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20 results for “Mutation bias”
Data and software supporting the manuscript 'The population frequency of human mitochondrial DNA variants is highly dependent upon mutational bias'
<p>Next-generation sequencing can quickly reveal genetic variation potentially linked to heritable disease. As databases encompassing human variation continue to expand, rare variants have been of high interest, since the frequency of a variant is expected to be low if the genetic change leads to a loss of fitness or fecundity. However, the use of variant frequency when seeking genomic changes linked to disease remains very challenging. Here, we explore the role of selection in controlling human variant frequency using the HelixMT database, which encompasses hundreds of thousands of mitochondrial DNA (mtDNA) samples. We find that a substantial number of synonymous substitutions, which have no effect on protein sequence, were never encountered in this large study, while many other synonymous changes are found at very low frequencies. Further analyses of human and mammalian mtDNA datasets indicate that the population frequency of synonymous variants is predominantly determined by mutational biases rather than by strong selection acting upon nucleotide choice. Our work has important implications that extend to the interpretation of variant frequency for non-synonymous substitutions. </p> <p> </p>
Data from: The role of mutation bias in adaptive molecular evolution: insights from convergent changes in protein function
<p>An underexplored question in evolutionary genetics concerns the extent to which mutational bias in the production of genetic variation influences outcomes and pathways of adaptive molecular evolution. In the genomes of at least some vertebrate taxa, an important form of mutation bias involves changes at CpG dinucleotides: If the DNA nucleotide cytosine (C) is immediately 5' to guanine (G) on the same coding strand, and if the C is methylated, then C→T and G→A mutations occur at an elevated rate relative to mutations at non-CpG sites. Here we examine experimental data from case studies in which it has been possible to identify the causative substitutions that are responsible for adaptive changes in the functional properties of vertebrate hemoglobin (Hb). Specifically, we examine the molecular basis of convergent increases in Hb-O<sub>2</sub> affinity in high-altitude birds. Using a data set of experimentally verified, affinity-enhancing mutations in the Hbs of highland avian taxa, we tested whether causative changes are enriched for mutations at CpG dinucleotides relative to the frequency of CpG mutations among all possible missense mutations. The tests revealed that a disproportionate number of causative amino acid replacements were attributable to CpG mutations, demonstrating that mutation bias can influence outcomes of molecular adaptation.</p>
Data from: The role of mutation bias in adaptive molecular evolution: insights from convergent changes in protein function
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Data from: Shifts in mutation bias promote mutators by altering the distribution of fitness effects
<p>Recent experimental evidence demonstrates that shifts in mutational biases, for example increases in transversion frequency, can change the distribution of fitness effects of mutations (DFE). In particular, reducing or reversing a prevailing bias can increase the probability that a <em>de novo</em> mutation is beneficial. It has also been shown that mutator bacteria are more likely to emerge if the beneficial mutations they generate have a larger effect-size than observed in the wildtype. Here, we connect these two results, demonstrating that mutator strains that reduce or reverse a prevailing bias have a positively-shifted DFE, which in turn can dramatically increase their emergence probability. Since changes in mutation rate and bias are often coupled through the gain and loss of DNA repair enzymes, our results predict that the invasion of mutator strains will be facilitated by shifts in mutation bias that offer improved access to previously under-sampled beneficial mutations.</p>
Data from: Shifts in mutation bias promote mutators by altering the distribution of fitness effects
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Divergent evolution of mutation rates and biases in the long-term evolution experiment with Escherichia coli
Abstract All organisms encode enzymes that replicate, maintain, pack, recombine, and repair their genetic material. For this reason, mutation rates and biases also evolve by mutation, variation, and natural selection. By examining metagenomic time series of the Lenski long-term evolution experiment (LTEE) with Escherichia coli (Good, et al. 2017), we find that local mutation rate variation has evolved during the LTEE. Each LTEE population has evolved idiosyncratic differences in their rates of point mutations, indels, and mobile element insertions, due to the fixation of various hypermutator and antimutator alleles. One LTEE population, called Ara+3, shows a strong, symmetric wave pattern in its density of point mutations, radiating from the origin of replication. This pattern is largely missing from the other LTEE populations, most of which evolved missense, indel, or structural mutations in topA, fis, and dusB— loci that all affect DNA topology. The distribution of mutations in those genes over time suggests epistasis and historical contingency in the evolution of DNA topology, which may have in turn affected local mutation rates. Overall, the replicate populations of the LTEE have largely diverged in their mutation rates and biases, even though they have adapted to identical abiotic conditions.
