scholarly journals Extremely rare variants reveal patterns of germline mutation rate heterogeneity in humans

2018 ◽  
Vol 9 (1) ◽  
Author(s):  
Jedidiah Carlson ◽  
◽  
Adam E. Locke ◽  
Matthew Flickinger ◽  
Matthew Zawistowski ◽  
...  
Keyword(s):  
Mutation Rate ◽  
Germline Mutation ◽  
Rare Variants ◽  
Rate Heterogeneity

scholarly journals The Impact of DNA Methylation Dynamics on the Mutation Rate During Human Germline Development

2020 ◽  
Vol 10 (9) ◽  
pp. 3337-3346
Author(s):  
Yijia Zhou ◽  
Funan He ◽  
Weilin Pu ◽  
Xun Gu ◽  
Jiucun Wang ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Mutation Rate ◽  
Germline Mutation ◽  
Developmental Stages ◽  
Rare Variants ◽  
Epigenetic Modification ◽  
Genome Project ◽  
Germline Development ◽  
Cpg Sites ◽  
The Impact

Abstract DNA methylation is a dynamic epigenetic modification found in most eukaryotic genomes. It is known to lead to a high CpG to TpG mutation rate. However, the relationship between the methylation dynamics in germline development and the germline mutation rate remains unexplored. In this study, we used whole genome bisulfite sequencing (WGBS) data of cells at 13 stages of human germline development and rare variants from the 1000 Genome Project as proxies for germline mutations to investigate the correlation between dynamic methylation levels and germline mutation rates at different scales. At the single-site level, we found a significant correlation between methylation and the germline point mutation rate at CpG sites during germline developmental stages. Then we explored the mutability of methylation dynamics in all stages. Our results also showed a broad correlation between the regional methylation level and the rate of C > T mutation at CpG sites in all genomic regions, especially in intronic regions; a similar link was also seen at all chromosomal levels. Our findings indicate that the dynamic DNA methylome during human germline development has a broader mutational impact than is commonly assumed.

scholarly journals Extremely rare variants reveal patterns of germline mutation rate heterogeneity in humans

2017 ◽  
Author(s):  
Jedidiah Carlson ◽  
Adam E Locke ◽  
Matthew Flickinger ◽  
Matthew Zawistowski ◽  
Shawn Levy ◽  
...  
Keyword(s):  
Mutation Rate ◽  
Germline Mutation ◽  
De Novo ◽  
Gc Content ◽  
Mutation Rates ◽  
Rate Heterogeneity ◽  
Genomic Features ◽  
Genome Wide ◽  
Wide Variability ◽  
Nucleotide Context

AbstractA detailed understanding of the genome-wide variability of single-nucleotide germline mutation rates is essential to studying human genome evolution. Here we use ∼36 million singleton variants from 3,560 whole-genome sequences to infer fine-scale patterns of mutation rate heterogeneity. Mutability is jointly affected by adjacent nucleotide context and diverse genomic features of the surrounding region, including histone modifications, replication timing, and recombination rate, sometimes suggesting specific mutagenic mechanisms. Remarkably, GC content, DNase hypersensitivity, CpG islands, and H3K36 trimethylation are associated with both increased and decreased mutation rates depending on nucleotide context. We validate these estimated effects in an independent dataset of ∼46,000 de novo mutations, and confirm our estimates are more accurate than previously published estimates based on ancestrally older variants without considering genomic features. Our results thus provide the most refined portrait to date of the factors contributing to genome-wide variability of the human germline mutation rate.

scholarly journals NIMBus: a Negative Binomial Regression based Integrative Method for Mutation Burden Analysis

2020 ◽  
Author(s):  
Jing Zhang ◽  
Jason Liu ◽  
Patrick McGillivray ◽  
Caroline Yi ◽  
Lucas Lochovsky ◽  
...  
Keyword(s):  
Mutation Rate ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Whole Genome ◽  
Rate Heterogeneity ◽  
Mutation Burden ◽  
Binomial Regression ◽  
Mutational Hotspots ◽  
Dna Elements ◽  
Integrative Method

ABSTRACTBackgroundIdentifying frequently mutated regions is a key approach to discover DNA elements influencing cancer progression. However, it is challenging to identify these burdened regions due to mutation rate heterogeneity across the genome and across different individuals. Moreover, it is known that this heterogeneity partially stems from genomic confounding factors, such as replication timing and chromatin organization. The increasing availability of cancer whole genome sequences and functional genomics data from the Encyclopedia of DNA Elements (ENCODE) may help address these issues.ResultsWe developed a Negative binomial regression-based Integrative Method for mutation Burden analysiS (NIMBus). Our approach addresses the over-dispersion of mutation count statistics by (1) using a Gamma-Poisson mixture model to capture the mutation-rate heterogeneity across different individuals and (2) estimating regional background mutation rates by regressing the varying local mutation counts against genomic features extracted from ENCODE.We applied NIMBus to whole-genome cancer sequences from the PanCancer Analysis of Whole Genomes project (PCAWG) and other cohorts. It successfully identified well-known coding and noncoding drivers, such as TP53 and the TERT promoter. To further characterize the burdening of non-coding regions, we used NIMBus to screen transcription factor binding sites in promoter regions that intersect DNase I hypersensitive sites (DHSs). This analysis identified mutational hotspots that potentially disrupt gene regulatory networks in cancer. We also compare this method to other mutation burden analysis methods.ConclusionNIMBus is a powerful tool to identify mutational hotspots. The NIMBus software and results are available as an online resource at github.gersteinlab.org/nimbus.

