Files in this directory are genome annotation files for cultivar Zhonghuang 13, Chu et al. (2021): Eight soybean reference genome resources from varying latitudes and agronmic traits.
To understand the genetic networks underlying phenotypic correlations, we collected 809 soybean accessions worldwide and phenotyped them for two years at three locations for 84 agronomic traits. Genome-wide association studies identified 245 significant genetic loci, among which 95 genetically interacted with other loci. We determined that 14 oil synthesis-related genes are responsible for fatty acid accumulation in soybean and function in line with an additive model. Network analyses demonstrated that 51 traits could be linked through the linkage disequilibrium of 115 associated loci and these links reflect phenotypic correlations. We revealed that 23 loci, including the known Dt1, E2, E1, Ln, Dt2, Fan, and Fap loci, as well as 16 undefined associated loci, have pleiotropic effects on different traits.
The Genomic DNA of the 440 accessions were partially sequenced using specific-locus amplified fragment sequen- cing (SLAF-seq) approach by Illumina Genome Analyzer II. The 347 million paired-end reads with 45 bp read length were mapped to the reference soybean genome (Wm82.a2.v1) and a mean of 57,418 high quality tags were identified from paired-end reads for each accession. A data set of 36,976 SNPs at Minor Allele Fre- quency (MAF)≥4 % was generated from 57,418 high quality tags. The rate of missing data was controlled at less than 10 % for each accession. The set of SNPs covered 20 chromosomes of soybean. The resulting SNP density of one SNP per 27 Kbp was available in the present study.
Soybean is globally cultivated primarily for its protein and oil. The protein and oil contents of the seeds are quantitatively inherited traits determined by the interaction of numerous genes. In order to gain a better understanding of the molecular foundation of soybean protein and oil content for the marker-assisted selection (MAS) of high quality traits, a population of 185 soybean germplasms was evaluated to identify the quantitative trait loci (QTLs) associated with the seed protein and oil contents. Using specific length amplified fragment sequencing (SLAF-seq) technology, a total of 12,072 single nucleotide polymorphisms (SNPs) with a minor allele frequency (MAF) ≥ 0.05 were detected across the 20 chromosomes (Chr), with a marker density of 78.7 kbp. A total of 31 SNPs located on 12 of the 20 soybean chromosomes were correlated with seed protein and oil content. Of the 31 SNPs that were associated with the two target traits, 31 beneficial alleles were identified. Two SNP markers, namely rs15774585 and rs15783346 on Chr 07, were determined to be related to seed oil content both in 2015 and 2016. Three SNP markers, rs53140888 on Chr 01, rs19485676 on Chr 13, and rs24787338 on Chr 20 were correlated with seed protein content both in 2015 and 2016. These beneficial alleles may potentially contribute towards the MAS of favorable soybean protein and oil characteristics.
The RAD-seq (restriction-site-association DNA sequencing) was used in the present study. The genomic DNA samples were extracted from the leaves of soybean seedlings using the CTAB method (Murray and Thompson 1980). The sequences of the 366 CSLRP accessions were obtained using Illumina HiSeq2000 instrument through the multiplexed shotgun genotyping method (Andolfatto et al. 2011) with DNA fragments between 400 and 600 bp, generating a total of 1144.56 million paired-end reads of 90 bp (including 6-bp index) in length (110.87 Gb of sequence) × approximately 3.86 in depth and 4.57 % coverage. All sequence reads were aligned against the reference genome Glyma.Wm82.a1.v1.1 (Schmutz et al. 2010) using the SOAP2 software (Li et al. 2009), with parameters that included sequence similarity, pair-end relationships and sequence quality. The RealSFS software (Yi et al. 2010) was used for population SNP calling, based on the Bayesian estimation of site frequency at every site. The SNPs of the 366 accessions were polymorphic with a rate of missing and heterozygous allele calls ≤30 % and minor allele frequency (MAF) ≥0.01 (the third or more alleles were replaced no more than once with the missing alleles, when available). The fastPHASE software (Scheet and Stephens 2006) was used for genotyping SNP imputation after heterozygous alleles were turned into missing alleles.
Domestication of soybeans occurred under the intense human-directed selections aimed at developing high-yielding lines. Tracing the domestication history and identifying the genes underlying soybean domestication require further exploration. Here, we developed a high-throughput NJAU 355K SoySNP array and used this array to study the genetic variation patterns in 367 soybean accessions, including 105 wild soybeans and 262 cultivated soybeans. The population genetic analysis suggests that cultivated soybeans have tended to originate from northern and central China, from where they spread to other regions, accompanied with a gradual increase in seed weight. Genome-wide scanning for evidence of artificial selection revealed signs of selective sweeps involving genes controlling domestication-related agronomic traits including seed weight. To further identify genomic regions related to seed weight, a genome-wide association study (GWAS) was conducted across multiple environments in wild and cultivated soybeans. As a result, a strong linkage disequilibrium region on chromosome 20 was found to be significantly correlated with seed weight in cultivated soybeans. Collectively, these findings should provide an important basis for genomic-enabled breeding and advance the study of functional genomics in soybean.
