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Sequencing of 50 Human Exomes Reveals Adaptation to High Altitude
Open accessAbstract
No Genetic Vertigo: Peoples living in high altitudes have adapted to their situation (see the Perspective by Storz ). To identify gene regions that might have contributed to high-altitude adaptation in Tibetans, Simonson et al. (p. 72 , published online 13 May) conducted a genome scan of nucleotide polymorphism comparing Tibetans, Han Chinese, and Japanese, while Yi et al. (p. 75 ) performed comparable analyses on the coding regions of all genes—their exomes. Both studies converged on a gene, endothelial Per-Arnt-Sim domain protein 1 (also known as hypoxia-inducible factor 2 α), which has been linked to the regulation of red blood cell production. Other genes identified that were potentially under selection included adult and fetal hemoglobin and two functional candidate loci that were correlated with low hemoglobin concentration in Tibetans. Future detailed functional studies will now be required to examine the mechanistic underpinnings of physiological adaptation to high altitudes.
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“For example, by studying genes that show population-specific allele-frequency differences between Tibetans and Han Chinese, a signal of positive natural selection was detected in EPAS1, a transcription factor involved in the response to hypoxia, which most probably helps the Tibetans to live at high altitudes [40].”
From Ancient DNA and the rewriting of human history: be sparing with Occam’s razor (2016) · cites this paper as [40]
In the citing paper
“Genome-wide searches for single-nucleotide polymorphisms (SNP), candidate gene approaches and exome sequencing have identified genetic variations in the HIF2A, PHD2 and PPARA genes that associate with lower hemoglobins in native Tibetans compared to Han Chinese and with high altitude adaptation in other populations.”
From Regulation of erythropoiesis by hypoxia-inducible factors (2013) · cites this paper as [173]
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“Although WES can generate sequencing data on regions outside the exome [18,19], it is not”
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“Compared with the commonly used statistic to estimate levels of population differentiation—FST, PBS calculates allele frequency change specific to one focal population by adding pairwise FST values involving a third “outgroup” population (Yi et al. 2010).”
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“The resulting raw reads in fastq format were aligned (overlap) with minimap and an assembly graph (layout) was generated with miniasm2 (16).”
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“PBS statistics measure the amount of sequence change along branches of a population tree.(27,28) These statistics have also been called locus-specific branch length(29) and relative rate statistics.”
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“Several methods make use of sequence capture hybridization techniques to target HTS toward particular regions of the genome (e.g., exon-capture, ultra-conserved element, RAD loci) (Yi et al. 2010; Faircloth et al. 2012; Suchan et al. 2016).”
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“Himalayan signatures Studies comparing high-altitude Himalayan genomes (Tibetan and Sherpa) with matched low landers have identified a positive selection of EPAS1 (endothelial PAS domain protein 1), which encodes the HIF-2α subunit of HIF complex, and EGLN1, which encodes PHD2, members of the HIF-oxygen-sensing pathwa…”
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“Some other genes involved in adaptation to high elevations in endothermic species also had a low Ka/Ks ratio in our comparison, for example, EPAS1 [20,21] (Ka/Ks=0.1057), ARG2 [10] (Ka/Ks=0.1095), and EP300 [19] (Ka/Ks=0.1725).”
BackgroundInfluentialHuman adaptation to extreme environmental conditions
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Self-citationRecent Evolutionary History of Tigers Highlights Contrasting Roles of Genetic Drift and Selection
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“We computed a statistic, mPBS [metapopulation branch statistic, a simple extension of the PBS statistic of Yi et al. (2010), see Materials and Methods section], measuring the length of the branch leading to a given subspecies since its divergence from the others (fig.”
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“Similar to the pattern for EGLN1, SNPs at the EPAS1 locus are correlated with erythrocyte abundance and haemoglobin concentration (Beall et al., 2010; Yang & Jin, 2017; Yi et al., 2010).”
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“Using a number of statistics traditionally applied to modern data, including PBS (Yi et al. 2010) and Tajima’s D (Tajima 1989), they first identify a number of candidate loci under selection.”
MethodGenes, Evolution and Intelligence
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A genome-wide scan for signatures of directional selection in domesticated pigs
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“The population branch statistic (PBS) has recently been proposed [8] to detect a significant change in allele or haplotype frequency along the lineage of one population after it diverged from other populations.”
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“EGLN1 and EPAS1 variants are thought to play a major role in the elevated haemoglobin phenotype seen in Tibetans and confer a selective advantage in the high-altitude environment [49–51].”
