Fast-GBS: a new pipeline for the efficient and highly accurate calling of SNPs from genotyping-by-sequencing data

Abstract

BackgroundNext-generation sequencing (NGS) technologies have accelerated considerably the investigation into the composition of genomes and their functions. Genotyping-by-sequencing (GBS) is a genotyping approach that makes use of NGS to rapidly and economically scan a genome. It has been shown to allow the simultaneous discovery and genotyping of thousands to millions of SNPs across a wide range of species. For most users, the main challenge in GBS is the bioinformatics analysis of the large amount of sequence information derived from sequencing GBS libraries in view of calling alleles at SNP loci. Herein we describe a new GBS bioinformatics pipeline, Fast-GBS, designed to provide highly accurate genotyping, to require modest computing resources and to offer ease of use.ResultsFast-GBS is built upon standard bioinformatics language and file formats, is capable of handling data from different sequencing platforms, is capable of detecting different kinds of variants (SNPs, MNPs, and Indels). To illustrate its performance, we called variants in three collections of samples (soybean, barley, and potato) that cover a range of different genome sizes, levels of genome complexity, and ploidy. Within these small sets of samples, we called 35 k, 32 k and 38 k SNPs for soybean, barley and potato, respectively. To assess genotype accuracy, we compared these GBS-derived SNP genotypes with independent data sets obtained from whole-genome sequencing or SNP arrays. This analysis yielded estimated accuracies of 98.7, 95.2, and 94% for soybean, barley, and potato, respectively.ConclusionsWe conclude that Fast-GBS provides a highly efficient and reliable tool for calling SNPs from GBS data.

Temporal variation in spatial genetic structure during population outbreaks: Distinguishing among different potential drivers of spatial synchrony

“…Sequence processing through the fast-GBS pipeline (Torkamaneh et al, 2017) Most SNPs (73,489; 99.4%) had at least one missing genotype which was then imputed (mean fraction of missing genotype per SNP ± SD = 0.17 ± 0.15; range = 0-0.49; Figure S1) and 0.7% (480) of imputed SNPs were removed when filtering for R 2 . Many SNPs (69,045; 94%) were discarded when filtering for MAF and LD.…”

“…Finally, an additional PCR step using a selective reverse primer extending a single base (C) into the insert past the 3′ restriction site was used to selectively amplify one-quarter of the total number of fragments, thereby increasing the read depth of sequenced fragments(Sonah et al, 2013). Single-end sequencing (100 bp reads) of these libraries was then performed with an Illumina HiSeq2000 (McGill University-Génome Québec Innovation Centre, Montreal, QC).Bioinformatic processing of reads was performed using the Fast-GBS pipeline(Torkamaneh, Laroche, Bastien, Abed, & Belzile, 2017…”

Soybean Haplotype Map (GmHapMap): A Universal Resource for Soybean Translational and Functional Genomics

“…Sequencing reads from all 1,007 accessions were processed using the same analytical bioinformatics pipeline (Fast-WGS) (Torkamaneh et al 2017) to create a uniform catalogue of genetic variants. In brief, the 100-150-bp paired-end reads were mapped against the G. max reference genome [Gmax_275 (Wm82.a2)] (Schmutz et al 2010).…”

“…A first set of 20,087 accessions (the entire USDA Soybean Germplasm Collection) had been characterized using the SoySNP50K iSelect Bead Chip (Song et al 2013) to yield a set of 43K polymorphic markers. A second set comprised 1,531 accessions which had been subjected to genotyping-by-sequencing (GBS; Ape KI protocol) (Sonah et al 2013) and in which SNPs had been called using the Fast-GBS pipeline (Torkamaneh et al 2017). Finally, a third set of 1,531 accessions (GBS set) with a combined SNP catalogue derived from GBS and SoySNP50K ( Supplementary Note ).…”

Identification of quantitative trait loci for seed isoflavone concentration in soybean (Glycine max) against soybean cyst nematode stress

“…For genotyping by sequencing (GBS), 30 μl samples of 10 ng/μl DNA were shipped to the Université Laval's Plate‐forme D'analyses Génomiques (Université Laval, Québec, Canada) where GBS libraries were constructed using the ApeKI restriction enzyme and then sequenced using an Ion Proton Sequencer. Sequence data were processed using the Fast‐GBS pipeline (Torkamenah, Laroche, Bastien, Abed, & Belzile, ). Single nucleotide polymorphisms (SNPs) were filtered to discard loci with >20% missing data, and a minimum minor allele frequency of 0.3 was set prior to imputation with Beagle v4.1 (Browning & Browning, ).…”