IDEAS home Printed from https://ideas.repec.org/a/eee/thpobi/v112y2016icp1-13.html
   My bibliography  Save this article

Testing neutrality at copy-number-variable loci under the finite-allele and finite-site models

Author

Listed:
  • Hu, Xin-Sheng
  • Hu, Yang
  • Chen, Xiaoyang

Abstract

Copy-number variation (CNV) is an important form of DNA structural variation because a certain proportion of genomes in many eukaryotic species can contribute to such variations. Owing to the differences between CNVs and single nucleotide polymorphisms (SNPs) in size, mutation rate and maintaining mechanism, it is more realistic to characterize CNV evolution under the finite-allele and finite-site models. Here, we propose a method to test multiple CNVs neutrality under the finite-allele and finite-site models and the assumption of mutation–drift process. The statistical property of the method is evaluated through Monte Carlo simulations under the effects of the sample size, the scaled mutation rates, the number of CNVs, the population demographic change, and selection. Different from Tajima’s D test, a bootstrap or a permutation approach is suggested to conduct a neutrality test. Application of this method is illustrated using the diploid CNV genotypes measured in discrete copy numbers in 11 HapMap phase III populations. The results show that the mutation–drift process can explain the variation of genome-wide CNVs among 1184 individuals (856 CNVs, ∼0.02Mb on average in size), irrespective of the historical demographic changes. Patterns from allele-frequency-spectrum analysis also support the hypothesis of neutral CNVs. Our results suggest that most human chromosomal changes in healthy individuals via unbalanced rearrangements of the segments with certain sizes are neutral.

Suggested Citation

  • Hu, Xin-Sheng & Hu, Yang & Chen, Xiaoyang, 2016. "Testing neutrality at copy-number-variable loci under the finite-allele and finite-site models," Theoretical Population Biology, Elsevier, vol. 112(C), pages 1-13.
    • Handle: RePEc:eee:thpobi:v:112:y:2016:i:c:p:1-13
    DOI: 10.1016/j.tpb.2016.07.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040580916300338
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tpb.2016.07.002?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. David E. Reich & Michele Cargill & Stacey Bolk & James Ireland & Pardis C. Sabeti & Daniel J. Richter & Thomas Lavery & Rose Kouyoumjian & Shelli F. Farhadian & Ryk Ward & Eric S. Lander, 2001. "Linkage disequilibrium in the human genome," Nature, Nature, vol. 411(6834), pages 199-204, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pietro Biroli & Titus Galama & Stephanie von Hinke & Hans van Kippersluis & Kevin Thom, 2022. "Economics and Econometrics of Gene-Environment Interplay," Bristol Economics Discussion Papers 22/759, School of Economics, University of Bristol, UK.
    2. Chung-Feng Kao & Jia-Rou Liu & Hung Hung & Po-Hsiu Kuo, 2015. "A Robust GWSS Method to Simultaneously Detect Rare and Common Variants for Complex Disease," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-14, April.
    3. Haipeng Li & Thomas Wiehe, 2013. "Coalescent Tree Imbalance and a Simple Test for Selective Sweeps Based on Microsatellite Variation," PLOS Computational Biology, Public Library of Science, vol. 9(5), pages 1-14, May.
    4. Shuxia Guo & Yunhua Hu & Yusong Ding & Jiaming Liu & Mei Zhang & Rulin Ma & Heng Guo & Kui Wang & Jia He & Yizhong Yan & Dongsheng Rui & Feng Sun & Lati Mu & Qiang Niu & Jingyu Zhang & Shugang Li, 2015. "Association between Eight Functional Polymorphisms and Haplotypes in the Cholesterol Ester Transfer Protein (CETP) Gene and Dyslipidemia in National Minority Adults in the Far West Region of China," IJERPH, MDPI, vol. 12(12), pages 1-14, December.
    5. Li Qin & Wu Rongling, 2009. "A Multilocus Model for Constructing a Linkage Disequilibrium Map in Human Populations," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-27, February.
    6. Shpak, Max & Ni, Yang & Lu, Jie & Müller, Peter, 2017. "Variance in estimated pairwise genetic distance under high versus low coverage sequencing: The contribution of linkage disequilibrium," Theoretical Population Biology, Elsevier, vol. 117(C), pages 51-63.
    7. Zhang, Hong & Wu, Zheyang, 2022. "The general goodness-of-fit tests for correlated data," Computational Statistics & Data Analysis, Elsevier, vol. 167(C).
    8. Wei Zhao & Erin B. Ware & Zihuai He & Sharon L. R. Kardia & Jessica D. Faul & Jennifer A. Smith, 2017. "Interaction between Social/Psychosocial Factors and Genetic Variants on Body Mass Index: A Gene-Environment Interaction Analysis in a Longitudinal Setting," IJERPH, MDPI, vol. 14(10), pages 1-17, September.
    9. Hou, Wei & Liu, Tian & Li, Yao & Li, Qin & Li, Jiahan & Das, Kiranmoy & Berg, Arthur & Wu, Rongling, 2009. "Multilocus genomics of outcrossing plant populations," Theoretical Population Biology, Elsevier, vol. 76(1), pages 68-76.
    10. Xiaoshuai Zhang & Xiaowei Yang & Zhongshang Yuan & Yanxun Liu & Fangyu Li & Bin Peng & Dianwen Zhu & Jinghua Zhao & Fuzhong Xue, 2013. "A PLSPM-Based Test Statistic for Detecting Gene-Gene Co-Association in Genome-Wide Association Study with Case-Control Design," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-8, April.
    11. Kari E. North & Lisa J. Martin, 2008. "The Importance of Gene—Environment Interaction," Sociological Methods & Research, , vol. 37(2), pages 164-200, November.
    12. Shuo Jiao & Li Hsu & Sonja Berndt & Stéphane Bézieau & Hermann Brenner & Daniel Buchanan & Bette J Caan & Peter T Campbell & Christopher S Carlson & Graham Casey & Andrew T Chan & Jenny Chang-Claude &, 2012. "Genome-Wide Search for Gene-Gene Interactions in Colorectal Cancer," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-14, December.
    13. Konstantin Schildknecht & Sven Olek & Thorsten Dickhaus, 2015. "Simultaneous Statistical Inference for Epigenetic Data," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-15, May.
    14. Zhuling Yu & Wei Li & Deren Hou & Lin Zhou & Yanyao Deng & Mi Tian & Xialu Feng, 2015. "Relationship between Adiponectin Gene Polymorphisms and Late-Onset Alzheimer’s Disease," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-11, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:thpobi:v:112:y:2016:i:c:p:1-13. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/intelligence .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.