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“High-altitude human populations such as Sherpas, Tibetans, Ethiopians, and Andeans were found to possess specific SNPs associated with hypoxia tolerance (Beall 2000; Yi et al. 2010; Jha et al. 2016).”
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“To further characterise these PBS peaks, we (i) calculated Hudson’s F ST in each genomic window (S7 Data); (ii) built neighbour joining phylogenies from the phased variants within each peak, to identify swept haplotypes (S16A Data; nj tool in the ape R package [75]); and (iii) calculated the profile of Garud’s H 12 in…”
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“The population branch statistic computes the amount of genetic differentiation at a given locus along a branch leading to a population of interest by comparing transformed pairwise FST values between each pair of three populations (4).”
BackgroundInfluentialHuman genome variability, natural selection and infectious diseases
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Himalayan wolf distribution and admixture based on multiple genetic markers
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“Similar hypoxia adaptations have been found in the Tibetan people that share these high-altitude ecosystems (Beall, 2007; HuertaSanchez, 2014; Peng et al., 2011; Yi et al., 2010), as well as in domestic yaks (Bos grunniens) (Qiu et al., 2012) and Tibetan mastiff dogs (Canis lupus familiaris).”
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Dissecting human population variation in single-cell responses to SARS-CoV-2
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“Genes in the HIF pathway have some of the strongest genome-wide signals of directional selection in high-altitude populations (e.g. Yi et al. 2010; Scheinfeldt et al. 2012), and oxygen transport in general is a frequent target of selection in high-altitude environments (Storz et al. 2012).”
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“Besides, the discovery of a particular Tibetan-Denisovan haplotype motif characterized by derived alleles from five SNVs in the EPAS1 region indicated shared genetic drift between Tibetans and extinct non-AMH populations (Yi et al. 2010; Huerta-Sánchez et al. 2014; Lu et al. 2016).”
BackgroundSelf-citationDetecting Selection in Multiple Populations by Modeling Ancestral Admixture Components
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“…methods (Sabeti et al. 2006), and are sensitive to different types of positive selection events, including sweeps from a de novo mutation, sweeps from standing variation, incomplete sweeps, and adaptive introgression (Bonhomme et al. 2010; Yi et al. 2010; Fumagalli et al. 2015; Racimo et al. 2017).”
BackgroundInfluentialSelf-citationThe human brain in a high altitude natural environment: A review
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“Positive natural selection in the Egl nine homolog 1 (EGLN1), endothelial PAS domain protein 1 (EPAS1), and peroxisome proliferator activated receptor alpha (PPARA) genes, all of which are associated with the hypoxiainducible transcription factor (HIF) pathway (Simonson et al., 2010; Yi et al., 2010; Yang et al., 2017…”
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“In addition to the well-recognized, but still on a mechanistic level incompletely understood, genetic underpinnings of CHPH (11, 103), there is now an increasing interest in epigenetic control mechanisms of PAH (39).”
BackgroundA variant-centric perspective on geographic patterns of human allele frequency variation
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Rapid adaptation to malaria facilitated by admixture in the human population of Cabo Verde
Hamid, I., Korunes, K. L., Beleza, S. S., & Goldberg, A. (2021) · eLife · doi:10.7554/elife.63177 · Cited by 64
Genome-wide signatures of the geographic expansion and breeding of soybean
Li, Y., Qin, C., Wang, L., Jiao, C., Hong, H., Tian, Y., Li, Y., Xing, G., Wang, J., Gu, Y., et al. (2022) · Science China Life Sciences · doi:10.1007/s11427-022-2158-7 · Cited by 67
“We then identified selection signatures for each of the four stages using three statistics: log2 (θπ ratio) (Nei and Li, 1979), Population Branch Statistics (PBS) (Weir and Cockerham, 1984b; Yi et al., 2010), and cross-population composite likelihood ratio (XP-CLR) (Chen et al., 2010b).”