Soya bean is a major source of edible oil and protein for human consumption as well as animal feed. Understanding the genetic basis of different traits in soya bean will provide important insights for improving breeding strategies for this crop. A genome-wide association study (GWAS) was conducted to accelerate molecular breeding for the improvement of agronomic traits in soya bean. A genotyping-by-sequencing (GBS) approach was used to provide dense genome-wide marker coverage (>47 000 SNPs) for a panel of 304 short-season soya bean lines. A subset of 139 lines, representative of the diversity among these, was characterized phenotypically for eight traits under six environments (3 sites × 2 years). Marker coverage proved sufficient to ensure highly significant associations between the genes known to control simple traits (flower, hilum and pubescence colour) and flanking SNPs. Between one and eight genomic loci associated with more complex traits (maturity, plant height, seed weight, seed oil and protein) were also identified. Importantly, most of these GWAS loci were located within genomic regions identified by previously reported quantitative trait locus (QTL) for these traits. In some cases, the reported QTLs were also successfully validated by additional QTL mapping in a biparental population. This study demonstrates that integrating GBS and GWAS can be used as a powerful complementary approach to classical biparental mapping for dissecting complex traits in soya bean.
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.
Synteny calculations involves identification of orthologous genes by selecting reciprocal top hits between chromosome pairs from an all-against-all blastp search of genes between two species (evalue threshold of 1e-10), followed by DAGchainer to predict chains of syntenic genes in complete genomes. Proportions of synonymous-site changes (Ks) between orthologs are calculated, and synteny blocks are filtered for block-wise median Ks values. Synteny blocks have also been calculated to show these paralogous WGD-derived duplications.
In this research, we conducted the first comprehensive analysis of population structure on the collection of 14,000 soybean accessions [Glycine max (L.) Merr. and G. soja Siebold & Zucc.] using a 50KSNP chip. Accessions originating from Japan were relatively homogenous and distinct from the Korean accessions. As a whole, both Japanese and Korean accessions diverged from the Chinese accessions. The ancestry of founders of the American accessions derived mostly from two Chinese subpopulations, which reflects the composition of the American accessions as a whole. A 12,000 accession GWAS conducted on seed protein and oil is the largest reported to date in plants and identified single nucleotide polymorphisms (SNPs) with strong signals on chromosomes 20 and 15. A chromosome 20 region previously reported to be important for protein and oil content was further narrowed and now contains only three plausible candidate genes. The haplotype effects show a strong negative relationship between oil and protein at this locus, indicating negative pleiotropic effects or multiple closely linked loci in repulsion phase linkage. The vast majority of accessions carry the haplotype allele conferring lower protein and higher oil.
Sudden death syndrome (SDS), caused by Fusarium virguliforme, has spread to northern soybean growing regions in the US causing significant yield losses. The objectives of this study were to identify loci underlying variation in plant responses to SDS through association mapping (AM) and to assess prediction accuracy of genomic selection (GS) in a panel of early maturing soybean germplasm. A set of 282 soybean breeding lines was selected from the University of Minnesota soybean breeding program and then genotyped using a genome-wide panel of 1536 single-nucleotide polymorphism markers. Four resistance traits, root lesion severity (RLS), foliar symptom severity (FSS), root retention (RR), and dry matter reduction (DMR), were evaluated using soil inoculation in the greenhouse. AM identified significant peaks in genomic regions of known SDS resistance quantitative trait loci cqSDS001, cqRfs4, and SDS11-2. Additionally, two novel loci, one on chromosome 3 and another on chromosome 18, were tentatively identified. A ninefold cross-validation scheme was used to assess the prediction accuracy of GS for SDS resistance. The prediction accuracy of single-trait GS (ST-GS) was 0.64 for RLS, but less than 0.30 for RR, DMR, and FSS. Compared to STGS, none of multi-trait GS (MT-GS) models significantly improved the prediction accuracy due to weak correlations between the four traits. This study suggests both AM and GS hold promise for implementation in genetic improvement of SDS resistance in existing soybean breeding programs.
DNA samples were genotyped using an Illumina GoldenGate SNP assay with the Universal Soy Linkage Panel 1.0 of 1536 single nucleotide polymorphism (SNP) markers. The SNPs with >5% minor allele frequency (MAF) and a missing data rate < 50% were retained, followed by imputation of missing SNP data based on population mean of each marker. Total 1247 SNP markers passed the filters and were used in the subsequent analysis.
