Eun-Young Hwang

A genome-wide association study of seed protein and oil content in soybean.

BackgroundAssociation analysis is an alternative to conventional family-based methods to detect the location of gene(s) or quantitative trait loci (QTL) and provides relatively high resolution in terms of defining the genome position of a gene or QTL. Seed protein and oil concentration are quantitative traits which are determined by the interaction among many genes with small to moderate genetic effects and their interaction with the environment. In this study, a genome-wide association study (GWAS) was performed to identify quantitative trait loci (QTL) controlling seed protein and oil concentration in 298 soybean germplasm accessions exhibiting a wide range of seed protein and oil content.ResultsA total of 55,159 single nucleotide polymorphisms (SNPs) were genotyped using various methods including Illumina Infinium and GoldenGate assays and 31,954 markers with minor allele frequency >0.10 were used to estimate linkage disequilibrium (LD) in heterochromatic and euchromatic regions. In euchromatic regions, the mean LD (r2) rapidly declined to 0.2 within 360 Kbp, whereas the mean LD declined to 0.2 at 9,600 Kbp in heterochromatic regions. The GWAS results identified 40 SNPs in 17 different genomic regions significantly associated with seed protein. Of these, the five SNPs with the highest associations and seven adjacent SNPs were located in the 27.6-30.0 Mbp region of Gm20. A major seed protein QTL has been previously mapped to the same location and potential candidate genes have recently been identified in this region. The GWAS results also detected 25 SNPs in 13 different genomic regions associated with seed oil. Of these markers, seven SNPs had a significant association with both protein and oil.ConclusionsThis research indicated that GWAS not only identified most of the previously reported QTL controlling seed protein and oil, but also resulted in narrower genomic regions than the regions reported as containing these QTL. The narrower GWAS-defined genome regions will allow more precise marker-assisted allele selection and will expedite positional cloning of the causal gene(s).

High-throughput SNP discovery and assay development in common bean

BackgroundNext generation sequencing has significantly increased the speed at which single nucleotide polymorphisms (SNPs) can be discovered and subsequently used as molecular markers for research. Unfortunately, for species such as common bean (Phaseolus vulgaris L.) which do not have a whole genome sequence available, the use of next generation sequencing for SNP discovery is much more difficult and costly. To this end we developed a method which couples sequences obtained from the Roche 454-FLX system (454) with the Illumina Genome Analyzer (GA) for high-throughput SNP discovery.ResultsUsing a multi-tier reduced representation library we discovered a total of 3,487 SNPs of which 2,795 contained sufficient flanking genomic sequence for SNP assay development. Using Sanger sequencing to determine the validation rate of these SNPs, we found that 86% are likely to be true SNPs. Furthermore, we designed a GoldenGate assay which contained 1,050 of the 3,487 predicted SNPs. A total of 827 of the 1,050 SNPs produced a working GoldenGate assay (79%).ConclusionsThrough combining two next generation sequencing techniques we have developed a method that allows high-throughput SNP discovery in any diploid organism without the need of a whole genome sequence or the creation of normalized cDNA libraries. The need to only perform one 454 run and one GA sequencer run allows high-throughput SNP discovery with sufficient sequence for assay development to be performed in organisms, such as common bean, which have limited genomic resources.

Discovery of single nucleotide polymorphisms in soybean using primers designed from ESTs

Discovery of single nucleotide polymorphisms (SNPs), including small insertions and deletions (indels), is one of the hot topics in genetic research. SNPs were surveyed using nine soybean genotypes from Korea. Sequence variations in a total of 110 genes from GenBank among the nine genotypes were studied using genomic DNA as a template. Direct fluorescent dideoxynucleotide sequencing data of PCR products from primers designed from soybean ESTs were analyzed by SeqScape software to ensure high accuracy. Approximately 70% of the primer sets produced a single PCR product from which reliable sequence data were obtained, and 23.6% of these had at least one SNP. Overall, a total of 110 ESTs for SNPs were screened in 33,262 bp, consisting of 16,302 bp from coding regions and 16,960 bp from adjacent non-coding regions (5′ UTR, 3′ UTR and introns). SNPs in coding and non-coding regions occurred at a frequency of 1 per 3,260 bp, corresponding to a nucleotide diversity (θ) of 0.00011, and 1 per 278 bp (θ = 0.00128), respectively. This suggested that the higher level of sequence variation in non-coding regions would make them good regions in which to search for SNPs. The SNPs in partial cDNA sequences could be valuable for gene-targeted map construction in soybean.

