Single nucleotide polymorphism markers for rapid detection of the <Emphasis Type="Italic">Rsv4</Emphasis> locus for soybean mosaic virus resistance in diverse germplasm

Soybean mosaic virus (SMV) causes a substantial decrease in soybean yield and reduction of seed quality. The most effective management strategy to control the virus is the deployment of host resistance. Seven SMV strains and three independent multi-allelic loci for SMV resistance have been identified previously. The goal of this research was to detect single nucleotide polymorphisms (SNPs) associated with SMV resistance at the Rsv4 locus. Ten soybean accessions, with confirmed resistance genes, were used for sequencing the candidate gene Glyma.02g121400. Alignment of these sequences revealed three SNPs displaying 100% consistency for genotypes carrying the Rsv4 gene. These SNPs were applied for a rapid screen of diverse soybean germplasm using the Sequenom iPLEX Gold platform, phenotyped with SMV-G1 and G7 strains to determine phenotype and classified into several groups carrying the proposed R-gene. The population of V94-5152 (Rsv4) × Lee 68 (rsv) was screened using novel SNPs to create a genetic map with improved resolution to determine the location of the Rsv4. To observe the recombination frequencies within the population, three additional SNPs on both sides of the Glyma.02g121400 gene were added. A linkage map revealed a distance of 3.6 cM between the Rsv4 locus and the closest SNP, thus shifting the putative Rsv4 region downstream on chromosome 2. With this region, five candidate genes have been proposed. The genomic position of the discovered SNPs, linked to the Rsv4, could increase screening precision and accelerate breeding efforts to develop multi-strain-resistant crops.     

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.     

Mapping Locus RSC11K and predicting candidate gene resistant to Soybean mosaic virus strain SC11 through linkage analysis combined with genome resequencing of the parents in soybean

Soybean mosaic virus (SMV) strain SC11 was prevalent in middle China. Its resistance was controlled by a Mendelian single dominant gene R_SC11K in soybean Kefeng-1. This study aimed at mapping R_SC11K and identifying its candidate gene. R_SC11K locus was mapped ~217 kb interval between two SNP-linkage-disequilibrium-blocks (Gm02_BLOCK_11273955_11464884 and Gm02_BLOCK_11486875_11491354) in W82.a1.v1 genome using recombinant inbred lines population derived from Kefeng-1 (Resistant) × NN1138-2 (Susceptible), but inserted with a ~245 kb segment in W82.a2.v1 genome. In the entire 462 kb R_SC11K region, 429 SNPs, 142 InDels and 34 putative genes were identified with more SNPs/InDels distributed in non-functional regions. Thereinto, ten genes contained SNP/InDel variants with high and moderate functional impacts on proteins, among which Glyma.02G119700 encoded a typical innate immune receptor-like kinase involving in virus disease process and responded to SMV inoculation, therefore was recognized as R_SC11K's candidate gene. The novel R_SC11K locus and candidate genes may help developing SMV resistance germplasm.     

Loci and candidate gene identification for resistance to Sclerotinia sclerotiorum in soybean (Glycine max L. Merr.) via association and linkage maps

Soybean white mold (SWM), caused by Sclerotinia sclerotiorum ((Lib.) W. Phillips), is currently considered to be the second most important cause of soybean yield loss due to disease. Research is needed to identify SWM‐resistant germplasm and gain a better understanding of the genetic and molecular basis of SWM resistance in soybean. Stem pigmentation after treatment with oxaloacetic acid is an effective indicator of resistance to SWM. A total of 128 recombinant inbred lines (RILs) derived from a cross of ‘Maple Arrow’ (partial resistant to SWM) and ‘Hefeng 25’ (susceptible) and 330 diverse soybean cultivars were screened for the soluble pigment concentration of their stems, which were treated with oxalic acid. Four quantitative trait loci (QTLs) underlying soluble pigment concentration were detected by linkage mapping of the RILs. Three hundred and thirty soybean cultivars were sequenced using the whole‐genome encompassing approach and 25 179 single‐nucleotide polymorphisms (SNPs) were detected for the fine mapping of SWM resistance genes by genome‐wide association studies. Three out of five SNP markers representing a linkage disequilibrium (LD) block and a single locus on chromosome 13 (Gm13) were significantly associated with the soluble pigment content of stems. Three more SNPs that represented three minor QTLs for the soluble pigment content of stems were identified on another three chromosomes by association mapping. A major locus with the largest effect on Gm13 was found both by linkage and association mapping. Four potential candidate genes involved in disease response or the anthocyanin biosynthesis pathway were identified at the locus near the significant SNPs (<60 kbp). The beneficial allele and candidate genes should be useful in soybean breeding for improving resistance to SWM.     