We used both a linkage and association mapping methodology to dissect the genetic basis of seed oil content of Chinese soybean cultivars in various environments in the Jiang-Huai River Valley. One recombinant inbred line (RIL) population (NJMN-RIL), with 104 lines developed from a cross between M8108 and NN1138-2, was planted in five environments to investigate phenotypic data, and a new genetic map with 2,062 specific-locus amplified fragment markers was constructed to map oil content QTLs. A derived F2 population between MN-5 (a line of NJMN-RIL) and NN1138-2 was also developed to confirm one major QTL. A soybean breeding germplasm population (279 lines) was established to perform a genome-wide association study (GWAS) using 59,845 high-quality single nucleotide polymorphism markers. In the NJMN-RIL population, 8 QTLs were found that explained a range of phenotypic variance from 6.3 to 26.3% in certain planting environments. Among them, qOil-5-1, qOil-10-1, and qOil-14-1 were detected in different environments, and qOil-5-1 was further confirmed using the secondary F2 population. Three loci located on chromosomes 5 and 20 were detected in a 2-year long GWAS, and one locus that overlapped with qOil-5-1 was found repeatedly and treated as the same locus. qOil-5-1 was further localized to a linkage disequilibrium block region of approximately 440 kb. These results will not only increase our understanding of the genetic control of seed oil content in soybean, but will also be helpful in marker-assisted selection for breeding high seed oil content soybean and gene cloning to elucidate the mechanisms of seed oil content.
TRSV-induced disease sensitivities of the 697 soybean PIs were rated on a one to five scale with plants rated as one exhibiting mild symptoms and plants rated as five displaying terminal bud necrosis (i.e., bud blight). The GWAS identified a single locus on soybean chromosome 2 strongly associated with TRSV sensitivity. Crossvalidation showed a correlation of 0.55 (P < 0.01) to TRSV sensitivity without including the most significant SNP marker from the GWAS as a covariate, which was a better estimation compared to the mean separation by using significant SNPs. The genomic estimated breeding values for the remaining 18,955 unscreened soybean PIs in the USDA Soybean Germplasm Collection were obtained using the GAPIT R package. To evaluate the prediction accuracy, an additional 55 soybean accessions were evaluated for sensitivity to TRSV, which resulted in a correlation of 0.67 (P < 0.01) between actual and predicted severities.
A genome-wide association study was conducted to accelerate molecular breeding for the improvement of resistance to SMV in soybean. A population of 165 soybean mutants derived from two soybean parents was used in this study. There were 104 SNPs identified significantly associated with resistance to SC7, some of which were located within previous reported quantitative trait loci. Three putative genes on chromosome 1, 9, and 12 were homologous to WRKY72, eEF1Bβ, and RLP9, which were involved in defense response to insect and disease in Arabidopsis.
A genome-wide associating mapping approach was employed using 31,253 single nucleotide polymorphisms (SNPs) to identify loci associated with the extract based eChl_A, eChl_B, eChl_R and eChl_T measurements and the two canopy spectral reflectance-based methods (tChl_T and iChl_T). A total of 23 (14 loci), 15 (7 loci) and 14 SNPs (10 loci) showed significant association with eChl_A, eChl_B and eChl_R respectively. A total of 52 unique SNPs were significantly associated with total chlorophyll content based on at least one of the three approaches (eChl_T, tChl_T and iChl_T) and likely tagged 27 putative loci for total chlorophyll content, four of which were indicated by all three approaches.
To understand the genetic networks underlying phenotypic correlations, we collected 809 soybean accessions worldwide and phenotyped them for two years at three locations for 84 agronomic traits. Genome-wide association studies identified 245 significant genetic loci, among which 95 genetically interacted with other loci. We determined that 14 oil synthesis-related genes are responsible for fatty acid accumulation in soybean and function in line with an additive model. Network analyses demonstrated that 51 traits could be linked through the linkage disequilibrium of 115 associated loci and these links reflect phenotypic correlations. We revealed that 23 loci, including the known Dt1, E2, E1, Ln, Dt2, Fan, and Fap loci, as well as 16 undefined associated loci, have pleiotropic effects on different traits.
The Genomic DNA of the 440 accessions were partially sequenced using specific-locus amplified fragment sequencing (SLAF-seq) approach by Illumina Genome Analyzer II. The 347 million paired-end reads with 45 bp read length were mapped to the reference soybean gen- ome (Wm82.a2.v1) and a mean of 57,418 high quality tags were identified from paired-end reads for each accession. A data set of 36,976 SNPs at Minor Allele Fre- quency (MAF)≥4 % was generated from 57,418 high quality tags. The rate of missing data was controlled at less than 10 % for each accession. The set of SNPs covered 20 chromosomes of soybean. The resulting SNP density of one SNP per 27 Kbp was available in the present study.
