尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

Lin Zeng, He-Qun Liu, Xiao-Long Tu, Chang-Mian Ji, Xiao Gou, Ali Esmailizadeh, Sheng Wang, Ming-Shan Wang, Ming-Cheng Wang, Xiao-Long Li, Hadi Charati, Adeniyi C. Adeola, Rahamon Akinyele Moshood Adedokun, Olatunbosun Oladipo, Sunday Charles Olaogun, Oscar J. Sanke, Mangbon Godwin F., Sheila Cecily Ommeh, Bernard Agwanda, Jacqueline Kasiiti Lichoti, Jian-Lin Han, Hong-Kun Zheng, Chang-Fa Wang, Ya-Ping Zhang, Laurent A. F. Frantz, Dong-Dong Wu. Genomes reveal selective sweeps in kiang and donkey for high-altitude adaptation. Zoological Research, 2021, 42(4): 450-460. doi: 10.24272/j.issn.2095-8137.2021.095
Citation: Lin Zeng, He-Qun Liu, Xiao-Long Tu, Chang-Mian Ji, Xiao Gou, Ali Esmailizadeh, Sheng Wang, Ming-Shan Wang, Ming-Cheng Wang, Xiao-Long Li, Hadi Charati, Adeniyi C. Adeola, Rahamon Akinyele Moshood Adedokun, Olatunbosun Oladipo, Sunday Charles Olaogun, Oscar J. Sanke, Mangbon Godwin F., Sheila Cecily Ommeh, Bernard Agwanda, Jacqueline Kasiiti Lichoti, Jian-Lin Han, Hong-Kun Zheng, Chang-Fa Wang, Ya-Ping Zhang, Laurent A. F. Frantz, Dong-Dong Wu. Genomes reveal selective sweeps in kiang and donkey for high-altitude adaptation. Zoological Research, 2021, 42(4): 450-460. doi: 10.24272/j.issn.2095-8137.2021.095


doi: 10.24272/j.issn.2095-8137.2021.095

Genomes reveal selective sweeps in kiang and donkey for high-altitude adaptation

Funds: This work was supported by the National Natural Science Foundation of China (31621062), Strategic Priority Research Program of the Chinese Academy of Sciences (XDA2004010302), and Second Tibetan Plateau Scientific Expedition and Research (STEP) Program (2019QZKK05010703). D.D.W. was supported by the National Natural Science Foundation of China (91731304, 31822048), Strategic Priority Research Program of the Chinese Academy of Sciences (XDB13020600), Qinghai Department of Science and Technology Major Project, and State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, Yunnan University (2018KF001). Sampling of this work was also supported by the Animal Branch of the Germplasm Bank of Wild Species, Chinese Academy of Sciences (Large Research Infrastructure Funding)
More Information
  • 摘要: 在过去的几百年里,生活在青藏高原的家驴已经适应了高海拔的环境。有趣的是,同属于马科的近缘物种藏野驴也居住在这一地区。以往的研究阐述了不同谱系中特定基因的适应性渐渗对青藏高原低氧环境适应有重要的作用。在这项研究中,我们对藏家驴和藏野驴是否通过相同或不同的生物途径适应高原环境,以及是否发生了适应性渐渗现象展开了研究。我们从头组装了一个藏野驴的基因组,结合5个藏野驴和93个家驴(包括24个藏家驴)的基因组重测序数据展开了分析研究。分析表明,藏野驴EPAS1基因存在强的选择性清除信号;然而,藏家驴的高原适应,则是另一与高原适应相关的基因EGLN1,参与它们适应高海拔环境。此外,针对基因流的分析,我们未发现藏野驴和藏家驴中与高原适应相关的基因流动。我们的研究结果表明,尽管家驴在青藏高原的进化时间较短,且存在一个已经适应高原低氧环境的近缘物种,但藏家驴并没有通过与藏野驴的适应性渐渗来获得对高原的适应性,藏野驴与藏家驴这两个物种通过不同的生物途径进化出了对高原的适应能力。
    #Authors contributed equally to this work
  • Figure  1.  Genome evolution in kiangs

    A: Distribution of structural variants compared with horse genome. Tracks (outside to inside) show chromosomes, a: indel density, b: insertion density, c: deletion density, d: translocation density, e: gene density, f: repeat density. Density of indels, insertions, deletions, and translocations, was calculated from a 1 Mb non-overlapping sliding window, and 500 kb non-overlapping sliding window for gene density and repeat density of the horse. B: Expression analysis of REGs based on human expression data. Analysis was performed as described previously (Li et al., 2013). Human gene expression data (Human U133A Gene Atlas) in 84 tissues or cells were downloaded from BioGPS (Wu et al., 2016) (http://biogps.org/#goto=welcome). Relative expression level of REGs in each tissue was calculated by mean expression value of REGs in tissue divided by average whole-genome expression value. Only top 10 tissues/cell lines are presented. Species tree of six mammals was used to detect positively selected genes in kiang lineage (as foreground lineage) by branch site model in PAML. C: McDonald-Kreitman (MK) test identified several genes related to immunity, DNA damage, energy metabolism, and angiogenesis under positive selection in kiang lineage.

