SNP identification and marker assay development for high-throughput selection of soybean cyst nematode resistance

Background

Soybean cyst nematode (SCN) is the most economically devastating pathogen of soybean. Two resistance loci, Rhg1 and Rhg4 primarily contribute resistance to SCN race 3 in soybean. Peking and PI 88788 are the two major sources of SCN resistance with Peking requiring both Rhg1 and Rhg4 alleles and PI 88788 only the Rhg1 allele. Although simple sequence repeat (SSR) markers have been reported for both loci, they are linked markers and limited to be applied in breeding programs due to accuracy, throughput and cost of detection methods. The objectives of this study were to develop robust functional marker assays for high-throughput selection of SCN resistance and to differentiate the sources of resistance.

Results

Based on the genomic DNA sequences of 27 soybean lines with known SCN phenotypes, we have developed Kompetitive Allele Specific PCR (KASP) assays for two Single nucleotide polymorphisms (SNPs) from Glyma08g11490 for the selection of the Rhg4 resistance allele. Moreover, the genomic DNA of Glyma18g02590 at the Rhg1 locus from 11 soybean lines and cDNA of Forrest, Essex, Williams 82 and PI 88788 were fully sequenced. Pairwise sequence alignment revealed seven SNPs/insertion/deletions (InDels), five in the 6th exon and two in the last exon. Using the same 27 soybean lines, we identified one SNP that can be used to select the Rhg1 resistance allele and another SNP that can be employed to differentiate Peking and PI 88788-type resistance. These SNP markers have been validated and a strong correlation was observed between the SNP genotypes and reactions to SCN race 3 using a panel of 153 soybean lines, as well as a bi-parental population, F₅–derived recombinant inbred lines (RILs) from G00-3213 x LG04-6000.

Conclusions

Three functional SNP markers (two for Rhg1 locus and one for Rhg4 locus) were identified that could provide genotype information for the selection of SCN resistance and differentiate Peking from PI 88788 source for most germplasm lines. The robust KASP SNP marker assays were developed. In most contexts, use of one or two of these markers is sufficient for high-throughput marker-assisted selection of plants that will exhibit SCN resistance.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1531-3) contains supplementary material, which is available to authorized users.     

SNPs discovery and CAPS marker conversion in soybean

To discover new SNPs and develop an easy assay method in soybean, we compared the high-throughput pyrosequencing ESTs with whole genome sequences in different soybean varieties and identified 3899 SNPs. Transitions were found to be much more frequent than transversions in these SNPs. We found that SNPs were widely distributed in the soybean genome, targeting numerous genes involved in various physiological and biochemical processes influencing important agronomic traits. A set of 16 SNPs were validated in nine soybean varieties, and seven SNPs were converted into CAPS. From functional gene association analysis, the marker CAPS282 on the 3′-UTR of gene Glyma07g03490 was identified as associated with 100-seed weight in soybean. The SNP discovery and CAPS markers conversion system developed in this study is fast and cost effective, and holds great promise for molecular-assisted breeding of soybean.     

Fine mapping of the soybean aphid-resistance gene Rag2 in soybean PI 200538

The discovery of biotype diversity of soybean aphid (SA: Aphis glycines Matsumura) in North America emphasizes the necessity to identify new aphid-resistance genes. The soybean [Glycine max (L.) Merr.] plant introduction (PI) 200538 is a promising source of SA resistance because it shows a high level of resistance to a SA biotype that can overcome the SA-resistance gene Rag1 from ‘Dowling’. The SA-resistance gene Rag2 was previously mapped from PI 200538 to a 10-cM marker interval on soybean chromosome 13 [formerly linkage group (LG) F]. The objective of this study was to fine map Rag2. This fine mapping was carried out using lines derived from 5,783 F₂ plants at different levels of backcrossing that were screened with flanking genetic markers for the presence of recombination in the Rag2 interval. Fifteen single nucleotide polymorphism (SNP) markers and two dominant polymerase chain reaction-based markers near Rag2 were developed by re-sequencing target intervals and sequence-tagged sites. These efforts resulted in the mapping of Rag2 to a 54-kb interval on the Williams 82 8× assembly (Glyma1). This Williams 82 interval contains seven predicted genes, which includes one nucleotide-binding site-leucine-rich repeat gene. SNP marker and candidate gene information identified in this study will be an important resource in marker-assisted selection for aphid resistance and for cloning the gene.     

