Genomic library preparation and hybridization capture of formalin‐fixed tissues and allozyme supernatant for population genomics and considerations for combining capture‐ and RADseq‐based single nucleotide polymorphism data sets. (19th August 2021) - O'Connell, Kyle A.; Mulder, Kevin P.; Wynn, Addison; de Queiroz, Kevin; Bell, Rayna C.
Abstract: Until recently many historical museum specimens were largely inaccessible to genomic inquiry, but high‐throughput sequencing (HTS) approaches have allowed researchers to successfully sequence genomic DNA from dried and fluid‐preserved museum specimens. In addition to preserved specimens, many museums contain large series of allozyme supernatant samples, but the amenability of these samples to HTS has not yet been assessed. Here, we compared the performance of a target‐capture approach using alternative sources of genomic DNA from 10 specimens of spring salamanders (Plethodontidae: Gyrinophilus porphyriticus ) collected between 1985 and 1990: allozyme supernatants, allozyme homogenate pellets and formalin‐fixed tissues. We designed capture probes based on double‐digest restriction‐site associated sequencing (RADseq) derived loci from frozen blood samples available for seven of the specimens and assessed the success and consistency of capture and RADseq approaches. This study design enabled direct comparisons of data quality and potential biases among the different data sets for phylogenomic and population genomic analyses. We found that in phylogenetic analyses, all enrichment types for a given specimen clustered together. In principal component space all capture‐based samples clustered together, but RADseq samples did not cluster with corresponding capture‐based samples. Single nucleotide polymorphism calls were on average 18.3% different between enrichment types for a given individual, but these discrepancies were primarily due to differences in heterozygous/homozygous single nucleotide polymorphism calls. We demonstrate that both allozyme supernatant and formalin‐fixed samples can be successfully used for population genomic analyses and we discuss ways to identify and reduce biases associated with combining capture and RADseq data.