This study reports on the identification of candidate markers associated with flower time in soybean (Glycine max). A large population of 2,662 cultivated soybean accessions was genotyped using the 180k Axiom SoyaSNP array, and the genomic architecture of these accessions was investigated to confirm the population structure. Then, GWAS was conducted to evaluate the association between SNP markers and flower ytime. A tyyotal of 93 significant SNP markers were detected within 59 significant genes, including E1 and E3, which are the main determinants of flower time. Based on the GWAS results, multilocus epistatic interactions were examined between the significant and non-significant SNP markers. Two significant and 16 non-significant SNP markers were discovered as candidate markers affecting flower time via interactions with each other. These 18 candidate SNP markers mapped to 18 candidate genes including E1 and E3, and the 18 candidate genes were involved in six major flower pathways.
A GWAS study of seed protein and oil content using a population of 185 soybean (Glycine max) accessions from China and across the northern hemisphere. Specific length amplified fragment sequencing (SLAF-seq) tecyyhnology detected 12,072 SNPs across 20 chromosomes showing a marker density of 78.7 kbp. Thirty-one SNPs, and their 31 beneficial alleles, placed on 12 of the chromosomes represented QTLs associateyd with protein and oil. In both 2015 and 2016, the SNPs rs15774585 and rs15783346 (Chr 7) were correlated with seed oil, and the SNPs rs53140888 (Chr 01), rs19485676 (Chr 13), and rs24787338 (Chr 20) with seed protein.
The objective of this analysis was to employ single nucleotide polymorphism (SNP)-based genome-wide association mapping to uncover genomic regions associated with IDC tolerance. Two populations [2005 (n = 143) and 2006 (n = 141)] were evaluated in replicated, multilocation IDC trials. After controlling for population structure and individual relatedness, and selecting statistical models that minimized false positives, 42 and 88 loci, with minor allele frequency >10%, were significant in 2005 and 2006, respectively. The loci accounted for 74.5% of the phenotypic variation in IDC in2005 and 93.8% of the variation in 2006. Nine loci from seven genomic locations were significant in both years. These loci accounted for 43.7% of the variation in 2005 and 47.6% in 2006. A number of the loci discovered here mapped at or near previously discovered IDC quantitative trait loci (QTL). A total of 15 genes known to be involved in iron metabolism mapped in the vicinity (<500 kb) of significant markers in one or both populations.
The seed isoflavone content (SIFC) of soybeans is of great importance to health care. The Chinese soybean landrace population (CSLRP) as a genetic reservoir was studied for its whole-genome quantitative trait loci (QTL) system of the SIFC using an innovative restricted twostage multi-locus genome-wide association study procedure (RTM-GWAS). A sample of 366 landraces was tested under four environments and sequenced using RAD-seq (restriction-site-associated DNA sequencing) technique to obtain 116,769 single nucleotide polymorphisms (SNPs) then organized into 29,119 SNP linkage disequilibrium blocks (SNPLDBs) for GWAS. The detected 44 QTL 199 alleles on 16 chromosomes (explaining 72.2 % of the total phenotypic variation) with the allele effects (92 positive and 107 negative) of the CSLRP were organized into a QTL-allele matrix showing the SIFC population genetic structure. Additional differentiation among eco-regions due to the SIFC in addition to that of genome-wide markers was found. All accessions comprised both positive and negative alleles, implying a great potential for recombination within the population. The optimal crosses were predicted from the matrices, showing transgressive potentials in the CSLRP. From the detected QTL system, 55 candidate genes related to 11 biological processes were χ2 -tested as an SIFC candidate gene system. The present study explored the genome-wide SIFC QTL/gene system with the innovative RTM-GWAS and found the potentials of the QTLallele matrix in optimal cross design and population genetic and genomic studies, which may have provided a solution to match the breeding by design strategy at both QTL and gene levels in breeding programs.
GWAS and GWES studies along with expression studies in soybean were leveraged to dissect the genetics of Sclerotinia stem rot (SSR), a significant fungal disease causing yield and quality losses. A large association panel of 466 diverse plant introduction accessions were phenotyped in multiple field and controlled environments to: (1) discover sources of resistance, (2) identify SNPs associated with resistance, and (3) determine putative candidate genes to elucidate the mode of resistance.
Soya bean is a major source of edible oil and protein for human consumption as well as animal feed. Understanding the genetic basis of different traits in soya bean will provide important insights for improving breeding strategies for this crop. A genome-wide association study (GWAS) was conducted to accelerate molecular breeding for the improvement of agronomic traits in soya bean. A genotyping-by-sequencing (GBS) approach was used to provide dense genome-wide marker coverage (>47 000 SNPs) for a panel of 304 short-season soya bean lines. A subset of 139 lines, representative of the diversity among these, was characterized phenotypically for eight traits under six environments (3 sites × 2 years). Marker coverage proved sufficient to ensure highly significant associations between the genes known to control simple traits (flower, hilum and pubescence colour) and flanking SNPs. Between one and eight genomic loci associated with more complex traits (maturity, plant height, seed weight, seed oil and protein) were also identified. Importantly, most of these GWAS loci were located within genomic regions identified by previously reported quantitative trait locus (QTL) for these traits. In some cases, the reported QTLs were also successfully validated by additional QTL mapping in a biparental population. This study demonstrates that integrating GBS and GWAS can be used as a powerful complementary approach to classical biparental mapping for dissecting complex traits in soya bean.
