Bioinformatic Analysis of Genotype by Sequencing (GBS) Data with NGSEP

Genotype by sequencing (GBS) protocols provide a cost-effective approach to perform high-resolution genomic analysis of entire populations in different species. These protocols are based on the initial digestion of DNA with known restriction enzymes, to generate sequencing fragments at predictable and reproducible sites. This allows to genotype thousands of genetic markers on hundreds of individuals.

Because GBS protocols achieve parallel genotyping through high throughput sequencing (HTS), every GBS protocol must include a bioinformatics pipeline for analysis of HTS data. Our bioinformatics group recently developed the Next Generation Sequencing Eclipse Plugin (NGSEP) for accurate, efficient, and user-friendly analysis of HTS data. Here we present the latest functionalities implemented in NGSEP in the context of analyzing GBS data.

We developed a one step wizard to perform parallel read alignment, variants identification and genotyping from HTS reads from entire populations. We added new filters for variants, samples and genotype calls, as well as calculation of summary statistics overall and per sample, and diversity statistics per site. For integration with downstream analysis tools (e.g: to calculate population structure, genetic maps, GWAS or genomic selection), NGSEP translates genotype calls to several widely used formats.

We assessed the accuracy of NGSEP on two F1 cassava populations and on an inbred bean population. We showed that NGSEP provides similar or better accuracy compared to other commonly used software for variants detection such as GATK, Samtools and Tassel. NGSEP is an efficient bioinformatic package for analyzing the genomic variability obtained from GBS experiments for population genomics.