Fine mapping the soybean aphid resistance gene Rag1 in soybean

The soybean aphid (Aphis glycines Matsumura) is an important soybean [Glycine max (L.) Merr.] pest in North America. The dominant aphid resistance gene Rag1 was previously mapped from the cultivar ‘Dowling’ to a 12 cM marker interval on soybean chromosome 7 (formerly linkage group M). The development of additional genetic markers mapping closer to Rag1 was needed to accurately position the gene to improve the effectiveness of marker-assisted selection (MAS) and to eventually clone it. The objectives of this study were to identify single nucleotide polymorphisms (SNPs) near Rag1 and to position these SNPs relative to Rag1. To generate a fine map of the Rag1 interval, 824 BC₄F₂ and 1,000 BC₄F₃ plants segregating for the gene were screened with markers flanking Rag1. Plants with recombination events close to the gene were tested with SNPs identified in previous studies along with new SNPs identified from the preliminary Williams 82 draft soybean genome shotgun sequence using direct re-sequencing and gene-scanning melt-curve analysis. Progeny of these recombinant plants were evaluated for aphid resistance. These efforts resulted in the mapping of Rag1 between the two SNP markers 46169.7 and 21A, which corresponds to a physical distance on the Williams 82 8× draft assembly (Glyma1.01) of 115 kilobase pair (kb). Several candidate genes for Rag1 are present within the 115-kb interval. The markers identified in this study that are closely linked to Rag1 will be a useful resource in MAS for this important aphid resistance gene.     

Development,validation and genetic analysis of a large soybean SNP genotyping array

Cultivated soybean (Glycine max) suffers from a narrow germplasm relative to other crop species, probably because of under‐use of wild soybean (Glycine soja) as a breeding resource. Use of a single nucleotide polymorphism (SNP) genotyping array is a promising method for dissecting cultivated and wild germplasms to identify important adaptive genes through high‐density genetic mapping and genome‐wide association studies. Here we describe a large soybean SNP array for use in diversity analyses, linkage mapping and genome‐wide association analyses. More than four million high‐quality SNPs identified from high‐depth genome re‐sequencing of 16 soybean accessions and low‐depth genome re‐sequencing of 31 soybean accessions were used to select 180 961 SNPs for creation of the Axiom^® SoyaSNP array. Validation analysis for a set of 222 diverse soybean lines showed that 170 223 markers were of good quality for genotyping. Phylogenetic and allele frequency analyses of the validation set data indicated that accessions showing an intermediate morphology between cultivated and wild soybeans collected in Korea were natural hybrids. More than 90 unanchored scaffolds in the current soybean reference sequence were assigned to chromosomes using this array. Finally, dense average spacing and preferential distribution of the SNPs in gene‐rich chromosomal regions suggest that this array may be suitable for genome‐wide association studies of soybean germplasm. Taken together, these results suggest that use of this array may be a powerful method for soybean genetic analyses relating to many aspects of soybean breeding.     

