title: Targeted capture in evolutionary and ecological genomics.
abstract: The rapid expansion of next-generation sequencing has yielded a powerful array of tools to address fundamental biological questions at a scale that was inconceivable just a few years ago. Various genome-partitioning strategies to sequence select subsets of the genome have emerged as powerful alternatives to whole-genome sequencing in ecological and evolutionary genomic studies. High-throughput targeted capture is one such strategy that involves the parallel enrichment of preselected genomic regions of interest. The growing use of targeted capture demonstrates its potential power to address a range of research questions, yet these approaches have yet to expand broadly across laboratories focused on evolutionary and ecological genomics. In part, the use of targeted capture has been hindered by the logistics of capture design and implementation in species without established reference genomes. Here we aim to (i) increase the accessibility of targeted capture to researchers working in nonmodel taxa by discussing capture methods that circumvent the need of a reference genome, (ii) highlight the evolutionary and ecological applications where this approach is emerging as a powerful sequencing strategy and (iii) discuss the future of targeted capture and other genome-partitioning approaches in the light of the increasing accessibility of whole-genome sequencing. Given the practical advantages and increasing feasibility of high-throughput targeted capture, we anticipate an ongoing expansion of capture-based approaches in evolutionary and ecological research, synergistic with an expansion of whole-genome sequencing.
authors.affiliation: Division of Biological Sciences, University of Montana, 32 Campus Dr. HS104, Missoula, MT, 59812, USA.
authors.forename: Matthew R
authors.initials: MR
authors.lastname: Jones
authors.affiliation: Division of Biological Sciences, University of Montana, 32 Campus Dr. HS104, Missoula, MT, 59812, USA.
authors.forename: Jeffrey M
authors.initials: JM
authors.lastname: Good
mesh_terms: D000818:Animals; D005075:Biological Evolution; D002874:Chromosome Mapping; D004463:Ecology / Q000379:methods*; D005828:Genetics, Population; D023281:Genomics / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods; D006801:Humans; D010641:Phenotype; D010802:Phylogeny; D017422:Sequence Analysis, DNA / Q000379:methods
keywords: ancient DNA; detecting selection; genetic mapping; metagenomics; next-generation sequencing; phylogenomics