scholarly journals Mutation bias reflects natural selection in Arabidopsis thaliana

Nature ◽  
2022 ◽  
Author(s):  
J. Grey Monroe ◽  
Thanvi Srikant ◽  
Pablo Carbonell-Bejerano ◽  
Claude Becker ◽  
Mariele Lensink ◽  
...  
Keyword(s):  
Arabidopsis Thaliana ◽  
De Novo ◽  
Purifying Selection ◽  
Sequence Evolution ◽  
Deleterious Mutations ◽  
De Novo Mutations ◽  
Mutation Bias ◽  
Prevailing Paradigm ◽  
Genome Wide ◽  
Physical Features

AbstractSince the first half of the twentieth century, evolutionary theory has been dominated by the idea that mutations occur randomly with respect to their consequences1. Here we test this assumption with large surveys of de novo mutations in the plant Arabidopsis thaliana. In contrast to expectations, we find that mutations occur less often in functionally constrained regions of the genome—mutation frequency is reduced by half inside gene bodies and by two-thirds in essential genes. With independent genomic mutation datasets, including from the largest Arabidopsis mutation accumulation experiment conducted to date, we demonstrate that epigenomic and physical features explain over 90% of variance in the genome-wide pattern of mutation bias surrounding genes. Observed mutation frequencies around genes in turn accurately predict patterns of genetic polymorphisms in natural Arabidopsis accessions (r = 0.96). That mutation bias is the primary force behind patterns of sequence evolution around genes in natural accessions is supported by analyses of allele frequencies. Finally, we find that genes subject to stronger purifying selection have a lower mutation rate. We conclude that epigenome-associated mutation bias2 reduces the occurrence of deleterious mutations in Arabidopsis, challenging the prevailing paradigm that mutation is a directionless force in evolution.

scholarly journals Contribution of retrotransposition to developmental disorders

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Eugene J. Gardner ◽  
Elena Prigmore ◽  
Giuseppe Gallone ◽  
Petr Danecek ◽  
Kaitlin E. Samocha ◽  
...  
Keyword(s):  
Developmental Disorders ◽  
De Novo ◽  
Purifying Selection ◽  
Selective Constraint ◽  
Protein Coding ◽  
Genome Wide ◽  
De Novo Gene ◽  
The Impact ◽  
Transcribed Sequences

Abstract Mobile genetic Elements (MEs) are segments of DNA which can copy themselves and other transcribed sequences through the process of retrotransposition (RT). In humans several disorders have been attributed to RT, but the role of RT in severe developmental disorders (DD) has not yet been explored. Here we identify RT-derived events in 9738 exome sequenced trios with DD-affected probands. We ascertain 9 de novo MEs, 4 of which are likely causative of the patient’s symptoms (0.04%), as well as 2 de novo gene retroduplications. Beyond identifying likely diagnostic RT events, we estimate genome-wide germline ME mutation rate and selective constraint and demonstrate that coding RT events have signatures of purifying selection equivalent to those of truncating mutations. Overall, our analysis represents a comprehensive interrogation of the impact of retrotransposition on protein coding genes and a framework for future evolutionary and disease studies.

scholarly journals Selection bias in mutation accumulation

2021 ◽  
Author(s):  
Lindi M Wahl ◽  
Deepa Agashe
Keyword(s):  
Positive Selection ◽  
Negative Selection ◽  
De Novo ◽  
Mutation Accumulation ◽  
Microbial Populations ◽  
Single Individual ◽  
Deleterious Mutations ◽  
De Novo Mutations ◽  
Fitness Effects ◽  
Wide Range

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. Finally, 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. 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.

scholarly journals Transition from background selection to associative overdominance promotes diversity in regions of low recombination

2019 ◽  
Author(s):  
Kimberly J. Gilbert ◽  
Fanny Pouyet ◽  
Laurent Excoffier ◽  
Stephan Peischl
Keyword(s):  
Genetic Diversity ◽  
Balancing Selection ◽  
Purifying Selection ◽  
Heterozygote Advantage ◽  
Background Selection ◽  
Deleterious Mutations ◽  
Recombination Rates ◽  
Locus Model ◽  
Genome Wide ◽  
Linked Selection

