![]() ![]() 2002) or flow cytometry ( Vinogradov 1994 Dolezel et al. Genome sizes can be approximated in non-model organisms through sequencing-independent techniques such as Feulgen densitometry ( Hardie et al. most cases, this number can be approximated as twice the product of the genome size and the probability of the enzyme’s recognition sequence in a given genome. For cases in which the whole genome sequence is not available, i.e. The theoretical maximum number of RAD markers that can be obtained for a given combination of restriction enzyme and biological species can be easily calculated as twice the frequency (absolute number of occurrences) of the enzyme’s recognition sequence (which for type II restriction enzymes is also the cleavage site) in the genome, but only when the fully sequenced genome is available. This choice determines the number of RAD markers that can be obtained, which in turn dictates the amount of sequencing needed for a desired coverage level, the number of samples that can be multiplexed, the monetary cost, and ultimately the success of a project. 2011), double digest RAD-seq ( Peterson et al. 2011), multiplexed shotgun genotyping (Andolfatto et al. The choice of appropriate type II restriction enzyme(s) is critical for the effective design and application of RAD sequencing (RAD-seq) and a rapidly growing number of related methods such as genotyping-by-sequencing (Elshire et al. 2015 Herrera & Shank 2015), and SNP marker discovery ( Scaglione et al. 2013) to population genomics ( Hohenlohe et al. 2008) have myriad uses in biology, which range from genetic mapping ( Wang et al. The single nucleotide polymorphisms (SNPs) embedded in the resulting restriction-site associated DNA (RAD) sequence tags (M R Miller et al. The use of type II restriction enzymes to obtain reduced representation libraries from nuclear genomes, combined with the power of next-generation sequencing technologies, is rapidly becoming one of the most-used commonly strategies to generate genome-wide genotypic and sequence data in both model and non-model organisms (Baird et al. The analytical pipeline developed in this study, PredRAD ( ), and the resulting databases constitute valuable resources that will help guide the design of any study using RAD-seq or related methods. Models based on genomic compositions are also effective tools to accurately calculate probabilities of recognition sequences across taxa, and can be applied to species for which reduced-representation data is available (including transcriptomes and ‘neutral’ RAD-seq datasets). We demonstrate that genome sizes can be predicted from cleavage frequency data obtained with restriction enzymes targeting ‘neutral’ elements. Our observations reveal that recognition-sequence frequencies for a given restriction enzyme are strikingly variable among broad eukaryotic taxonomic groups, being largely determined by phylogenetic relatedness. ![]() Here, we performed systematic in silico surveys of recognition sequences, for diverse and commonly used type II restriction enzymes across the eukaryotic tree of life. However, both scenarios are uncommon for non-model species. This number can only be directly determined if a reference genome sequence is available, or it can be estimated if the genome size and restriction recognition sequence probabilities are known. A critical design element of any RAD-seq study is a knowledge of the approximate number of genetic markers that can be obtained for a taxon using different restriction enzymes, as this number determines the scope of a project, and ultimately defines its success. High-throughput sequencing of reduced representation libraries obtained through digestion with restriction enzymes – generically known as restriction-site associated DNA sequencing (RAD-seq) – is a common strategy to generate genome-wide genotypic and sequence data from eukaryotes. ![]()
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