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"Biased mutation spectra are ubiquitous, with a multitude of direction and magnitude of mutational biases that influence genome evolution and adaptation. " Changeing the mutation spectrum allows populations to sample previously under-sampled mutation space, including beneficial mutations, according to our experiments. The resulting change in the distribution of fitness effects is advantageous: both improved mutation supply and beneficial pleiotropy both rise, and deleterious load decreases. Mutations can change under control of selection, and can thus directly influence adaptive evolution by allowing access to beneficial mutations. If the new bias increases sampling of mutational classes that were previously under-sampled, altering mutational bias is also beneficial. We also show that bacteria have often experienced such beneficial bias shifts in the past. Modified mutation biases could spur rapid evolution even in constant habitats, which could lead to rapid migration even in permanent environments. ".
Source link: https://doi.org/10.1101/2020.09.05.284158
"Due to other RNA viruses, the conversion rate of severe acute respiratory syndrome coronavirus 2 is very low relative to other RNA viruses because coronaviruses, including SARS-CoV-2, encodes non-structural protein 14," which is an error-correcting exonuclease protein. " Mutations of SARS-CoV-2 nsp14 that could have hampered its error-correcting function were found in this research, which sought to investigate SARS-CoV-2 genome evolution in the current pandemic. We then examined nsp14 sequences obtained from 28,082 SARS-CoV-2 genomes, finding six amino acid changes in nsp14 mutants that were not present in the 62 representative coronaviruses. "We investigated genome substitution rates of these mutants and discovered that an nsp14 mutant with a proline to leucine change at position 203 had a higher substitution rate than SARS-CoV-2 possessing wild-type nsp14. ".
Source link: https://doi.org/10.1101/2020.12.23.424231
"Mutation rate plays a significant role in adaptive evolution due to its influence on the rate of emergence of both beneficial and deleterious mutations, which is also subject to second-order selection. Here we investigate how the rate of adaptive evolution on rugged, complicated fitness landscapes is affected by mutation rate phenotype switching. We model an asexual population of two mutation rate phenotypes, non-mutator, and mutator, inspired by recent experimental findings of mutation rate variation. An offspring's phenotype may change from its parental phenotype to the other phenotype. The mutation rate can be interpreted as a genetically inheriting trait when the switching rate is low, as an epigenetically inherited characteristic when the switching rate is low, or as a randomly determined characteristic when the switching rate is high. We find that intermediate switching rates raise the rate of adaptation on rugged fitness landscapes.
Source link: https://doi.org/10.1101/2021.07.14.452333
"Mutation rate plays a significant role in adaptive evolution due to its effect on the rate of emergence of both useful and deleterious mutations, which is also subject to second-order selection. " Here we investigate how adaptive evolution on rugged, diverse fitness landscapes is influenced by mutation rate phenotype switching. We model an asexual population with two mutation rate phenotypes, non-mutator, and mutator, influenced by recent experimental findings of mutation rate variation. An offspring can change from its parental phenotype to the other phenotype. Since the switching rate is low, the mutation rate can be interpreted as a genetically inherited trait when the switching rate is low, as an epigenetically inherited trait when the switching rate is intermediate, or as a randomly determined trait when the switching rate is high. "Intermediate switching rates improve the rate of adaptation on rugged fitness landscapes," we find.
Source link: https://doi.org/10.1101/2021.07.14.452333
"Once the AIRE SAND domain is deaced, the AIRE SAND domain becomes free, and the siRT1 is undone," the AIRE complex's failure proceeds downstream. Understanding the relationship and energetics of binding/release between AIRE G228W mutation mechanism and in vitro binding of the SAND domain with SIRT1 and a vein binding of the SAND domain with SIRT1 syndrome, we present a comprehensive model system for investigating the ubiquitous SAND domain's genetic mutation mechanism, which causes the autoimmune APS-1 syndrome. The turbulent link between the AIRE SAND domain and the SIRT1 catalytic site may cause a disruption in the AIRE SAND domain's link with the SIRT1 catalytic site, making it impossible for the AIRE complex to proceed downstream. ".
Source link: https://doi.org/10.1101/2021.08.24.457565
A common task in population genetics is "Estimating the mutation rate, or equivalently large population size. " As an alternative to model-based estimation, neural networks and other machine learning technologies may help to produce accurate estimators in these challenging scenarios. Here we examine feedforward neural networks for the determination of the mutation rate based on the site frequency spectrum and compare their results to model-based estimators. Remarkably, only one hidden layer is needed to obtain a single estimator that does almost as well as model-based estimators for low and high recombination rates while still providing a superior estimation method for intermediate recombination rates, while at the same time providing a more accurate estimate for intermediate recombination rates. We apply the procedure to simulate results based on the human chromosome 2 recombination map, showing its stability in a realistic context in which local recombination rates differ and/or are unknown. ".
Source link: https://doi.org/10.1101/2021.09.02.457550
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