Whole genome sequencing data from pedigrees suggests linkage disequilibrium among rare variants created by population admixture

被引:5
|
作者
Tao Feng
Xiaofeng Zhu
机构
[1] Case Western Reserve University,Department of Epidemiology and Biostatistics
关键词
Rare Variant; Transmission Disequilibrium Test; Population Admixture; Affected Offspring; Family Trio;
D O I
10.1186/1753-6561-8-S1-S44
中图分类号
学科分类号
摘要
Next-generation sequencing technologies have been designed to discover rare and de novo variants and are an important tool for identifying rare disease variants. Many statistical methods have been developed to test, using next-generation sequencing data, for rare variants that are associated with a trait. However, many of these methods make assumptions that rare variants are in linkage equilibrium in a gene. In this report, we studied whether transmitted or untransmitted haplotypes carry an excess of rare variants using the whole genome sequencing data of 15 large Mexican American pedigrees provided by the Genetic Analysis Workshop 18. We observed that an excess of rare variants are carried on either transmitted or nontransmitted haplotypes from parents to offspring. Further analyses suggest that such nonrandom associations among rare variants can be attributed to population admixture and single-nucleotide variant calling errors. Our results have significant implications for rare variant association studies, especially those conducted in admixed populations.
引用
收藏
相关论文
共 50 条
  • [1] Whole Genome Sequencing in a Founder Population Identifies Novel Candidate Rare Variants for Schizophrenia
    Lencz, Todd
    Yu, Jin
    Malhotra, Anil
    Pe'er, Itsik
    Darvasi, Ariel
    [J]. NEUROPSYCHOPHARMACOLOGY, 2015, 40 : S572 - S572
  • [2] Genome-Wide Estimation of Linkage Disequilibrium from Population-Level High-Throughput Sequencing Data
    Maruki, Takahiro
    Lynch, Michael
    [J]. GENETICS, 2014, 197 (04) : 1303 - U421
  • [3] Higher criticism approach to detect rare variants using whole genome sequencing data
    Jing Xuan
    Li Yang
    Zheyang Wu
    [J]. BMC Proceedings, 8 (Suppl 1)
  • [4] Identifying rare variants inconsistent with identity-by-descent in population-scale whole-genome sequencing data
    Johnson, Kelsey E.
    Adams, Christopher J.
    Voight, Benjamin F.
    [J]. METHODS IN ECOLOGY AND EVOLUTION, 2022, 13 (11): : 2429 - 2442
  • [5] Linkage disequilibrium maps for European and African populations constructed from whole genome sequence data
    Vergara-Lope, Alejandra
    Jabalameli, M. Reza
    Horscroft, Clare
    Ennis, Sarah
    Collins, Andrew
    Pengelly, Reuben J.
    [J]. SCIENTIFIC DATA, 2019, 6 (1)
  • [6] Linkage disequilibrium maps for European and African populations constructed from whole genome sequence data
    Alejandra Vergara-Lope
    M. Reza Jabalameli
    Clare Horscroft
    Sarah Ennis
    Andrew Collins
    Reuben J. Pengelly
    [J]. Scientific Data, 6
  • [7] Inferring disease risk genes from sequencing data in multiplex pedigrees through sharing of rare variants
    Bureau, Alexandre
    Begum, Ferdouse
    Taub, Margaret A.
    Hetmanski, Jacqueline B.
    Parker, Margaret M.
    Albacha-Hejazi, Hasan
    Scott, Alan F.
    Murray, Jeffrey C.
    Marazita, Mary L.
    Bailey-Wilson, Joan E.
    Beaty, Terri H.
    Ruczinski, Ingo
    [J]. GENETIC EPIDEMIOLOGY, 2019, 43 (01) : 37 - 49
  • [9] A rare variant non-parametric linkage method for nuclear and extended pedigrees with application to exome and whole genome sequence data
    Zhao, Linhai
    Zhang, Di
    Broadbent, Carl A.
    Wang, Gao T.
    Vardarajan, Badri N.
    Goate, Alison M.
    Mayeux, Richard
    Leal, Suzanne M.
    [J]. GENETIC EPIDEMIOLOGY, 2018, 42 (07) : 748 - 748
  • [10] Predicting rare allele carriers from genotyping-array data using whole genome sequencing data in the Estonian population
    Sikka, T.
    Palover, M.
    Nikopensius, T.
    Alver, M.
    Nelis, M.
    Metspalu, A.
    Tonisson, N.
    Esko, T.
    [J]. EUROPEAN JOURNAL OF HUMAN GENETICS, 2019, 27 : 649 - 650