seed traits. A total of 119,672 raw SNPs were discovered, which after stringent filtering revealed 3,977 high quality SNPs of which 39.5% were present in genic regions. Comparative analysis using physically mapped marker loci revealed a higher degree of synteny with Medicago in comparison to soybean. The SNP genotyping data was utilized to construct one of the most saturated intra-specific genetic linkage maps of chickpea having 3,363 mapped positions including 3,228 SNPs on 8 linkage groups spanning 1006.98 cM at an average inter marker distance of 0.33 cM. The map was utilized to identify 20 quantitative trait loci (QTLs) associated with seed traits accounting for phenotypic variations ranging from 9.97% to 29.71%. Analysis of the genomic sequence corresponding to five robust QTLs led to the identification of 684 putative candidate genes whose expression profiling revealed that 101 genes exhibited seed specific expression. The integrated approach utilizing the identified QTLs along with the available genome and transcriptome could serve as a platform for candidate gene identification for molecular breeding of chickpea.

Genotyping-by-sequencing map permits identification of clubroot resistance QTLs and revision of the reference genome assembly in cabbage (Brassica oleracea L.)

Clubroot is a devastating disease caused by Plasmodiophora brassicae and results in severe losses of yield and quality in Brassica crops. Many clubroot resistance genes and markers are available in Brassica rapa but less is known in Brassica oleracea. Here, we applied the genotyping-by-sequencing (GBS) technique to construct a high-resolution genetic map and identify clubroot resistance (CR) genes. A total of 43,821 SNPs were identified using GBS data for two parental lines, one resistant and one susceptible lines to clubroot, and 18,187 of them showed >5× coverage in the GBS data. Among those, 4,103 were credibly genotyped for all 78 F₂ individual plants. These markers were clustered into nine linkage groups spanning 879.9 cM with an average interval of 1.15 cM. Quantitative trait loci (QTLs) survey based on three rounds of clubroot resistance tests using F_2:3 progenies revealed two and single major QTLs for Race 2 and Race 9 of P. brassicae, respectively. The QTLs show similar locations to the previously reported CR loci for Race 4 in B. oleracea but are in different positions from any of the CR loci found in B. rapa. We utilized two reference genome sequences in this study. The high-resolution genetic map developed herein allowed us to reposition 37 and 2 misanchored scaffolds in the 02–12 and TO1000DH genome sequences, respectively. Our data also support additional positioning of two unanchored 3.3 Mb scaffolds into the 02–12 genome sequence.

A Genome-wide Combinatorial Strategy Dissects Complex Genetic Architecture of Seed Coat Color in Chickpea

The study identified 9045 high-quality SNPs employing both genome-wide GBS- and candidate gene-based SNP genotyping assays in 172, including 93 cultivated (desi and kabuli) and 79 wild chickpea accessions. The GWAS in a structured population of 93 sequenced accessions detected 15 major genomic loci exhibiting significant association with seed coat color. Five seed color-associated major genomic loci underlying robust QTLs mapped on a high-density intra-specific genetic linkage map were validated by QTL mapping. The integration of association and QTL mapping with gene haplotype-specific LD mapping and transcript profiling identified novel allelic variants (non-synonymous SNPs) and haplotypes in a MATE secondary transporter gene regulating light/yellow brown and beige seed coat color differentiation in chickpea. The down-regulation and decreased transcript expression of beige seed coat color-associated MATE gene haplotype was correlated with reduced proanthocyanidins accumulation in the mature seed coats of beige than light/yellow brown seed colored desi and kabuli accessions for their coloration/pigmentation. This seed color-regulating MATE gene revealed strong purifying selection pressure primarily in LB/YB seed colored desi and wild Cicer reticulatum accessions compared with the BE seed colored kabuli accessions. The functionally relevant molecular tags identified have potential to decipher the complex transcriptional regulatory gene function of seed coat coloration and for understanding the selective sweep-based seed color trait evolutionary pattern in cultivated and wild accessions during chickpea domestication. The genome-wide integrated approach employed will expedite marker-assisted genetic enhancement for developing cultivars with desirable seed coat color types in chickpea.

Application of Population Sequencing (POPSEQ) for Ordering and Imputing Genotyping-by-Sequencing Markers in Hexaploid Wheat

The advancement of next-generation sequencing technologies in conjunction with new bioinformatics tools enabled fine-tuning of sequence-based, high-resolution mapping strategies for complex genomes. Although genotyping-by-sequencing (GBS) provides a large number of markers, its application for association mapping and genomics-assisted breeding is limited by a large proportion of missing data per marker. For species with a reference genomic sequence, markers can be ordered on the physical map. However, in the absence of reference marker order, the use and imputation of GBS markers is challenging. Here, we demonstrate how the population sequencing (POPSEQ) approach can be used to provide marker context for GBS in wheat. The utility of a POPSEQ-based genetic map as a reference map to create genetically ordered markers on a chromosome for hexaploid wheat was validated by constructing an independent de novo linkage map of GBS markers from a Synthetic W7984 × Opata M85 recombinant inbred line (SynOpRIL) population. The results indicated that there is strong agreement between the independent de novo linkage map and the POPSEQ mapping approach in mapping and ordering GBS markers for hexaploid wheat. After ordering, a large number of GBS markers were imputed, thus providing a high-quality reference map that can be used for QTL mapping for different traits. The POPSEQ-based reference map and whole-genome sequence assemblies are valuable resources that can be used to order GBS markers and enable the application of highly accurate imputation methods to leverage the application GBS markers in wheat.

Heterozygous Mapping Strategy (HetMappS) for High Resolution Genotyping-By-Sequencing Markers: A Case Study in Grapevine

Genotyping by sequencing (GBS) provides opportunities to generate high-resolution genetic maps at a low genotyping cost, but for highly heterozygous species, missing data and heterozygote undercalling complicate the creation of GBS genetic maps. To overcome these issues, we developed a publicly available, modular approach called HetMappS, which functions independently of parental genotypes and corrects for genotyping errors associated with heterozygosity. For linkage group formation, HetMappS includes both a reference-guided synteny pipeline and a reference-independent de novo pipeline. The de novo pipeline can be utilized for under-characterized or high diversity families that lack an appropriate reference. We applied both HetMappS pipelines in five half-sib F1 families involving genetically diverse Vitis spp. Starting with at least 116,466 putative SNPs per family, the HetMappS pipelines identified 10,440 to 17,267 phased pseudo-testcross (Pt) markers and generated high-confidence maps. Pt marker density exceeded crossover resolution in all cases; up to 5,560 non-redundant markers were used to generate parental maps ranging from 1,047 cM to 1,696 cM. The number of markers used was strongly correlated with family size in both de novo and synteny maps (r = 0.92 and 0.91, respectively). Comparisons between allele and tag frequencies suggested that many markers were in tandem repeats and mapped as single loci, while markers in regions of more than two repeats were removed during map curation. Both pipelines generated similar genetic maps, and genetic order was strongly correlated with the reference genome physical order in all cases. Independently created genetic maps from shared parents exhibited nearly identical results. Flower sex was mapped in three families and correctly localized to the known sex locus in all cases. The HetMappS pipeline could have wide application for genetic mapping in highly heterozygous species, and its modularity provides opportunities to adapt portions of the pipeline to other family types, genotyping technologies or applications.