The most damaging pest in the production of Soybean (Glycine max) is the soybean cyst nematode (SCN) (Heterodera glycines). This study assessed the genome-wide marker–trait associations of SCN resistance in soybean. 462 genotypes were analyzed using Illumina's SoySNP50K iSelect Beadchips and three functional SCN KASP SNP markers GSM 381, GSM 383, and GSM 191 developed at the Rhg1 and Rhg4 loci. SCN resistance was measured using the FI index, which was defined as a ratio between the number of cysts on a given line and on Lee 74 (susceptible control line). The genome-wide association study (GWAS) identified 12 single-nucleotide polymorphisms (SNPs) on four chromosomes that had a significant (P < 0.05) association with the FI index. Significance was defined as a FI index below 30% and therefore sub-catagorized as resistant (R) (FI > 10%) or moderately resistant (MR) (10% < FI < 30%) to soybean cyst nematodes. 26 other SCN associated SNPs were identified on other chromosomes of soybean, but none of them were above the p-value cutoff point of 0.05.
A diverse panel of 553 soybean germplasm accessions, which were undergone multivariate selection procedures and best represents the diversity of the total collection, was evaluated for response to SCN HG Type 0. Over 50,000 SNP markers of the soybean genome generated in the SoySNP50K iSelect BeadChip were accessed from www.soybase.org. A total of 35,270 SNPs were selected for GWAS after excluding SNPs with more than 20 % missing data and a minor allele frequency less than 5 %. GWAS was performed using generalized linear model (GLM) identified 223 SNPs distributed over 19 different chromosomes and associated with resistance to SCN HG Type 0. The MLM identified 41 SNPs distributed over 16 loci on 14 different chromosomes that were significantly associated with resistance to SCN HG Type 0 (Table 2, Fig. 7). The known loci rhg1 on Chr. 18 and Rhg4 on Chr. 8, were also identified in this study. Highly significant SNPs on Chr. 8 between 7.5 to 8.6 Mb and on Chr. 18 between 1.2 to 6.6 Mb were associated with SCN resistance. These loci did not show a high level of significance even though these loci harbor a very high level of resistance.
We selected 166 accessions from the USDA Soybean Germplasm Collection with either large or small seed weight and could typically grow in the same location. The accessions were evaluated for seed weight in the field for two years and genotyped with the SoySNP50K BeadChip containing >42,000 SNPs. Of the 17 SNPs on six chromosomes that were significantly associated with seed weight in two years based on a GWAS of the selective population, eight on chromosome 4 or chromosome 17 had significant Fst values between the large and small seed weight sub-populations. The seed weight difference of the two alleles of these eight significant SNPs varied from 8.1 g to 11.7 g/100 seeds in two years. We also identified haplotypes in three haplotype blocks with significant effects on seed weight. These findings were validated in a panel with 3753 accessions from the USDA Soybean Germplasm Collection.
In this study, we performed genetic association analysis to dissect the relationships between plant architecture and yield component traits. Two hundred and nineteen accessions were employed, and eight agronomic traits were evaluated in six environments. Our results revealed strong positive correlations of plant architecture traits with yield components and the significant association of 4 SNPs with plant architecture traits and of 7 SNPs with yield component traits in two or more environments. Eight SNPs were co-associated with two traits.
The linkage disequilibrium (LD) decayed slowly in soybean, and a substantial difference in LD pattern was observed between euchromatic and heterochromatic regions. A total of 27, 6, 18 and 27 loci for DTF, DTM, DFTM and PH were detected via GWAS, respectively. The Dt1 gene was identified in the locus strongly associated with both DTM and PH. Ten candidate genes homologous to Arabidopsis flowering genes were identified near the peak single nucleotide polymorphisms (SNPs) associated with DTF. Four of them encode MADS-domain containing proteins. Additionally, a pectin lyase-like gene was also identified in a major-effect locus for PH where LD decayed rapidly.
Genome-wide association study in a population of 309 soybean germplasm accessions using 31,045 single nucleotide polymorphisms (SNPs), estimating the prediction accuracy of genomic selection (GS) and marker-assisted selection (MAS) for seed weight (SW). Twenty-two loci of minor effect associated with SW were identified, including hotspots on Gm04 and Gm19. The mixed model containing these loci explained 83.4 % of phenotypic variation.
