Stacks 2: Analytical methods for paired‐end sequencing improve RADseq‐based population genomics

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 fir...

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Veröffentlicht in:Molecular ecology Jg. 28; H. 21; S. 4737 - 4754
Hauptverfasser: Rochette, Nicolas C., Rivera‐Colón, Angel G., Catchen, Julian M.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: England Blackwell Publishing Ltd 01.11.2019
Schlagworte:
Algorithms
analytical methods
Bayesian analysis
Bayesian theory
bioinformatics
Computer programs
Computer simulation
computer software
conservation genetics
data collection
Datasets
Empirical analysis
Genetics
genotype calling
Genotypes
Genotyping
Graph theory
haplotype phasing
Haplotypes
Loci
metagenomics
Metapopulations
Population genetics
Population studies
restriction endonucleases
restriction‐site associated DNA sequencing
Single-nucleotide polymorphism
Software
Stacks
population genetics
genotype calling
restriction-site associated DNA sequencing
bioinformatics
conservation genetics
haplotype phasing
ISSN:0962-1083, 1365-294X, 1365-294X
Online-Zugang:Volltext
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Zusammenfassung: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 natively capable of using paired‐end sequencing to derive short contigs from de novo RAD data. Stacks version 2 employs a de Bruijn graph assembler to build and connect contigs from forward and reverse reads for each de novo RAD locus, which it then uses as a reference for read alignments. The new architecture allows all the individuals in a metapopulation 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 400–800 bp in length. To prove its recall and precision, we tested the software with simulated data and compared reference‐aligned and de novo analyses of three empirical data sets. Our study shows that the latest version of Stacks is highly accurate and outperforms other software in assembling and genotyping paired‐end de novo data sets.
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ISSN:0962-1083
1365-294X
1365-294X
DOI:10.1111/mec.15253