Genome-wide high-throughput SNP discovery and genotyping for understanding natural (functional) allelic diversity and domestication patterns in wild chickpea

We identified 82489 high-quality genome-wide SNPs from 93 wild and cultivated Cicer accessions through integrated reference genome- and de novo-based GBS assays. High intra- and inter-specific polymorphic potential (66-85%) and broader natural allelic diversity (6-64%) detected by genome-wide SNPs among accessions signify their efficacy for monitoring introgression and transferring target trait-regulating genomic (gene) regions/allelic variants from wild to cultivated Cicer gene pools for genetic improvement. The population-specific assignment of wild Cicer accessions pertaining to the primary gene pool are more influenced by geographical origin/phenotypic characteristics than species/gene-pools of origination. The functional significance of allelic variants (non-synonymous and regulatory SNPs) scanned from transcription factors and stress-responsive genes in differentiating wild accessions (with potential known sources of yield-contributing and stress tolerance traits) from cultivated desi and kabuli accessions, fine-mapping/map-based cloning of QTLs and determination of LD patterns across wild and cultivated gene-pools are suitably elucidated. The correlation between phenotypic (agromorphological traits) and molecular diversity-based admixed domestication patterns within six structured populations of wild and cultivated accessions via genome-wide SNPs was apparent. This suggests utility of whole genome SNPs as a potential resource for identifying naturally selected trait-regulating genomic targets/functional allelic variants adaptive to diverse agroclimatic regions for genetic enhancement of cultivated gene-pools.

Genotyping-by-sequencing (GBS) identified SNP tightly linked to QTL for pre-harvest sprouting resistance

Using a GBS-SNP map, a QTL for pre-harvest sprouting resistance on 4AL of Totoumai A was delimited to 2.9-cM interval, and SNP closely linked to several other QTL were identified. Pre-harvest sprouting (PHS) of wheat is a major constraint to wheat production in many wheat-growing areas worldwide, because it reduces both wheat grain yield and the end-use quality. To identify markers tightly linked to the quantitative trait loci (QTL) for PHS resistance and seed dormancy (SD), we evaluated 155 recombinant inbred lines (RIL) derived from a cross between a PHS-resistant parent 'Tutoumai A' and a PHS-susceptible parent 'Siyang 936' for single-nucleotide polymorphisms (SNP) using genotyping-by-sequencing (GBS), and for PHS resistance and SD using both field and greenhouse grown plants. Two SNP, GBS109947 and GBS212432, were mapped to a major QTL region for PHS resistance and SD on chromosome 4AL, and delimited the QTL to a 2.9-cM interval. Two and nine additional SNP were mapped to minor QTL regions for SD on chromosome 5B and 5A, respectively. Critical SNP in these QTL regions were converted into KBioscience Competitive Allele-Specific PCR (KASP) assays that can be easily used for marker-assisted selection to improve PHS resistance.

More than one way to evolve a weed: parallel evolution of US weedy rice through independent genetic mechanisms

Many different crop species were selected for a common suite of 'domestication traits', which facilitates their use for studies of parallel evolution. Within domesticated rice (Oryza sativa), there has also been independent evolution of weedy strains from different cultivated varieties. This makes it possible to examine the genetic basis of parallel weed evolution and the extent to which this process occurs through shared genetic mechanisms. We performed comparative QTL mapping of weediness traits using two recombinant inbred line populations derived from crosses between an indica crop variety and representatives of each of the two independently evolved weed strains found in US rice fields, strawhull (S) and blackhull awned (B). Genotyping-by-sequencing provided dense marker coverage for linkage map construction (average marker interval <0.25 cM), with 6016 and 13 730 SNPs mapped in F5 lines of the S and B populations, respectively. For some weediness traits (awn length, hull pigmentation and pericarp pigmentation), QTL mapping and sequencing of underlying candidate genes confirmed that trait variation was largely attributable to individual loci. However, for more complex quantitative traits (including heading date, panicle length and seed shattering), we found multiple QTL, with little evidence of shared genetic bases between the S and B populations or across previous studies of weedy rice. Candidate gene sequencing revealed causal genetic bases for 8 of 27 total mapped QTL. Together these findings suggest that despite the genetic bottleneck that occurred during rice domestication, there is ample genetic variation in this crop to allow agricultural weed evolution through multiple genetic mechanisms.

A genome-wide SNP scan accelerates trait-regulatory genomic loci identification in chickpea

We identified 44844 high-quality SNPs by sequencing 92 diverse chickpea accessions belonging to a seed and pod trait-specific association panel using reference genome- and de novo-based GBS (genotyping-by-sequencing) assays. A GWAS (genome-wide association study) in an association panel of 211, including the 92 sequenced accessions, identified 22 major genomic loci showing significant association (explaining 23-47% phenotypic variation) with pod and seed number/plant and 100-seed weight. Eighteen trait-regulatory major genomic loci underlying 13 robust QTLs were validated and mapped on an intra-specific genetic linkage map by QTL mapping. A combinatorial approach of GWAS, QTL mapping and gene haplotype-specific LD mapping and transcript profiling uncovered one superior haplotype and favourable natural allelic variants in the upstream regulatory region of a CesA-type cellulose synthase (Ca_Kabuli_CesA3) gene regulating high pod and seed number/plant (explaining 47% phenotypic variation) in chickpea. The up-regulation of this superior gene haplotype correlated with increased transcript expression of Ca_Kabuli_CesA3 gene in the pollen and pod of high pod/seed number accession, resulting in higher cellulose accumulation for normal pollen and pollen tube growth. A rapid combinatorial genome-wide SNP genotyping-based approach has potential to dissect complex quantitative agronomic traits and delineate trait-regulatory genomic loci (candidate genes) for genetic enhancement in crop plants, including chickpea.

