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Genetics Mar 2022Genetic background often influences the phenotypic consequences of mutations, resulting in variable expressivity. How standing genetic variants collectively cause this...
Genetic background often influences the phenotypic consequences of mutations, resulting in variable expressivity. How standing genetic variants collectively cause this phenomenon is not fully understood. Here, we comprehensively identify loci in a budding yeast cross that impact the growth of individuals carrying a spontaneous missense mutation in the nuclear-encoded mitochondrial ribosomal gene MRP20. Initial results suggested that a single large effect locus influences the mutation's expressivity, with 1 allele causing inviability in mutants. However, further experiments revealed this simplicity was an illusion. In fact, many additional loci shape the mutation's expressivity, collectively leading to a wide spectrum of mutational responses. These results exemplify how complex combinations of alleles can produce a diversity of qualitative and quantitative responses to the same mutation.
Topics: Alleles; Genetic Background; Humans; Mutation; Phenotype
PubMed: 35078232
DOI: 10.1093/genetics/iyac013 -
Nature Genetics Feb 2022The infinite sites model of molecular evolution posits that every position in the genome is mutated at most once. By restricting the number of possible mutation...
The infinite sites model of molecular evolution posits that every position in the genome is mutated at most once. By restricting the number of possible mutation histories, haplotypes and alleles, it forms a cornerstone of tumor phylogenetic analysis and is often implied when calling, phasing and interpreting variants or studying the mutational landscape as a whole. Here we identify 18,295 biallelic mutations, where the same base is mutated independently on both parental copies, in 559 (21%) bulk sequencing samples from the Pan-Cancer Analysis of Whole Genomes study. Biallelic mutations reveal ultraviolet light damage hotspots at E26 transformation-specific (ETS) and nuclear factor of activated T cells (NFAT) binding sites, and hypermutable motifs in POLE-mutant and other cancers. We formulate recommendations for variant calling and provide frameworks to model and detect biallelic mutations. These results highlight the need for accurate models of mutation rates and tumor evolution, as well as their inference from sequencing data.
Topics: Alleles; Evolution, Molecular; Genome, Human; Humans; Models, Genetic; Mutation; Mutation Rate; Neoplasms; Whole Genome Sequencing
PubMed: 35145300
DOI: 10.1038/s41588-021-01005-8 -
Oncogene Sep 2023Advances in sequencing have revealed a highly variegated landscape of mutational signatures and somatic driver mutations in a range of normal tissues. Normal tissues... (Review)
Review
Advances in sequencing have revealed a highly variegated landscape of mutational signatures and somatic driver mutations in a range of normal tissues. Normal tissues accumulate mutations at varying rates ranging from 11 per cell per year in the liver, to 1879 per cell per year in the bladder. In addition, some normal tissues are also comprised of a large proportion of cells which possess driver mutations while appearing phenotypically normal, as in the oesophagus where a majority of cells harbour driver mutations. Individual tissue proliferation and mutation rate, unique mutagenic stimuli, and local tissue architecture contribute to this highly variegated landscape which confounds the functional characterization of driver mutations found in normal tissue. In particular, our understanding of the relationship between normal tissue somatic mutations and tumour initiation or future cancer risk remains poor. Here, we describe the mutational signatures and somatic driver mutations in solid and hollow viscus organs, highlighting unique characteristics in a tissue-specific manner, while simultaneously seeking to describe commonalities which can bring forward a basic unified theory on the role of these driver mutations in tumour initiation. We discuss novel findings which can be used to inform future research in this field.
Topics: Humans; Mutation; Mutagenesis; Mutation Rate; Cell Transformation, Neoplastic; Liver
PubMed: 37573406
DOI: 10.1038/s41388-023-02802-7 -
Current Hematologic Malignancy Reports Oct 2017The purpose of this study is to review established prognostic models in myelodysplastic syndromes (MDS) and describe how molecular data can be used to improve patient... (Review)
Review
PURPOSE OF REVIEW
The purpose of this study is to review established prognostic models in myelodysplastic syndromes (MDS) and describe how molecular data can be used to improve patient risk stratification.
RECENT FINDINGS
Somatic mutations are common in MDS and are associated with disease features including outcomes. Several recurrently mutated genes have prognostic significance independent of risk stratification tools used in practice. However, this prognostic impact can depend on the clinicogenetic context in which mutations occur. Qualitatively, SF3B1 mutations appear favorable only in patients with < 5% bone marrow blasts while mutations of several genes, including ASXL1, SRSF2, U2AF1, NRAS, and IDH2, appear adverse in this context. Mutations of TP53, RUNX1, and EZH2 appear adverse regardless of blast percentage. Consensus on how to best incorporate mutations into risk assessment is still being developed. Somatic mutations can refine risk stratification and improve the accuracy of existing prognostic models, often upstaging or downstaging patients across the boundary of higher- and lower-risk MDS.