SummaryLinked selection is a major driver of genetic diversity. Selection against deleterious mutations removes linked neutral diversity (background selection, BGS, Charlesworth et al. 1993), creating a positive correlation between recombination rates and genetic diversity. Purifying selection against recessive variants, however, can also lead to associative overdominance (AOD, Ohta 1971, Zhao & Charlesworth, 2016), due to an apparent heterozygote advantage at linked neutral loci that opposes the loss of neutral diversity by BGS. Zhao & Charlesworth (2016) identified the conditions when AOD should dominate over BGS in a single-locus model and suggested that the effect of AOD could become stronger if multiple linked deleterious variants co-segregate. We present a model describing how and under which conditions multi-locus dynamics can amplify the effects of AOD. We derive the conditions for a transition from BGS to AOD due to pseudo-overdominance (Ohta & Kimura 1970), i.e. a form of balancing selection that maintains complementary deleterious haplotypes that mask the effect of recessive deleterious mutations. Simulations confirm these findings and show that multi-locus AOD can increase diversity in low recombination regions much more strongly than previously appreciated. While BGS is known to drive genome-wide diversity in humans (Pouyet et al. 2018), the observation of a resurgence of genetic diversity in regions of very low recombination is indicative of AOD. We identify 21 such regions in the human genome showing clear signals of multi-locus AOD. Our results demonstrate that AOD may play an important role in the evolution of low recombination regions of many species.

scholarly journals Paternally inherited noncoding structural variants contribute to autism

2017 ◽  
Author(s):  
William M. Brandler ◽  
Danny Antaki ◽  
Madhusudan Gujral ◽  
Morgan L. Kleiber ◽  
Michelle S. Maile ◽  
...  
Keyword(s):  
De Novo ◽  
Fetal Brain ◽  
Wide Distribution ◽  
Autism Spectrum ◽  
Structural Variants ◽  
De Novo Mutations ◽  
Whole Genome Analysis ◽  
Protein Coding ◽  
Genome Wide ◽  
Exome Aggregation Consortium

AbstractThe genetic architecture of autism spectrum disorder (ASD) is known to consist of contributions from gene-disrupting de novo mutations and common variants of modest effect. We hypothesize that the unexplained heritability of ASD also includes rare inherited variants with intermediate effects. We investigated the genome-wide distribution and functional impact of structural variants (SVs) through whole genome analysis (≥30X coverage) of 3,169 subjects from 829 families affected by ASD. Genes that are intolerant to inactivating variants in the exome aggregation consortium (ExAC) were depleted for SVs in parents, specifically within fetal-brain promoters, UTRs and exons. Rare paternally-inherited SVs that disrupt promoters or UTRs were over-transmitted to probands (P = 0.0013) and not to their typically-developing siblings. Recurrent functional noncoding deletions implicate the gene LEO1 in ASD. Protein-coding SVs were also associated with ASD (P = 0.0025). Our results establish that rare inherited SVs predispose children to ASD, with differing contributions from each parent.

scholarly journals HAPDeNovo: a haplotype-based approach for filtering and phasing de novo mutations in linked read sequencing data

2017 ◽  
Author(s):  
Xin Zhou ◽  
Serafim Batzoglou ◽  
Arend Sidow ◽  
Lu Zhang
Keyword(s):  
False Positive ◽  
De Novo ◽  
False Positives ◽  
Sequencing Data ◽  
De Novo Mutations ◽  
Congenital Diseases ◽  
Genome Wide ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Haplotype Information

AbstractBackgroundDe novo mutations (DNMs) are associated with neurodevelopmental and congenital diseases, and their detection can contribute to understanding disease pathogenicity. However, accurate detection is challenging because of their small number relative to the genome-wide false positives in next generation sequencing (NGS) data. Software such as DeNovoGear and TrioDeNovo have been developed to detect DNMs, but at good sensitivity they still produce many false positive calls.ResultsTo address this challenge, we develop HAPDeNovo, a program that leverages phasing information from linked read sequencing, to remove false positive DNMs from candidate lists generated by DNM-detection tools. Short reads from each phasing block are allocated to each of the two haplotypes followed by generating a haploid genotype for each putative DNM.HAPDeNovo removes variants that are called as heterozygous in one of the haplotypes because they are almost certainly false positives. Our experiments on 10X Chromium linked read sequencing trio data reveal that HAPDeNovo eliminates 80% to 99% of false positives regardless of how large the candidate DNM set is.ConclusionsHAPDeNovo leverages the haplotype information from linked read sequencing to remove spurious false positive DNMs effectively, and it increases accuracy of DNM detection dramatically without sacrificing sensitivity.

