05 February 2018 by Christina Eichstaedt

New evidence of genetic adaptation to high altitude in Andean populations


High altitude represents an extreme environment characterised by low concentrations of atmospheric oxygen (hypoxia), arid climate, high solar radiation and other environmental stressors. Andeans have resided at high elevations for several millennia and have developed an unique array of physiological adaptations. However, the genetic changes that led to these adaptations remain largely elusive


The aim of this study is to identify genetic variants that harbour signatures of recent positive selection and may facilitate physiological adaptations to hypobaric hypoxia.
Methods: We conducted whole genome sequencing and lung function tests in 19 Argentinean highlanders (>3500 m) comparing them to 16 Native American lowlanders. We developed a new statistical procedure using a combination of population branch statistics (PBS) and number of segregating sites by length (nSL) to detect beneficial alleles that arose since the settlement of the Andes and are currently present in 15-50% of the population.


We identified two missense variants as significant targets of selection. One of these variants, located within the GPR126 gene, has been previously associated with the forced expiratory volume/forced vital capacity ratio. The derived allele of GPR126 is associated with lung function in our sample of highlanders (p<0.05). The other novel missense variant mapped to the EPAS1 gene encoding the hypoxia inducible factor 2α. EPAS1 is known to be the major selection candidate gene in Tibetans and mutations within this gene lead to erythrocytosis and pulmonary hypertension.


These variants may contribute to the physiological adaptations to hypobaric hypoxia, possibly by altering lung function and preventing excessive erythrocytosis and hypoxia induced pulmonary hypertension in Andean populations.

Key Contributors

Christina A. Eichstaedt,1,2 Luca Pagani,3,4 Tiago Antao,5 Charlotte E. Inchley,3 Alexia Cardona,6 Alexander Mörseburg,3 Florian J. Clemente,7 Timothy J. Sluckin,8 Ene Metspalu,4,9 Mario Mitt,10, 11 Reedik Mägi,10 Georgi Hudjashov,4, 12 Mait Metspalu,4, 9 Maru Mormina,13 Guy S. Jacobs14 and Toomas Kivisild3, 4 1: Thoraxclinic at the University Hospital Heidelberg, Heidelberg, Baden-Württemberg, Germany 2: Institute of Human Genetics, Heidelberg University, Heidelberg, Baden-Württemberg, Germany 3: Department of Archaeology and Anthropology, University of Cambridge, Cambridge, Cambridgeshire, UK 4: Estonian Biocentre, Tartu, Tartumaa, Estonia 5: Division of Biological Sciences, University of Montana, Missoula, Missoula County, Montana, USA 6: MRC Epidemiology Unit, University of Cambridge, Cambridge, Cambridgeshire, UK 7: Institute for Computational Biology, University of Montpellier, Montferrier-sur-Lez, Hérault, France 8: Mathematical Sciences, University of Southampton, Southampton, Hampshire, UK 9: Department of Evolutionary Biology, Institute of Molecular and Cell Biology, University of Tartu, Tartu, Tartumaa, Estonia 10: Estonian Genome Centre, University of Tartu, Tartumaa, Estonia 11: Department of Biotechnology, Institute of Molecular and Cell Biology, University of Tartu, Tartumaa, Estonia 12: Statistics and Bioinformatics Group, Institute of Fundamental Sciences, Massey University, Palmerston North, Kairanga, New Zealand 13: Department of Applied Sciences, Faculty of Humanities and Social Sciences, University of Winchester, Winchester, Hampshire, UK 14: Complexity Institute, Nayang Technological University, Singapore

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