MethodSelf-citationThe transcriptional and regulatory identity of erythropoietin producing cells
Kragesteen, B. K., Giladi, A., David, E., Halevi, S., Geirsdóttir, L., Lempke, O. M., Li, B., Bapst, A. M., Xie, K., Katzenelenbogen, Y., et al. (2023) · Nature Medicine · doi:10.1038/s41591-023-02314-7 · Cited by 67
Self-citationMore than a decade of genetic research on the Denisovans
Peyrégne, S., Slon, V., & Kelso, J. F. (2023) · Nature Reviews Genetics · doi:10.1038/s41576-023-00643-4 · Cited by 75
Simonson, T. S., Wei, G., Wagner, H. E., Wuren, T., Ga, Q., Ma, Y., Wagner, P. D., & Ge, R. L. (2015) · The Journal of Physiology · doi:10.1113/jp270518 · Cited by 65
Ding, D., Liu, G., Hou, L., Gui, W., Chen, B., & Kang, L. (2018) · Nature Communications · doi:10.1038/s41467-018-07529-8 · Cited by 63
A genome-wide genetic screen uncovers determinants of human pigmentation
Bajpai, V. K., Swigut, T., Mohammed, J., Tycko, J., Naqvi, S., Villanueva, M. A., Kim, T. C., Arora, N., Pritchard, J. K., Bassik, M. C., et al. (2023) · Science · doi:10.1126/science.ade6289 · Cited by 69
“To identify genes among our screen hits that might have undergone a recent adaptation for skin pigmentation variation among human populations, we used a tree-based statistic called population branch statistic (PBS) ( 41 ).”
Guan, L., Chi, W., Xiao, W., Chen, L., & He, S. (2014) · BMC Evolutionary Biology · doi:10.1186/s12862-014-0192-1 · Cited by 62
“For instance, EPAS1 (HIF-2α), EGLN1, and PPARA were detected in Tibetans [59,60]; ADAM17 in the yak [61]; ADORA2A, CCL2, ENG, PIK3C2A, PKLR, ATP12A, and NOS3 in the Tibetan antelope [62]; SRF, TXNRD2, and WNT7B in the ground tit [63]; and EPAS1, SIRT7, PLXNA4, and MAFG in the Tibetan mastiff [64].”
BackgroundGenomic Scan Reveals Loci under Altitude Adaptation in Tibetan and Dahe Pigs
Dong, K., Yao, N., Pu, Y., He, X., Zhao, Q., Luan, Y., Guan, W., Rao, S., & Ma, Y. (2014) · PLoS ONE · doi:10.1371/journal.pone.0110520 · Cited by 65
“In the past few years, increasing attentions have been devoted to identify the underlying genetic factors for Tibetan people [2,3], yak [4], Tibetan chicken [5], Tibetan antelope [6], pika [7] as well as Tibetan pigs [8,9].”
BackgroundmtDNA Lineage Expansions in Sherpa Population Suggest Adaptive Evolution in Tibetan Highlands
Kang, L., Zheng, H., Chen, F., Yan, S. L., Liu, K., Qin, Z., Liu, L., Zhao, Z., Li, L., Wang, X., et al. (2013) · Molecular Biology and Evolution · doi:10.1093/molbev/mst147 · Cited by 67
“In recent years, genome-wide studies have shown probable candidates of hypoxia adaption for Tibetan populations (Beall et al. 2010; Simonson et al. 2010; Yi et al. 2010; Peng, Yang et al. 2011; Xu et al. 2011).”
BackgroundSelf-citationAryal, N., Weatherall, M., Bhatta, Y. K. D., & Mann, S. (2016) · High Altitude Medicine & Biology · doi:10.1089/ham.2015.0118 · Cited by 64
Human genetic adaptation to high altitudes: Current status and future prospects
MOORE, L. G. (2016) · Quaternary International · doi:10.1016/j.quaint.2016.09.045 · Cited by 66
“Tibetan studies Several groups have shown that putatively adaptive variants in the EPAS1 and EGLN1 gene regions in Tibetans are associated with lower Hb levels (Beall et al., 2010; Simonson et al., 2010; Yi et al., 2010).”
BackgroundGenetic-Driven Druggable Target Identification and Validation
Floris, M., Olla, S., Schlessinger, D., & Cucca, F. (2018) · Trends in Genetics · doi:10.1016/j.tig.2018.04.004 · Cited by 67
Shanfelter, A. F., Archambeault, S., & White, M. A. (2019) · Genome Biology and Evolution · doi:10.1093/gbe/evz090 · Cited by 66
The fine‐scale genetic structure and selection signals of Chinese indigenous pigs
Huang, M., Yang, B., Chen, H., Zhang, H., Wu, Z., Ai, H., Ren, J., & Huang, L. (2019) · Evolutionary Applications · doi:10.1111/eva.12887 · Cited by 65
“The adaptive variants of EPAS1 reduced hemoglobin concentrations in Tibetans relative to their lowland counterparts, serving as a crucial protection mech‐ anism for excessive erythrocytosis in Tibetans (Beall et al., 2010; Yi et al., 2010).”
