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Expert Review of Proteomics Oct 2019: Due to the relatively low mutation rate and high frequency of copy number variation, finding actionable genetic drivers of high-grade serous carcinoma (HGSC) is a... (Review)
Review
: Due to the relatively low mutation rate and high frequency of copy number variation, finding actionable genetic drivers of high-grade serous carcinoma (HGSC) is a challenging task. Furthermore, emerging studies show that genetic alterations are frequently poorly represented at the protein level adding a layer of complexity. With improvements in large-scale proteomic technologies, proteomics studies have the potential to provide robust analysis of the pathways driving high HGSC behavior. : This review summarizes recent large-scale proteomics findings across adequately sized ovarian cancer sample sets. Key words combined with 'ovarian cancer' including 'proteomics', 'proteogenomic', 'reverse-phase protein array', 'mass spectrometry', and 'adaptive response', were used to search PubMed. : Proteomics analysis of HGSC as well as their adaptive responses to therapy can uncover new therapeutic liabilities, which can reduce the emergence of drug resistance and potentially improve patient outcomes. There is a pressing need to better understand how the genomic and epigenomic heterogeneity intrinsic to ovarian cancer is reflected at the protein level and how this information could be used to improve patient outcomes.
Topics: DNA Copy Number Variations; Female; Gene Expression Regulation, Neoplastic; Humans; Mutation; Mutation Rate; Ovarian Neoplasms; Proteome; Proteomics
PubMed: 31512530
DOI: 10.1080/14789450.2019.1666004 -
Genome Biology and Evolution May 2024Intrinsic rates of genetic mutation have diverged greatly across taxa and exhibit statistical associations with several other parameters and features. These include...
Intrinsic rates of genetic mutation have diverged greatly across taxa and exhibit statistical associations with several other parameters and features. These include effective population size (Ne), genome size, and gametic multicellularity, with the latter being associated with both increased mutation rates and decreased effective population sizes. However, data sufficient to test for possible relationships between microbial multicellularity and mutation rate (µ) are lacking. Here, we report estimates of two key population-genetic parameters, Ne and µ, for Myxococcus xanthus, a bacterial model organism for the study of aggregative multicellular development, predation, and social swarming. To estimate µ, we conducted an ∼400-day mutation accumulation experiment with 46 lineages subjected to regular single colony bottlenecks prior to clonal regrowth. Upon conclusion, we sequenced one clonal-isolate genome per lineage. Given collective evolution for 85,323 generations across all lines, we calculate a per base-pair mutation rate of ∼5.5 × 10-10 per site per generation, one of the highest mutation rates among free-living eubacteria. Given our estimate of µ, we derived Ne at ∼107 from neutral diversity at four-fold degenerate sites across two dozen M. xanthus natural isolates. This estimate is below average for eubacteria and strengthens an already clear negative correlation between µ and Ne in prokaryotes. The higher and lower than average mutation rate and Ne for M. xanthus, respectively, amplify the question of whether any features of its multicellular life cycle-such as group-size reduction during fruiting-body development-or its highly structured spatial distribution have significantly influenced how these parameters have evolved.
Topics: Myxococcus xanthus; Mutation Rate; Population Density; Genome, Bacterial
PubMed: 38526062
DOI: 10.1093/gbe/evae066 -
Journal of the National Cancer Institute Jul 2022We hypothesize that genes that directly or indirectly interact with core cancer genes (CCGs) in a comprehensive gene-gene interaction network may have functional...
BACKGROUND
We hypothesize that genes that directly or indirectly interact with core cancer genes (CCGs) in a comprehensive gene-gene interaction network may have functional importance in cancer.
METHODS
We categorized 12 767 human genes into CCGs (n = 468), 1 (n = 5467), 2 (n = 5573), 3 (n = 915), and more than 3 steps (n = 416) removed from the nearest CCG in the Search Tool for the Retrieval of Interacting Genes/Proteins network. We estimated cancer-relevant functional importance in these neighborhood categories using 1) gene dependency score, which reflects the effect of a gene on cell viability after knockdown; 2) somatic mutation frequency in The Cancer Genome Atlas; 3) effect size that estimates to what extent a mutation in a gene enhances cell survival; and 4) negative selection pressure of germline protein-truncating variants in healthy populations.
RESULTS
Cancer biology-related functional importance of genes decreases as their distance from the CCGs increases. Genes closer to cancer genes show greater connectedness in the network, have greater importance in maintaining cancer cell viability, are under greater negative germline selection pressure, and have higher somatic mutation frequency in cancer. Based on these 4 metrics, we provide cancer relevance annotation to known human genes.
CONCLUSIONS
A large number of human genes are connected to CCGs and could influence cancer biology to various extent when dysregulated; any given mutation may be functionally important in one but not in another individual depending on genomic context.