Genome-wide association study for soybean cyst nematode resistance in Chinese elite soybean cultivars

Soybean cyst nematode (SCN) (Heterodera glycines Ichinohe) is a highly recalcitrant endoparasite of soybean roots, causing more yield loss than any other pest. To identify quantitative trait loci (QTL) controlling resistance to SCN (HG type 2.5.7, race 1), a genome-wide association study (GWAS) was performed. The association panel, consisting of 120 Chinese soybean cultivars, was genotyped with 7189 single nucleotide polymorphism (SNPs). A total of 6204 SNPs with minor allele frequency >0.05 were used to estimate linkage disequilibrium (LD) and population structure. The mean level of LD measured by r ² declined very rapidly to half its maximum value (0.51) at 220 kb. The overall population structure was approximately coincident with geographic origin. The GWAS results identified 13 SNPs in 7 different genomic regions significantly associated with SCN resistance. Of these, three SNPs were localized in previously mapped QTL intervals, including rhg1 and Rhg4. The GWAS results also detected 10 SNPs in 5 different genomic regions associated with SCN resistance. The identified loci explained an average of 95.5% of the phenotypic variance. The proportion of phenotypic variance was due to additive genetic variance of the validated SNPs. The present study identified multiple new loci and refined chromosomal regions of known loci associated with SCN resistance. The loci and trait-associated SNPs identified in this study can be used for developing soybean cultivars with durable resistance against SCN.     

Fine-mapping and identification of a novel locus <Emphasis Type="Italic">Rsc15</Emphasis> underlying soybean resistance to <Emphasis Type="Italic">Soybean mosaic virus</Emphasis>

Key message

Rsc15, a novel locus underlying soybean resistance to SMV, was fine mapped to a 95-kb region on chromosome 6. The Rsc15- mediated resistance is likely attributed to the gene GmPEX14 , the relative expression of which was highly correlated with the accumulation of H ₂ O ₂ along with the activities of POD and CAT during the early stages of SMV infection in RN-9.

Abstract

Soybean mosaic virus (SMV) causes severe yield losses and seed quality deterioration in soybean [Glycine max (L.) Merr.] worldwide. A series of single dominant SMV resistance genes have been identified on respective soybean chromosomes 2, 13 and 14, while one novel locus, Rsc15, underlying resistance to the virulent SMV strain SC15 from soybean cultivar RN-9 has been recently mapped to a 14.6-cM region on chromosome 6. However, candidate gene has not yet been identified within this region. In the present study, we aimed to fine map the Rsc15 region and identify candidate gene(s) for this invaluable locus. High-resolution fine-mapping revealed that the Rsc15 gene was located in a 95-kb genomic region which was flanked by the two simple sequence repeat (SSR) markers SSR_06_17 and BARCSOYSSR_06_0835. Allelic sequence comparison and expression profile analysis of candidate genes inferred that the gene Glyma.06g182600 (designated as GmPEX14) was the best candidate gene attributing for the resistance of Rsc15, and that genes encoding receptor-like kinase (RLK) (i.e., Glyma.06g175100 and Glyma.06g184400) and serine/threonine kinase (STK) (i.e., Glyma.06g182900 and Glyma.06g183500) were also potential candidates. High correlations were established between the relative expression level of GmPEX14 and the hydrogen peroxide (H₂O₂) concentration and activities of catalase (CAT) and peroxidase (POD) during the early stages of SMV-SC15 infection in RN-9. The results of the present study will be useful in marker-assisted breeding for SMV resistance and will lead to further understanding of the molecular mechanisms of host resistance against SMV.

     

Association mapping for partial resistance to Phytophthora sojae in soybean (Glycine max (L.) Merr.)

Association mapping is a powerful high-resolution mapping tool for complex traits. The objective of this study was to identify QTLs for partial resistance to Phytophthora sojae. In this study, we evaluated a total of 214 soybean accessions by the hypocotyl inoculation method, and 175 were susceptible. The 175 susceptible accessions were then evaluated for P. sojae partial resistance using slant board assays. The 175 accessions were screened with 138 SSR markers that generated 730 SSR alleles. A subset of 495 SSR loci with minor allele frequency (MAF) ≥ 0.05 was used for association mapping by the Tassel general linear model (GLM) and mixed linear model (MLM) program. This soybean population could be divided into two subpopulations and no or weak relatedness was detected between pairwise accessions. Four SSR alleles, Satt634-133, Satt634-149, Sat_222-168 and Satt301-190, associated with partial resistance to P. sojae were detected by both GLM and MLM methods. Of these identified markers, one marker, Satt301, was located in regions where P. sojae resistance QTL have been previously mapped using linkage analysis. The identified markers will help to understand the genetic basis of partial resistance, and facilitate future marker-assistant selection aimed to improve resistance to P. sojae and reduce disease-related mortality in soybean.     

