Genome-Wide SNP Calling Using Next Generation Sequencing Data in Tomato

Abstract

The tomato (Solanum lycopersicum L.) is a model plant for genome research in Solanaceae, as well as for studying crop breeding. Genome-wide single nucleotide polymorphisms (SNPs) are a valuable resource in genetic research and breeding. However, to do discovery of genome-wide SNPs, most methods require expensive high-depth sequencing. Here, we describe a method for SNP calling using a modified version of SAMtools that improved its sensitivity. We analyzed 90 Gb of raw sequence data from next-generation sequencing of two resequencing and seven transcriptome data sets from several tomato accessions. Our study identified 4,812,432 non-redundant SNPs. Moreover, the workflow of SNP calling was improved by aligning the reference genome with its own raw data. Using this approach, 131,785 SNPs were discovered from transcriptome data of seven accessions. In addition, 4,680,647 SNPs were identified from the genome of S. pimpinellifolium, which are 60 times more than 71,637 of the PI212816 transcriptome. SNP distribution was compared between the whole genome and transcriptome of S. pimpinellifolium. Moreover, we surveyed the location of SNPs within genic and intergenic regions. Our results indicated that the sufficient genome-wide SNP markers and very sensitive SNP calling method allow for application of marker assisted breeding and genome-wide association studies.

Genome-wide SNP discovery and QTL mapping for fruit quality traits in inbred backcross lines (IBLs) of solanum pimpinellifolium using genotyping by sequencing

“…In comparison with previous work, this study discovered fewer validated SNPs than are available in The Solanaceae Genomics Network database (9,226 SNPs) and those reported by Chen et al [15] (4,697 SNPs). The current number of SNPs is also much lower than discovered by Causse et al [16] (16,000 SNPs) and Kim et al [17] (4,680,647); however, these SNPs were not validated. The average frequency of SNPs identified in this study was 1 SNP per 256.4 kb, much higher than reported for the S. lycopersicum  ×  S. pimpinellifolium linkage maps of Salinan et al [13] (1 SNP per 8,482 kb), Capel et al [14] (1 SNP per 4,077 kb) and Chen et al [15] (1 SNP per 1,821 kb).…”

“…In the work of Causse et al [16], eight (four cherry-type and four cultivars) S. lycopersicum accessions were sequenced to identify 16,000 unique, non-synonymous SNPs and 1,686 putative copy-number variations (CNVs). The other study used sequencing data available from the NCBI database for nine tomato accessions (two resequenced genomes and seven transcriptomes and yielded 4,680,647 SNPs [17]. However, none of the SNPs from these two projects were validated in segregated populations.…”

A Combinatorial Approach of Biparental QTL Mapping and Genome-Wide Association Analysis Identifies Candidate Genes for Phytophthora Blight Resistance in Sesame

“…However, associated SNPs to Phytophthora resistance for mining putative candidate disease resistance genes were located in intergenic regions not in exon regions. It is reported that the number of SNPs called from the GBS approach may not be large enough for GWAS and that SNP density in genic regions is much lower than that in intergenic regions (Ahn et al, 2018; Kim et al, 2014). Although, our germplasm panel subjected to GWAS identified sufficient and common SNPs associated with Phytophthora blight resistance to the three main strains (isolates KACC48121, KACC48120, No2040) which represents dominant types of strains in Korea and no resistance report in elsewhere before.…”

Identification of potential gene‐associated major traits using GBS‐GWAS for Korean apple germplasm collections

“…SNPs were discovered through comparison between the reference genome and each sample‐specific candidate for construction of a combined list and for comparison analysis among the population and raw SNP positions by the SEEDERS in‐house script. The SNP matrix was generated after filtering non‐SNP loci, and, finally, significant candidate SNPs were selected from the filtered SNPs, for use in the genetic diversity and population structure assays, with the following filtering set‐up conditions: SNP loci = biallelic; missing rate <10%; and minor allele frequency >5% (Kim, Oh, Lee, Lee, & Jo, ).…”