scholarly journals Haplotype-based inference of the distribution of fitness effects

2019 ◽  
Author(s):  
Diego Ortega-Del Vecchyo ◽  
Kirk E. Lohmueller ◽  
John Novembre
Keyword(s):  
Low Frequency ◽  
Similar Proportion ◽  
Human Genetic Variation ◽  
Pairwise Identity ◽  
Fitness Effects ◽  
Sequencing Studies ◽  
Identity By State ◽  
Source Of Information ◽  
New Framework ◽  
New Mutations

AbstractRecent genome sequencing studies with large sample sizes in humans have discovered a vast quantity of low-frequency variants, providing an important source of information to analyze how selection is acting on human genetic variation. In order to estimate the strength of natural selection acting on low-frequency variants, we have developed a likelihood-based method that uses the lengths of pairwise identity-by-state between haplotypes carrying low-frequency variants. We show that in some non-equilibrium populations (such as those that have had recent population expansions) it is possible to distinguish between positive or negative selection acting on a set of variants. With our new framework, one can infer a fixed selection intensity acting on a set of variants at a particular frequency, or a distribution of selection coefficients for standing variants and new mutations. We apply our method to the UK10K phased haplotype dataset of 3,781 individuals and find a similar proportion of neutral, moderately deleterious, and deleterious variants compared to previous estimates made using the site frequency spectrum. We discuss several interpretations for this result, including that selective constraints have remained constant over time.

scholarly journals Haplotype-based inference of the distribution of fitness effects

Genetics ◽  
2022 ◽  
Author(s):  
Diego Ortega-Del Vecchyo ◽  
Kirk E Lohmueller ◽  
John Novembre
Keyword(s):  
Negative Selection ◽  
Low Frequency ◽  
Human Genetic Variation ◽  
Pairwise Identity ◽  
Fitness Effects ◽  
Sequencing Studies ◽  
Identity By State ◽  
Source Of Information ◽  
New Framework ◽  
New Mutations

Abstract Recent genome sequencing studies with large sample sizes in humans have discovered a vast quantity of low-frequency variants, providing an important source of information to analyze how selection is acting on human genetic variation. In order to estimate the strength of natural selection acting on low-frequency variants, we have developed a likelihood-based method that uses the lengths of pairwise identity-by-state between haplotypes carrying low-frequency variants. We show that in some non-equilibrium populations (such as those that have had recent population expansions) it is possible to distinguish between positive or negative selection acting on a set of variants. With our new framework, one can infer a fixed selection intensity acting on a set of variants at a particular frequency, or a distribution of selection coefficients for standing variants and new mutations. We show an application of our method to the UK10K phased haplotype dataset of individuals.

scholarly journals The distribution of mutational effects on fitness in Caenorhabditis elegans inferred from standing genetic variation

2020 ◽  
Author(s):  
Kimberly J. Gilbert ◽  
Stefan Zdraljevic ◽  
Daniel E. Cook ◽  
Asher D. Cutter ◽  
Erik C. Andersen ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Caenorhabditis Elegans ◽  
Population Size ◽  
Genomic Structure ◽  
Random Mating ◽  
Population Substructure ◽  
C Elegans ◽  
Fitness Effects ◽  
Self Fertilization ◽  
New Mutations

ABSTRACTThe distribution of fitness effects for new mutations is one of the most theoretically important but difficult to estimate properties in population genetics. A crucial challenge to inferring the distribution of fitness effects (DFE) from natural genetic variation is the sensitivity of the site frequency spectrum to factors like population size change, population substructure, and non-random mating. Although inference methods aim to control for population size changes, the influence of non-random mating remains incompletely understood, despite being a common feature of many species. We report the distribution of fitness effects estimated from 326 genomes of Caenorhabditis elegans, a nematode roundworm with a high rate of self-fertilization. We evaluate the robustness of DFE inferences using simulated data that mimics the genomic structure and reproductive life history of C. elegans. Our observations demonstrate how the combined influence of self-fertilization, genome structure, and natural selection can conspire to compromise estimates of the DFE from extant polymorphisms. These factors together tend to bias inferences towards weakly deleterious mutations, making it challenging to have full confidence in the inferred DFE of new mutations as deduced from standing genetic variation in species like C. elegans. Improved methods for inferring the distribution of fitness effects are needed to appropriately handle strong linked selection and selfing. These results highlight the importance of understanding the combined effects of processes that can bias our interpretations of evolution in natural populations.