    Figure  2.  Population genetics analysis of kiangs and domestic donkeys

    A: Geographical location of domestic donkeys with re-sequenced genomes. Blue through light green indicate low to high altitude. B: Population structure analysis by Admixture with K from 2 to 5. C, D: No genetic introgression between kiang and Tibetan donkey was revealed by D-statistic and TreeMix.

    Figure  3.  Hard selective sweep in EPAS1 in kiangs

    A: Composite-likelihood ratio (CLR) detected by SweeD and nucleotide diversity levels around EPAS1 gene in different populations, including kiang, Tibetan donkey, and plain donkey. Results indicate that this gene likely experienced a hard selective sweep in kiangs. B: Haplotype of nucleotide mutations in EPAS1 showing high level of divergence between kiangs and domestic donkeys. Pink, yellow, blue, and black indicate genotypes of Homozygous variant, Heterozygote, Homozygous reference, and No call, respectively. C: Partial EPAS1 amino acid sequences among different species.

    Figure  4.  Rare hard selective sweep in kiangs at genome-wide scale

    Normalized nucleotide diversity was calculated as nucleotide diversity level in kiang population divided by donkey-kiang divergence around fixed substitutions using a non-overlapping window size of 10 kb.

    Figure  5.  Evidence of high-altitude adaptation in Tibetan domestic donkeys

    A: By comparing the genomes of Tibetan donkey populations and others, the genic region exhibited significantly higher FST values than the intergenic region. Statistical significance was calculated by Mann-Whitney U test. B: Population differentiation was more pronounced in non-synonymous SNPs than other types of SNPs. Statistical significance was calculated by chi-square test. C: A pattern of excess genic SNPs with high FST values (>0.4) between Tibetan domestic donkeys and lowland donkeys was found when constraining analyses to SNPs presenting similar minor allele frequencies (MAF). Statistical significance was calculated by chi-square test. D: Landscape of FST, Pi (nucleotide diversity), and LSBL values corroborates strong positive selection on EGLN1 gene. –log10 transformed FDR P-values are presented.

    Figure  6.  Selective sweep analysis by SweeD in kiang, Tibetan donkey, and plain donkey populations (A) and rare high CLR regions overlapped in the three populations(B)

