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Development of multi-null-hypotheses method for detection of selective forces at molecular level in evolution of human genes involved in DNA-repair mechanism impaired in cancer progression

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

We developed a multi-null-hypotheses (MNH) method for testing signatures of natural selection in Kimura's neutral model of human evolution with population growth and limited migration between dems. To evaluate the influence of such time changes and demography in population size, we employed different variants of the null hypothesis, corresponding to constancy, growth, or substructure and growth, respectively. We apply the model for searching in SNP haplotypes from four genes implicated in impairing DNA-repair mechanism in human familial cancers: ataxia telangiectasia (ATM), human helicase RECQL, Bloom's syndrome (BLM) and Werner's syndrome (WRN). The sample is composed of about 600 chromosomes, derived from residents of Houston, TX (USA), representing major ethnic backgrounds: Caucasian, African, Asian and Hispanic. The method is illustrated with Bloom's neutrality tests B and Q. Our study suggests that detected deviations from neutrality may be obscured by presence of recombination, substructure and changes of population size in the case of RECQL haplotypes, while in the ATM haplotypes the signal is rather strong. The BLM and especially WRN haplotypes do not register deviations from neutrality.

Original languageEnglish
Title of host publication19th IFAC World Congress IFAC 2014, Proceedings
EditorsEdward Boje, Xiaohua Xia
PublisherIFAC Secretariat
Pages11547-11552
Number of pages6
ISBN (Electronic)9783902823625
DOIs
Publication statusPublished - 2014
Event19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014 - Cape Town, South Africa
Duration: 24 Aug 2014 → 29 Aug 2014

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
Volume19
ISSN (Print)1474-6670

Conference

Conference19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014
Country/TerritorySouth Africa
CityCape Town
Period24/08/14 → 29/08/14

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

  • Bioinformatics
  • Cancer genes evolution
  • DNA-repair mechanism in cancer progression
  • Data mining tools
  • Modeling and identification
  • Searching natural selection

ASJC Scopus subject areas

  • Control and Systems Engineering

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