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Validating the use of non-invasively sourced DNA for population genetic studies using pedigree data
Web Ecology ( IF 2.2 ) Pub Date : 2017-03-09 , DOI: 10.5194/we-17-9-2017
Faye Wedrowicz , Jennifer Mosse , Wendy Wright , Fiona E. Hogan

Abstract. Non-invasive genetic sampling has provided valuable ecological data for many species – data which may have been unobtainable using invasive sampling methods. However, DNA obtained non-invasively may be prone to increased levels of amplification failure and genotyping error. Utilizing genotype data from 32 pedigreed koalas, this study aimed to validate the reliability of final consensus genotypes obtained using DNA isolated from koala scats. Pedigree analysis, duplicate genotyping, analysis of mismatched loci and tests for null alleles were used to look for evidence of errors. All genetically confirmed parent–offspring relationships were found to follow Mendelian rules of inheritance. Duplicate genotypes matched in all cases and there was no evidence of null alleles. Related individuals always had different 12-marker genotypes having a minimum of three unique loci (in one full sibling pair), a mode of seven unique loci and a maximum of 11 unique loci. This study demonstrates the capacity of DNA recovered from koala scats to provide reliable genotypes that can unequivocally discriminate individuals and infer parentage, provided data are missing from no more than two loci. Validating data obtained using non-invasive sampling is an important step, allowing potential problems to be identified at an early stage.

中文翻译:

使用谱系数据验证非侵入性来源的 DNA 在群体遗传研究中的使用

摘要。非侵入性基因采样为许多物种提供了宝贵的生态数据——使用侵入性采样方法可能无法获得这些数据。然而,非侵入性获得的 DNA 可能会增加扩增失败和基因分型错误的程度。本研究利用 32 只纯种考拉的基因型数据,旨在验证使用从考拉粪便中分离的 DNA 获得的最终共有基因型的可靠性。谱系分析、重复基因分型、错配位点分析和无效等位基因测试用于寻找错误证据。发现所有经基因证实的亲子关系都遵循孟德尔遗传规则。重复基因型在所有情况下都匹配,并且没有无效等位基因的证据。相关个体总是具有不同的 12 标记基因型,这些基因型具有至少三个独特的基因座(在一对完整的兄弟姐妹中)、七个独特基因座的模式和最多 11 个独特基因座。这项研究证明了从考拉粪便中回收的 DNA 能够提供可靠的基因型,这些基因型可以明确区分个体并推断亲子关系,前提是数据缺失不超过两个基因座。验证使用非侵入性采样获得的数据是重要的一步,可以在早期发现潜在问题。提供的数据缺失不超过两个位点。验证使用非侵入性采样获得的数据是重要的一步,可以在早期发现潜在问题。提供的数据缺失不超过两个位点。验证使用非侵入性采样获得的数据是重要的一步,可以在早期发现潜在问题。
更新日期:2017-03-09
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