Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Wertheim cung cấp cho các bạn kiến thức về ngành y đề tài: The promise and limitations of population exomics for human evolution studies. | Tennessen et al. Genome Biology 2011 12 127 http 2011 12 9 127 Genome Biology OPINION L__ The promise and limitations of population exomies for human evolution studies Jacob A Tennessen1 Timothy D O Connor1 Michael J Bamshad1 2 and Joshua M Akey1 Abstract Exome sequencing is poised to yield substantial insights into human genetic variation and evolutionary history but there are significant challenges to overcome before this becomes a reality. For the past few decades advances in molecular biology have continuously refined our understanding of human evolutionary history. A simple model of expansion and global migrations from a single ancestral human population with adaptation at a few protein polymorphisms has transformed into a complex scenario involving introgression among numerous divergent groups multiple population-specific bottlenecks and thousands of candidate genomic sites of possible evolutionary importance 1-6 . Although the broad patterns of demographic trends geographic population structure and adaptation have now been well established 1-4 emerging genome-scale datasets will enable detailed inferences about particular populations and genes. Major ongoing goals include inferring intracontinental patterns of migration and admixture reconstructing the history of human population growth and bottlenecks and categorizing whether polymorphisms are selectively neutral deleterious or adaptive Box 1 . Until recently such questions could be addressed only with the limited statistical power and precision afforded by single nucleotide polymorphism SNP arrays or small sets of sequence data. However exome sequencing has the potential to address many of these questions. Exome sequencing is a new and powerful technique in which genomic DNA that binds to a predefined target of known exons is sequenced using next-generation technology in order to capture the protein-coding Correspondence akeyj@ department of Genome Sciences University of .
