Computational Simulation and Analysis of Mutations: Nucleotide Fixation, Allelic Age and rare Genetic Variations in population

Computational Simulation and Analysis of Mutations: Nucleotide Fixation, Allelic Age and rare Genetic Variations in population

Bibliographic Details
Main Author: Qiu, Shuhao
Language:English
Published: University of Toledo Health Science Campus / OhioLINK 2016
Subjects:
Biomedical Research
Biology
Computer Science
Genetics
Information Science
Online Access:http://rave.ohiolink.edu/etdc/view?acc_num=mco1430494327
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spelling ndltd-OhioLink-oai-etd.ohiolink.edu-mco14304943272021-08-03T06:30:58Z Computational Simulation and Analysis of Mutations: Nucleotide Fixation, Allelic Age and rare Genetic Variations in population Qiu, Shuhao Biomedical Research Biology Computer Science Genetics Information Science In order to investigate the complexity of mutations, a computational approach named Genome Evolution by Matrix Algorithms (GEMA) has been implemented. GEMA models genomic changes, taking into account hundreds of mutations within each individual in a population. By modeling of entire human chromosomes, GEMA precisely mimics real biological processes that influence genome evolution, and demonstrates that the number of meiotic recombination events per gamete is among the most crucial factors influencing population fitness. GEMA was further modified and employed in a study of genome evolution to re-evaluate Maruyama’s phenomenon in modeled populations, which include haplotypes approximating real genomes. It was determined that only under specific conditions, of high recombination rates and abundance of neutral mutations, were deleterious and beneficial mutations younger than the neutral ones as predicted by Maruyama. Under other conditions, the ages of negative, neutral, and beneficial mutations were almost the same. After simulating mutations in a population, actual human genome sequence data from the “1000 Genome Project” Phase I was analyzed. All detected nucleotide sequence differences for 1092 people from 14 populations were computed. The distribution of these differences in individuals were then characterized on basis of their origin (European, Asian or African). By analysis of this genetic information of individuals, the very rare genetic variants were found to largely improve the detection of familial relations. Thus, with affordable whole-genome sequencing techniques, very rare SNPs should become important genetic markers for familial relationships and population stratification. 2016-02-24 English text University of Toledo Health Science Campus / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=mco1430494327 http://rave.ohiolink.edu/etdc/view?acc_num=mco1430494327 unrestricted This thesis or dissertation is protected by copyright: some rights reserved. It is licensed for use under a Creative Commons license. Specific terms and permissions are available from this document's record in the OhioLINK ETD Center.
collection NDLTD
language English
sources NDLTD
topic Biomedical Research
Biology
Computer Science
Genetics
Information Science
spellingShingle Biomedical Research
Biology
Computer Science
Genetics
Information Science
Qiu, Shuhao
Computational Simulation and Analysis of Mutations: Nucleotide Fixation, Allelic Age and rare Genetic Variations in population
author Qiu, Shuhao
author_facet Qiu, Shuhao
author_sort Qiu, Shuhao
title Computational Simulation and Analysis of Mutations: Nucleotide Fixation, Allelic Age and rare Genetic Variations in population
title_short Computational Simulation and Analysis of Mutations: Nucleotide Fixation, Allelic Age and rare Genetic Variations in population
title_full Computational Simulation and Analysis of Mutations: Nucleotide Fixation, Allelic Age and rare Genetic Variations in population
title_fullStr Computational Simulation and Analysis of Mutations: Nucleotide Fixation, Allelic Age and rare Genetic Variations in population
title_full_unstemmed Computational Simulation and Analysis of Mutations: Nucleotide Fixation, Allelic Age and rare Genetic Variations in population
title_sort computational simulation and analysis of mutations: nucleotide fixation, allelic age and rare genetic variations in population
publisher University of Toledo Health Science Campus / OhioLINK
publishDate 2016
url http://rave.ohiolink.edu/etdc/view?acc_num=mco1430494327
work_keys_str_mv AT qiushuhao computationalsimulationandanalysisofmutationsnucleotidefixationallelicageandraregeneticvariationsinpopulation
_version_ 1719438045538680832

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