Data from: Selection bias in mutation accumulation
<p>Mutation accumulation (MA) experiments, in which de novo mutations are sampled and subsequently characterized, are an essential tool in understanding the processes underlying evolution. In microbial populations, MA protocols typically involve a period of population growth between severe bottlenecks, such that a single individual can form a visible colony. While it has long been appreciated that the action of positive selection during this growth phase cannot be eliminated, it is typically assumed to be negligible. Here, we quantify the effect of both positive and negative selection in MA studies, demonstrating that selective effects can substantially bias the distribution of fitness effects (DFE) and mutation rates estimated from typical MA protocols in microbes. We then present a simple correction for this bias which applies to both beneficial and deleterious mutations, and can be used to correct the observed DFE in multiple environments. We use simulated MA experiments to illustrate the extent to which the MA-inferred DFE differs from the underlying true DFE, and demonstrate that the proposed correction accurately reconstructs the true DFE over a wide range of scenarios; we also provide an example of these corrections applied to experimental data. These results highlight that positive selection during microbial MA experiments is in fact not negligible, but can be corrected to gain a more accurate understanding of fundamental evolutionary parameters.</p>
Divergent evolution of mutation rates and biases in the long-term evolution experiment with Escherichia coli
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Data from: Selection bias in mutation accumulation
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Data from: Male-biased fitness effects of spontaneous mutations in Drosophila melanogaster
In populations with males and females, sexual selection may often represent a major component of overall selection. Sexual selection could act to eliminate deleterious alleles in concert with other forms of selection, thereby improving the fitness of sexual populations. Alternatively, the divergent reproductive strategies of the sexes could promote the maintenance of sexually-antagonistic variation, causing sexual populations to be less fit. The net impact of sexual selection on fitness is not well understood, due in part to limited data on the sex-specific effects of spontaneous mutations on total fitness. Using a set of mutation accumulation lines of Drosophila melanogaster, we found that mutations were deleterious in both sexes and had larger effects on fitness in males than in females. This pattern is expected to reduce the mutation load of sexual females and promote the maintenance of sexual reproduction.
Variability in codon usage in Coronaviruses is mainly driven by mutational bias and selective constraints on CpG dinucleotide
<p>Supplementary Figures and Tables for the article called: " Variability in codon usage in Coronaviruses<em> </em>is mainly driven by mutational bias and selective constraints on CpG dinucleotide<sup>"</sup></p>
Data from: Male-biased fitness effects of spontaneous mutations in Drosophila melanogaster
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Data from: Stabilizing selection, mutational bias and the evolution of sex
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Sex-biased ZRSR2 mutations in myeloid malignancies impair plasmacytoid dendritic cell activation and apoptosis [PDX]
GEO Series GSE278318. Homo sapiens. 28 samples. Type: Expression profiling by high throughput sequencing.
TBL1XR1 mutations bias germinal center B-cells towards a pro-tumorigenic memory fate
GEO Series GSE139059. Mus musculus. 28 samples. Type: Expression profiling by high throughput sequencing.
Clonal biases dictate availability of colonic cancer driver mutations for transformation
GEO Series GSE312204. Homo sapiens. 20 samples. Type: Other.
Sex-biased ZRSR2 mutations in myeloid malignancies impair plasmacytoid dendritic cell activation and apoptosis [patients]
GEO Series GSE184656. Homo sapiens. 15 samples. Type: Expression profiling by high throughput sequencing.
Sex-biased ZRSR2 mutations in myeloid malignancies impair plasmacytoid dendritic cell activation and apoptosis [cell line]
GEO Series GSE185982. Homo sapiens. 18 samples. Type: Expression profiling by high throughput sequencing.
Sex-biased ZRSR2 mutations in myeloid malignancies impair plasmacytoid dendritic cell activation and apoptosis
GEO Series GSE185983. Homo sapiens. 61 samples. Type: Expression profiling by high throughput sequencing.
Independent mechanisms of myeloid bias and inflammation driven by UBA1 mutation
GEO Series GSE299813. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing.
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