Topics: Gene Regulatory Networks; Genomics; Germ-Line Mutation; Humans; Mutation; Mutation Rate; Neoplasms
PubMed: 35417011
DOI: 10.1093/jnci/djac068 -
Proceedings of the National Academy of... May 2023() is a multidrug-resistant pathogen increasingly responsible for severe pulmonary infections. Analysis of whole-genome sequences (WGS) of demonstrates dense genetic...
() is a multidrug-resistant pathogen increasingly responsible for severe pulmonary infections. Analysis of whole-genome sequences (WGS) of demonstrates dense genetic clustering of clinical isolates collected from disparate geographic locations. This has been interpreted as supporting patient-to-patient transmission, but epidemiological studies have contradicted this interpretation. Here, we present evidence for a slowing of the molecular clock rate coincident with the emergence of phylogenetic clusters. We performed phylogenetic inference using publicly available WGS from 483 patient isolates. We implement a subsampling approach in combination with coalescent analysis to estimate the molecular clock rate along the long internal branches of the tree, indicating a faster long-term molecular clock rate compared to branches within phylogenetic clusters. We used ancestry simulation to predict the effects of clock rate variation on phylogenetic clustering and found that the degree of clustering in the observed phylogeny is more easily explained by a clock rate slowdown than by transmission. We also find that phylogenetic clusters are enriched in mutations affecting DNA repair machinery and report that clustered isolates have lower spontaneous mutation rates in vitro. We propose that adaptation to the host environment through variation in DNA repair genes affects the organism's mutation rate and that this manifests as phylogenetic clustering. These results challenge the model that phylogenetic clustering in is explained by person-to-person transmission and inform our understanding of transmission inference in emerging, facultative pathogens.
Topics: Humans; Mycobacterium abscessus; Mutation Rate; Phylogeny; Mutation
PubMed: 37216535
DOI: 10.1073/pnas.2302033120 -
Environmental Microbiology Nov 2019The appearance of new mutations is determined by the equilibrium between DNA error formation and repair. In bacteria like Escherichia coli, stresses are thought shift... (Review)
Review
The appearance of new mutations is determined by the equilibrium between DNA error formation and repair. In bacteria like Escherichia coli, stresses are thought shift this balance towards increased mutagenesis. Recent findings, however, suggest a very uneven relationship between stress and mutations. Only a subset of stressful environments increase the net rate of mutation and different forms of nutritional stress (such as oxygen, carbon or phosphorus limitations) result in markedly different mutation rates after similar reductions in growth rate. Moreover, different stresses result in altered mutational spectra, with some increasing transposition and others increasing indel formation. Single-base substitution rates are lower with some stresses than in unstressed bacteria. Indeed, changes to the mix of mutations with stress are more widespread than a marked increase in net mutation rate. Much remains to be learned on how environments have unique mutational signatures and why some stresses are more mutagenic than others. Even beyond stress-induced genetic variation, the fundamental unresolved question in the stress-mutation relationship is the adaptive value of different types of mutations and mutation rates; is transposition, for example, more advantageous under anaerobic conditions? It remains to be investigated whether stress-specific genetic variation impacts on evolvability differentially in distinct environments.
Topics: DNA Damage; DNA Repair; Escherichia coli; Escherichia coli Proteins; Genetic Variation; Mutagenesis; Mutation; Mutation Rate; Stress, Physiological
PubMed: 31600848
DOI: 10.1111/1462-2920.14822 -
BMC Genomics Jan 2023Mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) is a frequently used typing method for identifying the Beijing genotype of...
BACKGROUND
Mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) is a frequently used typing method for identifying the Beijing genotype of Mycobacterium tuberculosis (Mtb), which is easily transformed into rifampicin (RIF) resistance. The RIF resistance of Mtb is considered to be highly related with the mutation of rpoB gene. Therefore, this study aimed to analyze the relationship between the repetitive number of MIRU loci and the mutation of rpoB gene.
METHODS
An open-source whole-genome sequencing data of Mtb was used to detect the mutation of rpoB gene and the repetitive number of MIRU loci by bioinformatics methods. Cochran-Armitage analysis was performed to analyze the trend of the rpoB gene mutation rate and the repetitive number of MIRU loci.
RESULTS
Among 357 rifampicin-resistant tuberculosis (RR-TB), 304 strains with mutated rpoB genes were detected, and 6 of 67 rifampicin susceptible strains were detected mutations. The rpoB gene mutational rate showed an upward trend with the increase of MIRU10, MIRU39, QUB4156 and MIRU16 repetitive number, but only the repetitive number of MIRU10, MRIU39 and QUB4156 were risk factors for rpoB gene mutation. The Hunter-Gaston discriminatory index (HGDI) of MIRU10 (0.65) and QUB4156 (0.62) was high in the overall sample, while MIRU39 (0.39) and MIRU16 (0.43) showed a moderate discriminatory Power.
CONCLUSION
The mutation rate of rpoB gene increases with the addition of repetitive numbers of MIRU10, QUB4156 and MIRU39 loci.
