TASSEL-GBS: a high capacity genotyping by sequencing analysis pipeline

PLoS One. 2014 Feb 28;9(2):e90346. doi: 10.1371/journal.pone.0090346. eCollection 2014.

Abstract

Genotyping by sequencing (GBS) is a next generation sequencing based method that takes advantage of reduced representation to enable high throughput genotyping of large numbers of individuals at a large number of SNP markers. The relatively straightforward, robust, and cost-effective GBS protocol is currently being applied in numerous species by a large number of researchers. Herein we describe a bioinformatics pipeline, TASSEL-GBS, designed for the efficient processing of raw GBS sequence data into SNP genotypes. The TASSEL-GBS pipeline successfully fulfills the following key design criteria: (1) Ability to run on the modest computing resources that are typically available to small breeding or ecological research programs, including desktop or laptop machines with only 8-16 GB of RAM, (2) Scalability from small to extremely large studies, where hundreds of thousands or even millions of SNPs can be scored in up to 100,000 individuals (e.g., for large breeding programs or genetic surveys), and (3) Applicability in an accelerated breeding context, requiring rapid turnover from tissue collection to genotypes. Although a reference genome is required, the pipeline can also be run with an unfinished "pseudo-reference" consisting of numerous contigs. We describe the TASSEL-GBS pipeline in detail and benchmark it based upon a large scale, species wide analysis in maize (Zea mays), where the average error rate was reduced to 0.0042 through application of population genetic-based SNP filters. Overall, the GBS assay and the TASSEL-GBS pipeline provide robust tools for studying genomic diversity.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Animals
  • Breeding
  • Data Mining
  • Genetics, Population
  • Genotyping Techniques / economics
  • Genotyping Techniques / methods*
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Polymorphism, Single Nucleotide
  • Software*
  • Zea mays / genetics*

Grant support

This work was supported by the National Science Foundation (www.nsf.gov) under the Plant Genome Research Program (PGRP) (grant numbers DBI-0820619 and IOS-1238014) and the Basic Research to Enable Agricultural Development (BREAD) project (ID:IOS-0965342), as well as by the USDA-ARS (www.usda.gov). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.