  • [1] Akey JM, Zhang G, Zhang K, Jin L, Shriver MD. 2002. Interrogating a high-density SNP map for signatures of natural selection. Genome Research, 12(12): 1805−1814. doi: 10.1101/gr.631202
    [2] Alexander DH, Novembre J, Lange K. 2009. Fast model-based estimation of ancestry in unrelated individuals. Genome Research, 19(9): 1655−1664. doi: 10.1101/gr.094052.109
    [3] Beall CM, Cavalleri GL, Deng LB, Elston RC, Gao Y, Knight J, et al. 2010. Natural selection on EPAS1 (HIF2α) associated with low hemoglobin concentration in Tibetan highlanders. Proceedings of the National Academy of Sciences of the United States of America, 107(25): 11459−11464. doi: 10.1073/pnas.1002443107
    [4] Beja-Pereira A, England PR, Ferrand N, Jordan S, Bakhiet AO, Abdalla MA, et al. 2004. African origins of the domestic donkey. Science, 304(5678): 1781. doi: 10.1126/science.1096008
    [5] Bigham A, Bauchet M, Pinto D, Mao XY, Akey JM, Mei R, et al. 2010. Identifying signatures of natural selection in tibetan and andean populations using dense genome scan data. PLoS Genetics, 6(9): e1001116. doi: 10.1371/journal.pgen.1001116
    [6] Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, et al. 2011. The variant call format and VCFtools. Bioinformatics, 27(15): 2156−2158. doi: 10.1093/bioinformatics/btr330
    [7] Edgar RC. 2004. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Research, 32(5): 1792−1797. doi: 10.1093/nar/gkh340
    [8] Enard D, Messer PW, Petrov DA. 2014. Genome-wide signals of positive selection in human evolution. Genome Research, 24(6): 885−895. doi: 10.1101/gr.164822.113
    [9] Ewing G, Hermisson J. 2010. MSMS: a coalescent simulation program including recombination, demographic structure and selection at a single locus. Bioinformatics, 26(16): 2064−2065. doi: 10.1093/bioinformatics/btq322
    [10] Flower SS. 1929. List of the vertebrated animals exhibited in the Gardens of the Zoological Society of London, 1828–1927 centenary edition in 3 volumesVol 1: mammals. Nature, 124(3135): 836.
    [11] Foll M, Gaggiotti OE, Daub JT, Vatsiou A, Excoffier L. 2014. Widespread signals of convergent adaptation to high altitude in Asia and America. The American Journal of Human Genetics, 95(4): 394−407. doi: 10.1016/j.ajhg.2014.09.002
    [12] Ge RL, Cai QL, Shen YY, San A, Ma L, Zhang Y, et al. 2013. Draft genome sequence of the Tibetan antelope. Nature Communications, 4: 1858. doi: 10.1038/ncomms2860
    [13] Gnerre S, MacCallum I, Przybylski D, Ribeiro FJ, Burton JN, Walker BJ, et al. 2011. High-quality draft assemblies of mammalian genomes from massively parallel sequence data. Proceedings of the National Academy of Sciences of the United States of America, 108(4): 1513−1518. doi: 10.1073/pnas.1017351108
    [14] Gou X, Wang Z, Li N, Qiu F, Xu Z, Yan DW, et al. 2014. Whole-genome sequencing of six dog breeds from continuous altitudes reveals adaptation to high-altitude hypoxia. Genome Research, 24(8): 1308−1315. doi: 10.1101/gr.171876.113
    [15] Gray AP. 1972. Mammalian Hybrids. 2nd ed. Farnham Royal, Slough, United Kingdom: Commonwealth Agricultural Bureaux.
    [16] Gutenkunst RN, Hernandez RD, Williamson SH, Bustamante CD. 2009. Inferring the joint demographic history of multiple populations from multidimensional SNP frequency data. PLoS Genetics, 5(10): e1000695. doi: 10.1371/journal.pgen.1000695
    [17] Hay WE. 1859. Notes on the kiang of Thibet (E. kiang). Proceedings of the Zoological Society of London, 27: 353−357.
    [18] Hernandez RD, Kelley JL, Elyashiv E, Melton SC, Auton A, McVean G, et al. 2011. Classic selective sweeps were rare in recent human evolution. Science, 331(6019): 920−924. doi: 10.1126/science.1198878
    [19] Huerta-Sánchez E, Jin X, As an, Bianba Z, Peter BM, Vinckenbosch N, et al. 2014. Altitude adaptation in Tibetans caused by introgression of Denisovan-like DNA. Nature, 512(7513): 194−197. doi: 10.1038/nature13408
    [20] Jónsson H, Schubert M, Seguin-Orlando A, Ginolhac A, Petersen L, Fumagalli M, et al. 2014. Speciation with gene flow in equids despite extensive chromosomal plasticity. Proceedings of the National Academy of Sciences of the United States of America, 111(52): 18655−18660. doi: 10.1073/pnas.1412627111
