PubMed · 15313833
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Roger N Rosenberg. 2004. Genes for movement.. https://doi.org/10.1001/archneur.61.8.1182
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DNA sequencing can be used to gain important information on genes, genetic variation and gene function for biological and medical studies. The growing collection of publicly available reference genome sequences will underpin a new era of whole genome re-sequencing, but sequencing costs need to fall and throughput needs to rise by several orders of magnitude. Novel technologies are being developed to meet this need by generating massive amounts of sequence that can be aligned to the reference sequence. The challenge is to maintain the high standards of accuracy and completeness that are hallmarks of the previous genome projects. One or more new sequencing technologies are expected to become the mainstay of future research, and to make DNA sequencing centre stage as a routine tool in genetic research in the coming years.
Identifying regions of the human genome that have been targets of positive selection will provide important insights into recent human evolutionary history and may facilitate the search for complex disease genes. However, the confounding effects of population demographic history and selection on patterns of genetic variation complicate inferences of selection when a small number of loci are studied. To this end, identifying outlier loci from empirical genome-wide distributions of genetic variation is a promising strategy to detect targets of selection. Here, we evaluate the power and efficiency of a simple outlier approach and describe a genome-wide scan for positive selection using a dense catalog of 1.58 million SNPs that were genotyped in three human populations. In total, we analyzed 14,589 genes, 385 of which possess patterns of genetic variation consistent with the hypothesis of positive selection. Furthermore, several extended genomic regions were found, spanning >500 kb, that contained multiple contiguous candidate selection genes. More generally, these data provide important practical insights into the limits of outlier approaches in genome-wide scans for selection, provide strong candidate selection genes to study in greater detail, and may have important implications for disease related research.
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