STEM-05. FUNCTIONAL MAPPING REVEALS WIDESPREAD REMODELLING AND UNRECOGNIZED PATHWAY DEPENDENCIES IN RECURRENT GLIOBLASTOMA

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi22-vi22
Author(s):  
Chirayu R Chokshi ◽  
David Tieu ◽  
Kevin R Brown ◽  
Chitra Venugopal ◽  
Lina Liu ◽  
...  
Keyword(s):  
Tumor Recurrence ◽  
De Novo ◽  
Tyrosine Phosphatase ◽  
Treatment Resistance ◽  
Recurrent Glioblastoma ◽  
De Novo Mutations ◽  
Genome Wide ◽  
Molecule Inhibitor ◽  
Signaling Axis ◽  
Single Domain Antibodies

Abstract Resistance to genotoxic therapies and tumor recurrence are hallmarks of glioblastoma (GBM), an aggressive brain tumor. Here, we explore the functional drivers of post-treatment recurrent GBM. By conducting genome-wide CRISPR-Cas9 screens in patient-derived GBM models, we uncover distinct genetic dependencies in recurrent tumor cells that were absent in their patient-matched primary predecessors, accompanied by increased mutational burden and differential transcript and protein expression. These analyses support parallel tumor-intrinsic mechanisms of treatment resistance which rely on acquisition of immunosuppressive capacity, including a defective mismatch repair pathway, ablation of PTEN activity, and a novel combination of de novo mutations in SWI/SNF components. We map a multilayered genetic and functional response to resist chemoradiotherapy and drive tumor recurrence, identifying protein tyrosine phosphatase 4A2 (PTP4A2) as a novel driver of self-renewal, proliferation and tumorigenicity at GBM recurrence. Mechanistically, genetic perturbation and a small molecule inhibitor of PTP4A2 repress axon guidance activity through a dephosphorylation axis with roundabout guidance receptor 1 (ROBO1) and exploit a genetic dependency on ROBO signaling. Importantly, engineered anti-ROBO1 single-domain antibodies also mimic the effects of PTP4A2 inhibition. We conclude that functional reprogramming drives tumorigenicity and present a dependence on a PTP4A2-ROBO1 signaling axis at GBM recurrence.

Brain-expressed exons under purifying selection are enriched for de novo mutations in autism spectrum disorder

2014 ◽  
Vol 46 (7) ◽  
pp. 742-747 ◽  
Author(s):  
Mohammed Uddin ◽  
Kristiina Tammimies ◽  
Giovanna Pellecchia ◽  
Babak Alipanahi ◽  
Pingzhao Hu ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
De Novo ◽  
Purifying Selection ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
De Novo Mutations

scholarly journals Network analysis of genome-wide selective constraint reveals a gene network active in early fetal brain intolerant of mutation

2015 ◽  
Author(s):  
Jinmyung Choi ◽  
Parisa Shooshtari ◽  
Kaitlin E Samocha ◽  
Mark J Daly ◽  
Chris Cotsapas
Keyword(s):  
De Novo ◽  
Sequence Data ◽  
Fetal Brain ◽  
Selective Constraint ◽  
Adverse Outcomes ◽  
Integrated Analysis ◽  
Disease Genes ◽  
De Novo Mutations ◽  
Strong Constraint ◽  
Genome Wide

Using robust, integrated analysis of multiple genomic datasets, we show that genes depleted for non-synonymous de novo mutations form a subnetwork of 72 members under strong selective constraint. We further show this subnetwork is preferentially expressed in the early development of the human hippocampus and is enriched for genes mutated in neurological, but not other, Mendelian disorders. We thus conclude that carefully orchestrated developmental processes are under strong constraint in early brain development, and perturbations caused by mutation have adverse outcomes subject to strong purifying selection. Our findings demonstrate that selective forces can act on groups of genes involved in the same process, supporting the notion that adaptation can act coordinately on multiple genes. Our approach provides a statistically robust, interpretable way to identify the tissues and developmental times where groups of disease genes are active. Our findings highlight the importance of considering the interactions between genes when analyzing genome-wide sequence data.