    [21] Katoh K, Misawa K, Kuma KI, Miyata T. 2002. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Research, 30(14): 3059−3066. doi: 10.1093/nar/gkf436
    [22] Kent WJ. 2002. BLAT—the BLAST-like alignment tool. Genome Research, 12(4): 656−664. doi: 10.1101/gr.229202
    [23] Kinloch AAA. 1869. Large Game Shooting in Thibet and the North West. Oxford: Harrison.
    [24] Kong Y. 2011. Btrim: a fast, lightweight adapter and quality trimming program for next-generation sequencing technologies. Genomics, 98(2): 152−153. doi: 10.1016/j.ygeno.2011.05.009
    [25] Kosiol C, Vinař T, da Fonseca RR, Hubisz MJ, Bustamante CD, Nielsen R, et al. 2008. Patterns of positive selection in six mammalian genomes. PLoS Genetics, 4(8): e1000144. doi: 10.1371/journal.pgen.1000144
    [26] Li H, Coghlan A, Ruan J, Coin LJ, Hériché JK, Osmotherly L, et al. 2006. TreeFam: a curated database of phylogenetic trees of animal gene families. Nucleic Acids Research, 34(suppl_1): D572−D580.
    [27] Li Y, Vonholdt BM, Reynolds A, Boyko AR, Wayne RK, Wu DD, et al. 2013. Artificial selection on brain-expressed genes during the domestication of dog. Molecular Biology and Evolution, 30(8): 1867−1876. doi: 10.1093/molbev/mst088
    [28] Limbourg FP, Takeshita K, Radtke F, Bronson RT, Chin MT, Liao JK. 2005. Essential role of endothelial Notch1 in angiogenesis. Circulation, 111(14): 1826−1832. doi: 10.1161/01.CIR.0000160870.93058.DD
    [29] Lorenzo FR, Huff C, Myllymäki M, Olenchock B, Swierczek S, Tashi T, et al. 2014. A genetic mechanism for Tibetan high-altitude adaptation. Nature Genetics, 46(9): 951−956. doi: 10.1038/ng.3067
    [30] Löytynoja A, Goldman N. 2008. Phylogeny-aware gap placement prevents errors in sequence alignment and evolutionary analysis. Science, 320(5883): 1632−1635. doi: 10.1126/science.1158395
    [31] Ma XY, Ning T, Adeola AC, Li J, Esmailizadeh A, Lichoti JK, et al. 2020. Potential dual expansion of domesticated donkeys revealed by worldwide analysis on mitochondrial sequences. Zoological Research, 41(1): 51−60. doi: 10.24272/j.issn.2095-8137.2020.007
    [32] Martin SH, Davey JW, Jiggins CD. 2015. Evaluating the use of ABBA-BABA statistics to locate introgressed loci. Molecular Biology and Evolution, 32(1): 244−257. doi: 10.1093/molbev/msu269
    [33] McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, et al. 2010. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Research, 20(9): 1297−1303. doi: 10.1101/gr.107524.110
    [34] McVean GAT, Myers SR, Hunt S, Deloukas P, Bentley DR, Donnelly P. 2004. The fine-scale structure of recombination rate variation in the human genome. Science, 304(5670): 581−584. doi: 10.1126/science.1092500
    [35] Miao BP, Wang Z, Li YX. 2017. Genomic analysis reveals hypoxia adaptation in the Tibetan Mastiff by introgression of the gray wolf from the Tibetan Plateau. Molecular Biology and Evolution, 34(3): 734−743.
    [36] Orlando L, Ginolhac A, Zhang GJ, Froese D, Albrechtsen A, Stiller M, et al. 2013. Recalibrating Equus evolution using the genome sequence of an early Middle Pleistocene horse. Nature, 499(7456): 74−78. doi: 10.1038/nature12323
    [37] Patterson N, Moorjani P, Luo YT, Mallick S, Rohland N, Zhan YP, et al. 2012. Ancient admixture in human history. Genetics, 192(3): 1065−1093. doi: 10.1534/genetics.112.145037
    [38] Pavlidis P, Živković D, Stamatakis A, Alachiotis N. 2013. SweeD: likelihood-based detection of selective sweeps in thousands of genomes. Molecular Biology and Evolution, 30(9): 2224−2234. doi: 10.1093/molbev/mst112
    [39] Peng Y, Yang ZH, Zhang H, Cui CY, Qi XB, Luo XJ, et al. 2011. Genetic variations in Tibetan populations and high-altitude adaptation at the Himalayas. Molecular Biology and Evolution, 28(2): 1075−1081. doi: 10.1093/molbev/msq290
    [40] Pfeifer B, Wittelsbürger U, Ramos-Onsins SE, Lercher MJ. 2014. PopGenome: an efficient swiss army knife for population genomic analyses in R. Molecular Biology and Evolution, 31(7): 1929−1936. doi: 10.1093/molbev/msu136
    [41] Puri MC, Partanen J, Rossant J, Bernstein A. 1999. Interaction of the TEK and TIE receptor tyrosine kinases during cardiovascular development. Development, 126(20): 4569−4580. doi: 10.1242/dev.126.20.4569
