The capability to generate densely sampled single nucleotide polymorphism (SNP) data is essential in diverse subdisciplines of biology, including crop breeding, pathology, forensics, forestry, ecology, evolution and conservation. However, the wet‐laboratory expertise and bioinformatics training required to conduct genome‐scale variant discovery remain limiting factors for investigators with limited resources. Here we present ISSRseq, a PCR‐based method for reduced representation of genomic variation using simple sequence repeats as priming sites to sequence inter simple sequence repeat (ISSR) regions. Briefly, ISSR regions are amplified with single primers, pooled, used to construct sequencing libraries with a commercially available kit, and sequenced on the Illumina platform. We also present a flexible bioinformatic pipeline that assembles ISSR loci, calls and hard filters variants, outputs data matrices in common formats, and conducts population analyses using R. Using three angiosperm species as case studies, we demonstrate that ISSRseq is highly repeatable, necessitates only simple wet‐laboratory skills and commonplace instrumentation, is flexible in terms of the number of single primers used, and can generate genomic‐scale variant discovery on par with existing RRS methods which require more complex wet‐laboratory procedures. ISSRseq represents a straightforward approach to SNP genotyping in any organism, and we predict that this method will be particularly useful for those studying population genomics and phylogeography of non‐model organisms. Furthermore, the ease of ISSRseq relative to other RRS methods should prove useful to those lacking advanced expertise in wet‐laboratory methods or bioinformatics.
This content will become publicly available on November 3, 2024
Whole‐genome sequencing data allow survey of variation from across the genome, reducing the constraint of balancing genome sub‐sampling with estimating recombination rates and linkage between sampled markers and target loci. As sequencing costs decrease, low‐coverage whole‐genome sequencing of pooled or indexed‐individual samples is commonly utilized to identify loci associated with phenotypes or environmental axes in non‐model organisms. There are, however, relatively few publicly available bioinformatic pipelines designed explicitly to analyse these types of data, and fewer still that process the raw sequencing data, provide useful metrics of quality control and then execute analyses. Here, we present an updated version of a bioinformatics pipeline called
- Award ID(s):
- 1757324
- NSF-PAR ID:
- 10495578
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Molecular Ecology Resources
- ISSN:
- 1755-098X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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