The distribution of fitness effects of new mutations

2007 ◽  
Vol 8 (8) ◽  
pp. 610-618 ◽  
Author(s):  
Adam Eyre-Walker ◽  
Peter D. Keightley
Keyword(s):  
Fitness Effects ◽  
New Mutations

scholarly journals The distribution of fitness effects of new beneficial mutations in Pseudomonas fluorescens

2010 ◽  
Vol 7 (1) ◽  
pp. 98-100 ◽  
Author(s):  
Michael J. McDonald ◽  
Tim F. Cooper ◽  
Hubertus J. E. Beaumont ◽  
Paul B. Rainey
Keyword(s):  
Natural Selection ◽  
Normal Distribution ◽  
Pseudomonas Fluorescens ◽  
Genetic Architecture ◽  
Rank Order ◽  
Detailed Knowledge ◽  
Theoretical Studies ◽  
Fitness Effects ◽  
Reference Type ◽  
New Mutations

Theoretical studies of adaptation emphasize the importance of understanding the distribution of fitness effects (DFE) of new mutations. We report the isolation of 100 adaptive mutants—without the biasing influence of natural selection—from an ancestral genotype whose fitness in the niche occupied by the derived type is extremely low. The fitness of each derived genotype was determined relative to a single reference type and the fitness effects found to conform to a normal distribution. When fitness was measured in a different environment, the rank order changed, but not the shape of the distribution. We argue that, even with detailed knowledge of the genetic architecture underpinning the adaptive types (as is the case here), the DFEs remain unpredictable, and we discuss the possibility that general explanations for the shape of the DFE might not be possible in the absence of organism-specific biological details.

scholarly journals What does the Distribution of Fitness Effects of new mutations (DFE) reflect? Insights from plants

2021 ◽  
Author(s):  
Jun Chen ◽  
Thomas Bataillon ◽  
Sylvain Glémin ◽  
Martin Lascoux
Keyword(s):  
Fitness Effects ◽  
New Mutations

scholarly journals Detecting cancer vulnerabilities through gene networks under purifying selection in 4,700 cancer genomes

2017 ◽  
Author(s):  
Anika Gupta ◽  
Heiko Horn ◽  
Parisa Razaz ◽  
April Kim ◽  
Michael Lawrence ◽  
...  
Keyword(s):  
Gene Networks ◽  
Large Scale ◽  
Significant Proportion ◽  
Low Frequency ◽  
Interaction Network ◽  
Purifying Selection ◽  
Sequencing Data ◽  
Gene Sets ◽  
Sequencing Studies ◽  
Significant Enrichment

ABSTRACTLarge-scale cancer sequencing studies have uncovered dozens of mutations critical to cancer initiation and progression. However, a significant proportion of genes linked to tumor propagation remain hidden, often due to noise in sequencing data confounding low frequency alterations. Further, genes in networks under purifying selection (NPS), or those that are mutated in cancers less frequently than would be expected by chance, may play crucial roles in sustaining cancers but have largely been overlooked. We describe here a statistical framework that identifies genes that have a first order protein interaction network significantly depleted for mutations, to elucidate key genetic contributors to cancers. Not reliant on and thus, unbiased by, the gene of interest’s mutation rate, our approach has identified 685 putative genes linked to cancer development. Comparative analysis indicates statistically significant enrichment of NPS genes in previously validated cancer vulnerability gene sets, while further identifying novel cancer-specific candidate gene targets. As more tumor genomes are sequenced, integrating systems level mutation data through this network approach should become increasingly useful in pinpointing gene targets for cancer diagnosis and treatment.

scholarly journals Unidirectional incompatibility in Drosophila simulans: inheritance, geographic variation and fitness effects.

Genetics ◽  
1988 ◽  
Vol 119 (2) ◽  
pp. 435-444 ◽  
Author(s):  
A A Hoffmann ◽  
M Turelli
Keyword(s):  
Side Effects ◽  
North America ◽  
Reciprocal Cross ◽  
Low Frequency ◽  
Drosophila Simulans ◽  
Fitness Effects ◽  
Population Type ◽  
Population Cage ◽  
Males And Females ◽  
Population Controls

Abstract In California, Drosophila simulans females from some populations (type W) produce relatively few adult progeny when crossed to males from some other populations (type R), but the productivity of the reciprocal cross is comparable to within-population controls. These two incompatibility types are widespread in North America and are also present elsewhere. Both types sometimes occur in the same population. Type R females always produce type R progeny irrespective of the father's type. However, matings between R males and females from stocks classified as type W produce type R progeny at low frequency. This suggests rare paternal transmission of the R incompatibility type, as we have found no evidence for segregation of incompatibility types in the W stocks. There is quantitative variation among type R lines for compatibility with W females, but not vice versa. Population cage studies and productivity tests suggest that deleterious side effects are associated with the type R cytoplasm.

