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

eLife

Mikkel H Schierup¹  Meritxell Riera¹  Elora H López-Nandam²  Susanne P Pfeifer³  Cyril J Versoza⁴  Richard J Wang⁵  Matthew W Hahn⁵  Anne D Yoder⁶  George P Tiley⁶  Ellie Armstrong⁷  Tychele Turner⁸  Jedidiah Carlson⁹  Kelley Harris⁹  Søren Besenbacher^1,10  April Snøfrid Kleppe^1,10  Priya Moorjani^1,11  Hwei-yen Chen^1,12  Lucie A Bergeron^1,12  Guojie Zhang^1,12  Alivia Lee Price^1,12 

[1] Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark;California Academy of Sciences, San Francisco, United States;Center for Evolution and Medicine, Center for Mechanisms of Evolution, School of Life Sciences, Arizona State University, Tempe, United States;Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, United States;Department of Biology and Department of Computer Science, Indiana University, Bloomington, United States;Department of Biology, Duke University, Durham, United States;Department of Biology, Stanford University, Stanford, United States;Department of Genetics, Washington University School of Medicine, St. Louis, United States;Department of Genome Sciences, University of Washington, Computational Biology Division, Fred Hutchinson Cancer Research Center, Seattle, United States;Department of Molecular Medicine, Aarhus University, Aarhus, Denmark;Department of Molecular and Cell Biology, Center for Computational Biology, University of California, Berkeley, Berkeley, United States;Section for Ecology and Evolution, Department of Biology, University of Copenhagen, Copenhagen, Denmark;

关键词: mutation rate;    ngs analysis;    pedigree-based estimation;    computational pipeline;   

DOI  :  10.7554/eLife.73577

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown