Advantages and disadvantages of our workflow
The here presented workflow provides good perspectives to enrich entire ORFs and intronic/intergenic flanking regions without prior knowledge of exon-intron boundaries, thus in the absence of a proximate well-assembled and annotated reference genome. Combining the selection of candidate ORFs using existing databases with orthology assessment from ingroup transcriptomes provides a useful approach for non-model organisms, that moreover allows leveraging museum specimens as long as some fresh samples across the ingroup are available. Our verification includes target alignment and manual verification, as recommended previously (Teasdale et al., 2016), which provides empirical scientists a trackable connection to their high-throughput sequencing data. Our procedures indicate good recovery of ORFs, but if one aims to integrate UCE and ORF targets in the same enrichment reactions additional verifications to balance such reactions are recommended. Despite the reduced alignment length compared to ORFs or the smaller pool of SNPs, our retained UCEs contain substantial phylogenetic and population genetic information. At both scales, analyses based on ORFs and UCEs produced highly comparable results, suggesting that our genomic sampling is representative. Estimates of nucleotide diversity for UCEs were closer to those at non-synonymous than at synonymous sites of ORFs, indicating that UCEs and their flanking regions are under selective constraints rather than being neutrally-evolving. Decisions on whether or not to include multiple marker types in the same enrichment strategy strongly depend on the questions to be addressed (see Hendriks et al., 2021). Whereas certain questions may adequately be answered using a single marker type, more representative sampling across the genome increases opportunities to reliably document evolutionary patterns, including the degree of phylogenetic congruence or the robustness of population-level summary statistics, and, therefore, it may enhance comparability across taxa. Furthermore, mitochondrial (or chloroplast) genomes may be recovered by skimming off-target reads, albeit with more variable sequencing depth.