Department of Sociology, University of Wisconsin-Madison, 8128 Social Science Building, 1180 Observatory Drive, Madison, WI 53706, USA.
Soc Stud Sci. 2011 Feb;41(1):5-30. doi: 10.1177/0306312710379170.
This article presents findings from our ethnographic research on biomedical scientists' studies of human genetic variation and common complex disease. We examine the socio-material work involved in genome-wide association studies (GWAS) and discuss whether, how, and when notions of race and ethnicity are or are not used. We analyze how researchers produce simultaneously different kinds of populations and population differences. Although many geneticists use race in their analyses, we find some who have invented a statistical genetics method and associated software that they use specifically to avoid using categories of race in their genetic analysis. Their method allows them to operationalize their concept of 'genetic ancestry' without resorting to notions of race and ethnicity. We focus on the construction and implementation of the software's algorithms, and discuss the consequences and implications of the software technology for debates and policies around the use of race in genetics research. We also demonstrate that the production and use of their method involves a dynamic and fluid assemblage of actors in various disciplines responding to disciplinary and sociopolitical contexts and concerns. This assemblage also includes particular discourses on human history and geography as they become entangled with research on genetic markers and disease.We introduce the concept of'genome geography' to analyze how some researchers studying human genetic variation'locate' stretches of DNA in different places and times. The concept of genetic ancestry and the practice of genome geography rely on old discourses, but they also incorporate new technologies, infrastructures, and political and scientific commitments. Some of these new technologies provide opportunities to change some of our institutional and cultural forms and frames around notions of difference and similarity. Nevertheless, we also highlight the slipperiness of genome geography and the tenacity of race and race concepts.
本文介绍了我们对生物医学科学家研究人类遗传变异和常见复杂疾病的人种志研究的发现。我们考察了全基因组关联研究(GWAS)中涉及的社会物质工作,并讨论了种族和民族的概念是否以及如何被使用。我们分析了研究人员如何同时产生不同种类的人群和人群差异。尽管许多遗传学家在他们的分析中使用种族,但我们发现一些人发明了一种统计遗传学方法和相关软件,专门用于避免在他们的遗传分析中使用种族类别。他们的方法允许他们在不诉诸种族和民族概念的情况下操作他们的“遗传祖先”概念。我们专注于软件算法的构建和实施,并讨论软件技术对围绕遗传学研究中使用种族的争论和政策的影响和意义。我们还表明,该方法的生产和使用涉及到不同学科的参与者的动态和灵活组合,他们对学科和社会政治背景和关注点做出反应。这种组合还包括关于人类历史和地理的特定论述,因为它们与遗传标记和疾病的研究纠缠在一起。我们引入“基因组地理”的概念来分析研究人类遗传变异的一些研究人员如何在不同的地方和时间“定位” DNA 片段。遗传祖先的概念和基因组地理的实践依赖于旧的论述,但也纳入了新技术、基础设施以及政治和科学承诺。其中一些新技术提供了改变我们关于差异和相似性概念的机构和文化形式和框架的机会。然而,我们也强调了基因组地理的易变性和种族和种族概念的顽固性。