Too much of a good thing? Finding the most informative genetic dataset to answer conservation questions

Molecular markers are a useful tool allowing conservation and population managers to shed light on genetic processes affecting threatened populations. However, as technological advancements in molecular techniques continue to evolve, conservationists are frequently faced with new genetic markers, each with nuanced variation in their characteristics as well as advantages and disadvantages for informing various questions. We used a well-studied population of Tasmanian devils from Maria Island to illustrate the issues associated with combining multiple genetic datasets and to help answer a question posed by many population managers: which dataset will provide the most precise and accurate estimates of the population processes we are trying to measure? We analysed individual heterozygosity (as internal relatedness, IR) of 96 individuals, calculated using four genetic marker types (putatively neutral microsatellites, MHC-linked microsatellites, reduced representation sequencing, and candidate region resequencing). We found no correlation in IR values across marker types, suggesting that various genetic markers reflect different aspects of genomic diversity. In addition, some marker types were more informative than others for conservation decision-making. Reduced representation sequencing provided the highest precision (lowest error) for estimating population-level genetic diversity, and most closely reflected genome-wide heterozygosity both theoretically and empirically. Within the conservation context, our results highlight important considerations when choosing a molecular technique for wildlife genetics.

分子标记（molecular markers）是一类实用工具，可助力保护与种群管理者阐明影响受威胁种群的遗传过程。然而，随着分子技术的持续迭代革新，保护生物学家时常会接触到各类新型遗传标记——每种标记在特性上均存在细微差异，且在解答不同研究问题时各有优劣。本研究以玛利亚岛（Maria Island）一处已被充分研究的袋獾（Tasmanian devil）种群为研究对象，旨在阐明整合多套遗传数据集时面临的诸多问题，并解答诸多种群管理者提出的核心疑问：哪类数据集能够对我们拟测定的种群过程提供最精准、准确的估算结果？我们对96个个体的个体杂合度（以内部亲缘度（internal relatedness, IR）表示）进行了分析，该指标通过四类遗传标记类型计算得到：推定中性微卫星（putatively neutral microsatellites）、与主要组织相容性复合体（MHC）连锁的微卫星、简化基因组测序（reduced representation sequencing）以及候选区域重测序（candidate region resequencing）。研究发现，不同标记类型对应的IR值之间不存在相关性，这表明各类遗传标记所反映的是基因组多样性的不同维度。此外，部分标记类型在辅助保护决策方面相较于其他类型更具信息价值。在估算种群水平的遗传多样性时，简化基因组测序的精度最高（误差最低）；且无论从理论层面还是实证层面而言，其均最贴近全基因组杂合度水平。在保护生物学的研究框架下，本研究结果为野生动物遗传学研究中分子技术的选择提供了重要参考依据。