Stacks 2: Analytical Methods for Paired-end Sequencing Improve RADseq-based Population Genomics

作者：Nicolas C. Rochette, Angel G. Rivera‐Colón, Julian Catchen · 发表于：bioRxiv (Cold Spring Harbor Laboratory) · 年份：2019 · DOI：10.1101/615385 · 被引用次数：88 · 研究领域：CRISPR and Genetic Engineering、Genomics and Phylogenetic Studies、RNA and protein synthesis mechanisms

Abstract For half a century population genetics studies have put type II restriction endonucleases to work. Now, coupled with massively-parallel, short-read sequencing, the family of RAD protocols that wields these enzymes has generated vast genetic knowledge from the natural world. Here we describe the first software capable of using paired-end sequencing to derive short contigs from de novo RAD data natively. Stacks version 2 employs a de Bruijn graph assembler to build contigs from paired-end reads and overlap those contigs with the corresponding single-end loci. The new architecture allows all the individuals in a meta population to be considered at the same time as each RAD locus is processed. This enables a Bayesian genotype caller to provide precise SNPs, and a robust algorithm to phase those SNPs into long haplotypes – generating RAD loci that are 400-800bp in length. To prove its recall and precision, we test the software with simulated data and compare reference-aligned and de novo analyses of three empirical datasets. We show that the latest version of Stacks is highly accurate and outperforms other software in assembling and genotyping paired-end de novo datasets.