High‐throughput SNP discovery in the rabbit (Oryctolagus cuniculus) genome by next‐generation semiconductor‐based sequencing

The European rabbit (Oryctolagus cuniculus) is a domesticated species with one of the broadest ranges of economic and scientific applications and fields of investigation. Rabbit genome information and assembly are available (oryCun2.0), but so far few studies have investigated its variability, and massive discovery of polymorphisms has not been published yet for this species. Here, we sequenced two reduced representation libraries (RRLs) to identify single nucleotide polymorphisms (SNPs) in the rabbit genome. Genomic DNA of 10 rabbits belonging to different breeds was pooled and digested with two restriction enzymes (HaeIII and RsaI) to create two RRLs which were sequenced using the Ion Torrent Personal Genome Machine. The two RRLs produced 2 917 879 and 4 046 871 reads, for a total of 280.51 Mb (248.49 Mb with quality >20) and 417.28 Mb (360.89 Mb with quality >20) respectively of sequenced DNA. About 90% and 91% respectively of the obtained reads were mapped on the rabbit genome, covering a total of 15.82% of the oryCun2.0 genome version. The mapping and ad hoc filtering procedures allowed to reliably call 62 491 SNPs. SNPs in a few genomic regions were validated by Sanger sequencing. The Variant Effect Predictor Web tool was used to map SNPs on the current version of the rabbit genome. The obtained results will be useful for many applied and basic research programs for this species and will contribute to the development of cost‐effective solutions for high‐throughput SNP genotyping in the rabbit.     

Development and mapping of SNP assays in allotetraploid cotton

A narrow germplasm base and a complex allotetraploid genome have made the discovery of single nucleotide polymorphism (SNP) markers difficult in cotton (Gossypium hirsutum). To generate sequence for SNP discovery, we conducted a genome reduction experiment (EcoRI, BafI double digest, followed by adapter ligation, biotin–streptavidin purification, and agarose gel separation) on two accessions of G. hirsutum and two accessions of G. barbadense. From the genome reduction experiment, a total of 2.04 million genomic sequence reads were assembled into contigs with an N₅₀ of 508 bp and analyzed for SNPs. A previously generated assembly of expressed sequence tags (ESTs) provided an additional source for SNP discovery. Using highly conservative parameters (minimum coverage of 8× at each SNP and 20% minor allele frequency), a total of 11,834 and 1,679 non-genic SNPs were identified between accessions of G. hirsutum and G. barbadense in genome reduction assemblies, respectively. An additional 4,327 genic SNPs were also identified between accessions of G. hirsutum in the EST assembly. KBioscience KASPar assays were designed for a portion of the intra-specific G. hirsutum SNPs. From 704 non-genic and 348 genic markers developed, a total of 367 (267 non-genic, 100 genic) mapped in a segregating F₂ population (Acala Maxxa × TX2094) using the Fluidigm EP1 system. A G. hirsutum genetic linkage map of 1,688 cM was constructed based entirely on these new SNP markers. Of the genic-based SNPs, we were able to identify within which genome (‘A’ or ‘D’) each SNP resided using diploid species sequence data. Genetic maps generated by these newly identified markers are being used to locate quantitative, economically important regions within the cotton genome.     

Development and Evaluation of SoySNP50K,a High-Density Genotyping Array for Soybean

The objective of this research was to identify single nucleotide polymorphisms (SNPs) and to develop an Illumina Infinium BeadChip that contained over 50,000 SNPs from soybean (Glycine max L. Merr.). A total of 498,921,777 reads 35–45bp in length were obtained from DNA sequence analysis of reduced representation libraries from several soybean accessions which included six cultivated and two wild soybean (G. soja Sieb. et Zucc.) genotypes. These reads were mapped to the soybean whole genome sequence and 209,903 SNPs were identified. After applying several filters, a total of 146,161 of the 209,903 SNPs were determined to be ideal candidates for Illumina Infinium II BeadChip design. To equalize the distance between selected SNPs, increase assay success rate, and minimize the number of SNPs with low minor allele frequency, an iteration algorithm based on a selection index was developed and used to select 60,800 SNPs for Infinium BeadChip design. Of the 60,800 SNPs, 50,701 were targeted to euchromatic regions and 10,000 to heterochromatic regions of the 20 soybean chromosomes. In addition, 99 SNPs were targeted to unanchored sequence scaffolds. Of the 60,800 SNPs, a total of 52,041 passed Illumina’s manufacturing phase to produce the SoySNP50K iSelect BeadChip. Validation of the SoySNP50K chip with 96 landrace genotypes, 96 elite cultivars and 96 wild soybean accessions showed that 47,337 SNPs were polymorphic and generated successful SNP allele calls. In addition, 40,841 of the 47,337 SNPs (86%) had minor allele frequencies ≥10% among the landraces, elite cultivars and the wild soybean accessions. A total of 620 and 42 candidate regions which may be associated with domestication and recent selection were identified, respectively. The SoySNP50K iSelect SNP beadchip will be a powerful tool for characterizing soybean genetic diversity and linkage disequilibrium, and for constructing high resolution linkage maps to improve the soybean whole genome sequence assembly.     

