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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Vydané v:	Molecular ecology Ročník 28; číslo 21; s. 4737 - 4754
Hlavní autori:	Rochette, Nicolas C., Rivera‐Colón, Angel G., Catchen, Julian M.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	England Blackwell Publishing Ltd 01.11.2019
Predmet:	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
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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 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.
AbstractList	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. 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. 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.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.
Author	Catchen, Julian M. Rivera‐Colón, Angel G. Rochette, Nicolas C.
Author_xml	– sequence: 1 givenname: Nicolas C. orcidid: 0000-0003-1899-1765 surname: Rochette fullname: Rochette, Nicolas C. organization: University of Illinois at Urbana‐Champaign – sequence: 2 givenname: Angel G. orcidid: 0000-0001-9097-3241 surname: Rivera‐Colón fullname: Rivera‐Colón, Angel G. organization: University of Illinois at Urbana‐Champaign – sequence: 3 givenname: Julian M. orcidid: 0000-0002-4798-660X surname: Catchen fullname: Catchen, Julian M. email: jcatchen@illinois.edu organization: University of Illinois at Urbana‐Champaign
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/31550391$$D View this record in MEDLINE/PubMed
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Snippet	For half a century population genetics studies have put type II restriction endonucleases to work. Now, coupled with massively‐parallel, short‐read sequencing,... For half a century population genetics studies have put type II restriction endonucleases to work. Now, coupled with massively-parallel, short-read sequencing,...
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SubjectTerms	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
Title	Stacks 2: Analytical methods for paired‐end sequencing improve RADseq‐based population genomics
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