BackgroundVerma, P., Sharma, A., Sodhi, M., Thakur, K., Kataria, R. S., Niranjan, S. K., Bharti, V. K., Kumar, P., Giri, A., Kalia, S., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-25736-7 · Cited by 63
Genetic variants underlying differences in facial morphology in East Asian and European populations
Zhang, M., Wu, S., Du, S., Qian, W., Chen, J., Qiao, L., Yang, Y., Tan, J., Yuan, Z., Peng, Q., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01038-7 · Cited by 67
Self-citationGenomic Analysis of Natural Selection and Phenotypic Variation in High-Altitude Mongolians
Xing, J., Wuren, T., Simonson, T. S., Watkins, W. S., Witherspoon, D. J., Wu, W., Ga, Q., Huff, C. D., Jorde, L. B., & Ge, R.-L. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003634 · Cited by 63
“(population branch statistic) selection scans were performed as previously described [20,21].”
MethodSilva, J., Scheffler, B. E., Sanabria, Y., Guzman, C. D., Galam, D. C., Farmer, A. D., Woodward, J. E., May, G. D., & Oard, J. H. (2011) · Theoretical and Applied Genetics · doi:10.1007/s00122-011-1687-4 · Cited by 61
Neo-functionalization of a Teosinte branched 1 homologue mediates adaptations of upland rice
Lyu, J., Huang, L., Zhang, S., Zhang, Y., He, W., Zeng, P., Zeng, Y., Huang, G., Zhang, J., Ning, M., et al. (2020) · Nature Communications · doi:10.1038/s41467-019-14264-1 · Cited by 65
Self-citationRubinstein, N. D., Doron‐Faigenboim, A., Mayrose, I., & Pupko, T. (2011) · Molecular Biology and Evolution · doi:10.1093/molbev/msr162 · Cited by 58
Genomic Evidence for Local Adaptation of Hunter-Gatherers to the African Rainforest
Lopez, M., Choin, J., Sikora, M., Siddle, K. J., Harmant, C., Costa, H. A., Silvert, M., Mouguiama-Daouda, P., Hombert, J.-M., Froment, A., et al. (2019) · Current Biology · doi:10.1016/j.cub.2019.07.013 · Cited by 62
Evolutionary forces shaping genomic islands of population differentiation in humans
Hofer, T., Foll, M., & Excoffier, L. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-107 · Cited by 62
“[28-31]].”
Parallel Evolution of Cold Tolerance Within Drosophila melanogaster
Pool, J. E., Braun, D. T., & Lack, J. (2016) · Molecular Biology and Evolution · doi:10.1093/molbev/msw232 · Cited by 61
“Like the related PBS (Yi et al. 2010), PBE uses FST values among three populations.”
MethodSelf-citationGenetic variation of world soybean maturity date and geographic distribution of maturity groups
Liu, X., Wu, J., Ren, H., Qi, Y., Li, C., Cao, J., Zhang, X., Zhang, Z., Cai, Z., & Gai, J. (2017) · Ikushugaku zasshi · doi:10.1270/jsbbs.16167 · Cited by 61
“The SNPs of the population were identified by the RealSFS (Yi et al. 2010), and 98,482 SNPs were finally confirmed according to the criteria, from which the SNPs of 371 varieties were polymorphic with a rate of missing and heterozygous alleles calls ≤30% and minor allele frequencies ≥1%.”