Genome-Wide Association Study of Partial Resistance to P. sojae in Wild Soybeans from Heilongjiang Province,China

Phytophthora root rot (PRR) is a destructive disease of soybeans (Glycine max (L.) Merr) caused by Phytophthora sojae (P. sojae). The most effective way to prevent the disease is growing resistant or tolerant varieties. Partial resistance provides a more durable resistance against the pathogen compared to complete resistance. Wild soybean (Glycine soja Sieb. & Zucc.) seems to be an extraordinarily important gene pool for soybean improvement due to its high level of genetic variation. In this study, 242 wild soybean germplasms originating from different regions of Heilongjiang province were used to identify resistance genes to P. sojae race 1 using a genome-wide association study (GWAS). A total of nine significant SNPs were detected, repeatedly associated with P. sojae resistance and located on chromosomes 1, 10, 12, 15, 17, 19 and 20. Among them, seven favorable allelic variations associated with P. sojae resistance were evaluated by a t-test. Eight candidate genes were predicted to explore the mechanistic hypotheses of partial resistance, including Glysoja.19G051583, which encodes an LRR receptor-like serine/threonine protein kinase protein, Glysoja.19G051581, which encodes a receptor-like cytosolic serine/threonine protein kinase protein. These findings will provide additional insights into the genetic architecture of P. sojae resistance in a large sample of wild soybeans and P. sojae-resistant breeding through marker-assisted selection.     

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 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.     

RNA sequencing analysis of salt tolerance in soybean (Glycine max)

Salt stress causes foliar chlorosis and scorch, plant stunting, and eventually yield reduction in soybean. There are differential responses, namely tolerance (excluder) and intolerance (includer), among soybean germplasm. However, the genetic and physiological mechanisms for salt tolerance is complex and not clear yet. Based on the results from the screening of the RA-452 x Osage mapping population, two F_4:6 lines with extreme responses, most tolerant and most sensitive, were selected for a time-course gene expression study in which the 250 mM NaCl treatment was initially imposed at the V1 stage and continued for 24 h (hrs). Total RNA was isolated from the leaves harvested at 0, 6, 12, 24 h after the initiation of salt treatment, respectively. The RNA-Seq analysis was conducted to compare the salt tolerant genotype with salt sensitive genotype at each time point using RNA-Seq pipeline method. A total of 2374, 998, 1746, and 630 differentially expressed genes (DEGs) between salt-tolerant line and salt-sensitive line, were found at 0, 6, 12, and 24 h, respectively. The expression patterns of 154 common DEGs among all the time points were investigated, of which, six common DEGs were upregulated and seven common DEGs were downregulated in salt-tolerant line. Moreover, 13 common DEGs were dramatically expressed at all the time points. Based on Log2 (fold change) of expression level of salt-tolerant line to salt-sensitive line and gene annotation, Glyma.02G228100, Glyma.03G226000, Glyma.03G031000, Glyma.03G031400, Glyma.04G180300, Glyma.04G180400, Glyma.05 g204600, Glyma.08G189600, Glyma.13G042200, and Glyma.17G173200, were considered to be the key potential genes involving in the salt-tolerance mechanism in the soybean salt-tolerant line.     

Genome-Wide SNP Identification and Characterization in Two Soybean Cultivars with Contrasting Mungbean Yellow Mosaic India Virus Disease Resistance Traits