Genome-wide indel markers shared by diverse Asian rice cultivars compared to Japanese rice cultivar 'Koshihikari'

Insertion-deletion (indel) polymorphisms, such as simple sequence repeats, have been widely used as DNA markers to identify QTLs and genes and to facilitate rice breeding. Recently, next-generation sequencing has produced deep sequences that allow genome-wide detection of indels. These polymorphisms can potentially be used to develop high-accuracy polymerase chain reaction (PCR)-based markers. Here, re-sequencing of 5 indica, 2 aus, and 3 tropical japonica cultivars and Japanese elite cultivar 'Koshihikari' was performed to extract regions containing large indels (10-51 bp) shared by diverse cultivars. To design indel markers for the discrimination of genomic regions between 'Koshihikari' and other diverse cultivars, we subtracted the indel regions detected in 'Koshihikari' from those shared in other cultivars. Two sets of indel markers, KNJ8-indel (shared in eight or more cultivars, including 'Khao Nam Jen' as a representative tropical japonica cultivar) and C5-indel (shared in five to eight cultivars), were established, with 915 and 9,899 indel regions, respectively. Validation of the two marker sets by using 23 diverse cultivars showed a high PCR success rate (≥95%) for 83.3% of the KNJ8-indel markers and 73.9% of the C5-indel markers. The marker sets will therefore be useful for the effective breeding of Japanese rice cultivars.

Construction of High Density Sweet Cherry (Prunus avium L.) Linkage Maps Using Microsatellite Markers and SNPs Detected by Genotyping-by-Sequencing (GBS)

Linkage maps are valuable tools in genetic and genomic studies. For sweet cherry, linkage maps have been constructed using mainly microsatellite markers (SSRs) and, recently, using single nucleotide polymorphism markers (SNPs) from a cherry 6K SNP array. Genotyping-by-sequencing (GBS), a new methodology based on high-throughput sequencing, holds great promise for identification of high number of SNPs and construction of high density linkage maps. In this study, GBS was used to identify SNPs from an intra-specific sweet cherry cross. A total of 8,476 high quality SNPs were selected for mapping. The physical position for each SNP was determined using the peach genome, Peach v1.0, as reference, and a homogeneous distribution of markers along the eight peach scaffolds was obtained. On average, 65.6% of the SNPs were present in genic regions and 49.8% were located in exonic regions. In addition to the SNPs, a group of SSRs was also used for construction of linkage maps. Parental and consensus high density maps were constructed by genotyping 166 siblings from a ‘Rainier’ x ‘Rivedel’ (Ra x Ri) cross. Using Ra x Ri population, 462, 489 and 985 markers were mapped into eight linkage groups in ‘Rainier’, ‘Rivedel’ and the Ra x Ri map, respectively, with 80% of mapped SNPs located in genic regions. Obtained maps spanned 549.5, 582.6 and 731.3 cM for ‘Rainier’, ‘Rivedel’ and consensus maps, respectively, with an average distance of 1.2 cM between adjacent markers for both ‘Rainier’ and ‘Rivedel’ maps and of 0.7 cM for Ra x Ri map. High synteny and co-linearity was observed between obtained maps and with Peach v1.0. These new high density linkage maps provide valuable information on the sweet cherry genome, and serve as the basis for identification of QTLs and genes relevant for the breeding of the species.

Ultra-high density intra-specific genetic linkage maps accelerate identification of functionally relevant molecular tags governing important agronomic traits in chickpea

We discovered 26785 and 16573 high-quality SNPs differentiating two parental genotypes of a RIL mapping population using reference desi and kabuli genome-based GBS assay. Of these, 3625 and 2177 SNPs have been integrated into eight desi and kabuli chromosomes, respectively in order to construct ultra-high density (0.20-0.37 cM) intra-specific chickpea genetic linkage maps. One of these constructed high-resolution genetic map has potential to identify 33 major genomic regions harbouring 35 robust QTLs (PVE: 17.9-39.7%) associated with three agronomic traits, which were mapped within <1 cM mean marker intervals on desi chromosomes. The extended LD (linkage disequilibrium) decay (~15 cM) in chromosomes of genetic maps have encouraged us to use a rapid integrated approach (comparative QTL mapping, QTL-region specific haplotype/LD-based trait association analysis, expression profiling and gene haplotype-based association mapping) rather than a traditional QTL map-based cloning method to narrow-down one major seed weight (SW) robust QTL region. It delineated favourable natural allelic variants and superior haplotype-containing one seed-specific candidate embryo defective gene regulating SW in chickpea. The ultra-high-resolution genetic maps, QTLs/genes and alleles/haplotypes-related genomic information generated and integrated strategy for rapid QTL/gene identification developed have potential to expedite genomics-assisted breeding applications in crop plants, including chickpea for their genetic enhancement.

Deploying QTL-seq for rapid delineation of a potential candidate gene underlying major trait-associated QTL in chickpea

A rapid high-resolution genome-wide strategy for molecular mapping of major QTL(s)/gene(s) regulating important agronomic traits is vital for in-depth dissection of complex quantitative traits and genetic enhancement in chickpea. The present study for the first time employed a NGS-based whole-genome QTL-seq strategy to identify one major genomic region harbouring a robust 100-seed weight QTL using an intra-specific 221 chickpea mapping population (desi cv. ICC 7184 × desi cv. ICC 15061). The QTL-seq-derived major SW QTL (CaqSW1.1) was further validated by single-nucleotide polymorphism (SNP) and simple sequence repeat (SSR) marker-based traditional QTL mapping (47.6% R² at higher LOD >19). This reflects the reliability and efficacy of QTL-seq as a strategy for rapid genome-wide scanning and fine mapping of major trait regulatory QTLs in chickpea. The use of QTL-seq and classical QTL mapping in combination narrowed down the 1.37 Mb (comprising 177 genes) major SW QTL (CaqSW1.1) region into a 35 kb genomic interval on desi chickpea chromosome 1 containing six genes. One coding SNP (G/A)-carrying constitutive photomorphogenic9 (COP9) signalosome complex subunit 8 (CSN8) gene of these exhibited seed-specific expression, including pronounced differential up-/down-regulation in low and high seed weight mapping parents and homozygous individuals during seed development. The coding SNP mined in this potential seed weight-governing candidate CSN8 gene was found to be present exclusively in all cultivated species/genotypes, but not in any wild species/genotypes of primary, secondary and tertiary gene pools. This indicates the effect of strong artificial and/or natural selection pressure on target SW locus during chickpea domestication. The proposed QTL-seq-driven integrated genome-wide strategy has potential to delineate major candidate gene(s) harbouring a robust trait regulatory QTL rapidly with optimal use of resources. This will further assist us to extrapolate the molecular mechanism underlying complex quantitative traits at a genome-wide scale leading to fast-paced marker-assisted genetic improvement in diverse crop plants, including chickpea.