MethodSelf-citationKarikari, B., Wang, Z., Zhou, Y., Yan, W., Feng, J., & Zhao, T. (2020) · BMC Plant Biology · doi:10.1186/s12870-020-02604-z · Cited by 60
Barnes, A. C., Rodríguez-Zapata, F., Juárez-Núñez, K. A., Gates, D. J., Janzen, G. M., Kur, A., Wang, L., Jensen, S. E., Estévez-Palmas, J. M., Crow, T. M., et al. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2100036119 · Cited by 63
“D-myo-inositol (1,4,5)-trisphosphate biosynthesis”
Rytkönen, K. T., Akbarzadeh, A., Miandare, H. K., Kamei, H., Duan, C., Leder, E. H., Williams, T. A., & Nikinmaa, M. (2012) · Evolution · doi:10.1111/j.1558-5646.2012.01820.x · Cited by 61
Ouzhuluobu, He, Y., Lou, H., Cui, C., Deng, L., Gao, Y., Zheng, W., Guo, Y., Wang, X., Ning, Z., et al. (2019) · National Science Review · doi:10.1093/nsr/nwz160 · Cited by 58
Self-citationMulching: Boosting crop productivity and improving soil environment in herbal plants
Thakur, M., & Kumar, R. (2020) · Journal of Applied Research on Medicinal and Aromatic Plants · doi:10.1016/j.jarmap.2020.100287 · Cited by 59
Ahmad, A. M., Ahmad, S., Malcolm, K. C., Miller, S. M., Hendry‐Hofer, T. B., Schaack, J. B., & White, C. W. (2013) · American Journal of Respiratory Cell and Molecular Biology · doi:10.1165/rcmb.2012-0107oc · Cited by 57
Wang, Y., Yang, L., Wu, B. M., Song, Z., & He, S. (2015) · Gene · doi:10.1016/j.gene.2015.04.023 · Cited by 57
Self-citationFabian, D. K., Lack, J., Mathur, V. S., Schlötterer, C., SCHMIDT, P. S., Pool, J. E., & Flatt, T. (2015) · Journal of Evolutionary Biology · doi:10.1111/jeb.12607 · Cited by 57
“While elevational gradients have major effects on phenotypic differentiation in numerous organisms (Hodkinson 2005; Körner 2007; Yi et al. 2010; Bresson et al. 2011; Keller et al. 2013; Hille & Cooper 2014), considerably less is known about altitudinal clines in Drosophila.”
Self-citationChen, M., Raffield, L. M., Mousas, A., Sakaue, S., Huffman, J. E., Jiang, T., Akbari, P., Vuckovic, D., Bao, E. L., Moscati, A., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.01.17.910497 · Cited by 59
“To further explore this possibility, we assessed whether variants that tag selective sweeps (tagSweeps, variants with the highest integrated haplotype score (iHS)) within continental populations from the 1000 Genomes Project (1000G) are associated with blood-cell phenotypes (Johnson and Voight, 2018).”
BackgroundMethodInfluentialSelf-citationYu, Z., Chang, F., Lv, W., Sharmin, R. A., Wang, Z., Kong, J., Bhat, J. A., & Zhao, T. (2019) · Genes · doi:10.3390/genes10120957 · Cited by 58
“Based on the Bayesian estimation of the site frequency, RealSFS was utilized for the SNP calling [31].”
Regulation of bone marrow hematopoietic stem cell is involved in high-altitude erythrocytosis
Li, P., Huang, J., Tian, H., Huang, Q., Jiang, C., & Gao, Y. (2010) · Experimental Hematology · doi:10.1016/j.exphem.2010.10.006 · Cited by 58
Chabris, C. F., Lee, J. J., Benjamin, D. J., Beauchamp, J. P., Glaeser, E. L., Borst, G., Pinker, S. A., & Laibson, D. (2013) · American Journal of Public Health · doi:10.2105/ajph.2013.301327 · Cited by 67
The Kalash Genetic Isolate: Ancient Divergence, Drift, and Selection
Ayub, Q., Mezzavilla, M., Pagani, L., Haber, M., Mohyuddin, A., Khaliq, S., Mehdi, S. Q., & Tyler‐Smith, C. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.03.012 · Cited by 61
“Selection in the Kalash populations was estimated as described by Yi et al.(30) In brief, we obtained estimates of the population time of divergence (T) from FST values and corrected for the effective population size of the population considered (Nep), as shown in”
MethodRadwan, J., & Babik, W. (2012) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2012.2322 · Cited by 58
Meng, S., He, J., Zhao, T., Xing, G., Li, Y., Yang, S., Lu, J., Wang, Y., & Gai, J. (2016) · Theoretical and Applied Genetics · doi:10.1007/s00122-016-2724-0 · Cited by 58
Self-citation
Metadata
- Authors
- Yi, X., Liang, Y., Huerta-Sanchez, E., Jin, X., Cuo, Z. X. P., Pool, J. E., Xu, X., Jiang, H., Vinckenbosch, N., Korneliussen, T. S., Zheng, H., Liu, T., He, W., Li, K., Luo, R., Nie, X., Wu, H., Zhao, M., Cao, H., Zou, J., Shan, Y., Li, S., Yang, Q., Asan, Ni, P., Tian, G., Xu, J., Liu, X., Jiang, T., Wu, R., Zhou, G., Tang, M., Qin, J., Wang, T., Feng, S., Li, G., Huasang, Luosang, J., Wang, W., Chen, F., Wang, Y., Zheng, X., Li, Z., Bianba, Z., Yang, G., Wang, X., Tang, S., Gao, G., Chen, Y., Luo, Z., Gusang, L., Cao, Z., Zhang, Q., Ouyang, W., Ren, X., Liang, H., Zheng, H., Huang, Y., Li, J., Bolund, L., Kristiansen, K., Li, Y., Zhang, Y., Zhang, X., Li, R., Li, S., Yang, H., Nielsen, R., Wang, J., & Wang, J.
