AccuMUlate: a mutation caller designed for mutation accumulation experiments.
Ontology highlight
ABSTRACT:
SUBMITTER: Winter DJ
PROVIDER: S-EPMC6061804 | biostudies-other | 2018 Aug
REPOSITORIES: biostudies-other
Publications
accuMUlate: a mutation caller designed for mutation accumulation experiments.
Winter David J DJ Wu Steven H SH Howell Abigail A AA Azevedo Ricardo B R RBR Zufall Rebecca A RA Cartwright Reed A RA
Bioinformatics (Oxford, England) 20180801 15
<h4>Summary</h4>Mutation accumulation (MA) is the most widely used method for directly studying the effects of mutation. By sequencing whole genomes from MA lines, researchers can directly study the rate and molecular spectra of spontaneous mutations and use these results to understand how mutation contributes to biological processes. At present there is no software designed specifically for identifying mutations from MA lines. Here we describe accuMUlate, a probabilistic mutation caller that re ...[more]
Similar Datasets
Project description:Despite the general assumption that site-specific mutation rates are independent of the local sequence context, a growing body of evidence suggests otherwise. To further examine context-dependent patterns of mutation, we amassed 5,645 spontaneous mutations in wild- type (WT) and mismatch-repair deficient (MMR(-)) mutation-accumulation (MA) lines of the gram-positive model organism Bacillus subtilis. We then analyzed>7,500 spontaneous base-substitution mutations across B. subtilis, Escherichia coli, and Mesoplasma florum WT and MMR(-) MA lines, finding a context-dependent mutation pattern that is asymmetric around the origin of replication. Different neighboring nucleotides can alter site-specific mutation rates by as much as 75-fold, with sites neighboring G:C base pairs or dimers involving alternating pyrimidine-purine and purine-pyrimidine nucleotides having significantly elevated mutation rates. The influence of context-dependent mutation on genome architecture is strongest in M. florum, consistent with the reduced efficiency of selection in organisms with low effective population size. If not properly accounted for, the disparities arising from patterns of context-dependent mutation can significantly influence interpretations of positive and purifying selection.
| S-EPMC4476155 | biostudies-literature
Project description:MotivationGenome sequencing experiments have revolutionized molecular biology by allowing researchers to identify important DNA-encoded elements genome wide. Regions where these elements are found appear as peaks in the analog signal of an assay's coverage track, and despite the ease with which humans can visually categorize these patterns, the size of many genomes necessitates algorithmic implementations. Commonly used methods focus on statistical tests to classify peaks, discounting that the background signal does not completely follow any known probability distribution and reducing the information-dense peak shapes to simply maximum height. Deep learning has been shown to be highly accurate for many pattern recognition tasks, on par or even exceeding human capabilities, providing an opportunity to reimagine and improve peak calling.ResultsWe present the peak calling framework LanceOtron, which combines deep learning for recognizing peak shape with multifaceted enrichment calculations for assessing significance. In benchmarking ATAC-seq, ChIP-seq and DNase-seq, LanceOtron outperforms long-standing, gold-standard peak callers through its improved selectivity and near-perfect sensitivity.Availability and implementationA fully featured web application is freely available from LanceOtron.molbiol.ox.ac.uk, command line interface via python is pip installable from PyPI at https://pypi.org/project/lanceotron/, and source code and benchmarking tests are available at https://github.com/LHentges/LanceOtron.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC9477537 | biostudies-literature
Project description:Mutations provide the raw material for natural selection to act. Therefore, understanding the variety and relative frequency of different type of mutations is critical to understanding the nature of genetic diversity in a population. Mutation accumulation (MA) experiments have been used in this context to estimate parameters defining mutation rates, distribution of fitness effects (DFE), and spectrum of mutations. MA experiments can be performed with different effective population sizes. In MA experiments with bacteria, a single founder is grown to a size of a colony (~ 108). It is assumed that natural selection plays a minimal role in dictating the dynamics of colony growth. In this work, we simulate colony growth via a mathematical model, and use our model to mimic an MA experiment. We demonstrate that selection ensures that, in an MA experiment, fraction of all mutations that are beneficial is over-represented by a factor of almost two, and that the distribution of fitness effects of beneficial and deleterious mutations are inaccurately captured in an MA experiment. Given this, the estimate of mutation rates from MA experiments is non-trivial. We then perform an MA experiment with 160 lines of E. coli, and show that due to the effect of selection in a growing colony, the size and sector of a colony from which the experiment is propagated impacts the results. Overall, we demonstrate that the results of MA experiments need to be revisited taking into account the action of selection in a growing colony.