Employing genome-wide SNP discovery and genotyping strategy to extrapolate the natural allelic diversity and domestication patterns in chickpea

The genome-wide discovery and high-throughput genotyping of SNPs in chickpea natural germplasm lines is indispensable to extrapolate their natural allelic diversity, domestication, and linkage disequilibrium (LD) patterns leading to the genetic enhancement of this vital legume crop. We discovered 44,844 high-quality SNPs by sequencing of 93 diverse cultivated desi, kabuli, and wild chickpea accessions using reference genome- and de novo-based GBS (genotyping-by-sequencing) assays that were physically mapped across eight chromosomes of desi and kabuli. Of these, 22,542 SNPs were structurally annotated in different coding and non-coding sequence components of genes. Genes with 3296 non-synonymous and 269 regulatory SNPs could functionally differentiate accessions based on their contrasting agronomic traits. A high experimental validation success rate (92%) and reproducibility (100%) along with strong sensitivity (93-96%) and specificity (99%) of GBS-based SNPs was observed. This infers the robustness of GBS as a high-throughput assay for rapid large-scale mining and genotyping of genome-wide SNPs in chickpea with sub-optimal use of resources. With 23,798 genome-wide SNPs, a relatively high intra-specific polymorphic potential (49.5%) and broader molecular diversity (13-89%)/functional allelic diversity (18-77%) was apparent among 93 chickpea accessions, suggesting their tremendous applicability in rapid selection of desirable diverse accessions/inter-specific hybrids in chickpea crossbred varietal improvement program. The genome-wide SNPs revealed complex admixed domestication pattern, extensive LD estimates (0.54-0.68) and extended LD decay (400-500 kb) in a structured population inclusive of 93 accessions. These findings reflect the utility of our identified SNPs for subsequent genome-wide association study (GWAS) and selective sweep-based domestication trait dissection analysis to identify potential genomic loci (gene-associated targets) specifically regulating important complex quantitative agronomic traits in chickpea. The numerous informative genome-wide SNPs, natural allelic diversity-led domestication pattern, and LD-based information generated in our study have got multidimensional applicability with respect to chickpea genomics-assisted breeding.

Classification and characterization of species within the genus lens using genotyping-by-sequencing (GBS)

Lentil (Lens culinaris ssp. culinaris) is a nutritious and affordable pulse with an ancient crop domestication history. The genus Lens consists of seven taxa, however, there are many discrepancies in the taxon and gene pool classification of lentil and its wild relatives. Due to the narrow genetic basis of cultivated lentil, there is a need towards better understanding of the relationships amongst wild germplasm to assist introgression of favourable genes into lentil breeding programs. Genotyping-by-sequencing (GBS) is an easy and affordable method that allows multiplexing of up to 384 samples or more per library to generate genome-wide single nucleotide Polymorphism (SNP) markers. In this study, we aimed to characterize our lentil germplasm collection using a two-enzyme GBS approach. We constructed two 96-plex GBS libraries with a total of 60 accessions where some accessions had several samples and each sample was sequenced in two technical replicates. We developed an automated GBS pipeline and detected a total of 266,356 genome-wide SNPs. After filtering low quality and redundant SNPs based on haplotype information, we constructed a maximum-likelihood tree using 5,389 SNPs. The phylogenetic tree grouped the germplasm collection into their respective taxa with strong support. Based on phylogenetic tree and STRUCTURE analysis, we identified four gene pools, namely L. culinaris/L. orientalis/L. tomentosus, L. lamottei/L. odemensis, L. ervoides and L. nigricans which form primary, secondary, tertiary and quaternary gene pools, respectively. We discovered sequencing bias problems likely due to DNA quality and observed severe run-to-run variation in the wild lentils. We examined the authenticity of the germplasm collection and identified 17% misclassified samples. Our study demonstrated that GBS is a promising and affordable tool for screening by plant breeders interested in crop wild relatives.

Genome-wide association mapping for yield and other agronomic traits in an elite breeding population of tropical rice (Oryza sativa)

Genome-wide association mapping studies (GWAS) are frequently used to detect QTL in diverse collections of crop germplasm, based on historic recombination events and linkage disequilibrium across the genome. Generally, diversity panels genotyped with high density SNP panels are utilized in order to assay a wide range of alleles and haplotypes and to monitor recombination breakpoints across the genome. By contrast, GWAS have not generally been performed in breeding populations. In this study we performed association mapping for 19 agronomic traits including yield and yield components in a breeding population of elite irrigated tropical rice breeding lines so that the results would be more directly applicable to breeding than those from a diversity panel. The population was genotyped with 71,710 SNPs using genotyping-by-sequencing (GBS), and GWAS performed with the explicit goal of expediting selection in the breeding program. Using this breeding panel we identified 52 QTL for 11 agronomic traits, including large effect QTLs for flowering time and grain length/grain width/grain-length-breadth ratio. We also identified haplotypes that can be used to select plants in our population for short stature (plant height), early flowering time, and high yield, and thus demonstrate the utility of association mapping in breeding populations for informing breeding decisions. We conclude by exploring how the newly identified significant SNPs and insights into the genetic architecture of these quantitative traits can be leveraged to build genomic-assisted selection models.

A genetic map of cassava (Manihot esculenta Crantz) with integrated physical mapping of immunity-related genes

BACKGROUND

Cassava, Manihot esculenta Crantz, is one of the most important crops world-wide representing the staple security for more than one billion of people. The development of dense genetic and physical maps, as the basis for implementing genetic and molecular approaches to accelerate the rate of genetic gains in breeding program represents a significant challenge. A reference genome sequence for cassava has been made recently available and community efforts are underway for improving its quality. Cassava is threatened by several pathogens, but the mechanisms of defense are far from being understood. Besides, there has been a lack of information about the number of genes related to immunity as well as their distribution and genomic organization in the cassava genome.

RESULTS

A high dense genetic map of cassava containing 2,141 SNPs has been constructed. Eighteen linkage groups were resolved with an overall size of 2,571 cM and an average distance of 1.26 cM between markers. More than half of mapped SNPs (57.4%) are located in coding sequences. Physical mapping of scaffolds of cassava whole genome sequence draft using the mapped markers as anchors resulted in the orientation of 687 scaffolds covering 45.6% of the genome. One hundred eighty nine new scaffolds are anchored to the genetic cassava map leading to an extension of the present cassava physical map with 30.7 Mb. Comparative analysis using anchor markers showed strong co-linearity to previously reported cassava genetic and physical maps. In silico based searching for conserved domains allowed the annotation of a repertory of 1,061 cassava genes coding for immunity-related proteins (IRPs). Based on physical map of the corresponding sequencing scaffolds, unambiguous genetic localization was possible for 569 IRPs.