A total of 200 diverse soybean accessions were screened for resistance to SCN HG Type 2.5.7 and genotyped through sequencing using the Specific Locus Amplified Fragment Sequencing (SLAF-seq) approach with a 6.14-fold average sequencing depth. A total of 33,194 SNPs were identified with minor allele frequencies (MAF) over 4%, covering 97% of all the genotypes. Genome-wide association mapping (GWAS) revealed thirteen SNPs associated with resistance to SCN HG Type 2.5.7. These SNPs were distributed on five chromosomes (Chr), including Chr7, 8, 14, 15 and 18. Four SNPs were novel resistance loci and nine SNPs were located near known QTL. A total of 30 genes were identified as candidate genes underlying SCN resistance. Conclusions: A total of sixteen novel soybean accessions were identified with significant resistance to HG Type 2.5.7. The beneficial alleles and candidate genes identified by GWAS might be valuable for improving marker-assisted breeding efficiency and exploring the molecular mechanisms underlying SCN resistance.
To identify yield-enhancing quantitative trait locus (QTL) or gene from wild soybean, 113 wild soybeans accessions were phenotyped for five yield-related traits and genotyped with 85 simple sequence repeat (SSR) markers to conduct association mapping. A total of 892 alleles were detected for the 85 SSR markers, with an average 10.49 alleles; the corresponding PIC values ranged from 0.07 to 0.92, with an average 0.73. The genetic diversity of each SSR marker ranged from 0.07 to 0.93, with an average 0.75. A total of 18 SSR markers were identified for the five traits. Two SSR markers, sct_010 and satt316, which are associated with the yield per plant were stably expressed over two years at two experimental locations.
The soybean cyst nematode (SCN) is one of the most destructive pathogens of soybean plants worldwide. Host-plant resistance is an environmentally friendly method to mitigate SCN damage. To date, the resistant soybean cultivars harbor limited genetic variation, and some are losing resistance. Thus, a better understanding of the genetic mechanisms of the SCN resistance, as well as developing diverse resistant soybean cultivars, is urgently needed. In this study, a genome-wide association study (GWAS) was conducted using 1032 wild soybean (Glycine soja) accessions with over 42,000 single-nucleotide polymorphisms (SNPs) to understand the genetic architecture of G. soja resistance to SCN race 1. Ten SNPs were significantly associated with the response to race 1. Three SNPs on chromosome 18 were localized within the previously identified quantitative trait loci (QTLs), and two of which were localized within a strong linkage disequilibrium block encompassing a nucleotide-binding (NB)-ARC disease resistance gene (Glyma.18G102600). Genes encoding methyltransferases, the calcium-dependent signaling protein, the leucine-rich repeat kinase family protein, and the NB-ARC disease resistance protein, were identified as promising candidate genes. The identified SNPs and candidate genes can not only shed light on the molecular mechanisms underlying SCN resistance, but also can facilitate soybean improvement employing wild genetic resources.
The objectives of this study were to determine the abundance of SSRs in the soybean genome and to develop and test soybean SSR markers to create a database of locus-specific markers with a high likelihood of polymorphism. A total of 210,990 SSRs with di-, tri-, and tetranucleotide repeats of five or more were identified in the soybean whole genome sequence (WGS) which included 61,458 SSRs consisting of repeat units of di- (≥10), tri- (≥8), and tetranucleotide (≥7). Among the 61,458 SSRs, (AT)n, (ATT)n and (AAAT)n were the most abundant motifs among di-, tri-, and tetranucleotide SSRs, respectively. After screening for a number of factors including locus-specificity using e-PCR, a soybean SSR database (BARCSOYSSR_1.0) with the genome position and primer sequences for 33,065 SSRs was created.
To discover genes or QTLs underlying naturally occurring variations in soybean P.sojae resistance, we performed a genome-wide association study using 59,845 single-nucleotide polymorphisms identified from re-sequencing of 279 accessions from Yangtze-Huai soybean breeding germplasm. We used two models for association analysis. The same strong peak was detected by both two models on chromosome 13. Within the 500-kb flanking regions, three candidate genes (Glyma13g32980, Glyma13g33900, Glyma13g33512) had SNPs in their exon regions.
Files in this directory are genome annotation files for Glycine stenphyta, accession G1974,from Zhuang, Wang et al. (2022): "Phylogenomics of the genus Glycine sheds light on polyploid evolution and life-strategy transition"
Files in this directory are genome annotation files for Glycine syndetika, accession G1300, from Zhuang, Wang et al. (2022): "Phylogenomics of the genus Glycine sheds light on polyploid evolution and life-strategy transition"
Files in this directory are genome annotation files for cultivar Zhonghuang 35, Chu et al. (2021): Eight soybean reference genome resources from varying latitudes and agronmic traits.
Gene annotations for Glycine max accession ZhangChunManCangJin (SoyL06) from Liu, Du et al. 2020. Annotations of the protein-coding and small RNA genes employed Augustus trained by FGENESH, transcript support based on RNA samples from roots, stems, leaves, flowers, and seeds at different developmental stages;and integration of ab initio and evidence-based results with MAKER.
