Gene-based SNP identification and validation in soybean using next-generation transcriptome sequencing
Gene-based molecular markers are increasingly used in crop breeding programs for marker-assisted selection. However, identification of genetic variants associated with important agronomic traits has remained a difficult task in soybean. RNA-Seq provides an efficient way, other than assessing global expression variations of coding genes, to discover gene-based SNPs at the whole genome level. In this study, RNA isolated from four soybean accessions each with three replications was subjected to high-throughput sequencing and a range of 44.2–65.9 million paired-end reads were generated for each library. A total of 75,209 SNPs were identified among different genotypes after combination of replications, 89.1% of which were located in expressed regions and 27.0% resulted in amino acid changes. GO enrichment analysis revealed that most significant enriched genes with nonsynonymous SNPs were involved in ribonucleotide binding or catalytic activity. Of 22 SNPs subjected to PCR amplification and Sanger sequencing, all of them were validated. To test the utility of identified SNPs, these validated SNPs were also assessed by genotyping a relative large population with 393 wild and cultivated soybean accessions. These SNPs identified by RNA-Seq provide a useful resource for genetic and genomic studies of soybean. Moreover, the collection of nonsynonymous SNPs annotated with their predicted functional effects also provides a valuable asset for further discovery of genes, identification of gene variants, and development of functional markers.
KeywordsRNA-Seq Single-nucleotide polymorphism Soybean Nonsynonymous SNPs Next-generation sequencing
This work was supported by the National Natural Science Foundation of China (31471520), 13th Five-Year Plan for Precise Identification and Germplasm Enhancement of Economic Crops, and the Agricultural Science and Technology Innovation Program (ASTIP) of Chinese Academy of Agricultural Sciences.
YG and LJQ conceived and designed the experiments. YG, BS, JT and FZ performed the experiments. YG and LJQ analyzed data and wrote the manuscript. All authors read and approved the manuscript.
Compliance with ethical standards
Conflict of interest
All authors declare that they have no conflict of interest.
Research involving human and animal participants
This article does not contain any studies with human participants or animals performed by any of the authors.
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