CONCLUSIONS

This is the first study reported so far of an integrated high density genetic map using SNPs with integrated genetic and physical localization of newly annotated immunity related genes in cassava. These data build a solid basis for future studies to map and associate markers with single loci or quantitative trait loci for agronomical important traits. The enrichment of the physical map with novel scaffolds is in line with the efforts of the cassava genome sequencing consortium.

Genomic selection and association mapping in rice (Oryza sativa): effect of trait genetic architecture, training population composition, marker number and statistical model on accuracy of rice genomic selection in elite, tropical rice breeding lines

Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline.

Characterization of a panel of Vietnamese rice varieties using DArT and SNP markers for association mapping purposes

BACKGROUND

The development of genome-wide association studies (GWAS) in crops has made it possible to mine interesting alleles hidden in gene bank resources. However, only a small fraction of the rice genetic diversity of any given country has been exploited in the studies with worldwide sampling conducted to date. This study presents the development of a panel of rice varieties from Vietnam for GWAS purposes.

RESULTS

The panel, initially composed of 270 accessions, was characterized for simple agronomic traits (maturity class, grain shape and endosperm type) commonly used to classify rice varieties. We first genotyped the panel using Diversity Array Technology (DArT) markers. We analyzed the panel structure, identified two subpanels corresponding to the indica and japonica sub-species and selected 182 non-redundant accessions. However, the number of usable DArT markers (241 for an initial library of 6444 clones) was too small for GWAS purposes. Therefore, we characterized the panel of 182 accessions with 25,971 markers using genotyping by sequencing. The same indica and japonica subpanels were identified. The indica subpanel was further divided into six populations (I1 to I6) using a model-based approach. The japonica subpanel, which was more highly differentiated, was divided into 4 populations (J1 to J4), including a temperate type (J2). Passport data and phenotypic traits were used to characterize these populations. Some populations were exclusively composed of glutinous types (I3 and J2). Some of the upland rice varieties appeared to belong to indica populations, which is uncommon in this region of the world. Linkage disequilibrium decayed faster in the indica subpanel (r2 below 0.2 at 101 kb) than in the japonica subpanel (r2 below 0.2 at 425 kb), likely because of the strongest differentiation of the japonica subpanel. A matrix adapted for GWAS was built by eliminating the markers with a minor allele frequency below 5% and imputing the missing data. This matrix contained 21,814 markers. A GWAS was conducted on time to flowering to prove the utility of this panel.

CONCLUSIONS

This publicly available panel constitutes an important resource giving access to original allelic diversity. It will be used for GWAS on root and panicle traits.

To grow or not to grow: a stressful decision for plants

Progress in improving abiotic stress tolerance of crop plants using classic breeding and selection approaches has been slow. This has generally been blamed on the lack of reliable traits and phenotyping methods for stress tolerance. In crops, abiotic stress tolerance is most often measured in terms of yield-capacity under adverse weather conditions. "Yield" is a complex trait and is determined by growth and developmental processes which are controlled by environmental signals throughout the life cycle of the plant. The use of model systems has allowed us to gradually unravel how plants grow and develop, but our understanding of the flexibility and opportunistic nature of plant development and its capacity to adapt growth to environmental cues is still evolving. There is genetic variability for the capacity to maintain yield and productivity under abiotic stress conditions in crop plants such as cereals. Technological progress in various domains has made it increasingly possible to mine that genetic variability and develop a better understanding about the basic mechanism of plant growth and abiotic stress tolerance. The aim of this paper is not to give a detailed account of all current research progress, but instead to highlight some of the current research trends that may ultimately lead to strategies for stress-proofing crop species. The focus will be on abiotic stresses that are most often associated with climate change (drought, heat and cold) and those crops that are most important for human nutrition, the cereals.

Flexible and scalable genotyping-by-sequencing strategies for population studies

BACKGROUND

Many areas critical to agricultural production and research, such as the breeding and trait mapping in plants and livestock, require robust and scalable genotyping platforms. Genotyping-by-sequencing (GBS) is a one such method highly suited to non-human organisms. In the GBS protocol, genomic DNA is fractionated via restriction digest, then reduced representation is achieved through size selection. Since many restriction sites are conserved across a species, the sequenced portion of the genome is highly consistent within a population. This makes the GBS protocol highly suited for experiments that require surveying large numbers of markers within a population, such as those involving genetic mapping, breeding, and population genomics. We have modified the GBS technology in a number of ways. Custom, enzyme specific adaptors have been replaced with standard Illumina adaptors compatible with blunt-end restriction enzymes. Multiplexing is achieved through a dual barcoding system, and bead-based library preparation protocols allows for in-solution size selection and eliminates the need for columns and gels.

RESULTS

A panel of eight restriction enzymes was selected for testing on B73 maize and Nipponbare rice genomic DNA. Quality of the data was demonstrated by identifying that the vast majority of reads from each enzyme aligned to restriction sites predicted in silico. The link between enzyme parameters and experimental outcome was demonstrated by showing that the sequenced portion of the genome was adaptable by selecting enzymes based on motif length, complexity, and methylation sensitivity. The utility of the new GBS protocol was demonstrated by correctly mapping several in a maize F2 population resulting from a B73×Country Gentleman test cross.

CONCLUSIONS

This technology is readily adaptable to different genomes, highly amenable to multiplexing and compatible with over forty commercially available restriction enzymes. These advancements represent a major improvement in genotyping technology by providing a highly flexible and scalable GBS that is readily implemented for studies on genome-wide variation.

Flexible and scalable genotyping-by-sequencing strategies for population studies

Background

Many areas critical to agricultural production and research, such as the breeding and trait mapping in plants and livestock, require robust and scalable genotyping platforms. Genotyping-by-sequencing (GBS) is a one such method highly suited to non-human organisms. In the GBS protocol, genomic DNA is fractionated via restriction digest, then reduced representation is achieved through size selection. Since many restriction sites are conserved across a species, the sequenced portion of the genome is highly consistent within a population. This makes the GBS protocol highly suited for experiments that require surveying large numbers of markers within a population, such as those involving genetic mapping, breeding, and population genomics. We have modified the GBS technology in a number of ways. Custom, enzyme specific adaptors have been replaced with standard Illumina adaptors compatible with blunt-end restriction enzymes. Multiplexing is achieved through a dual barcoding system, and bead-based library preparation protocols allows for in-solution size selection and eliminates the need for columns and gels.