Mungbean yellow mosaic India virus (MYMIV) is a bipartite Geminivirus, which causes severe yield loss in soybean (Glycine max). Considering this, the present study was conducted to develop large-scale genome-wide single nucleotide polymorphism (SNP) markers and identify potential markers linked with known disease resistance loci for their effective use in genomics-assisted breeding to impart durable MYMIV tolerance. The whole-genome re-sequencing of MYMIV resistant cultivar ‘UPSM-534’ and susceptible Indian cultivar ‘JS-335’ was performed to identify high-quality SNPs and InDels (insertion and deletions). Approximately 234 and 255 million of 100-bp paired-end reads were generated from UPSM-534 and JS-335, respectively, which provided ~98% coverage of reference soybean genome. A total of 3083987 SNPs (1559556 in UPSM-534 and 1524431 in JS-335) and 562858 InDels (281958 in UPSM-534 and 280900 in JS-335) were identified. Of these, 1514 SNPs were found to be present in 564 candidate disease resistance genes. Among these, 829 non-synonymous and 671 synonymous SNPs were detected in 266 and 286 defence-related genes, respectively. Noteworthy, a non-synonymous SNP (in chromosome 18, named 18-1861613) at the 149^th base-pair of LEUCINE-RICH REPEAT RECEPTOR-LIKE PROTEIN KINASE gene responsible for a G/C transversion [proline (CCC) to alanine(GCC)] was identified and validated in a set of 12 soybean cultivars. Taken together, the present study generated a large-scale genomic resource such as, SNPs and InDels at a genome-wide scale that will facilitate the dissection of various complex traits through construction of high-density linkage maps and fine mapping. In the present scenario, these markers can be effectively used to design high-density SNP arrays for their large-scale validation and high-throughput genotyping in diverse natural and mapping populations, which could accelerate genomics-assisted MYMIV disease resistance breeding in soybean.     

Inheritance,fine-mapping,and candidate gene analyses of resistance to soybean mosaic virus strain SC5 in soybean

Soybean mosaic virus (SMV) is one of the most devastating pathogens for soybeans in China. Among the country-wide 22 strains, SC5 dominates in Huang-Huai and Changjiang valleys. For controlling its damage, the resistance gene was searched through Mendelian inheritance study, gene fine-mapping, and candidate gene analysis combined with qRT-PCR (quantitative real-time polymerase chain reaction) analysis. The parents F₁, F₂, and RILs (recombinant inbred lines) of the cross Kefeng-1 (Resistance, R)?×?NN1138-2 (Susceptible, S) were used to examine the inheritance of SC5-resistance. The F₁ was resistant and the F₂ and RILs segregated in a 3R:1S and 1R:1S ratio, respectively, indicating a single dominant gene conferring the Kefeng-1 resistance. Subsequently, the genomic region conferring the resistance was found in “Bin 352–Bin353 with 500 kb” on Chromosome 2 using the phenotyping data of the 427 RILs and a high-density genetic map with 4703 bin markers. In the 500 kb genomic region, 38 putative genes are contained. The association analysis between the SNPs in a putative gene and the resistance phenotype for the 427 RILs prioritized 11 candidate genes using Chi-square criterion. The expression levels of these genes were tested by qRT-PCR. On infection with SC5, 7 out of the 11 genes had differential expression in Kefeng-1 and NN1138-2. Furthermore, integrating SNP-phenotype association analysis with qRT-PCR expression profiling analysis, Glyma02g13495 was found the most possible candidate gene for SC5-resistance. This finding can facilitate the breeding for SC5-resistance through marker-assisted selection and provide a platform to gain a better understanding of SMV-resistance gene system in soybean.     

Identification and Candidate Gene Analysis of a Novel Phytophthora Resistance Gene Rps10 in a Chinese Soybean Cultivar

Resistance to Phytophthora sojae isolate PsMC1 was evaluated in 102 F_2∶3 families derived from a cross between the resistant soybean cultivar Wandou 15 and the susceptible cultivar Williams and genotyped using simple sequence repeat (SSR) markers. The segregation ratio of resistant, segregating, and susceptible phenotypes in the population suggested that the resistance in Wandou 15 was dominant and monogenic. Twenty-six polymorphic SSR markers were identified on soybean chromosome 17 (Molecular linkage group D2; MLG D2), which were linked to the resistance gene based on bulked segregation analysis (BSA). Markers Sattwd15-24/25 and Sattwd15-47 flanked the resistance gene at a distance of 0.5 cM and 0.8 cM, respectively. Two cosegregating markers, Sattwd15-28 and Sattwd15-32, were also screened in this region. This is the first Rps resistance gene mapped on chromosome 17, which is designated as Rps10. Eight putative genes were found in the mapped region between markers Sattwd15-24/25 and Sattwd15-47. Among them, two candidate genes encoding serine/threonine (Ser/Thr) protein kinases in Wandou 15 and Williams were identified and sequenced. And the differences in genomic sequence and the putative amino acid sequence, respectively, were identified within each candidate gene between Wandou 15 and Williams. This novel gene Rps10 and the linked markers should be useful in developing soybean cultivars with durable resistance to P. sojae.     

