Literature DB >> 17089882

Finding the genes underlying adaptation to hypoxia using genomic scans for genetic adaptation and admixture mapping.

Mark D Shriver1, Rui Mei, Abigail Bigham, Xianyun Mao, Tom D Brutsaert, Esteban J Parra, Lorna G Moore.   

Abstract

The complete sequencing the human genome and recent analytical advances have provided the opportunity to perform genome-wide studies of human variation. There is substantial potential for such population-genomic approaches to assist efforts to uncover the historical and demographic histories of human populations. Additionally, these genome-wide datasets allow for investigations of variability among genomic regions. Although all genomic regions in a population have experienced the same demographic events, they have not been affected by these events in precisely the same way. Much of the variability among genomic regions is simply the result of genetic drift (i.e., gene frequency changes resulting from the effects of small breeding-population size), but some is also the result of genetic adaptation, which will only affect the gene under selection and nearby regions. We have used a new DNA typing assay that allows for the genotyping of thousands of SNPs on hundreds of samples to identify regions most likely to have been affected by genetic adaptation. Populations that have inhabited different niches (e.g., high-altitude regions) can be used to identify genes underlying the physiological differences. We have used two methods (admixture mapping and genome scans for genetic adaptation) founded on the population-genomic paradigms to search for genes underlying population differences in response to chronic hypoxia. There is great promise that together these methods will facilitate the discovery of genes influencing hypoxic response.

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Year:  2006        PMID: 17089882     DOI: 10.1007/978-0-387-34817-9_9

Source DB:  PubMed          Journal:  Adv Exp Med Biol        ISSN: 0065-2598            Impact factor:   2.622


  6 in total

1.  Analysis of genomic admixture in Uyghur and its implication in mapping strategy.

Authors:  Shuhua Xu; Wei Huang; Ji Qian; Li Jin
Journal:  Am J Hum Genet       Date:  2008-03-20       Impact factor: 11.025

2.  Identifying signatures of natural selection in Tibetan and Andean populations using dense genome scan data.

Authors:  Abigail Bigham; Marc Bauchet; Dalila Pinto; Xianyun Mao; Joshua M Akey; Rui Mei; Stephen W Scherer; Colleen G Julian; Megan J Wilson; David López Herráez; Tom Brutsaert; Esteban J Parra; Lorna G Moore; Mark D Shriver
Journal:  PLoS Genet       Date:  2010-09-09       Impact factor: 5.917

3.  Association of EGLN1 gene with high aerobic capacity of Peruvian Quechua at high altitude.

Authors:  Tom D Brutsaert; Melisa Kiyamu; Gianpietro Elias Revollendo; Jenna L Isherwood; Frank S Lee; Maria Rivera-Ch; Fabiola Leon-Velarde; Sudipta Ghosh; Abigail W Bigham
Journal:  Proc Natl Acad Sci U S A       Date:  2019-11-11       Impact factor: 11.205

4.  Human population admixture in Asia.

Authors:  Shuhua Xu
Journal:  Genomics Inform       Date:  2012-09-28

5.  A novel candidate region for genetic adaptation to high altitude in Andean populations.

Authors:  Guido Valverde; Hang Zhou; Sebastian Lippold; Cesare de Filippo; Kun Tang; David López Herráez; Jing Li; Mark Stoneking
Journal:  PLoS One       Date:  2015-05-11       Impact factor: 3.240

6.  Positive selection of AS3MT to arsenic water in Andean populations.

Authors:  Christina A Eichstaedt; Tiago Antao; Alexia Cardona; Luca Pagani; Toomas Kivisild; Maru Mormina
Journal:  Mutat Res       Date:  2015-07-29       Impact factor: 2.433

  6 in total

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