- Affiliations
- BGI Group (China) (CN)
- Department of Integrative Biology and Department of Statistics, University of California Berkeley, Berkeley, CA 94820, USA.
- Tibet Autonomous Region People's Hospital (CN)
- University of California, Davis (US)
- University of California, Berkeley (US)
- University of Copenhagen (DK)
- The Military General Hospital of Tibet, Lhasa, 850007, China.
- The hospital of XiShuangBanNa Dai Nationalities, Autonomous Jinghong 666100, Yunnan, China.
- Corresponding author
- Yi, Xin
- Liang, Yu
- Jin, Xin
- Cuo, Zha Xi Ping
- Pool, John E.
- ORCID
- Yi, Xin
- Liang, Yu
- Jin, Xin
- Pool, John E.
- Xu, Xun
- Jiang, Hui
- Korneliussen, Thorfinn Sand
- Zheng, Hancheng
- Liu, Tao
- He, Weiming
- Luo, Ruibang
- Wu, Honglong
- Cao, Hongzhi
- Zou, Jing
- Shan, Ying
- Yang, Qi
- Tian, Geng
- Xu, Junming
- Liu, Xiao
- Wu, Renhua
- Zhou, Guangyu
- Tang, Meifang
- Qin, Junjie
- Wang, Tong
- Wang, Wei
- Chen, Fang
- Li, Zhuo
- Yang, Ge
- Tang, Shuhui
- Gao, Guoyi
- Luo, Zhen
- Gusang, Lamu
- Zhang, Qinghui
- Liang, Huiqing
- Bolund, Lars
- Kristiansen, Karsten
- Li, Yingrui
- Zhang, Yong
- Zhang, Xiuqing
- Li, Ruiqiang
- Li, Songgang
- Yang, Huanming
- Nielsen, Rasmus
- Wang, Jun
- Wang, Jian
- Venue
- Science
- Published
- 2010-07-02
- Volume
- 329
- Issue
- 5987
- Pages
- 75-78
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC3711608
- OpenAlex
- W2147575903
- Cited by
- 1,611
- References
- 35
- Citations by year
- 2026: 92 · 2025: 95 · 2024: 90 · 2023: 123 · 2022: 113 · 2021: 123 · 2020: 101 · 2019: 106 · 2018: 84 · 2017: 88 · 2016: 105 · 2015: 111 · 2014: 95 · 2013: 97 · 2012: 90
- FWCI
- 50.78
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- The HKU Scholars Hub (University of Hong Kong) (submittedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
- Funders
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (124318)
- U.S. Public Health Service (R01-MHG084695)
- National Institute on Alcohol Abuse and Alcoholism (R21AA022707)
- National Institute of Mental Health (R01MH084695)
- National Human Genome Research Institute (R01HG003229)
- Topics
- Health Sciences › Medicine › Physiology (medical) › High Altitude and Hypoxia
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Keywords
- high-altitude adaptation, Tibetan Plateau, EPAS1, natural selection, hypoxia response, allele frequency change, single nucleotide polymorphisms, Han Chinese, population genomics, exome sequencing
- MeSH terms
- Acclimatization, Endothelial PAS Domain-Containing Protein 1, Altitude, Bayes Theorem, China, Erythrocyte Count, Ethnicity, Exons, Female, Gene Frequency, Hemoglobins, Humans, Male, Oxygen, Selection, Genetic, Genome, Human, Sequence Analysis, DNA, Tibet, Polymorphism, Single Nucleotide, Asian People, Basic Helix-Loop-Helix Proteins, Basic Helix-Loop-Helix Transcription Factors, Genetic Association Studies
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