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EDARV370A associated facial characteristics in Uyghur population revealing further pleiotropic effects

Human Genetics volume 135, pages 99–108 (2016)Cite this article

Abstract

An adaptive variant of human Ectodysplasin receptor, EDARV370A, had undergone strong positive selection in East Asia. In mice and humans, EDARV370A was found to affect ectodermal-derived characteristics, including hair thickness, hair shape, active sweat gland density and teeth formation. Facial characteristics are also largely ectodermal derived. In this study, taking advantage of an admixed population of East Asian and European ancestry—the Uyghur, we aim to test whether EDARV370A is affecting facial characteristics and to investigate its pleiotropic nature and genetic model. In a sample of 1027 Uyghurs, we discover that EDARV370A is significantly associated with several facial characteristics, in particular shape of earlobe (P = 3.64 × 10 −6) and type of chin (P = 9.23 × 10 −5), with successful replication in other East Asian populations. Additionally, in this Uyghur population, we replicate previous association findings of incisors shoveling (P = 1.02 × 10 −7), double incisors shoveling (P = 1.86 × 10 −12) and hair straightness (P = 3.99 × 10 −16), providing strong evidence supporting an additive model for the EDARV370A associations. Partial least square path model confirms EDARV370A systematically affect these weakly related ectodermal-derived characteristics, suggesting the pleiotropic effect of EDARV370A mainly plays roles in early embryo development. This study extends our knowledge about the pleiotropic nature of EDARV370A and provides potential clues to its adaptation fitness in human evolution.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (31322030, 91331108 to S.W., 30890034, 31271338 to L. J., 91331204, 31171218 to S. X., 31401061 to Q. P., 31071102 to J. T., 31071096 to Y. Y.), National Science and Technology Infrastructure Program (2015FY111700 to L. J.), the National Basic Research Program (2012CB944600 to L. J.), Ministry of Science and Technology (2011BAI09B00 to L. J.), Ministry of Education (311016 to L. J.), National High-Tech Research and Development Program (2012AA021802 to Y.Y.), Chinese Academy of Sciences (XDB13040100 to S.X., 2014KIP214 to Q. P.), the National Program for Top-notch Young Innovative Talents of The “Wanren Jihua” Project to S. X., National Thousand Young Talents Award to S. W., Max Planck-CAS Paul Gerson Unna Independent Research Group Leadership Award to S. W., the State Key Laboratory of Genetic Engineering, Fudan University to S. W., and key lab of computational biology of Chinese Academy of Sciences to J. T.

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    Authors and Affiliations

    1. Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, 200031, Shanghai, China

      Qianqian Peng, Jinxi Li, Manfei Zhang, Sijie Wu, Yu Liu, Pengfei Qin, Kun Tang, Shuhua Xu, Li Jin & Sijia Wang

    2. State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, 200433, Shanghai, China

      Qianqian Peng, Jinxi Li, Jingze Tan, Yajun Yang, Manfei Zhang, Sijie Wu, Yu Liu, Juan Zhang, Shuhua Xu, Li Jin & Sijia Wang

    3. Fudan-Taizhou Institute of Health Sciences, 1 Yaocheng Road, 225300, Taizhou, Jiangsu, China

      Yajun Yang, Juan Zhang & Li Jin

    4. Department of Biochemistry, Preclinical Medicine College, Xinjiang Medical University, 830011, Urumqi, Xinjiang, China

      Yaqun Guan, Yi Jiao & Zhaoxia Zhang

    5. The Broad Institute of Harvard and MIT, Cambridge, MA, 02142, USA

      Pardis C. Sabeti

    6. Department of Organismic and Evolutionary Biology, Center for Systems Biology, Cambridge, MA, 02138, USA

      Pardis C. Sabeti

    7. School of Life Science and Technology, Shanghai Tec University, 200031, Shanghai, China

      Shuhua Xu

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    1. Qianqian Peng
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    Correspondence to Li Jin or Sijia Wang.

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    Qianqian Peng, Jinxi Li, Jingze Tan and Yajun Yang contributed equally to this study.

    Li Jin and Sijia Wang co-directed this study.

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    Peng, Q., Li, J., Tan, J. et al. EDARV370A associated facial characteristics in Uyghur population revealing further pleiotropic effects. Hum Genet 135, 99–108 (2016). https://doi.org/10.1007/s00439-015-1618-6

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