The discovery of novel SNPs associated with group A soyasaponin biosynthesis from Korea soybean core collection

Soyasaponin is a type of glycoside such as steroids, steroidal alkaloids or triterpenes, which enhance the body immunity. In order to efficiently identify genes and markers related to the soyasaponin, we used a 180K Axiom® SoyaSNP array and whole genome resequencing data from the Korean soybean core collection. As a result of conducting GWAS for group A soyasaponin (Aa and Ab derivatives), 16 significant common markers associated with Aa and Ab derivatives were mapped to chromosome 7, and three candidate genes including Glyma.07g254600 were detected. The functional haplotypes for candidate genes showed that Aa and Ab contents were mainly determined by alleles of AX-90322128, the marker of Glyma.07g254600. In addition, 14 novel SNPs variants closely associated with Aa and Ab derivatives were discovered for Glyma.07g254600. Therefore, the results of this study that identified soyasaponin-associated markers and useful genes utilizing various genomic information could provide insight into functional soybean breeding.     

Dynamic genetic features of chromosomes revealed by comparison of soybean genetic and sequence-based physical maps

Despite the intensive soybean [Glycine max (L.) Merrill] genome studies, the high chromosome number (20) of the soybean plant relative to many other major crops has hindered the development of a high-resolution genomewide genetic map derived from a single population. Here, we report such a map, which was constructed in an F₁₅ population derived from a cross between G. max and G. soja lines using indel polymorphisms detected via a G. soja genome resequencing. By targeting novel indel markers to marker-poor regions, all marker intervals were reduced to under 6 cM on a genome scale. Comparison of the Williams 82 soybean reference genome sequence and our genetic map indicated that marker orders of 26 regions were discrepant with each other. In addition, our comparison showed seven misplaced and two absent markers in the current Williams 82 assembly and six markers placed on the scaffolds that were not incorporated into the pseudomolecules. Then, we showed that, by determining the missing sequences located at the presumed beginning points of the five major discordant segments, these observed discordant regions are mostly errors in the Williams 82 assembly. Distributions of the recombination rates along the chromosomes were similar to those of other organisms. Genotyping of indel markers and genome resequencing of the two parental lines suggested that some marker-poor chromosomal regions may represent introgression regions, which appear to be prevalent in soybean. Given the even and dense distribution of markers, our genetic map can serve as a bridge between genomics research and breeding programs.     

The composition and origins of genomic variation among individuals of the soybean reference cultivar Williams 82

Soybean (Glycine max) is a self-pollinating species that has relatively low nucleotide polymorphism rates compared with other crop species. Despite the low rate of nucleotide polymorphisms, a wide range of heritable phenotypic variation exists. There is even evidence for heritable phenotypic variation among individuals within some cultivars. Williams 82, the soybean cultivar used to produce the reference genome sequence, was derived from backcrossing a Phytophthora root rot resistance locus from the donor parent Kingwa into the recurrent parent Williams. To explore the genetic basis of intracultivar variation, we investigated the nucleotide, structural, and gene content variation of different Williams 82 individuals. Williams 82 individuals exhibited variation in the number and size of introgressed Kingwa loci. In these regions of genomic heterogeneity, the reference Williams 82 genome sequence consists of a mosaic of Williams and Kingwa haplotypes. Genomic structural variation between Williams and Kingwa was maintained between the Williams 82 individuals within the regions of heterogeneity. Additionally, the regions of heterogeneity exhibited gene content differences between Williams 82 individuals. These findings show that genetic heterogeneity in Williams 82 primarily originated from the differential segregation of polymorphic chromosomal regions following the backcross and single-seed descent generations of the breeding process. We conclude that soybean haplotypes can possess a high rate of structural and gene content variation, and the impact of intracultivar genetic heterogeneity may be significant. This detailed characterization will be useful for interpreting soybean genomic data sets and highlights important considerations for research communities that are developing or utilizing a reference genome sequence.     