scholarly journals The evolutionary impacts of synonymous mutations

2021 ◽  
Author(s):  
Deepa Agashe
Keyword(s):  
Synonymous Codon ◽  
Analytical Framework ◽  
Synonymous Mutations ◽  
Fitness Effects ◽  
Distinct Category ◽  
Dramatic Shift ◽  
Evolutionary Consequences ◽  
New Mutations

During the 50 years since the genetic code was cracked, our understanding of the evolutionary consequences of synonymous mutations has undergone a dramatic shift. Synonymous codon changes were initially considered selectively neutral, and as such, exemplars of evolution via genetic drift. However, the pervasive and non-negligible fitness impacts of synonymous mutations are now clear across organisms. Despite the accumulated evidence, it remains challenging to incorporate the effects of synonymous changes in studies of selection, because the existing analytical framework was built with a focus on the fitness effects of nonsynonymous mutations. In this chapter, I trace the development of this topic and discuss the evidence that gradually transformed our thinking about the role of synonymous mutations in evolution. I suggest that our evolutionary framework should encompass the impacts of all mutations on various forms of information transmission. Folding synonymous mutations into a common distribution – rather than setting them apart as a distinct category – will allow a more complete and cohesive picture of the evolutionary consequences of new mutations.

scholarly journals MAESTRO affords ‘breadth and depth’ for mutation testing

2021 ◽  
Author(s):  
Gregory Gydush ◽  
Erica Nguyen ◽  
Jin H. Bae ◽  
Justin Rhoades ◽  
Sarah C. Reed ◽  
...  
Keyword(s):  
Residual Disease ◽  
Low Frequency ◽  
Mutation Testing ◽  
Liquid Biopsies ◽  
Cancer Genome Sequencing ◽  
Large Numbers ◽  
Powerful Approach ◽  
Sequencing Studies ◽  
Duplex Sequencing ◽  
Parallel Mutation

AbstractThe ability to assay large numbers of low-abundance mutations is crucial in biomedicine. Yet, the technical hurdles of sequencing multiple mutations at extremely high depth and accuracy remain daunting. For sequencing low-level mutations, it’s either ‘depth or breadth’ but not both. Here, we report a simple and powerful approach to accurately track thousands of distinct mutations with minimal reads. Our technique called MAESTRO (minor allele enriched sequencing through recognition oligonucleotides) employs massively-parallel mutation enrichment to empower duplex sequencing—one of the most accurate methods—to track up to 10,000 low-frequency mutations with up to 100-fold less sequencing. In example use cases, we show that MAESTRO could enable mutation validation from cancer genome sequencing studies. We also show that it could track thousands of mutations from a patient’s tumor in cell-free DNA, which may improve detection of minimal residual disease from liquid biopsies. In all, MAESTRO improves the breadth, depth, accuracy, and efficiency of mutation testing.

scholarly journals Inferring Parameters of the Distribution of Fitness Effects of New Mutations When Beneficial Mutations Are Strongly Advantageous and Rare

2020 ◽  
Vol 10 (7) ◽  
pp. 2317-2326 ◽  
Author(s):  
Tom R. Booker
Keyword(s):  
Evolutionary Genetics ◽  
Molecular Data ◽  
Substantial Contribution ◽  
Beneficial Mutations ◽  
Adaptive Mutations ◽  
Fitness Effects ◽  
Relative Contribution ◽  
Standing Variation ◽  
Accuracy And Precision ◽  
New Mutations

Characterizing the distribution of fitness effects (DFE) for new mutations is central in evolutionary genetics. Analysis of molecular data under the McDonald-Kreitman test has suggested that adaptive substitutions make a substantial contribution to between-species divergence. Methods have been proposed to estimate the parameters of the distribution of fitness effects for positively selected mutations from the unfolded site frequency spectrum (uSFS). Such methods perform well when beneficial mutations are mildly selected and frequent. However, when beneficial mutations are strongly selected and rare, they may make little contribution to standing variation and will thus be difficult to detect from the uSFS. In this study, I analyze uSFS data from simulated populations subject to advantageous mutations with effects on fitness ranging from mildly to strongly beneficial. As expected, frequent, mildly beneficial mutations contribute substantially to standing genetic variation and parameters are accurately recovered from the uSFS. However, when advantageous mutations are strongly selected and rare, there are very few segregating in populations at any one time. Fitting the uSFS in such cases leads to underestimates of the strength of positive selection and may lead researchers to false conclusions regarding the relative contribution adaptive mutations make to molecular evolution. Fortunately, the parameters for the distribution of fitness effects for harmful mutations are estimated with high accuracy and precision. The results from this study suggest that the parameters of positively selected mutations obtained by analysis of the uSFS should be treated with caution and that variability at linked sites should be used in conjunction with standing variability to estimate parameters of the distribution of fitness effects in the future.

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