Literature DB >> 31587867

Estimating the Genome-wide Mutation Rate with Three-Way Identity by Descent.

Xiaowen Tian1, Brian L Browning2, Sharon R Browning3.   

Abstract

The two primary methods for estimating the genome-wide mutation rate have been counting de novo mutations in parent-offspring trios and comparing sequence data between closely related species. With parent-offspring trio analysis it is difficult to control for genotype error, and resolution is limited because each trio provides information from only two meioses. Inter-species comparison is difficult to calibrate due to uncertainty in the number of meioses separating species, and it can be biased by selection and by changing mutation rates over time. An alternative class of approaches for estimating mutation rates that avoids these limitations is based on identity by descent (IBD) segments that arise from common ancestry within the past few thousand years. Existing IBD-based methods are limited to highly inbred samples, or lack robustness to genotype error and error in the estimated demographic history. We present an IBD-based method that uses sharing of IBD segments among sets of three individuals to estimate the mutation rate. Our method is applicable to accurately phased genotype data, such as parent-offspring trio data phased using Mendelian rules of inheritance. Unlike standard parent-offspring analysis, our method utilizes distant relationships and is robust to genotype error. We apply our method to data from 1,307 European-ancestry individuals in the Framingham Heart Study sequenced by the NHLBI TOPMed project. We obtain an estimate of 1.29 × 10-8 mutations per base pair per meiosis with a 95% confidence interval of [1.02 × 10-8, 1.56 × 10-8].
Copyright © 2019 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  de novo mutation; identity-by-descent; mutation rate

Mesh:

Year:  2019        PMID: 31587867      PMCID: PMC6848988          DOI: 10.1016/j.ajhg.2019.09.012

Source DB:  PubMed          Journal:  Am J Hum Genet        ISSN: 0002-9297            Impact factor:   11.025


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