The Mutationathon highlights the importance of reaching standardization in estimates of pedigree-based germline mutation rates.

Journal Article (Journal Article)

In the past decade, several studies have estimated the human per-generation germline mutation rate using large pedigrees. More recently, estimates for various nonhuman species have been published. However, methodological differences among studies in detecting germline mutations and estimating mutation rates make direct comparisons difficult. Here, we describe the many different steps involved in estimating pedigree-based mutation rates, including sampling, sequencing, mapping, variant calling, filtering, and appropriately accounting for false-positive and false-negative rates. For each step, we review the different methods and parameter choices that have been used in the recent literature. Additionally, we present the results from a 'Mutationathon,' a competition organized among five research labs to compare germline mutation rate estimates for a single pedigree of rhesus macaques. We report almost a twofold variation in the final estimated rate among groups using different post-alignment processing, calling, and filtering criteria, and provide details into the sources of variation across studies. Though the difference among estimates is not statistically significant, this discrepancy emphasizes the need for standardized methods in mutation rate estimations and the difficulty in comparing rates from different studies. Finally, this work aims to provide guidelines for computational and statistical benchmarks for future studies interested in identifying germline mutations from pedigrees.

Full Text

Duke Authors

Cited Authors

  • Bergeron, LA; Besenbacher, S; Turner, T; Versoza, CJ; Wang, RJ; Price, AL; Armstrong, E; Riera, M; Carlson, J; Chen, H-Y; Hahn, MW; Harris, K; Kleppe, AS; López-Nandam, EH; Moorjani, P; Pfeifer, SP; Tiley, GP; Yoder, AD; Zhang, G; Schierup, MH

Published Date

  • January 2022

Published In

Volume / Issue

  • 11 /

Start / End Page

  • e73577 -

PubMed ID

  • 35018888

Pubmed Central ID

  • PMC8830884

Electronic International Standard Serial Number (EISSN)

  • 2050-084X

International Standard Serial Number (ISSN)

  • 2050-084X

Digital Object Identifier (DOI)

  • 10.7554/elife.73577


  • eng