Variation in CHI3LI in Relation to Type 2 Diabetes and Related Quantitative Traits

Background

CHI3LI encoding the inflammatory glycoprotein YKL-40 is located on chromosome 1q32.1. YKL-40 is involved in inflammatory processes and patients with Type 2 Diabetes (T2D) have elevated circulating YKL-40 levels which correlate with their level of insulin resistance. Interestingly, it has been reported that rs10399931 (−329 G/A) of CHI3LI contributes to the inter-individual plasma YKL-40 levels in patients with sarcoidosis, and that rs4950928 (−131 C/G) is a susceptibility polymorphism for asthma and a decline in lung function. We hypothesized that single nucleotide polymorphisms (SNPs) or haplotypes thereof the CHI3LI locus might influence risk of T2D. The aim of the present study was to investigate the putative association between SNPs and haplotype blocks of CHI3LI and T2D and T2D related quantitative traits.

Methods/Principal Findings

Eleven SNPs of CHI3LI were genotyped in 6514 individuals from the Inter99 cohort and 2924 individuals from the outpatient clinic at Steno Diabetes Center. In cas-control studies a total of 2345 T2D patients and 5302 individuals with a normal glucose tolerance test were examined.We found no association between rs10399931 (OR, 0.98 (CI, 0.88–1.10), p = 0.76), rs4950928 (0.98 (0.87–1.10), p = 0.68) or any of the other SNPs with T2D. Similarly, we found no significant association between any of the 11 tgSNPs and T2D related quantitative traits, all p>0.14. None of the identified haplotype blocks of CHI3LI showed any association with T2D, all p>0.16.

Conclusions/Significance

None of the examined SNPs or haplotype blocks of CHI3LI showed any association with T2D or T2D related quantitative traits. Estimates of insulin resistance and dysregulated glucose homeostasis in T2D do not seem to be accounted for by the examined variations of CHI3LI.     

Quantitative trait loci controlling aluminum tolerance in soybean: candidate gene and single nucleotide polymorphism marker discovery

Aluminum (Al) toxicity is an important abiotic stress that affects soybean production in acidic soils throughout the world. Development of Al-tolerant cultivars is an efficient and environmentally friendly solution to the problem. A previous report identified quantitative trait loci (QTL) for Al tolerance inherited from PI 416937, using restriction fragment length polymorphism markers, in a population of Young × PI 416937. The population was genotyped with 162 simple sequence repeats to enhance the power of QTL detection and enable the selection of candidate genes for functional marker development. Two QTL that explained 54 % of the phenotypic variation in root extension under Al stress conditions (HIAL) were refined on chromosomes (chr) Gm08 and Gm16. Three QTL located on chr Gm08, Gm16 and Gm19 explained 59 % of the phenotypic variation in root extension as a percent of control (PC). Two major QTL, designated qAL_HIAL_08 and qAL_PC_08, controlling HIAL and PC, respectively, were mapped to the same genomic region on chr Gm08 and inherited their favorable allele from PI 416937. These QTL explained 45 and 41 % of phenotypic variation in HIAL and PC, respectively. Six homologues for citrate synthase (CS) genes were found in the soybean genome sequence at chr Gm02, Gm08, Gm14, Gm15, and Gm18. Sixteen single nucleotide polymorphisms (SNPs) were identified in the CS homologue on chr Gm08. A SimpleProbe assay of Glyma08g42400-SNP was developed for the major QTL on chr Gm08. The SNPs identified from this region could be used for marker-assisted selection of Al tolerance.     

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.     

Confirmation and fine‐mapping of clinical mastitis and somatic cell score QTL in Nordic Holstein cattle

A genome‐wide association study of 2098 progeny‐tested Nordic Holstein bulls genotyped for 36 387 SNPs on 29 autosomes was conducted to confirm and fine‐map quantitative trait loci (QTL) for mastitis traits identified earlier using linkage analysis with sparse microsatellite markers in the same population. We used linear mixed model analysis where a polygenic genetic effect was fitted as a random effect and single SNPs were successively included as fixed effects in the model. We detected 143 SNP‐by‐trait significant associations (P < 0.0001) on 20 chromosomes affecting mastitis‐related traits. Among them, 21 SNP‐by‐trait combinations exceeded the genome‐wide significant threshold. For 12 chromosomes, both the present association study and the previous linkage study detected QTL, and of these, six were in the same chromosomal locations. Strong associations of SNPs with mastitis traits were observed on bovine autosomes 6, 13, 14 and 20. Possible candidate genes for these QTL were identified. Identification of SNPs in linkage disequilibrium with QTL will enable marker‐based selection for mastitis resistance. The candidate genes identified should be further studied to detect candidate polymorphisms underlying these QTL.     

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.     

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.