Fishing for DNA? Designing baits for population genetics in target enrichment experiments: Guidelines, considerations and the new tool supeRbaits

Abstract

Targeted sequencing is an increasingly popular next‐generation sequencing (NGS) approach for studying populations that involves focusing sequencing efforts on specific parts of the genome of a species of interest. Methodologies and tools for designing targeted baits are scarce but in high demand. Here, we present specific guidelines and considerations for designing capture sequencing experiments for population genetics for both neutral genomic regions and regions subject to selection. We describe the bait design process for three diverse fish species: Atlantic salmon, Atlantic cod and tiger shark, which was carried out in our research group, and provide an evaluation of the performance of our approach across both historical and modern samples. The workflow used for designing these three bait sets has been implemented in the R‐package supeRbaits, which encompasses our considerations and guidelines for bait design for the benefit of researchers and practitioners. The supeRbaits R‐package is user‐friendly and versatile. It is written in C++ and implemented in R. supeRbaits and its manual are available from Github: https://github.com/BelenJM/supeRbaits

Sequence capture: Obsolete or irreplaceable? A thorough validation across phylogenetic distances and its applicability to hybrids and allopolyploids

“…Target enrichment approaches are not only not an outdated method, but have actually gained considerable popularity and are often the only meaningful solution to many research questions, particularly with respect to both efficiency and affordability, especially when dealing with non‐model species (e.g. Choquet et al, 2019; Jiménez‐Mena et al, 2022). This study has demonstrated that the robust design of exome capture experiment has predictable behaviour even when applied across a wide phylogenetic range encompassing species with very close relatedness to the model taxon to those dating its divergence at least up to ~40 Ma.…”

Phylogenetically‐conserved candidate genes unify biodiversity–ecosystem function relationships and eco‐evolutionary dynamics across biological scales

“…Phylogenetically‐conserved candidate genes sequencing benefits from the recent development of target enrichment methods (capture of specific regions of the genome, Jiménez‐Mena et al, 2022; Jones & Good, 2016; Mertes et al, 2011) such as the hybridization‐based capture sequencing (HBCS; Hawkins et al, 2016). In HBCS, we design oligonucleotides (called ‘probes’ or ‘baits’) that are complementary to the target (PCCG) sequences.…”

“…These oligos capture and enrich complementary target sequences from a next‐generation sequencing (NGS) library. This method has been used in many taxa (Albert et al, 2007; Mamanova et al, 2010); its use and potential for evolution are well described (Faircloth, 2017; Jiménez‐Mena et al, 2022). HBCS allows for mismatches between probes and the target sequences, allowing 15%–20% of divergence (Faircloth, 2017); this threshold should (ideally) be used to define the appropriate focal species.…”

HiMAP2: Identifying phylogenetically informative genetic markers from diverse genomic resources

“…Existing bioinformatic pipelines/approaches are generally tailored to the question at hand, but generally either ingest raw HTS data (Frías‐López et al, 2016; Schwartz et al, 2015), transcriptomes/genomes (Chamala et al, 2015; Choi et al, 2019; Tessema et al, 2020) or existing multiple sequence alignments (Frías‐López et al, 2016; Mayer et al, 2016; Santos et al, 2021), and output lists of phylogenetically informative or highly variable loci or regions from these data. Some approaches are specific to finding informative single nucleotide polymorphisms (SNPs) (Kavakiotis et al, 2017; Schmidt et al, 2020) or specifically for optimizing bait design for probe‐based methods (Jimenez‐Mena et al, 2022; Mayer et al, 2016). While each of these approaches have particular strengths, their diversity in terms of focus and implementation highlights the need for flexible and user‐friendly solutions for identifying informative loci from genomic‐scale data.…”