INTRODUCTION
Biological collections provide an invaluable window into the past, creating an irreplaceable record of biodiversity (Suarez & Tsutsui 2004; Yeates et al. 2016). Often, samples have been collected over long time periods from the same localities, providing time series to study evolution at multiple spatial and temporal scales (Splendiani et al. 2017; Schmitt et al. 2019; Schultz et al. 2020). Temporally sampled collections have been leveraged for a wide variety of applications (Holmes et al. 2016), including studying changes in allele frequency (Bi et al. 2013; 2019), disease incidence (Avila-Arcos et al. 2012; Muletz et al. 2014), microbiome composition (Heindler et al. 2018), geographic range shifts (Tingley et al. 2009), and changes in body size (Caruso et al., 2014). Most natural history specimens were collected before the routine preparation of tissue samples for genetic analysis, and thus while DNA sequencing has revolutionized the study of evolution, a large portion of collections are inaccessible to standard methods of genomic inquiry (Lamichhaney et al. 2019).
Nonetheless, recent advances in DNA extraction and library preparation have made DNA from museum samples more accessible (Paireder et al. 2013; Sørensen et al. 2016; Toutoiu et al. 2020). In particular, target capture techniques have enabled the sequencing of fragmented and low-yield DNA from vertebrate dried museum skin and bone preparations, as well as dried invertebrate, plant, and fungal specimens (Rowe et al. 2011; Avila-Arcos et al. 2012; Blaimer et al. 2016; Sánchez Barreiro et al. 2017; Schmid et al. 2018; St Laurent et al. 2018; Leavitt et al. 2019; Tsai et al. 2019; Bakker et al. 2020). Researchers have only just begun to apply this class of methods to fluid-preserved specimens that are formalin- or ethanol-fixed, often with mixed success (Hykin et al. 2015; Ruane & Austin, 2017; Hedin et al. 2018; McGuire et al. 2018; Wood et al. 2018; Derkarabetian et al. 2019; Turvey et al. 2019; Lyra et al. 2020). Formalin damages DNA in several ways (Campos & Gilbert, 2012; Cook et al. 2014), making the extraction and sequencing of genomic DNA from formalin-fixed specimens more challenging than other specimen preparation types (Stuart et al. 2006; Pierson et al. 2020).
Past work using historical DNA (hDNA) samples (including formalin-fixed samples) has mostly focused on phylogenetic applications (Wall et al. 2014; Ruane & Austin, 2017; McGuire et al. 2018; Derkarabetian et al. 2019; Turvey et al. 2019), primarily using ultraconserved elements (UCEs). A few studies have explored SNP-based population genetic analyses (Bi et al. 2013; Tin et al. 2014; Ewart et al. 2019); however, generating SNPs for hDNA samples using reduced representation approaches such as RADseq can be problematic because highly fragmented DNA may result in high rates of random allelic dropout and few overlapping loci between samples (Burrell et al. 2015). DNA fragmentation is less of a concern for capture-based approaches, but UCEs usually generate fewer SNPs at the population level than RADseq (but see McCormack, Tsai, & Faircloth, 2016). Accounting for formalin-induced damage is also important in SNP-based studies because these mutations can influence downstream analyses (Axelsson et al. 2008; Bi et al. 2013). RAD-capture approaches can bridge this divide by using target capture to generate robust SNP datasets that also have phylogenomic applications (Ali et al. 2016). This family of methods (Rapture, Ali et al. 2016; RADcap, Hoffberg et al. 2016; hyRAD, Suchan et al. 2016; hyRAD-X, Schmid et al. 2017) has been successfully applied to hDNA by capturing historical and modern samples in a single experiment (Suchan et al. 2016; Crates et al. 2018; Schmid et al. 2018; Gauthier et al. 2020) and by combining data collected from hDNA samples using target-capture with data from modern samples generated with RADseq (Bakker et al. 2020).
In contrast to other hDNA methods, only a few studies have investigated the utility of DNA from allozyme supernatant samples for genomic applications (Arbetman & Premoli, 2011; Yuan et al. 2018). Until DNA sequencing became widely adopted, allozymes were the primary marker used in studies of genomic variation (Schlötterer 2004). Large series of frozen allozyme supernatant samples are archived in some museum collections (Table 1) and likely in investigators’ individual research collections as well. Two studies have shown that high molecular weight DNA can be extracted from these frozen supernatant samples and nuclear, mitochondrial, and chloroplast markers sequenced using PCR-based methods (Arbetman & Premoli, 2011; Yuan et al. 2018). Yet the amenability of these samples to target-capture protocols has not yet been assessed and it is unknown whether the resulting sequence data would vary from that obtained from frozen tissue samples and/or formalin-fixed tissues.
Table 1: Information regarding allozyme supernatant samples in select natural history collections. Museum abbreviations are as follows: AMS: Australian Museum, Sydney NSW, Australia; FMNH: Field Museum, Chicago IL, USA; MVZ: Museum of Vertebrate Zoology, Berkeley CA, USA; TNHC: The University of Texas at Austin - Texas Natural History Collections, Austin TX, USA; USNM: United States National Museum of Natural History, Washington DC, USA. The following collections were consulted and indicate they do not have allozyme supernatants: MCZ: Museum of Comparative Zoology, Cambridge MA, USA; NCSM-Herpetology: North Carolina Museum of Natural Sciences, Raleigh NC, USA; AMNH-Herpetology: American Museum of Natural History, New York NY, USA; KU-Herpetology: Kansas University Biodiversity Institute and Natural History Museum, Lawrence KS, USA; SUI-Mammalogy, Ornithology, Herpetology: University of Iowa Museum of Natural History, Iowa City IA, USA; ANSP: Academy of Natural Sciences of Drexel University, Philadelphia PA, USA; CAS Herpetology: California Academy of Sciences, San Francisco CA.