Results

A panel of eight restriction enzymes was selected for testing on B73 maize and Nipponbare rice genomic DNA. Quality of the data was demonstrated by identifying that the vast majority of reads from each enzyme aligned to restriction sites predicted in silico. The link between enzyme parameters and experimental outcome was demonstrated by showing that the sequenced portion of the genome was adaptable by selecting enzymes based on motif length, complexity, and methylation sensitivity. The utility of the new GBS protocol was demonstrated by correctly mapping several in a maize F₂ population resulting from a B73 × Country Gentleman test cross.

Conclusions

This technology is readily adaptable to different genomes, highly amenable to multiplexing and compatible with over forty commercially available restriction enzymes. These advancements represent a major improvement in genotyping technology by providing a highly flexible and scalable GBS that is readily implemented for studies on genome-wide variation.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-979) contains supplementary material, which is available to authorized users.

Expanding frontiers in plant transcriptomics in aid of functional genomics and molecular breeding

The transcript pool of a plant part, under any given condition, is a collection of mRNAs that will pave the way for a biochemical reaction of the plant to stimuli. Over the past decades, transcriptome study has advanced from Northern blotting to RNA sequencing (RNA-seq), through other techniques, of which real-time quantitative polymerase chain reaction (PCR) and microarray are the most significant ones. The questions being addressed by such studies have also matured from a solitary process to expression atlas and marker-assisted genetic enhancement. Not only genes and their networks involved in various developmental processes of plant parts have been elucidated, but also stress tolerant genes have been highlighted. The transcriptome of a plant with altered expression of a target gene has given information about the downstream genes. Marker information has been used for breeding improved varieties. Fortunately, the data generated by transcriptome analysis has been made freely available for ample utilization and comparison. The review discusses this wide variety of transcriptome data being generated in plants, which includes developmental stages, abiotic and biotic stress, effect of altered gene expression, as well as comparative transcriptomics, with a special emphasis on microarray and RNA-seq. Such data can be used to determine the regulatory gene networks, which can subsequently be utilized for generating improved plant varieties.

Genotyping-by-sequencing (GBS), an ultimate marker-assisted selection (MAS) tool to accelerate plant breeding

Marker-assisted selection (MAS) refers to the use of molecular markers to assist phenotypic selections in crop improvement. Several types of molecular markers, such as single nucleotide polymorphism (SNP), have been identified and effectively used in plant breeding. The application of next-generation sequencing (NGS) technologies has led to remarkable advances in whole genome sequencing, which provides ultra-throughput sequences to revolutionize plant genotyping and breeding. To further broaden NGS usages to large crop genomes such as maize and wheat, genotyping-by-sequencing (GBS) has been developed and applied in sequencing multiplexed samples that combine molecular marker discovery and genotyping. GBS is a novel application of NGS protocols for discovering and genotyping SNPs in crop genomes and populations. The GBS approach includes the digestion of genomic DNA with restriction enzymes followed by the ligation of barcode adapter, PCR amplification and sequencing of the amplified DNA pool on a single lane of flow cells. Bioinformatic pipelines are needed to analyze and interpret GBS datasets. As an ultimate MAS tool and a cost-effective technique, GBS has been successfully used in implementing genome-wide association study (GWAS), genomic diversity study, genetic linkage analysis, molecular marker discovery and genomic selection under a large scale of plant breeding programs.

A saturated genetic linkage map of autotetraploid alfalfa (Medicago sativa L.) developed using genotyping-by-sequencing is highly syntenous with the Medicago truncatula genome

A genetic linkage map is a valuable tool for quantitative trait locus mapping, map-based gene cloning, comparative mapping, and whole-genome assembly. Alfalfa, one of the most important forage crops in the world, is autotetraploid, allogamous, and highly heterozygous, characteristics that have impeded the construction of a high-density linkage map using traditional genetic marker systems. Using genotyping-by-sequencing (GBS), we constructed low-cost, reasonably high-density linkage maps for both maternal and paternal parental genomes of an autotetraploid alfalfa F₁ population. The resulting maps contain 3591 single-nucleotide polymorphism markers on 64 linkage groups across both parents, with an average density of one marker per 1.5 and 1.0 cM for the maternal and paternal haplotype maps, respectively. Chromosome assignments were made based on homology of markers to the M. truncatula genome. Four linkage groups representing the four haplotypes of each alfalfa chromosome were assigned to each of the eight Medicago chromosomes in both the maternal and paternal parents. The alfalfa linkage groups were highly syntenous with M. truncatula, and clearly identified the known translocation between Chromosomes 4 and 8. In addition, a small inversion on Chromosome 1 was identified between M. truncatula and M. sativa. GBS enabled us to develop a saturated linkage map for alfalfa that greatly improved genome coverage relative to previous maps and that will facilitate investigation of genome structure. GBS could be used in breeding populations to accelerate molecular breeding in alfalfa.

Next-generation sequencing based genotyping, cytometry and phenotyping for understanding diversity and evolution of Guinea yams

Genotyping by sequencing (GBS) is used to understand the origin and domestication of guinea yams, including the contribution of wild relatives and polyploidy events to the cultivated guinea yams. Patterns of genetic diversity within and between two cultivated guinea yams (Dioscorea rotundata and D. cayenensis) and five wild relatives (D. praehensilis, D. mangenotiana, D. abyssinica, D. togoensis and D. burkilliana) were investigated using next-generation sequencing (genotyping by sequencing, GBS). Additionally, the two cultivated species were assessed for intra-specific morphological and ploidy variation. In guinea yams, ploidy level is correlated with species identity. Using flow cytometry a single ploidy level was inferred across D. cayenensis (3x, N = 21), D. praehensilis (2x, N = 7), and D. mangenotiana (3x, N = 5) accessions, whereas both diploid and triploid (or aneuploid) accessions were present in D. rotundata (N = 11 and N = 32, respectively). Multi-dimensional scaling and maximum parsimony analyses of 2,215 SNPs revealed that wild guinea yam populations form discrete genetic groupings according to species. D. togoensis and D. burkilliana were most distant from the two cultivated yam species, whereas D. abyssinica, D. mangenotiana, and D. praehensilis were closest to cultivated yams. In contrast, cultivated species were genetically less clearly defined at the intra-specific level. While D. cayenensis formed a single genetic group, D. rotundata comprised three separate groups consisting of; (1) a set of diploid individuals genetically similar to D. praehensilis, (2) a set of diploid individuals genetically similar to D. cayenensis, and (3) a set of triploid individuals. The current study demonstrates the utility of GBS for assessing yam genomic diversity. Combined with morphological and biological data, GBS provides a powerful tool for testing hypotheses regarding the evolution, domestication and breeding of guinea yams.

