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.