    [42] Qiu Q, Zhang GJ, Ma T, Qian WB, Wang JY, Ye ZQ, et al. 2012. The yak genome and adaptation to life at high altitude. Nature Genetics, 44(8): 946−949. doi: 10.1038/ng.2343
    [43] Qu YH, Zhao HW, Han NJ, Zhou GY, Song G, Gao B, et al. 2013. Ground tit genome reveals avian adaptation to living at high altitudes in the Tibetan plateau. Nature Communications, 4: 2071. doi: 10.1038/ncomms3071
    [44] Shriver MD, Kennedy GC, Parra EJ, Lawson HA, Sonpar V, Huang J, et al. 2004. The genomic distribution of population substructure in four populations using 8,525 autosomal SNPs. Human Genomics, 1(4): 274. doi: 10.1186/1479-7364-1-4-274
    [45] Simão FA, Waterhouse RM, Ioannidis P, Kriventseva EV, Zdobnov EM. 2015. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics, 31(19): 3210−3212. doi: 10.1093/bioinformatics/btv351
    [46] Simonson TS, Yang YZ, Huff CD, Yun HX, Qin G, Witherspoon DJ, et al. 2010. Genetic evidence for high-altitude adaptation in Tibet. Science, 329(5987): 72−75. doi: 10.1126/science.1189406
    [47] Stark C, Breitkreutz BJ, Reguly T, Boucher L, Breitkreutz A, Tyers M. 2006. BioGRID: a general repository for interaction datasets. Nucleic Acids Research, 34(suppl 1): D535−D539.
    [48] Venkat A, Hahn MW, Thornton JW. 2018. Multinucleotide mutations cause false inferences of lineage-specific positive selection. Nature Ecology & Evolution, 2(8): 1280−1288.
    [49] vonHoldt B, Fan ZX, Ortega-Del Vecchyo D, Wayne RK. 2017. EPAS1 variants in high altitude Tibetan wolves were selectively introgressed into highland dogs. PeerJ, 5: e3522. doi: 10.7717/peerj.3522
    [50] Wang C, Li H, Guo Y, Huang J, Sun Y, Min J, Wang J, Fang X, Zhao Z, Wang S, et al. 2020. Donkey genomes provide new insights into domestication and selection for coat color. Nature Communications, 11(1): 6014. doi: 10.1038/s41467-020-19813-7
    [51] Wang GD, Fan RX, Zhai WW, Liu F, Wang L, Zhong L, et al. 2014. Genetic convergence in the adaptation of dogs and humans to the high-altitude environment of the Tibetan Plateau. Genome Biology and Evolution, 6(8): 2122−2128. doi: 10.1093/gbe/evu162
    [52] Wang K, Li MY, Hakonarson H. 2010. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Research, 38(16): e164. doi: 10.1093/nar/gkq603
    [53] Wang MS, Yang HC, Otecko NO, Wu DD, Zhang YP. 2016. Olfactory genes in Tibetan wild boar. Nature Genetics, 48(9): 972−973. doi: 10.1038/ng.3631
    [54] Wu CL, Jin XF, Tsueng G, Afrasiabi C, Su AI. 2016. BioGPS: building your own mash-up of gene annotations and expression profiles. Nucleic Acids Research, 44(D1): D313−D316. doi: 10.1093/nar/gkv1104
    [55] Wu DD, Ding XD, Wang S, Wójcik JM, Zhang Y, Tokarska M, et al. 2018. Pervasive introgression facilitated domestication and adaptation in the Bos species complex. Nature Ecology & Evolution, 2(7): 1139−1145.
    [56] Xiang K, Ouzhuluobu, Peng Y, Yang ZH, Zhang XM, Cui CY, et al. 2013. Identification of a Tibetan-specific mutation in the hypoxic gene EGLN1 and its contribution to high-altitude adaptation. Molecular Biology and Evolution, 30(8): 1889−1898. doi: 10.1093/molbev/mst090
    [57] Xu SH, Li SL, Yang YJ, Tan JZ, Lou HY, Jin WF, et al. 2011. A genome-wide search for signals of high-altitude Adaptation in Tibetans. Molecular Biology and Evolution, 28(2): 1003−1011. doi: 10.1093/molbev/msq277
    [58] Yang ZH. 2007. PAML 4: phylogenetic analysis by maximum likelihood. Molecular Biology and Evolution, 24(8): 1586−1591. doi: 10.1093/molbev/msm088
    [59] Zhang B, Day DS, Ho JW, Song LY, Cao JJ, Christodoulou D, et al. 2013. A dynamic H3K27ac signature identifies VEGFA-stimulated endothelial enhancers and requires EP300 activity. Genome Research, 23(6): 917−927. doi: 10.1101/gr.149674.112
    [60] Zhang JZ, Nielsen R, Yang ZH. 2005. Evaluation of an improved branch-site likelihood method for detecting positive selection at the molecular level. Molecular Biology and Evolution, 22(12): 2472−2479. doi: 10.1093/molbev/msi237
  • 加载中
  • 文章访问数:  1565
  • HTML全文浏览量:  729
  • PDF下载量:  259
  • 被引次数: 0
  • 收稿日期:  2021-03-25
  • 录用日期:  2021-06-21
  • 网络出版日期:  2021-06-22
  • 刊出日期:  2021-07-18