scholarly journals Paternal Age Explains a Major Portion of De Novo Germline Mutation Rate Variability in Healthy Individuals

PLoS ONE ◽  
2016 ◽  
Vol 11 (10) ◽  
pp. e0164212 ◽  
Author(s):  
Simon L. Girard ◽  
Cynthia V. Bourassa ◽  
Louis-Philippe Lemieux Perreault ◽  
Marc-André Legault ◽  
Amina Barhdadi ◽  
...  
Keyword(s):  
Mutation Rate ◽  
Germline Mutation ◽  
De Novo ◽  
Paternal Age ◽  
Major Portion ◽  
Healthy Individuals

scholarly journals A deep learning-based framework for estimating fine-scale germline mutation rates

2021 ◽  
Author(s):  
Yiyuan Fang ◽  
Shuyi Deng ◽  
Cai Li
Keyword(s):  
Deep Learning ◽  
Mutation Rate ◽  
Germline Mutation ◽  
Homo Sapiens ◽  
Predictive Performance ◽  
Training Data ◽  
Mutation Rates ◽  
Fine Scale ◽  
Current State ◽  
Genome Wide

Germline mutation rates are essential for genetic and evolutionary analyses. Yet, estimating accurate fine-scale mutation rates across the genome is a great challenge, due to relatively few observed mutations and intricate relationships between predictors and mutation rates. Here we present MuRaL (Mutation Rate Learner), a deep learning-based framework to predict fine-scale mutation rates using only genomic sequences as input. Harnessing human germline variants for comprehensive assessment, we show that MuRaL achieves better predictive performance than current state-of-the-art methods. Moreover, MuRaL can build models with relatively few training mutations and a moderate number of sequenced individuals. It can leverage transfer learning to build models with further less training data and time. We apply MuRaL to produce genome-wide mutation rate profiles for four species - Homo sapiens, Macaca mulatta, Arabidopsis thaliana and Drosophila melanogaster, demonstrating its high applicability. The generated mutation rate profiles and open source software can greatly facilitate related research.

scholarly journals Higher Germline Mutagenesis of Genes with Stronger Testis Expressions Refutes the Transcriptional Scanning Hypothesis

2020 ◽  
Vol 37 (11) ◽  
pp. 3225-3231
Author(s):  
Haoxuan Liu ◽  
Jianzhi Zhang
Keyword(s):  
Mutation Rate ◽  
Germline Mutation ◽  
De Novo ◽  
Expression Level ◽  
Human Testis ◽  
Confounding Factors ◽  
De Novo Mutations ◽  
Gene Expressions ◽  
Specific Manner ◽  
Mammalian Testis

Abstract Why are more genes expressed in the testis than in any other organ in mammals? The recently proposed transcriptional scanning hypothesis posits that transcription alleviates mutagenesis through transcription-coupled repair so has been selected in the testis to modulate the germline mutation rate in a gene-specific manner. Here, we show that this hypothesis is theoretically untenable because the selection would be too weak to have an effect in mammals. Furthermore, the analysis purported to support the hypothesis did not control known confounding factors and inappropriately excluded genes with no observed de novo mutations. After remedying these problems, we find the human germline mutation rate of a gene to rise with its testis expression level. This trend also exists for inferred coding strand-originated mutations, suggesting that it arises from transcription-associated mutagenesis. Furthermore, the testis expression level of a gene robustly correlates with its overall expression in other organs, nullifying the need to explain the testis silencing of a minority of genes by adaptive germline mutagenesis. Taken together, our results demonstrate that human testis transcription increases the germline mutation rate, rejecting the transcriptional scanning hypothesis of extensive gene expressions in the mammalian testis.

scholarly journals Population heterogeneity in mutation rate increases mean fitness and the frequency of higher order mutants

2016 ◽  
Author(s):  
Helen K. Alexander ◽  
Stephanie I. Mayer ◽  
Sebastian Bonhoeffer
Keyword(s):  
Mutation Rate ◽  
Relative Effect ◽  
Relative Increase ◽  
Higher Order ◽  
Population Heterogeneity ◽  
Arbitrary Distribution ◽  
Rate Heterogeneity ◽  
Standing Variation ◽  
A Genome ◽  
Mean Fitness

AbstractMutation rate is a crucial evolutionary parameter that has typically been treated as a constant in population genetic analyses. However, mutation rate is likely to vary among co-existing individuals within a population, due to genetic polymorphisms, heterogeneous environmental influences, and random physiological fluctuations. We explore the consequences of such mutation rate heterogeneity in a model allowing an arbitrary distribution of mutation rate among individuals, either with or without inheritance. We find that variation of mutation rate about the mean results in a higher probability of producing zero or many simultaneous mutations on a genome. Moreover, it increases the frequency of higher order mutants even under ongoing mutation and selection. We gain a quantitative understanding of how this frequency depends on moments of the mutation rate distribution and selection coefficients. In particular, in a two-locus model, heterogeneity leads to a relative increase in double mutant frequency proportional to the squared coefficient of variation of the mutation rate. Relative effect sizes increase with the number of loci. Finally, this clustering of deleterious mutations into fewer individuals results in a higher population mean fitness. Our results imply that mutation rate heterogeneity allows a population to maintain a higher level of adaptedness to its current environment, while simultaneously harboring greater genetic diversity in the standing variation, which could be crucial for future adaptation to a new environment. Our results also have implications for interpreting mutation rate estimates and mutant frequencies in data.

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