Restriction site‐associated DNA sequencing, genotyping error estimation and de novo assembly optimization for population genetic inference. (3rd July 2014)

• Record Type: Journal Article
• Authors: Mastretta‐Yanes, A.; Arrigo, N.; Alvarez, N.; Jorgensen, T. H.; Piñero, D.; Emerson, B. C.
• Is Part Of: Molecular ecology resources. Volume 15:Number 1(2015:Jan.)
• Page Start: 28
• Page End: 41
• Publication Date: 2014-07-03
• Subjects: Molecular ecology -- Periodicals; 572.8
• DOI: 10.1111/1755-0998.12291
• Languages: English
• ISSNs: 1755-098X

Abstract

<abstract abstract-type="main" id="men12291-abs-0001"> <title>Abstract</title> <p>Restriction site‐associated DNA sequencing (RADseq) provides researchers with the ability to record genetic polymorphism across thousands of loci for nonmodel organisms, potentially revolutionizing the field of molecular ecology. However, as with other genotyping methods, RADseq is prone to a number of sources of error that may have consequential effects for population genetic inferences, and these have received only limited attention in terms of the estimation and reporting of genotyping error rates. Here we use individual sample replicates, under the expectation of identical genotypes, to quantify genotyping error in the absence of a reference genome. We then use sample replicates to (i) optimize <italic>de novo</italic> assembly parameters within the program <italic>Stacks, </italic> by minimizing error and maximizing the retrieval of informative loci; and (ii) quantify error rates for loci, alleles and single‐nucleotide polymorphisms. As an empirical example, we use a double‐digest RAD data set of a nonmodel plant species, <italic>Berberis alpina</italic>, collected from high‐altitude mountains in Mexico.</p> </abstract>