Topics: Humans; Bacterial Typing Techniques; Genotype; Minisatellite Repeats; Mutation Rate; Mycobacterium tuberculosis; Rifampin; Tuberculosis, Multidrug-Resistant; DNA-Directed DNA Polymerase; Bacterial Proteins
PubMed: 36646991
DOI: 10.1186/s12864-023-09120-y -
Trends in Genetics : TIG Aug 2023The germline mutation rate (GMR) sets the pace at which mutations, the raw material of evolution, are introduced into the genome. By sequencing a dataset of...
The germline mutation rate (GMR) sets the pace at which mutations, the raw material of evolution, are introduced into the genome. By sequencing a dataset of unprecedently broad phylogenetic scope, Bergeron et al. estimated species-specific GMR, offering numerous insights into how this parameter shapes and is shaped by life-history traits.
Topics: Phylogeny; Evolution, Molecular; Germ-Line Mutation; Mutation Rate; Mutation
PubMed: 37244758
DOI: 10.1016/j.tig.2023.05.001 -
Nature Reviews. Genetics Oct 2021Despite years of active research into the role of DNA repair and replication in mutagenesis, surprisingly little is known about the origin of spontaneous human mutation... (Review)
Review
Despite years of active research into the role of DNA repair and replication in mutagenesis, surprisingly little is known about the origin of spontaneous human mutation in the germ line. With the advent of high-throughput sequencing, genome-scale data have revealed statistical properties of mutagenesis in humans. These properties include variation of the mutation rate and spectrum along the genome at different scales in relation to epigenomic features and dependency on parental age. Moreover, mutations originated in mothers are less frequent than mutations originated in fathers and have a distinct genomic distribution. Statistical analyses that interpret these patterns in the context of known biochemistry can provide mechanistic models of mutagenesis in humans.
Topics: Genome, Human; Genomics; Germ Cells; Humans; Mutagenesis; Mutation; Mutation Rate
PubMed: 34163020
DOI: 10.1038/s41576-021-00376-2 -
American Journal of Human Genetics Dec 2022We provide a method for estimating the genome-wide mutation rate from sequence data on unrelated individuals by using segments of identity by descent (IBD). The length...
We provide a method for estimating the genome-wide mutation rate from sequence data on unrelated individuals by using segments of identity by descent (IBD). The length of an IBD segment indicates the time to shared ancestor of the segment, and mutations that have occurred since the shared ancestor result in discordances between the two IBD haplotypes. Previous methods for IBD-based estimation of mutation rate have required the use of family data for accurate phasing of the genotypes. This has limited the scope of application of IBD-based mutation rate estimation. Here, we develop an IBD-based method for mutation rate estimation from population data, and we apply it to whole-genome sequence data on 4,166 European American individuals from the TOPMed Framingham Heart Study, 2,996 European American individuals from the TOPMed My Life, Our Future study, and 1,586 African American individuals from the TOPMed Hypertension Genetic Epidemiology Network study. Although mutation rates may differ between populations as a result of genetic factors, demographic factors such as average parental age, and environmental exposures, our results are consistent with equal genome-wide average mutation rates across these three populations. Our overall estimate of the average genome-wide mutation rate per 10 base pairs per generation for single-nucleotide variants is 1.24 (95% CI 1.18-1.33).
Topics: Humans; Mutation Rate; Genome, Human; Polymorphism, Single Nucleotide; Haplotypes; Genotype
PubMed: 36370709
DOI: 10.1016/j.ajhg.2022.10.015 -
Methods (San Diego, Calif.) Apr 2020With the rapid advancement of sequencing technologies over the last two decades, it is becoming feasible to detect rare variants from somatic tissue samples. Studying... (Review)
Review
With the rapid advancement of sequencing technologies over the last two decades, it is becoming feasible to detect rare variants from somatic tissue samples. Studying such somatic mutations can provide deep insights into various senescence-related diseases, including cancer, inflammation, and sporadic psychiatric disorders. While it is still a difficult task to identify true somatic mutations, relentless efforts to combine experimental and computational methods have made it possible to obtain reliable data. Furthermore, state-of-the-art machine learning approaches have drastically improved the efficiency and sensitivity of these methods. Meanwhile, we can regard somatic mutations as a counterpart of germline mutations, and it is possible to apply well-formulated mathematical frameworks developed for population genetics and molecular evolution to analyze this 'somatic evolution'. For example, retrospective cell lineage tracing is a promising technique to elucidate the mechanism of pre-diseases using single-cell RNA-sequencing (scRNA-seq) data.
Topics: Aging; Genetic Testing; Genomics; Humans; Inflammation; Machine Learning; Mental Disorders; Mutation Rate; Neoplasms; RNA-Seq; Single-Cell Analysis
PubMed: 31711929
DOI: 10.1016/j.ymeth.2019.11.002