PT - JOURNAL ARTICLE AU - Daniel M. Portik AU - Lydia L. Smith AU - Ke Bi TI - An evaluation of transcriptome-based exon capture for frog phylogenomics across multiple scales of divergence (Class: Amphibia, Order: Anura) AID - 10.1101/031468 DP - 2015 Jan 01 TA - bioRxiv PG - 031468 4099 - http://biorxiv.org/content/early/2015/11/12/031468.short 4100 - http://biorxiv.org/content/early/2015/11/12/031468.full AB - Custom sequence capture experiments are becoming an efficient approach for gathering large sets of orthologous markers with targeted levels of informativeness in non-model organisms. Transcriptome-based exon capture utilizes transcript sequences to design capture probes, often with the aid of a reference genome to identify intron-exon boundaries and exclude shorter exons (< 200 bp). Here, we test an alternative approach that directly uses transcript sequences for probe design, which are often composed of multiple exons of varying lengths. Based on a selection of 1,260 orthologous transcripts, we conducted sequence captures across multiple phylogenetic scales for frogs, including species up to ~100 million years divergent from the focal group. After several conservative filtering steps, we recovered a large phylogenomic data set consisting of sequence alignments for 1,047 of the 1,260 transcriptome-based loci (~630,000 bp) and a large quantity of highly variable regions flanking the exons in transcripts (~70,000 bp). We recovered high numbers of both shorter (< 100 bp) and longer exons (> 200 bp), with no major reduction in coverage towards the ends of exons. We observed significant differences in the performance of blocking oligos for target enrichment and non-target depletion during captures, and observed differences in PCR duplication rates that can be attributed to the number of individuals pooled for capture reactions. We explicitly tested the effects of phylogenetic distance on capture sensitivity, specificity, and missing data, and provide a baseline estimate of expectations for these metrics based on nuclear pairwise differences among samples. We provide recommendations for transcriptome-based exon capture design based on our results, and describe multiple pipelines for data assembly and analysis.