Introduction
Microsatellites have been and are still widely applied in various biological sciences including population genetics, kinship/pedigree analysis, human and wildlife forensics, linkage analysis or disease association studies (e.g. Cunningham, Dooley, Splan, & Bradley, 2001; Goodwin, Linacre, & Hadi, 2011; Gulcher, 2012; Wasser et al., 2004). Population genetic information obtained by microsatellite genotyping is also important for monitoring wild populations in conservation contexts, for reintroduction programs or to refine captive breeding management (Arandjelovic & Vigilant, 2018; Norman, Putnam, & Ivy, 2019). Microsatellites are also often the markers of choice to genetically characterize (wild) populations in order to determine degrees of population fragmentation and hybridization, dispersal patterns, mating systems and reproductive success (e.g. Charpentier et al., 2012; De Moor, Roos, Ostner, & Schulke, 2020; Ferreira da Silva et al., 2018; Kheng et al., 2017; McCarthy, Lester, Cibot, Vigilant, & McLennan, 2020). The ongoing popularity of microsatellites is largely based on their high abundancy in animal genomes (Hamada, Petrino, & Kakunaga, 1982; Tautz & Renz, 1984), the high levels of allelic diversity (Ellegren, 2000) and the possibility to amplify them across related species. Accordingly, microsatellites are preferred, for example over SNPs, because of their higher statistical power per locus and their cross-species amplifiability, particularly when applied to small sample size datasets as typically found in forensic and kinship studies (Barbian et al., 2018; Guichoux et al., 2011)
However, traditional microsatellite genotyping via fragment length analysis (FLA) using polyacrylamide gel or capillary electrophoresis has several disadvantages, such as fragment size homoplasy, allele calling difficulties (stutter and split peaks, off-target PCR products), laborious work and high laboratory costs, as well as poor comparability of results among laboratories (De Barba et al., 2017; Guichoux et al., 2011; Pasqualotto, Denning, & Anderson, 2007). Even with attempts to improve PCR amplification and more accurate/reliable genotyping procedures (Arandjelovic et al., 2009; Buchan, Archie, Van Horn, Moss, & Alberts, 2005; Navidi, Arnheim, & Waterman, 1992; Sefc, Payne, & Sorenson, 2003; Taberlet et al., 1996), many of the problems remained.
With microsatellite genotyping-by-sequencing (GBS) using high-throughput sequencing technologies most of the difficulties can be mitigated (Barbian et al., 2018; Johannesen, Fabritzek, Ebner, & Bikar, 2017; Pimentel et al., 2018; Vartia et al., 2016). For instance, with GBS the exact length of the microsatellite alleles can be determined, which is a typical problem of FLA genotyping, particularly when alleles differ by only one basepair (bp) (Barbian et al., 2018; Vartia et al., 2016). Moreover, the nucleotide sequence is revealed so that cryptic alleles (alleles with the same length but containing a nucleotide variant) can be detected, resulting in an increased number of alleles and consequently greater statistical power per locus.
Nevertheless, problems with null alleles due to relatively large PCR products and allelic dropout as a result of primers binding in unconserved regions remain with GBS (Pompanon, Bonin, Bellemain, & Taberlet, 2005). As many microsatellites can be cross-amplified in phylogenetically related species, primers designed for one species are often tested in related species and then applied if successfully amplified and informative (i.e., polymorph) (Barbara et al., 2007; De Barba et al., 2017). For example, various microsatellite loci characterized for humans can be successfully amplified in non-human catarrhine primates (Old World monkeys, apes) (Coote & Bruford, 1996; Ely, Gonzalez, Reeves-Daniel, & Stone, 1998; Kayser et al., 1996; Morin, Mahboubi, Wedel, & Rogers, 1998; Newman, Fairbanks, Pollack, & Rogers, 2002; Roeder et al., 2009; Smith et al., 2000) and have been used since then in numerous studies (e.g. Arandjelovic, Head, Boesch, Robbins, & Vigilant, 2014; Kopp, Fischer, Patzelt, Roos, & Zinner, 2015; Minkner et al., 2018; Städele et al., 2019). Yet, attempts to reduce PCR product size or to adapt primers specifically to the study species have been rare (but see Bradley, Boesch, & Vigilant, 2000; Engelhardt, Muniz, Perwitasari-Farajallah, & Widdig, 2017; Inoue, Ogata, Seino, & Matsuda, 2016).
In our study, we screened a total of 269 microsatellite loci, widely targeted in catarrhine primates, and designed conserved primers for 45 loci based on available catarrhine genomes. We then tested the new microsatellite panel in ten primate species representing all major lineages of Catarrhini and further validated their applicability to low quality DNA samples using faecal samples of wild Guinea baboons (Papio papio ).