RAD Capture (Rapture): Flexible and Efficient Sequence-Based Genotyping

Abstract

Massively parallel sequencing has revolutionized many areas of biology, but sequencing large amounts of DNA in many individuals is cost-prohibitive and unnecessary for many studies. Genomic complexity reduction techniques such as sequence capture and restriction enzyme-based methods enable the analysis of many more individuals per unit cost. Despite their utility, current complexity reduction methods have limitations, especially when large numbers of individuals are analyzed. Here we develop a much improved restriction site-associated DNA (RAD) sequencing protocol and a new method called Rapture (RAD capture). The new RAD protocol improves versatility by separating RAD tag isolation and sequencing library preparation into two distinct steps. This protocol also recovers more unique (nonclonal) RAD fragments, which improves both standard RAD and Rapture analysis. Rapture then uses an in-solution capture of chosen RAD tags to target sequencing reads to desired loci. Rapture combines the benefits of both RAD and sequence capture, i.e., very inexpensive and rapid library preparation for many individuals as well as high specificity in the number and location of genomic loci analyzed. Our results demonstrate that Rapture is a rapid and flexible technology capable of analyzing a very large number of individuals with minimal sequencing and library preparation cost. The methods presented here should improve the efficiency of genetic analysis for many aspects of agricultural, environmental, and biomedical science.

Science Advancements Key to Increasing Management Value of Life Stage Monitoring Networks for Endangered Sacramento River Winter-Run Chinook Salmon in California

“…Thus, PBT is recommended to assess the extent to which fitness effects occur with hatchery SRWRC that spawn in the wild, and to inform the trade-offs associated with increased hatchery production during droughts or periods of low overall population abundance. Results from this previous reconstruction, in addition to recent advancements in rapid genome assays to identify parent-offspring linkages (with only a single parent sampled), highlight the feasibility of this tool to address these management-specific questions, as well as changes in within-population diversity (Ali et al 2016). …”

“…Given the recent advancements in rapid genome assay technologies that can track parental lineages (parentage-based tags [PBTs]; Sidebar 2), adult and juvenile tissue libraries and collections may soon provide greater insights into the reproductive success of individuals as a function of ambient environmental conditions, water project operations, spawn timing, habitat carrying capacities, and hatchery release strategies. Thus, PBTs should be incorporated into juvenile and adult surveys (Ali et al 2016;see Advancement 4). Advancements in the use of mucus swabs, as opposed to removing fish tissues (e.g., fin clips), may provide a less invasive sampling approach for future consideration (Le Vin et al 2011).…”

Harnessing the power of RADseq for ecological and evolutionary genomics

“…These RAD contigs allow for better identification of paralogs 22 , provide more sequence for BLAST searching of functionally important loci 20 , and could provide haplotype data for genealogical or phylogenetic analysis. Longer contig sequences also allow for the design of PCR primers or sequence capture probes to target loci of interest for further study 23,24 .…”

Comparing Pool‐seq, Rapture, and GBS genotyping for inferring weak population structure: The American lobster (Homarus americanus) as a case study

“…Therefore, choosing the most appropriate NGS genotyping approach sometimes remains challenging. To overcome this challenge, alternative protocols to the classic way of sequencing individuals separately (i.e., each individual is sequenced with a unique barcode) have been developed either by pooling DNA samples such as Pool sequencing (Futschik & Schlötterer, 2010;Lynch, Bost, & Wilson, 2014;Schlötterer, Tobler, Kofler, & Nolte, 2014) or by reducing genomic complexity using sequence capture methods (Ali et al, 2016;Boucher, Casazza, Szövényi, & Conti, 2016;Hoffberg et al, 2016;Jones & Good., 2016). This may substantially increase the analytical cost and computational time (Shendure & Aiden, 2012).…”