| S-EPMC9475022 | biostudies-literature
Project description:BackgroundPrincipal component analysis is used to summarize matrix data, such as found in transcriptome, proteome or metabolome and medical examinations, into fewer dimensions by fitting the matrix to orthogonal axes. Although this methodology is frequently used in multivariate analyses, it has disadvantages when applied to experimental data. First, the identified principal components have poor generality; since the size and directions of the components are dependent on the particular data set, the components are valid only within the data set. Second, the method is sensitive to experimental noise and bias between sample groups. It cannot reflect the experimental design that is planned to manage the noise and bias; rather, it estimates the same weight and independence to all the samples in the matrix. Third, the resulting components are often difficult to interpret. To address these issues, several options were introduced to the methodology. First, the principal axes were identified using training data sets and shared across experiments. These training data reflect the design of experiments, and their preparation allows noise to be reduced and group bias to be removed. Second, the center of the rotation was determined in accordance with the experimental design. Third, the resulting components were scaled to unify their size unit.ResultsThe effects of these options were observed in microarray experiments, and showed an improvement in the separation of groups and robustness to noise. The range of scaled scores was unaffected by the number of items. Additionally, unknown samples were appropriately classified using pre-arranged axes. Furthermore, these axes well reflected the characteristics of groups in the experiments. As was observed, the scaling of the components and sharing of axes enabled comparisons of the components beyond experiments. The use of training data reduced the effects of noise and bias in the data, facilitating the physical interpretation of the principal axes.ConclusionsTogether, these introduced options result in improved generality and objectivity of the analytical results. The methodology has thus become more like a set of multiple regression analyses that find independent models that specify each of the axes.
| S-EPMC4682404 | biostudies-literature
Project description:The ability to signal individual identity using vocal signals and distinguish between conspecifics based on vocal cues is important in several mammal species. Furthermore, it can be important for receivers to differentiate between callers in reproductive contexts. In this study, we used acoustic analyses to determine whether male koala bellows are individually distinctive and to investigate the relative importance of different acoustic features for coding individuality. We then used a habituation-discrimination paradigm to investigate whether koalas discriminate between the bellow vocalisations of different male callers. Our results show that male koala bellows are highly individualized, and indicate that cues related to vocal tract filtering contribute the most to vocal identity. In addition, we found that male and female koalas habituated to the bellows of a specific male showed a significant dishabituation when they were presented with bellows from a novel male. The significant reduction in behavioural response to a final rehabituation playback shows this was not a chance rebound in response levels. Our findings indicate that male koala bellows are highly individually distinctive and that the identity of male callers is functionally relevant to male and female koalas during the breeding season. We go on to discuss the biological relevance of signalling identity in this species' sexual communication and the potential practical implications of our findings for acoustic monitoring of male population levels.
| S-EPMC3102089 | biostudies-literature
Project description:The Neutral Theory of Molecular Evolution is considered the most powerful theory to understand the evolutionary behavior of proteins. One of the main predictions of this theory is that essential proteins should evolve slower than dispensable ones owing to increased selective constraints. Comparison of genomes of different species, however, has revealed only small differences between the rates of evolution of essential and nonessential proteins. In some analyses, these differences vanish once confounding factors are controlled for, whereas in other cases essentiality seems to have an independent, albeit small, effect. It has been argued that comparing relatively distant genomes may entail a number of limitations. For instance, many of the genes that are dispensable in controlled lab conditions may be essential in some of the conditions faced in nature. Moreover, essentiality can change during evolution, and rates of protein evolution are simultaneously shaped by a variety of factors, whose individual effects are difficult to isolate. Here, we conducted two parallel mutation accumulation experiments in Escherichia coli, during 5,500-5,750 generations, and compared the genomes at different points of the experiments. Our approach (a short-term experiment, under highly controlled conditions) enabled us to overcome many of the limitations of previous studies. We observed that essential proteins evolved substantially slower than nonessential ones during our experiments. Strikingly, rates of protein evolution were only moderately affected by expression level and protein length.
