Harnessing the power of RADseq for ecological and evolutionary genomics

By Kimberly R. Andrews, J. Good, Michael R. Miller, Gordon Luikart, Paul A Hohenlohe. Nature reviews genetics, 2016

1,343 citations recorded by the source corpus.

High-throughput techniques based on restriction site-associated DNA sequencing (RADseq) are enabling the low-cost discovery and genotyping of thousands of genetic markers for any species, including non-model organisms, which is revolutionizing ecological, evolutionary and conservation genetics. Technical differences among these methods lead to important considerations for all steps of genomics studies, from the specific scientific questions that can be addressed, and the costs of library preparation and sequencing, to the types of bias and error inherent in the resulting data. In this Review, we provide a comprehensive discussion of RADseq methods to aid researchers in choosing among the many different approaches and avoiding erroneous scientific conclusions from RADseq data, a problem that has plagued other genetic marker types in the past.

Subfields: Genetics, Molecular Biology, Plant Science

View Paper: https://www.semanticscholar.org/paper/e43777fc9504ae6f03bb58ce7171fcdc8bcb8491

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Citations in the corpus

Lost in parameter space: a road map for stacks (2017, methodology): “Many diﬀerent ﬂavours of the original RAD protocol are now used (e.g. ddRAD, ezRAD, GBS, 2bRAD) and several analysis programs exist (reviewed in Andrews et al. 2016).”
dartr: An r package to facilitate analysis of SNP data generated from reduced representation genome sequencing (2018, positive): “…nucleotide polymorphisms (SNPs) obtained through restriction site-associated DNA sequencing (RADSeq), double digest RADSeq (ddRADSeq) and DarTSeq (Andrews, Good, Miller, Luikart, & Hohenlohe, 2016; Baird et al., 2008; Jaccoud, Peng, Feinstein, & Kilian, 2001; Kilian et al., 2012; Peterson,…”
Stacks 2: Analytical Methods for Paired-end Sequencing Improve RADseq-based Population Genomics (2019, background): “…paired‐end sequencing to derive short contigs from de novo sdRAD data has been promoted repeatedly (Amores, Catchen, Ferrara, Fontenot, & Postlethwait, 2011; Andrews et al., 2016; Etter, Preston, Bassham, Cresko, & Johnson, 2011; Hohenlohe et al., 2013; Li et al., 2018; Nelson & Cresko, 2018).”
Finding the Genomic Basis of Local Adaptation: Pitfalls, Practical Solutions, and Future Directions (2016, positive): “A second set of methods for reduced representation uses restriction enzymes to isolate small pieces of DNA (such as restriction-associated digest sequencing [RAD-seq] or genotyping by sequencing [GBS; reviewed in Puritz et al. 2014 b ; Andrews et al. 2016]; table A2).”
Advances in the Application of Genetics in Marine Turtle Biology and Conservation (2017, background): “loci can now be rapidly and reliably quantified across large numbers of individuals (Campbell et al., 2015; Ali et al., 2016; Andrews et al., 2016).”
Landscape Genomics: Understanding Relationships Between Environmental Heterogeneity and Genomic Characteristics of Populations (2017, background): “For instance, next-generation sequencing (NGS) allows us to quantify genetic variation in many individuals at dense genomic coverage at decreasing costs (e.g., Luikart et al. 2003; Andrews et al. 2016).”
Ecological and Evolutionary Consequences of Environmental Change and Management Actions for Migrating Fish (2019, background): “, RAD-sequencing, WGS, GWAS and SNP-genotyping (Andrews et al., 2016)] together with information for closely related species and populations in different environments may help identify genes and underlying genomic regions under selection involved in shaping the diversity of migratory behavior.”
Urbanization Shapes the Ecology and Evolution of Plant-Arthropod Herbivore Interactions (2019, background): “With rapid advances in genome sequencing (Ekblom and Galindo, 2011; Andrews et al., 2016), it is becoming easier and more cost-effective to incorporate more taxa into studies of genome evolution.”
Deriving genotypes from RAD-seq short-read data using Stacks (2017, neutral): “1,2).”