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

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  • Bergeron, Lucie Adrienne
  • Søren Besenbacher
  • Tychele N. Turner
  • Cyril J. Versoza
  • Richard J. Wang
  • Alivia Lee Price
  • Ellie Armstrong
  • Meritxell Riera
  • Jedidiah Carlson
  • Chen, Hwei-Yen
  • Matthew W. Hahn
  • Kelley Harris
  • April Snøfrid Kleppe
  • Elora H. López-Nandam
  • Priya Moorjani
  • Susanne P. Pfeifer
  • George P. Tiley
  • Anne D. Yoder
  • KU, thw266
  • Mikkel H. Schierup

In the past decade, several studies have estimated the human per-generation germline mutation rate using large pedigrees. More recently, estimates for various non-human 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 how to appropriately account 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 two-fold 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.

Antal sider28
StatusUdgivet - 2022

Bibliografisk note

Funding Information:
We would like to thank GenomeDK at Aarhus University and Arizona State University's Research Computing for providing computational resources and support for the LB pipeline and CV pipeline, respectively. We also thank H?kon J?nsson, the editor George Perry, the reviewer Aaron R. Quinlan, as well as two additional anonymous reviewers for helpful comments on the manuscript and Maria Kamilari for helpful input on the PCR validation experiment. SPP is supported by a US National Science Foundation CAREER grant (DEB-2045343). LB was supported by a Carlsberg Foundation Grant to GZ (CF16-0663).

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