| S-EPMC5630975 | biostudies-literature
Project description:Mutations spawn genetic variation which, in turn, fuels evolution. Hence, experimental investigations into the rate and fitness effects of spontaneous mutations are central to the study of evolution. Mutation accumulation (MA) experiments have served as a cornerstone for furthering our understanding of spontaneous mutations for four decades. In the pregenomic era, phenotypic measurements of fitness-related traits in MA lines were used to indirectly estimate key mutational parameters, such as the genomic mutation rate, new mutational variance per generation, and the average fitness effect of mutations. Rapidly emerging next-generating sequencing technology has supplanted this phenotype-dependent approach, enabling direct empirical estimates of the mutation rate and a more nuanced understanding of the relative contributions of different classes of mutations to the standing genetic variation. Whole-genome sequencing of MA lines bears immense potential to provide a unified account of the evolutionary process at multiple levels-the genetic basis of variation, and the evolutionary dynamics of mutations under the forces of selection and drift. In this review, we have attempted to synthesize key insights into the spontaneous mutation process that are rapidly emerging from the partnering of classical MA experiments with high-throughput sequencing, with particular emphasis on the spontaneous rates and molecular properties of different mutational classes in nuclear and mitochondrial genomes of diverse taxa, the contribution of mutations to the evolution of gene expression, and the rate and stability of transgenerational epigenetic modifications. Future advances in sequencing technologies will enable greater species representation to further refine our understanding of mutational parameters and their functional consequences.
| S-EPMC6330053 | biostudies-literature
Project description:BackgroundHistone modifications play an important role in gene regulation. Their genomic locations are of great interest. Usually, the location is measured by ChIP-seq and analyzed with a peak-caller. Replicated ChIP-seq experiments become more and more available. However, their analysis is based on single-experiment peak-calling or on tools like PePr which allows peak-calling of replicates but whose underlying model might not be suitable for the conditions under which the experiments are performed.ResultsWe propose a new peak-caller called 'Sierra Platinum' that allows peak-calling of replicated ChIP-seq experiments. Moreover, it provides a variety of quality measures together with integrated visualizations supporting the assessment of the replicates and the resulting peaks, as well as steering the peak-calling process.ConclusionWe show that Sierra Platinum outperforms currently available methods using a newly generated benchmark data set and using real data from the NIH Roadmap Epigenomics Project. It is robust against noisy replicates.
| S-EPMC5025614 | biostudies-literature
Project description:Experiment to estimate mutatational variance of gene expression in Drosophila melanogaster at two times in development using 12 mutation accumulation lines. Keywords = evolution Keywords = quantitative genetics Keywords = Drosophila Keywords = mutation Each of 12 lines measured 8 times in each of two stages. For each stage, the design has two hexagons with 6 interior connections (=hybridizations) (all except opposite nodes). Each line in one hexagon is connected to one line in the other hexagon and that line's opposite. Each line is also connected to itself twice in the other stage. Dyes are balanced.
2010-06-09 | E-GEOD-2126 | biostudies-arrayexpress
Project description:BACKGROUND:The rate and fitness effects of mutations are key in understanding the evolution of every species. Traditionally, these parameters are estimated in mutation accumulation experiments where replicate lines are propagated in conditions that allow mutations to randomly accumulate without the purging effect of natural selection. These experiments have been performed with many model organisms but we still lack empirical estimates of the rate and effects of mutation in the protists. RESULTS:We performed a mutation accumulation (MA) experiment in Tetrahymena thermophila, a species that can reproduce sexually and asexually in nature, and measured both the mean decline and variance increase in fitness of 20 lines. The results obtained with T. thermophila were compared with T. pyriformis that is an obligate asexual species. We show that MA lines of T. thermophila go to extinction at a rate of 1.25 clonal extinctions per bottleneck. In contrast, populations of T. pyriformis show a much higher resistance to extinction. Variation in gene copy number is likely to be a key factor in explaining these results, and indeed we show that T. pyriformis has a higher mean copy number per cell than T. thermophila. From fitness measurements during the MA experiment, we infer a rate of mutation to copy number variation of 0.0333 per haploid MAC genome of T. thermophila and a mean effect against copy number variation of 0.16. A strong effect of population size in the rate of fitness decline was also found, consistent with the increased power of natural selection. CONCLUSIONS:The rate of clonal extinction measured for T. thermophila is characteristic of a mutational degradation and suggests that this species must undergo sexual reproduction to avoid the deleterious effects detected in the laboratory experiments. We also suggest that an increase in chromosomal copy number associated with the phenotypic assortment of amitotic divisions can provide an alternative mechanism to escape the deleterious effect of random chromosomal copy number variation in species like T. pyriformis that lack the resetting mechanism of sexual reproduction. Our results are relevant to the understanding of cell line longevity and senescence in ciliates.
| S-EPMC2998532 | biostudies-literature