SNPs in genes functional in starch-sugar interconversion associate with natural variation of tuber starch and sugar content of potato (Solanum tuberosum L.)

Starch accumulation and breakdown are vital processes in plant storage organs such as seeds, roots, and tubers. In tubers of potato (Solanum tuberosum L.) a small fraction of starch is converted into the reducing sugars glucose and fructose. Reducing sugars accumulate in response to cold temperatures. Even small quantities of reducing sugars affect negatively the quality of processed products such as chips and French fries. Tuber starch and sugar content are inversely correlated complex traits that are controlled by multiple genetic and environmental factors. Based on in silico annotation of the potato genome sequence, 123 loci are involved in starch-sugar interconversion, approximately half of which have been previously cloned and characterized. By means of candidate gene association mapping, we identified single-nucleotide polymorphisms (SNPs) in eight genes known to have key functions in starch-sugar interconversion, which were diagnostic for increased tuber starch and/or decreased sugar content and vice versa. Most positive or negative effects of SNPs on tuber-reducing sugar content were reproducible in two different collections of potato cultivars. The diagnostic SNP markers are useful for breeding applications. An allele of the plastidic starch phosphorylase PHO1a associated with increased tuber starch content was cloned as full-length cDNA and characterized. The PHO1a-HA allele has several amino acid changes, one of which is unique among all known starch/glycogen phosphorylases. This mutation might cause reduced enzyme activity due to impaired formation of the active dimers, thereby limiting starch breakdown.

Using genotyping-by-sequencing (GBS) for genomic discovery in cultivated oat

Advances in next-generation sequencing offer high-throughput and cost-effective genotyping alternatives, including genotyping-by-sequencing (GBS). Results have shown that this methodology is efficient for genotyping a variety of species, including those with complex genomes. To assess the utility of GBS in cultivated hexaploid oat (Avena sativa L.), seven bi-parental mapping populations and diverse inbred lines from breeding programs around the world were studied. We examined technical factors that influence GBS SNP calls, established a workflow that combines two bioinformatics pipelines for GBS SNP calling, and provided a nomenclature for oat GBS loci. The high-throughput GBS system enabled us to place 45,117 loci on an oat consensus map, thus establishing a positional reference for further genomic studies. Using the diversity lines, we estimated that a minimum density of one marker per 2 to 2.8 cM would be required for genome-wide association studies (GWAS), and GBS markers met this density requirement in most chromosome regions. We also demonstrated the utility of GBS in additional diagnostic applications related to oat breeding. We conclude that GBS is a powerful and useful approach, which will have many additional applications in oat breeding and genomic studies.

Fast and cost-effective genetic mapping in apple using next-generation sequencing

Next-generation DNA sequencing (NGS) produces vast amounts of DNA sequence data, but it is not specifically designed to generate data suitable for genetic mapping. Recently developed DNA library preparation methods for NGS have helped solve this problem, however, by combining the use of reduced representation libraries with DNA sample barcoding to generate genome-wide genotype data from a common set of genetic markers across a large number of samples. Here we use such a method, called genotyping-by-sequencing (GBS), to produce a data set for genetic mapping in an F1 population of apples (Malus × domestica) segregating for skin color. We show that GBS produces a relatively large, but extremely sparse, genotype matrix: over 270,000 SNPs were discovered but most SNPs have too much missing data across samples to be useful for genetic mapping. After filtering for genotype quality and missing data, only 6% of the 85 million DNA sequence reads contributed to useful genotype calls. Despite this limitation, using existing software and a set of simple heuristics, we generated a final genotype matrix containing 3967 SNPs from 89 DNA samples from a single lane of Illumina HiSeq and used it to create a saturated genetic linkage map and to identify a known QTL underlying apple skin color. We therefore demonstrate that GBS is a cost-effective method for generating genome-wide SNP data suitable for genetic mapping in a highly diverse and heterozygous agricultural species. We anticipate future improvements to the GBS analysis pipeline presented here that will enhance the utility of next-generation DNA sequence data for the purposes of genetic mapping across diverse species.

An ultra-high density bin-map for rapid QTL mapping for tassel and ear architecture in a large F₂ maize population

Background

Understanding genetic control of tassel and ear architecture in maize (Zea mays L. ssp. mays) is important due to their relationship with grain yield. High resolution QTL mapping is critical for understanding the underlying molecular basis of phenotypic variation. Advanced populations, such as recombinant inbred lines, have been broadly adopted for QTL mapping; however, construction of large advanced generation crop populations is time-consuming and costly. The rapidly declining cost of genotyping due to recent advances in next-generation sequencing technologies has generated new possibilities for QTL mapping using large early generation populations.

Results

A set of 708 F₂ progeny derived from inbreds Chang7-2 and 787 were generated and genotyped by whole genome low-coverage genotyping-by-sequencing method (average 0.04×). A genetic map containing 6,533 bin-markers was constructed based on the parental SNPs and a sliding-window method, spanning a total genetic distance of 1,396 cM. The high quality and accuracy of this map was validated by the identification of two well-studied genes, r1, a qualitative trait locus for color of silk (chromosome 10) and ba1 for tassel branch number (chromosome 3). Three traits of tassel and ear architecture were evaluated in this population, a total of 10 QTL were detected using a permutation-based-significance threshold, seven of which overlapped with reported QTL. Three genes (GRMZM2G316366, GRMZM2G492156 and GRMZM5G805008) encoding MADS-box domain proteins and a BTB/POZ domain protein were located in the small intervals of qTBN5 and qTBN7 (~800 Kb and 1.6 Mb in length, respectively) and may be involved in patterning of tassel architecture. The small physical intervals of most QTL indicate high-resolution mapping is obtainable with this method.

Conclusions

We constructed an ultra-high-dentisy linkage map for the large early generation population in maize. Our study provides an efficient approach for fast detection of quantitative loci responsible for complex trait variation with high accuracy, thus helping to dissect the underlying molecular basis of phenotypic variation and accelerate improvement of crop breeding in a cost-effective fashion.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-433) contains supplementary material, which is available to authorized users.