SNP Assay Development for Linkage Map Construction, Anchoring Whole-Genome Sequence, and Other Genetic and Genomic Applications in Common Bean

A total of 992,682 single-nucleotide polymorphisms (SNPs) was identified as ideal for Illumina Infinium II BeadChip design after sequencing a diverse set of 17 common bean (Phaseolus vulgaris L) varieties with the aid of next-generation sequencing technology. From these, two BeadChips each with >5000 SNPs were designed. The BARCBean6K_1 BeadChip was selected for the purpose of optimizing polymorphism among market classes and, when possible, SNPs were targeted to sequence scaffolds in the Phaseolus vulgaris 14× genome assembly with sequence lengths >10 kb. The BARCBean6K_2 BeadChip was designed with the objective of anchoring additional scaffolds and to facilitate orientation of large scaffolds. Analysis of 267 F2 plants from a cross of varieties Stampede × Red Hawk with the two BeadChips resulted in linkage maps with a total of 7040 markers including 7015 SNPs. With the linkage map, a total of 432.3 Mb of sequence from 2766 scaffolds was anchored to create the Phaseolus vulgaris v1.0 assembly, which accounted for approximately 89% of the 487 Mb of available sequence scaffolds of the Phaseolus vulgaris v0.9 assembly. A core set of 6000 SNPs (BARCBean6K_3 BeadChip) with high genotyping quality and polymorphism was selected based on the genotyping of 365 dry bean and 134 snap bean accessions with the BARCBean6K_1 and BARCBean6K_2 BeadChips. The BARCBean6K_3 BeadChip is a useful tool for genetics and genomics research and it is widely used by breeders and geneticists in the United States and abroad.

A Soybean Transcript Map: Gene Distribution, Haplotype and SNP Analysis

The first genetic transcript map of the soybean genome was created by mapping one SNP in each of 1141 genes in one or more of three recombinant inbred line mapping populations, thus providing a picture of the distribution of genic sequences across the mapped portion of the genome. Single-nucleotide polymorphisms (SNPs) were discovered via the resequencing of sequence-tagged sites (STSs) developed from expressed sequence tag (EST) sequence. From an initial set of 9459 polymerase chain reaction primer sets designed to a diverse set of genes, 4240 STSs were amplified and sequenced in each of six diverse soybean genotypes. In the resulting 2.44 Mbp of aligned sequence, a total of 5551 SNPs were discovered, including 4712 single-base changes and 839 indels for an average nucleotide diversity of θ = 0.000997. The analysis of the observed genetic distances between adjacent genes vs. the theoretical distribution based upon the assumption of a random distribution of genes across the 20 soybean linkage groups clearly indicated that genes were clustered. Of the 1141 genes, 291 mapped to 72 of the 112 gaps of 5–10 cM in the preexisting simple sequence repeat (SSR)-based map, while 111 genes mapped in 19 of the 26 gaps >10 cM. The addition of 1141 sequence-based genic markers to the soybean genome map will provide an important resource to soybean geneticists for quantitative trait locus discovery and map-based cloning, as well as to soybean breeders who increasingly depend upon marker-assisted selection in cultivar improvement.

Molecular Characterization of Hypernodulation in Soybean

SS2-2, a hypernodulating soybean mutant was isolated by EMS mutagenesis from Sinpaldalkong 2. This auto-regulation mutant showed greater number of nodules and smaller plant size than its wild type Sinpaldalkong 2. SSR markers were used to identify DNA variation at SSR loci from different soybean LG. The only SSR marker that detected a length polymorphism between SS2-2 and its wild type ancestor was Satt294 on LG C1 instead of LG H, locating a hypernodulating gene. Sequencing data of flanking Satt294 indicated that the size variation was due to extra stretch of TTA repeats of the SSR motif in SS2-2, along with G transversion. In spite of phenotypic differences between the wild type and its hypernodulating mutants, genomic DNA poly-morphisms at microsatellite loci could not control regulation of nodule formation. The cDNA-AFLP method was applied to compare differential display of cDNA between Sinpaldalkong 2 and SS2-2. After isolation and sequence comparison with many AELP fragments, several interesting genes were identified. Northern blot analysis, immunolocalization and/or the yeast two-hybrid system with these genes might provide information on regulation of nodule development in SS2-2.