A set of EST-SNPs for map saturation and cultivar identification in melon

Background

There are few genomic tools available in melon (Cucumis melo L.), a member of the Cucurbitaceae, despite its importance as a crop. Among these tools, genetic maps have been constructed mainly using marker types such as simple sequence repeats (SSR), restriction fragment length polymorphisms (RFLP) and amplified fragment length polymorphisms (AFLP) in different mapping populations. There is a growing need for saturating the genetic map with single nucleotide polymorphisms (SNP), more amenable for high throughput analysis, especially if these markers are located in gene coding regions, to provide functional markers. Expressed sequence tags (ESTs) from melon are available in public databases, and resequencing ESTs or validating SNPs detected in silico are excellent ways to discover SNPs.

Results

EST-based SNPs were discovered after resequencing ESTs between the parental lines of the PI 161375 (SC) × 'Piel de sapo' (PS) genetic map or using in silico SNP information from EST databases. In total 200 EST-based SNPs were mapped in the melon genetic map using a bin-mapping strategy, increasing the map density to 2.35 cM/marker. A subset of 45 SNPs was used to study variation in a panel of 48 melon accessions covering a wide range of the genetic diversity of the species. SNP analysis correctly reflected the genetic relationships compared with other marker systems, being able to distinguish all the accessions and cultivars.

Conclusion

This is the first example of a genetic map in a cucurbit species that includes a major set of SNP markers discovered using ESTs. The PI 161375 × 'Piel de sapo' melon genetic map has around 700 markers, of which more than 500 are gene-based markers (SNP, RFLP and SSR). This genetic map will be a central tool for the construction of the melon physical map, the step prior to sequencing the complete genome. Using the set of SNP markers, it was possible to define the genetic relationships within a collection of forty-eight melon accessions as efficiently as with SSR markers, and these markers may also be useful for cultivar identification in Occidental melon varieties.     

Fine mapping and identification of candidate genes controlling the resistance to southern root-knot nematode in PI 96354

Meloidogyne incognita (Kofoid and White) Chitwood (Mi) is the most economically damaging species of the root-knot nematode to soybean and other crops in the southern USA. PI 96354 was identified to carry a high level of resistance to galling and Mi egg production. Two Quantitative Trait Locus (QTLs) were found to condition the resistance in PI 96354 including a major QTL and a minor QTL on chromosome 10 and chromosome 18, respectively. To fine map the major QTL on chromosome 10, F_5:6 recombinant inbred lines from the cross between PI 96354 and susceptible genotype Bossier were genotyped with Simple Sequence Repeats (SSR) markers to identify recombinational events. Analysis of lines carrying key recombination events placed the Mi-resistant allele on chromosome 10 to a 235-kb region of the ‘Williams 82’ genome sequence with 30 annotated genes. Candidate gene analysis identified four genes with cell wall modification function that have several mutations in promoter, exon, 5′, and 3′UTR regions. qPCR analysis showed significant difference in expression levels of these four genes in Bossier compared to PI 96354 in the presence of Mi. Thirty Mi-resistant soybean lines were found to have same SNPs in these 4 candidate genes as PI 96354 while 12 Mi-susceptible lines possess the ‘Bossier’ genotype. The mutant SNPs were used to develop KASP assays to detect the resistant allele on chromosome 10. The four candidate genes identified in this study can be used in further studies to investigate the role of cell wall modification genes in conferring Mi resistance in PI 96354.     