scholarly journals Identification of de novo mutations in the Chinese ASD cohort via whole-exome sequencing unveils brain regions implicated in autism

2021 ◽  
Author(s):  
Bo Yuan ◽  
Mengdi Wang ◽  
Xinran Wu ◽  
Peipei Cheng ◽  
Ran Zhang ◽  
...  
Keyword(s):  
Human Brain ◽  
De Novo ◽  
Brain Regions ◽  
Imaging Data ◽  
De Novo Mutations ◽  
Genetic Studies ◽  
Single Cell Sequencing ◽  
Genome Wide ◽  
Whole Exome ◽  
Brain Imaging Data

Autism spectrum disorder (ASD) is a highly heritable neurodevelopmental disorder characterized by deficits in social interactions and repetitive behaviors. Although hundreds of ASD risk genes, implicated in synaptic formation and transcriptional regulation, have been identified through human genetic studies, the East Asian ASD cohorts is still under-represented in the genome-wide genetic studies. Here we performed whole-exome sequencing on 369 ASD trios including probands and unaffected parents of Chinese origin. Using a joint-calling analytical pipeline based on GATK toolkits, we identified numerous de novo mutations including 55 high-impact variants and 165 moderate-impact variants, as well as de novo copy number variations containing known ASD-related genes. Importantly, combining with single-cell sequencing data from the developing human brain, we found that expression of genes with de novo mutations were specifically enriched in pre-, post-central gyrus (PRC, PC) and banks of superior temporal (BST) regions in the human brain. By further analyzing the brain imaging data with ASD and health controls, we found that the gray volume of the right BST in ASD patients significantly decreased comparing to health controls, suggesting the potential structural deficits associated with ASD. Finally, we found that there was decrease in the seed-based functional connectivity (FC) between BST/PC/PRC and sensory areas, insula, as well as frontal lobes in ASD patients. This work indicated that the combinatorial analysis with genome-wide screening, single-cell sequencing and brain imaging data would reveal brain regions contributing to etiology of ASD.

scholarly journals Mutation bias shapes gene evolution in Arabidopsis thaliana

2020 ◽  
Author(s):  
J. Grey Monroe ◽  
Thanvi Srikant ◽  
Pablo Carbonell-Bejerano ◽  
Moises Exposito-Alonso ◽  
Mao-Lun Weng ◽  
...  
Keyword(s):  
Arabidopsis Thaliana ◽  
De Novo ◽  
Gene Evolution ◽  
Gc Content ◽  
Mutation Rates ◽  
Rate Variation ◽  
Recent Theory ◽  
De Novo Mutations ◽  
Coding Region ◽  
Mutational Hotspots

Classical evolutionary theory maintains that mutation rate variation between genes should be random with respect to fitness 1–4 and evolutionary optimization of genic mutation rates remains controversial 3,5. However, it has now become known that cytogenetic (DNA sequence + epigenomic) features influence local mutation probabilities 6, which is predicted by more recent theory to be a prerequisite for beneficial mutation rates between different classes of genes to readily evolve 7. To test this possibility, we used de novo mutations in Arabidopsis thaliana to create a high resolution predictive model of mutation rates as a function of cytogenetic features across the genome. As expected, mutation rates are significantly predicted by features such as GC content, histone modifications, and chromatin accessibility. Deeper analyses of predicted mutation rates reveal effects of introns and untranslated exon regions in distancing coding sequences from mutational hotspots at the start and end of transcribed regions in A. thaliana. Finally, predicted coding region mutation rates are significantly lower in genes where mutations are more likely to be deleterious, supported by numerous estimates of evolutionary and functional constraint. These findings contradict neutral expectations that mutation probabilities are independent of fitness consequences. Instead they are consistent with the evolution of lower mutation rates in functionally constrained loci due to cytogenetic features, with important implications for evolutionary biology8.

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