Genomic Analyses from Non-invasive Prenatal Testing Reveal Genetic Associations, Patterns of Viral Infections, and Chinese Population History

  • Siyang Liu
  • , Shujia Huang
  • , Fang Chen
  • , Lijian Zhao
  • , Yuying Yuan
  • , Stephen Starko Francis
  • , Lin Fang
  • , Zilong Li
  • , Long Lin
  • , Rong Liu
  • , Yong Zhang
  • , Huixin Xu
  • , Shengkang Li
  • , Yuwen Zhou
  • , Robert W. Davies
  • , Qiang Liu
  • , Robin G. Walters
  • , Kuang Lin
  • , Jia Ju
  • , Thorfinn Korneliussen
  • Melinda A. Yang, Qiaomei Fu, Jun Wang, Lijun Zhou, Anders Krogh, Hongyun Zhang, Wei Wang, Zhengming Chen, Zhiming Cai, Ye Yin, Huanming Yang, Mao Mao, Jay Shendure, Jian Wang, Anders Albrechtsen, Xin Jin, Rasmus Nielsen, Xun Xu

Research output: Contribution to journalArticlepeer-review

228 Scopus citations

Abstract

We analyze whole-genome sequencing data from 141,431 Chinese women generated for non-invasive prenatal testing (NIPT). We use these data to characterize the population genetic structure and to investigate genetic associations with maternal and infectious traits. We show that the present day distribution of alleles is a function of both ancient migration and very recent population movements. We reveal novel phenotype-genotype associations, including several replicated associations with height and BMI, an association between maternal age and EMB, and between twin pregnancy and NRG1. Finally, we identify a unique pattern of circulating viral DNA in plasma with high prevalence of hepatitis B and other clinically relevant maternal infections. A GWAS for viral infections identifies an exceptionally strong association between integrated herpesvirus 6 and MOV10L1, which affects piwi-interacting RNA (piRNA) processing and PIWI protein function. These findings demonstrate the great value and potential of accumulating NIPT data for worldwide medical and genetic analyses. Large-scale analysis of genome sequences from non-invasive prenatal testing in Chinese women yields insights into phenotypic trait associations, viral infection patterns, and population history.

Original languageEnglish
Pages (from-to)347-359.e14
JournalCell
Volume175
Issue number2
DOIs
StatePublished - 4 Oct 2018
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • genome-wide association study
  • low-pass sequencing
  • non-invasive prenatal testing
  • plasma virome
  • population genetics

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