Doctoral Dissertation Improvement: Genetic Marker Bias Effects on Inferences of Human Evolutionary History

人类作为一个物种，其基因组中的DNA变异模式可以证明他们的历史。人类学家利用人类种群的遗传变异模式来推断过去人类的迁徙和种群之间的分化。 遗传数据也被用来区分自然选择，人类行为和随机事件，在分子水平上影响人类进化。 然而，那些明显表明进化力量的模式可能是在研究中包含特定类型的遗传变异的偏见的产物。 在发现可测试的遗传变异或设计数据库或基因芯片的过程中，可能会引入偏倚。 在该项目中，研究人员将研究当前人类遗传变异公共数据库（即HapMap）设计中的偏差以及收集遗传数据的最新工具（基因芯片或微阵列）影响分子人类学研究结果的程度。 他们询问医学界广泛用于基因作图的预制基因芯片和基因数据库是否适合推断人口历史和人类进化，在什么类型的人口中预期会有显著的偏见影响，以及这种偏见的性质和后果。这项研究将主要使用东南亚人群，这些人群在人类基因组的原始研究和当前基因图谱技术的发展中代表性不足。 将从居住在泰国北方的至少四个少数民族（阿卡族、傈僳族、拉祜族、苗族或克伦族）（通常称为山地部落）的个体中采集唾液样本，作为DNA来源。 这些人口之所以令人感兴趣，是因为他们在整个亚洲都有复杂的移民历史，而且个人不太可能与其种族以外的人结婚。 来自其他亚裔和非亚裔多数人群的DNA已可用于本研究。 将测量每个群体内和群体之间的遗传变异，并将这些信息进行汇编，以创建用于测试假设的人工模拟群体，这将有助于研究人员更好地理解实际观察结果。然后将对结果进行分析，以寻找每组遗传变异的已知进化事件的证据。 结果的比较将显示什么类型的偏见有显着影响这样的推论，并允许一个更全面的遗传特征的人口正在研究中，这项研究的更广泛的影响包括描述在何种程度上科学家的观点的准确性，人类的扩散和人口的历史可能会受到偏见的影响广泛使用的基因分型工具和数据库最初设计的基因作图。 该项目还将促进国际（泰国和美国）、跨学科（人类学、精神病学和遗传学）和机构（纽约大学文理研究生院和耶鲁大学医学院）的合作。为这项研究收集的样本和数据将用于美国和泰国研究人员的研究生培训，目的是在未来继续这种国际合作。

Human beings carry evidence of much of their history as a species in patterns of DNA variation in their genomes. Anthropologists have used patterns of genetic variation in human populations to infer past human migrations and divergences between populations. Genetic data also have been used to distinguish between natural selection, human behavior, and random events, as influences on human evolution at the molecular level. However, patterns that are apparently indicative of evolutionary forces may instead be artifacts of biases towards the inclusion of particular types of genetic variants in a study. Biases can be introduced during the discovery of testable genetic variants or during the design of databases or gene chips. In this project, the researchers will examine the extent to which biases in the design of current public databases of human genetic variation (i.e. HapMap) and the latest tools for gathering genetic data (gene chips or microarrays) affect results of molecular anthropology studies. They ask whether or not pre-made gene chips and genetic databases widely used by the medical community for gene mapping are appropriate for inferring population history and human evolution, within what types of populations significant effects of bias would be expected, and the nature and consequences of such bias.As an example, this research will use predominantly Southeast Asian populations which were underrepresented in the original studies of the human genome and development of current gene mapping technologies. Saliva samples will be collected from individuals as a source of DNA from a minimum of four ethnic minorities (Akha, Lisu, Lahu, Hmong, or Karen), commonly referred to as Hill Tribes, residing in Northern Thailand. These populations are of interest because they are known to have complex migratory histories throughout Asia, and individuals are unlikely to marry outside of their ethnicity. DNA from other Asian and non-Asian majority populations is already available for use in this study. Genetic variation within and between each population will be measured, and this information will be compiled to create artificial simulated populations with which to test hypotheses, which will help the researchers to understand actual observations better. Results will then be analyzed for evidence of known kinds of evolutionary events for each group of genetic variants. Comparison of the results will show what types of biases have significant affects on such inferences, and allow for a more comprehensive genetic characterization of the populations under study.The broader impacts of this study include describing the extent to which the accuracy of scientists' views of human dispersal and population history may be affected by biases in widely-available genotyping tools and databases originally designed for gene mapping. This project will also facilitate international (Thailand and United States), interdisciplinary (Anthropology, Psychiatry, and Genetics), and institutional (New York University Graduate School of Arts and Sciences and Yale University School of Medicine) collaborations. Both samples and data collected for this study will be used for graduate student training of American and Thai researchers, with the intent to continue this international collaboration in the future.