The challenge and promise of estimating the de novo mutation rate from whole‐genome comparisons among closely related individuals
Germline mutations are the raw material for natural selection, driving species evolution and the generation of earth's biodiversity. Without this driver of genetic diversity, life on earth would stagnate. Yet, it is a double‐edged sword. An excess of mutations can have devastating effects on fi...
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Veröffentlicht in: | Molecular ecology 2021-12, Vol.30 (23), p.6087-6100 |
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Sprache: | eng |
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Zusammenfassung: | Germline mutations are the raw material for natural selection, driving species evolution and the generation of earth's biodiversity. Without this driver of genetic diversity, life on earth would stagnate. Yet, it is a double‐edged sword. An excess of mutations can have devastating effects on fitness and population viability. It is therefore one of the great challenges of molecular ecology to determine the rate and mechanisms by which these mutations accrue across the tree of life. Advances in high‐throughput sequencing technologies are providing new opportunities for characterizing the rates and mutational spectra within species and populations thus informing essential evolutionary parameters such as the timing of speciation events, the intricacies of historical demography, and the degree to which lineages are subject to the burdens of mutational load. Here, we will focus on both the challenge and promise of whole‐genome comparisons among parents and their offspring from known pedigrees for the detection of germline mutations as they arise in a single generation. The potential of these studies is high, but the field is still in its infancy and much uncertainty remains. Namely, the technical challenges are daunting given that pedigree‐based genome comparisons are essentially searching for needles in a haystack given the very low signal to noise ratio. Despite the challenges, we predict that rapidly developing methods for whole‐genome comparisons hold great promise for integrating empirically derived estimates of de novo mutation rates and mutation spectra across many molecular ecological applications. |
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ISSN: | 0962-1083 1365-294X |
DOI: | 10.1111/mec.16007 |