Topics: Humans; Models, Biological; Mutation; Myelodysplastic Syndromes; Prognosis; Risk Assessment; Risk Factors
PubMed: 28844082
DOI: 10.1007/s11899-017-0407-9 -
Legal Medicine (Tokyo, Japan) Sep 2022The short tandem repeats (STRs) or microsatellites are used for paternity testing and these sequences mutate more rapidlythanbulkDNAsequences. A total of 746 paternity...
The short tandem repeats (STRs) or microsatellites are used for paternity testing and these sequences mutate more rapidlythanbulkDNAsequences. A total of 746 paternity cases were analysed to understand the mutation rate of 21 autosomal STR loci. We identified 41 mutations in 11 STR Loci with a maximum at SE33. No mutations occurred in the remaining 10 STR loci. The overall average mutation rate was estimated as 0.004523 and the estimated locus-specific mutation rate varied between 0.001214 and 0.016990. Among these 90.24% was accounted for single-step mutation, 2.44% for two steps, and 7.32 % for three or muti steps. The obtained data is crucial and could be helpful for ensuring the accuracy of DNA testing and interpretation.
Topics: DNA; Humans; Microsatellite Repeats; Mutation; Mutation Rate; Paternity
PubMed: 35526480
DOI: 10.1016/j.legalmed.2022.102080 -
PLoS Computational Biology Apr 2019Determining the cancer type and molecular subtype has important clinical implications. The primary site is however unknown for some malignancies discovered in the...
Determining the cancer type and molecular subtype has important clinical implications. The primary site is however unknown for some malignancies discovered in the metastatic stage. Moreover liquid biopsies may be used to screen for tumoral DNA, which upon detection needs to be assigned to a site-of-origin. Classifiers based on genomic features are a promising approach to prioritize the tumor anatomical site, type and subtype. We examined the predictive ability of causal (driver) somatic mutations in this task, comparing it against global patterns of non-selected (passenger) mutations, including features based on regional mutation density (RMD). In the task of distinguishing 18 cancer types, the driver mutations-mutated oncogenes or tumor suppressors, pathways and hotspots-classified 36% of the patients to the correct cancer type. In contrast, the features based on passenger mutations did so at 92% accuracy, with similar contribution from the RMD and the trinucleotide mutation spectra. The RMD and the spectra covered distinct sets of patients with predictions. In particular, introducing the RMD features into a combined classification model increased the fraction of diagnosed patients by 50 percentage points (at 20% FDR). Furthermore, RMD was able to discriminate molecular subtypes and/or anatomical site of six major cancers. The advantage of passenger mutations was upheld under high rates of false negative mutation calls and with exome sequencing, even though overall accuracy decreased. We suggest whole genome sequencing is valuable for classifying tumors because it captures global patterns emanating from mutational processes, which are informative of the underlying tumor biology.
Topics: Algorithms; Computational Biology; DNA, Neoplasm; Exome; Genomics; Humans; Machine Learning; Mutation; Neoplasms; Software; Exome Sequencing; Whole Genome Sequencing
PubMed: 30986244
DOI: 10.1371/journal.pcbi.1006953 -
Genome Biology and Evolution Mar 2022The rate of mutations varies >100-fold across the genome, altering the rate of evolution, and susceptibility to genetic diseases. The strongest predictor of mutation...
The rate of mutations varies >100-fold across the genome, altering the rate of evolution, and susceptibility to genetic diseases. The strongest predictor of mutation rate is the sequence itself, varying 75-fold between trinucleotides. The fact that DNA sequence drives its own mutation rate raises a simple but important prediction; highly mutable sequences will mutate more frequently and eliminate themselves in favor of sequences with lower mutability, leading to a lower equilibrium mutation rate. However, purifying selection constrains changes in mutable sequences, causing higher rates of mutation. We conduct a simulation using real human mutation data to test if 1) DNA evolves to a low equilibrium mutation rate and 2) purifying selection causes a higher equilibrium mutation rate in the genome's most important regions. We explore how this simple process affects sequence evolution in the genome, and discuss the implications for modeling evolution and susceptibility to DNA damage.
