EAGER: New Methods for Genomic Analysis of Noninvasive Samples

这项研究的目的是开发新的方法，从以非侵入性方式收集的生物样本中生成和分析基因组规模的数据。非侵入性样本通常是自然种群可用的唯一类型的生物样本，特别是在濒危或受威胁的物种中，但它们产生的DNA质量很低。在过去的二十年里，非侵入性基因分析技术几乎没有什么变化，这意味着基因组革命还没有到来，对于那些只有非侵入性样本的物种来说。这项研究将通过制定新的实验室方案来解决这个问题，以增加和纯化非侵入性样本的DNA产量，使其达到适合基因组分析的水平，并开发新的软件来分析由此产生的基因组数据。它将通过比较来自非侵入性样本的基因组数据和来自高质量DNA样本的数据，使用东非安博塞利盆地经过充分研究的野生狒狒的已知谱系的数据，来验证这些方法。该项目将在研究许多不同物种和样本类型的基因组学工具方面取得重大飞跃。将发布公开可用的协议和软件，这些协议和软件可用于研究以前无法进行此类研究的物种的进化和种群历史。它还将以评估脆弱物种保护状况的工具的形式提供社会效益。最后，研究生和本科生都将被培训为该项目的合作者。

The objective of this study is to develop novel methods for generating and analyzing genome-scale data from biological samples that have been collected in a noninvasive manner. Noninvasive samples are often the only type of biological sample available for natural populations, especially in endangered or threatened species, but they yield tiny quantities of low-quality DNA. Noninvasive genetic analysis techniques have changed little in the past twenty years, meaning that the genomic revolution has not yet arrived for species for which only noninvasive samples are available. This study will address this problem by producing new lab protocols for increasing and purifying the DNA yield from noninvasive samples to a level appropriate for genomic analysis, and by developing new software to analyze the resulting genomic data. It will validate these approaches by comparing genomic data from noninvasive samples to data from high-quality DNA samples, using data for a known pedigree from the well-studied wild baboons of the Amboseli basin in East Africa. This project will result in a major leap forward in tools for studying the genomics of many different species and sample types. Publicly available protocols and software will be released, which can be used to investigate evolutionary and population history in species for which such studies were previously impossible. It will also provide societal benefits in the form of tools for assessing the conservation status of vulnerable species. Finally, both graduate and undergraduate students will be trained as collaborators on the project.