SoySNP50K is an Illumina Infinium II BeadChip that contains over 50,000 SNPs from soybean. Of 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.
The limited number of recombinant events in recombinant inbred lines suggests that for a biparental population with a limited number of recombinant inbred lines, it is unnecessary to genotype the lines with many markers. For genomic prediction and selection, previous studies have demonstrated that only 1000–2000 genome-wide common markers across all lines/accessions are needed to reach maximum efficiency of genomic prediction in populations. Evaluation of too many markers will not only increase the cost but also generate redundant information. We developed a soybean (Glycine max) assay, BARCSoySNP6K, containing 6000 markers, which were carefully chosen from the SoySNP50K assay based on their position in the soybean genome and haplotype block, polymorphism among accessions and genotyping quality. The assay includes 5000 single nucleotide polymorphisms (SNPs) from euchromatic and 1000 from heterochromatic regions. The percentage of SNPs with minor allele frequency >0.10 was 95% and 91% in the euchromatic and heterochromatic regions, respectively. Analysis of progeny from two large families genotyped with SoySNP50K versus BARCSoySNP6K showed that the position of the common markers and number of unique bins along linkage maps were consistent based on the SNPs genotyped with the two assays; however, the rate of redundant markers was dramatically reduced with the BARCSoySNP6K. The BARCSoySNP6K assay is proven as an excellent tool for detecting quantitative trait loci, genomic selection and assessing genetic relationships. The assay is commercialized by Illumina Inc. and being used by soybean breeders and geneticists and the list of SNPs in the assay is an ideal resource for SNP genotyping by targeted amplicon sequencing.
The objective of the work reported here was to develop and map a large set of SSR markers. A total of 606 SSR loci were mapped in one or more of three populations: the USDA/Iowa State G. max × G. soja F2 population, the Univ. of Utah Minsoy × Noir 1 recombinant inbred population, and the Univ. of Nebraska Clark × Harosoy F2 population. Each SSR mapped to a single locus in the genome, with a map order that was essentially identical in all three populations. Many SSR loci were segregating in two or all three populations. Thus, it was relatively simple to align the 20+ linkage groups derived from each of the three populations into a consensus set of 20 homologous linkage groups presumed to correspond to the 20 pairs of soybean chromosomes.
A total of 200 diverse soybean accessions were screened for resistance to SCN HG Type 2.5.7 and genotyped through sequencing using the Specific Locus Amplified Fragment Sequencing (SLAF-seq) approach with a 6.14-fold average sequencing depth. A total of 33,194 SNPs were identified with minor allele frequencies (MAF) over 4%, covering 97% of all the genotypes. Genome-wide association mapping (GWAS) revealed thirteen SNPs associated with resistance to SCN HG Type 2.5.7. These SNPs were distributed on five chromosomes (Chr), including Chr7, 8, 14, 15 and 18. Four SNPs were novel resistance loci and nine SNPs were located near known QTL. A total of 30 genes were identified as candidate genes underlying SCN resistance. Conclusions: A total of sixteen novel soybean accessions were identified with significant resistance to HG Type 2.5.7. The beneficial alleles and candidate genes identified by GWAS might be valuable for improving marker-assisted breeding efficiency and exploring the molecular mechanisms underlying SCN resistance.
Our objectives were to add 2500 additional SNP markers to the soybean integrated map and select a set of 1536 SNPs to create a universal linkage panel for high-throughput soybean quantitative trait locus (QTL) mapping. The GoldenGate assay is one high-throughput analysis method capable of genotyping 1536 SNPs in 192 DNA samples over a 3-d period. We designed GoldenGate assays for 3456 SNPs (2956 new plus 500 previously mapped) which were used to screen three recombinant inbred line populations and diverse germplasm. A total of 3000 workable assays were obtained which added about 2500 new SNP markers to create a fourth version of the soybean integrated linkage map. To create this Universal Soy Linkage Panel (USLP 1.0) of 1536 SNP loci, SNPs were selected based on even distribution throughout each of the 20 consensus linkage groups and to have a broad range of allele frequencies in diverse germplasm. The 1536 USLP 1.0 will be able to quickly create a comprehensive genetic map in most QTL mapping populations and thus will serve as a useful tool for high-throughput QTL mapping.
The objectives of this study were to determine the abundance of SSRs in the soybean genome and to develop and test soybean SSR markers to create a database of locus-specific markers with a high likelihood of polymorphism. A total of 210,990 SSRs with di-, tri-, and tetranucleotide repeats of five or more were identified in the soybean whole genome sequence (WGS) which included 61,458 SSRs consisting of repeat units of di- (≥10), tri- (≥8), and tetranucleotide (≥7). Among the 61,458 SSRs, (AT)n, (ATT)n and (AAAT)n were the most abundant motifs among di-, tri-, and tetranucleotide SSRs, respectively. After screening for a number of factors including locus-specificity using e-PCR, a soybean SSR database (BARCSOYSSR_1.0) with the genome position and primer sequences for 33,065 SSRs was created.