High-Resolution Inflorescence Phenotyping Using a Novel Image-Analysis Pipeline, PANorama

Variation in inflorescence development is an important target of selection for numerous crop species, including many members of the Poaceae (grasses). In Asian rice (Oryza sativa), inflorescence (panicle) architecture is correlated with yield and grain-quality traits. However, many rice breeders continue to use composite phenotypes in selection pipelines, because measuring complex, branched panicles requires a significant investment of resources. We developed an open-source phenotyping platform, PANorama, which measures multiple architectural and branching phenotypes from images simultaneously. PANorama automatically extracts skeletons from images, allows users to subdivide axes into individual internodes, and thresholds away structures, such as awns, that normally interfere with accurate panicle phenotyping. PANorama represents an improvement in both efficiency and accuracy over existing panicle imaging platforms, and flexible implementation makes PANorama capable of measuring a range of organs from other plant species. Using high-resolution phenotypes, a mapping population of recombinant inbred lines, and a dense single-nucleotide polymorphism data set, we identify, to our knowledge, the largest number of quantitative trait loci (QTLs) for panicle traits ever reported in a single study. Several areas of the genome show pleiotropic clusters of panicle QTLs, including a region near the rice Green Revolution gene SEMIDWARF1. We also confirm that multiple panicle phenotypes are distinctly different among a small collection of diverse rice varieties. Taken together, these results suggest that clusters of small-effect QTLs may be responsible for varietal or subpopulation-specific panicle traits, representing a significant opportunity for rice breeders selecting for yield performance across different genetic backgrounds.

Biparental resequencing coupled with SNP genotyping of a segregating population offers insights into the landscape of recombination and fixed genomic regions in elite soybean

Identification of genes underlying agronomic traits is dependent on the segregation of quantitative trait loci (QTL). A popular hypothesis is that elite lines are becoming increasingly similar to each other, resulting in large genomic regions with fixed genes. Here, we resequenced two parental modern elite soybean lines [ZhongHuang13 (ZH) and ZhongPin03-5373 (ZP)] and discovered 794,876 SNPs with reference to the published Williams82 genome. SNPs were distributed unevenly across the chromosomes, with 87.1% of SNPs clustering in 4.9% of the soybean reference genome. Most of the regions with a high density of SNP polymorphisms were located in the chromosome arms. Moreover, seven large regions that were highly similar between parental lines were identified. A GoldenGate SNP genotyping array was designed using 384 SNPs and the 254 recombinant inbred lines (F8) derived from the cross of ZP × ZH were genotyped. We constructed a genetic linkage map using a total of 485 molecular markers, including 313 SNPs from the array, 167 simple sequence repeats (SSRs), 4 expressed sequence tag-derived SSRs, and 1 insertion/deletion marker. The total length of the genetic map was 2594.34 cM, with an average marker spacing of 5.58 cM. Comparing physical and genetic distances, we found 20 hotspot and 14 coldspot regions of recombination. Our results suggest that the technology of resequencing of parental lines coupled with high-throughput SNP genotyping could efficiently bridge the genotyping gap and provide deep insights into the landscape of recombination and fixed genomic regions in biparental segregating populations of soybean with implications for fine mapping of QTL.

Reduced representation approaches to interrogate genome diversity in large repetitive plant genomes

Technology and software improvements in the last decade now provide methodologies to access the genome sequence of not only a single accession, but also multiple accessions of plant species. This provides a means to interrogate species diversity at the genome level. Ample diversity among accessions in a collection of species can be found, including single-nucleotide polymorphisms, insertions and deletions, copy number variation and presence/absence variation. For species with small, non-repetitive rich genomes, re-sequencing of query accessions is robust, highly informative, and economically feasible. However, for species with moderate to large sized repetitive-rich genomes, technical and economic barriers prevent en masse genome re-sequencing of accessions. Multiple approaches to access a focused subset of loci in species with larger genomes have been developed, including reduced representation sequencing, exome capture and transcriptome sequencing. Collectively, these approaches have enabled interrogation of diversity on a genome scale for large plant genomes, including crop species important to worldwide food security.

Genotyping-by-sequencing (GBS), an ultimate marker-assisted selection (MAS) tool to accelerate plant breeding

Marker-assisted selection (MAS) refers to the use of molecular markers to assist phenotypic selections in crop improvement. Several types of molecular markers, such as single nucleotide polymorphism (SNP), have been identified and effectively used in plant breeding. The application of next-generation sequencing (NGS) technologies has led to remarkable advances in whole genome sequencing, which provides ultra-throughput sequences to revolutionize plant genotyping and breeding. To further broaden NGS usages to large crop genomes such as maize and wheat, genotyping-by-sequencing (GBS) has been developed and applied in sequencing multiplexed samples that combine molecular marker discovery and genotyping. GBS is a novel application of NGS protocols for discovering and genotyping SNPs in crop genomes and populations. The GBS approach includes the digestion of genomic DNA with restriction enzymes followed by the ligation of barcode adapter, PCR amplification and sequencing of the amplified DNA pool on a single lane of flow cells. Bioinformatic pipelines are needed to analyze and interpret GBS datasets. As an ultimate MAS tool and a cost-effective technique, GBS has been successfully used in implementing genome-wide association study (GWAS), genomic diversity study, genetic linkage analysis, molecular marker discovery and genomic selection under a large scale of plant breeding programs.

A high-density SNP map for accurate mapping of seed fibre QTL in Brassica napus L

A high density genetic linkage map for the complex allotetraploid crop species Brassica napus (oilseed rape) was constructed in a late-generation recombinant inbred line (RIL) population, using genome-wide single nucleotide polymorphism (SNP) markers assayed by the Brassica 60 K Infinium BeadChip Array. The linkage map contains 9164 SNP markers covering 1832.9 cM. 1232 bins account for 7648 of the markers. A subset of 2795 SNP markers, with an average distance of 0.66 cM between adjacent markers, was applied for QTL mapping of seed colour and the cell wall fiber components acid detergent lignin (ADL), cellulose and hemicellulose. After phenotypic analyses across four different environments a total of 11 QTL were detected for seed colour and fiber traits. The high-density map considerably improved QTL resolution compared to the previous low-density maps. A previously identified major QTL with very high effects on seed colour and ADL was pinpointed to a narrow genome interval on chromosome A09, while a minor QTL explaining 8.1% to 14.1% of variation for ADL was detected on chromosome C05. Five and three QTL accounting for 4.7% to 21.9% and 7.3% to 16.9% of the phenotypic variation for cellulose and hemicellulose, respectively, were also detected. To our knowledge this is the first description of QTL for seed cellulose and hemicellulose in B. napus, representing interesting new targets for improving oil content. The high density SNP genetic map enables navigation from interesting B. napus QTL to Brassica genome sequences, giving useful new information for understanding the genetics of key seed quality traits in rapeseed.