Determining microsatellite genotyping reliability and mutation detection ability: an approach using small-pool PCR from sperm DNA
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Microsatellite genotyping from trace DNA is now common in fields as diverse as medicine, forensics and wildlife genetics. Conversely, small-pool PCR (SP-PCR) has been used to investigate microsatellite mutation mechanisms in human DNA, but has had only limited application to non-human species. Trace DNA and SP-PCR studies share many challenges, including problems associated with allelic drop-out, false alleles and other PCR artefacts, and the need to reliably identify genuine alleles and/or mutations. We provide a framework for the validation of such studies without a multiple tube approach and demonstrate the utility of that approach with an analysis of microsatellite mutations in the tammar wallaby (Macropus eugenii). Specifically, we amplified three autosomal microsatellites from somatic DNA to characterise efficiency and reliability of PCR from low-template DNA. Reconstruction experiments determined our ability to discriminate mutations from parental alleles. We then developed rules to guide data interpretation. We estimated mutation rates in sperm DNA to range from 1.5 × 10−2 to 2.2 × 10−3 mutations per locus per generation. Large multi-step mutations were observed, providing evidence for complex mutation processes at microsatellites and potentially violating key assumptions in the stepwise mutation model. Our data demonstrate the necessity of actively searching for large mutation events when investigating microsatellite evolution and highlight the need for a thorough understanding of microsatellite amplification characteristics before embarking on SP-PCR or trace DNA studies.
KeywordsMicrosatellite STR Genotyping reliability Small-pool PCR Marsupial
Thanks to Merrilee Harris for the donation of tammar wallaby sperm samples and to Marilyn Renfree for the donation of tissue samples from Kangaroo Island wallabies. Thanks to Dennis McNevin for the use of laboratory space for PCR setups and to David Pederson for advice on statistical analyses. This work was supported by the Australian Research Council (DP0211687 to S.S. and N.F.).
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