SoySNP50K is an Illumina Infinium II BeadChip that contains over 50,000 SNPs from soybean. Of 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.
The limited number of recombinant events in recombinant inbred lines suggests that for a biparental population with a limited number of recombinant inbred lines, it is unnecessary to genotype the lines with many markers. For genomic prediction and selection, previous studies have demonstrated that only 1000–2000 genome-wide common markers across all lines/accessions are needed to reach maximum efficiency of genomic prediction in populations. Evaluation of too many markers will not only increase the cost but also generate redundant information. We developed a soybean (Glycine max) assay, BARCSoySNP6K, containing 6000 markers, which were carefully chosen from the SoySNP50K assay based on their position in the soybean genome and haplotype block, polymorphism among accessions and genotyping quality. The assay includes 5000 single nucleotide polymorphisms (SNPs) from euchromatic and 1000 from heterochromatic regions. The percentage of SNPs with minor allele frequency >0.10 was 95% and 91% in the euchromatic and heterochromatic regions, respectively. Analysis of progeny from two large families genotyped with SoySNP50K versus BARCSoySNP6K showed that the position of the common markers and number of unique bins along linkage maps were consistent based on the SNPs genotyped with the two assays; however, the rate of redundant markers was dramatically reduced with the BARCSoySNP6K. The BARCSoySNP6K assay is proven as an excellent tool for detecting quantitative trait loci, genomic selection and assessing genetic relationships. The assay is commercialized by Illumina Inc. and being used by soybean breeders and geneticists and the list of SNPs in the assay is an ideal resource for SNP genotyping by targeted amplicon sequencing.
The objective of the work reported here was to develop and map a large set of SSR markers. A total of 606 SSR loci were mapped in one or more of three populations: the USDA/Iowa State G. max × G. soja F2 population, the Univ. of Utah Minsoy × Noir 1 recombinant inbred population, and the Univ. of Nebraska Clark × Harosoy F2 population. Each SSR mapped to a single locus in the genome, with a map order that was essentially identical in all three populations. Many SSR loci were segregating in two or all three populations. Thus, it was relatively simple to align the 20+ linkage groups derived from each of the three populations into a consensus set of 20 homologous linkage groups presumed to correspond to the 20 pairs of soybean chromosomes.
SoySNP50K is an Illumina Infinium II BeadChip that contains over 50,000 SNPs from soybean. Of 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. This marker set was used in combination with three KASP SNP markers developed at the Rhg1 and Rhg4 loci to perfrom this GWAS and haplotype analysis at the previously stated SCN resistance loci. In total, 35,820 SNPs were used for GWAS, which identified 12 SNPs at four genomic regions on Chrs 7, 8, 10, and 18 that were significantly associated with SCN resistance (P < 0.001). Of those, three SNPs were located at Rhg1 and Rhg4. KASP SNP genotyping results of the 462 accessions at the Rhg1 and Rhg4 loci identified 30 that carried PI 88788-type resistance, 50 that carried Peking-type resistance, and 58 that carried neither the Peking-type nor the PI 88788-type resistance alleles, indicating they may possess novel SCN resistance alleles.
SoySNP50K is an Illumina Infinium II BeadChip that contains over 50,000 SNPs from soybean. Of 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 35,270 SNPs from this set were selected for GWAS in this study after excluding SNPs with more than 20 % missing data and a minor allele frequency less than 5 %. GWAS was performed using generalized linear model (GLM) identified 223 SNPs distributed over 19 different chromosomes and associated with resistance to SCN HG Type 0. GWAS identified 14 loci distributed over different chromosomes comprising 60 SNPs significantly associated with SCN resistance.
A total of 200 diverse soybean accessions were screened for resistance to SCN HG Type 2.5.7 and genotyped through sequencing using the Specific Locus Amplified Fragment Sequencing (SLAF-seq) approach with a 6.14-fold average sequencing depth. A total of 33,194 SNPs were identified with minor allele frequencies (MAF) over 4%, covering 97% of all the genotypes. Genome-wide association mapping (GWAS) revealed thirteen SNPs associated with resistance to SCN HG Type 2.5.7. These SNPs were distributed on five chromosomes (Chr), including Chr7, 8, 14, 15 and 18. Four SNPs were novel resistance loci and nine SNPs were located near known QTL. A total of 30 genes were identified as candidate genes underlying SCN resistance. Conclusions: A total of sixteen novel soybean accessions were identified with significant resistance to HG Type 2.5.7. The beneficial alleles and candidate genes identified by GWAS might be valuable for improving marker-assisted breeding efficiency and exploring the molecular mechanisms underlying SCN resistance.