GWAS of agronomic traits in soybean collection included in breeding pool in Kazakhstan

Background

In recent years soybean is becoming one of the most important oilseed crops in Kazakhstan. Only within the last ten years (2006–2016), the area under soybean is expanded from 45 thousand hectares (ha) in 2006 to 120 thousand ha in 2016. The general trend of soybean expansion is from south-eastern to eastern and northern regions of the country, where average temperatures are lower and growing seasons are shorter. These new soybean growing territories were poorly examined in terms of general effects on productivity level among the diverse sample of soybean accessions. In this study, phenotypic data were collected in three separate regions of Kazakhstan and entire soybean sample was genotyped for identification of marker-trait associations (MTA).

Results

In this study, the collection of 113 accessions representing five different regions of the World was planted in 2015–2016 in northern, eastern, and south-eastern regions of Kazakhstan. It was observed that North American accessions showed the highest yield in four out of six trials especially in Northern Kazakhstan in both years. The entire sample was genotyped with 6 K SNP Illumina array. 4442 SNPs found to be polymorphic and were used for whole genome genotyping purposes. Obtained SNP markers data and field data were used for GWAS (genome-wide association study). 30 SNPs appear to be very significant in 42 MTAs in six studied environments.

Conclusions

The study confirms the efficiency of GWAS for the identification of molecular markers which tag important agronomic traits. Overall thirty SNP markers associated with time to flowering and maturation, plant height, number of fertile nodes, seeds per plant and yield were identified. Physical locations of 32 identified out of 42 total MTAs coincide well with positions of known analogous QTLs. This result indicates importance of revealed MTAs for soybean growing regions in Kazakhstan. Obtained results would serve as required prerequisite for forming and realization of specific breeding programs towards effective adaptation and increased productivity of soybean in three different regions of Kazakhstan.

     

Mining conifers’ mega-genome using rapid and efficient multiplexed high-throughput genotyping-by-sequencing (GBS) SNP discovery platform

Next-generation sequencing (NGS) technologies are revolutionizing both medical and biological research through generation of massive SNP data sets for identifying heritable genome variation underlying key traits, from rare human diseases to important agronomic phenotypes in crop species. We evaluated the performance of genotyping-by-sequencing (GBS), one of the emerging NGS-based platforms, for genotyping two economically important conifer species, lodgepole pine (Pinus contorta) and white spruce (Picea glauca). Both species have very large genomes (>20,000 Mbp), are highly heterozygous, and lack reference sequences. From a small set (six accessions each) of independent replicated DNA samples and a 48-plex read depth, we obtained ~60,000 SNPs per species. After stringent filtering, we obtained 17,765 and 17,845 high-coverage SNPs without missing data for lodgepole pine and white spruce, respectively. Our results demonstrated that GBS is a robust and suitable method for genotyping conifers. The application of GBS to forest tree breeding and genomic selection is discussed.     

SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries

High-density single-nucleotide polymorphism (SNP) arrays have revolutionized the ability of genome-wide association studies to detect genomic regions harboring sequence variants that affect complex traits. Extensive numbers of validated SNPs with known allele frequencies are essential to construct genotyping assays with broad utility. We describe an economical, efficient, single-step method for SNP discovery, validation and characterization that uses deep sequencing of reduced representation libraries (RRLs) from specified target populations. Using nearly 50 million sequences generated on an Illumina Genome Analyzer from DNA of 66 cattle representing three populations, we identified 62,042 putative SNPs and predicted their allele frequencies. Genotype data for these 66 individuals validated 92% of 23,357 selected genome-wide SNPs, with a genotypic and sequence allele frequency correlation of r = 0.67. This approach for simultaneous de novo discovery of high-quality SNPs and population characterization of allele frequencies may be applied to any species with at least a partially sequenced genome.