Data from: High-throughput SNP genotyping of historical and modern samples of five bird species via sequence capture of ultraconserved elements
Lim, Haw Chuan; Braun, Michael J. (2016), Data from: High-throughput SNP genotyping of historical and modern samples of five bird species via sequence capture of ultraconserved elements, Dryad, Dataset, https://doi.org/10.5061/dryad.2c220
Sample availability limits population genetics research on many species, especially taxa from regions with high diversity. However, many such species are well represented in museum collections assembled before the molecular era. Development of techniques to recover genetic data from these invaluable specimens will benefit biodiversity science. Using a mixture of freshly preserved and historical tissue samples, and a sequence capture probe set targeting >5000 loci, we produced high-confidence genotype calls on thousands of single nucleotide polymorphisms (SNPs) in each of five South-East Asian bird species and their close relatives (N = 27–43). On average, 66.2% of the reads mapped to the pseudo-reference genome of each species. Of these mapped reads, an average of 52.7% was identified as PCR or optical duplicates. We achieved deeper effective sequencing for historical samples (122.7×) compared to modern samples (23.5×). The number of nucleotide sites with at least 8× sequencing depth was high, with averages ranging from 0.89 × 106 bp (Arachnothera, modern samples) to 1.98 × 106 bp (Stachyris, modern samples). Linear regression revealed that the amount of sequence data obtained from each historical sample (represented by per cent of the pseudo-reference genome recovered with ≥8× sequencing depth) was positively and significantly (P ≤ 0.013) related to how recently the sample was collected. We observed characteristic post-mortem damage in the DNA of historical samples. However, we were able to reduce the error rate significantly by truncating ends of reads during read mapping (local alignment) and conducting stringent SNP and genotype filtering.