Topics: DNA; Evolution, Molecular; Genome; Humans; Mutation; Mutation Rate
PubMed: 35218359
DOI: 10.1093/gbe/evac032 -
AIDS Research and Therapy Sep 2017APOBEC3G (A3G) and APOBEC3F (A3F) are DNA-mutating enzymes expressed in T cells, dendritic cells and macrophages. A3G/F have been considered innate immune host factors,... (Review)
Review
APOBEC3G (A3G) and APOBEC3F (A3F) are DNA-mutating enzymes expressed in T cells, dendritic cells and macrophages. A3G/F have been considered innate immune host factors, based on reports that they lethally mutate the HIV genome in vitro. In vivo, A3G/F effectiveness is limited by viral proteins, entrapment in inactive complexes and filtration of mutations during viral life cycle. We hypothesized that the impact of sub-lethal A3G/F action could extend beyond the realm of innate immunity confined to the cytoplasm of infected cells. We measured recognition of wild type and A3G/F-mutated epitopes by cytotoxic T lymphocytes (CTL) from HIV-infected individuals and found that A3G/F-induced mutations overwhelmingly diminished CTL recognition of HIV peptides, in a human histocompatibility-linked leukocyte antigen (HLA)-dependent manner. Furthermore, we found corresponding enrichment of A3G/F-favored motifs in CTL epitope-encoding sequences within the HIV genome. These findings illustrate that A3G/F-mediated mutations mediate immune evasion by HIV in vivo. Therefore, we suggest that vaccine strategies target T cell or antibody epitopes that are not poised for mutation into escape variants by A3G/F action.
Topics: APOBEC-3G Deaminase; Adaptive Immunity; Animals; Cytosine Deaminase; Epitopes; Genome, Viral; HIV Infections; HIV-1; HLA Antigens; Host-Pathogen Interactions; Humans; Immune Evasion; Immunity, Innate; Mice; Mutation; Virus Replication
PubMed: 28893290
DOI: 10.1186/s12981-017-0173-8 -
Thrombosis and Haemostasis Nov 2018Numerous mutations in , or lead to congenital fibrinogen disorders (CFDs), but their epidemiology is not well characterized. The aim of this study was to evaluate...
BACKGROUND
Numerous mutations in , or lead to congenital fibrinogen disorders (CFDs), but their epidemiology is not well characterized. The aim of this study was to evaluate the molecular epidemiology of CFD and to develop a genotyping strategy.
METHODS
Genetic data from 266 unrelated CFD patients genotyped at our laboratory and from a CFD open access database ( = 1,142) were evaluated. We developed a step-wise screening strategy for the molecular diagnosis of CFD and prospectively tested this strategy on 32 consecutive CFD probands.
RESULTS
We identified 345 mutated alleles overall, among 187 heterozygous, 63 homozygous and 16 compound heterozygous individuals. Afibrinogenemia was almost always caused by null mutations (98.6%), mainly in (85%). Hypofibrinogenemia was mainly caused by missense mutations of or (54.2%). Dysfibrinogenemia was almost always caused by heterozygous missense mutations (99.3%) in and . Hotspot mutations were prevalent among quantitative (33.1%) and qualitative fibrinogen disorders (71.1%). The mutational cluster at our laboratory was similar with that reported in the CFD open access database. The proposed step-wise genetic screening strategy proved efficient in both the development and validation samples for CFD: the screening of exons 2, 4, 5 and exon 8 and search for the 11 kb deletion of led to the identification of approximately 80% of mutated alleles, including 15 new mutations.
CONCLUSION
The described molecular epidemiology of CFD is complex. The proposed step-wise genetic screening strategy may provide an efficient way to identify causative mutations analysing a minimal number of exons.
Topics: Adolescent; Adult; Afibrinogenemia; Alleles; Child; Child, Preschool; DNA Mutational Analysis; Female; Fibrinogen; Genetic Testing; Genotype; Hemostasis; Humans; Male; Molecular Epidemiology; Mutation; Prospective Studies; Switzerland; Young Adult
PubMed: 30332696
DOI: 10.1055/s-0038-1673685 -
Scientific Reports Apr 2020Epidemics and evolution of many pathogens occur on similar timescales so that their dynamics are often entangled. Here, in a first step to study this problem...
Epidemics and evolution of many pathogens occur on similar timescales so that their dynamics are often entangled. Here, in a first step to study this problem theoretically, we analyze mutating pathogens spreading on simple SIR networks with grid-like connectivity. We have in mind the spatial aspect of epidemics, which often advance on transport links between hosts or groups of hosts such as cities or countries. We focus on the case of mutations that enhance an agent's infection rate. We uncover that the small-world property, i.e., the presence of long-range connections, makes the network very vulnerable, supporting frequent supercritical mutations and bringing the network from disease extinction to full blown epidemic. For very large numbers of long-range links, however, the effect reverses and we find a reduced chance for large outbreaks. We study two cases, one with discrete number of mutational steps and one with a continuous genetic variable, and we analyze various scaling regimes. For the continuous case we derive a Fokker-Planck-like equation for the probability density and solve it for small numbers of shortcuts using the WKB approximation. Our analysis supports the claims that a potentiating mutation in the transmissibility might occur during an epidemic wave and not necessarily before its initiation.
Topics: Communicable Diseases; Epidemics; Humans; Models, Biological; Mutation Rate; Probability
PubMed: 32246023
DOI: 10.1038/s41598-020-62597-5