Showing papers on "Mutation (genetic algorithm) published in 2015"

Analysis of protein-coding genetic variation in 60,706 humans

Abstract: Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) sequence data for 60,706 individuals of diverse ethnicities. The resulting catalogue of human genetic diversity has unprecedented resolution, with an average of one variant every eight bases of coding sequence and the presence of widespread mutational recurrence. The deep catalogue of variation provided by the Exome Aggregation Consortium (ExAC) can be used to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; we identify 3,230 genes with near-complete depletion of truncating variants, 79% of which have no currently established human disease phenotype. Finally, we show that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human knockout variants in protein-coding genes.

Acquired EGFR C797S mutation mediates resistance to AZD9291 in non–small cell lung cancer harboring EGFR T790M

Abstract: Here we studied cell-free plasma DNA (cfDNA) collected from subjects with advanced lung cancer whose tumors had developed resistance to the epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) AZD9291. We first performed next-generation sequencing of cfDNA from seven subjects and detected an acquired EGFR C797S mutation in one; expression of this mutant EGFR construct in a cell line rendered it resistant to AZD9291. We then performed droplet digital PCR on serial cfDNA specimens collected from 15 AZD9291-treated subjects. All were positive for the T790M mutation before treatment, but upon developing AZD9291 resistance three molecular subtypes emerged: six cases acquired the C797S mutation, five cases maintained the T790M mutation but did not acquire the C797S mutation and four cases lost the T790M mutation despite the presence of the underlying EGFR activating mutation. Our findings provide insight into the diversity of mechanisms through which tumors acquire resistance to AZD9291 and highlight the need for therapies that are able to overcome resistance mediated by the EGFR C797S mutation.

Genome-wide patterns and properties of de novo mutations in humans

Abstract: Mutations create variation in the population, fuel evolution and cause genetic diseases. Current knowledge about de novo mutations is incomplete and mostly indirect. Here we analyze 11,020 de novo mutations from the whole genomes of 250 families. We show that de novo mutations in the offspring of older fathers are not only more numerous but also occur more frequently in early-replicating, genic regions. Functional regions exhibit higher mutation rates due to CpG dinucleotides and show signatures of transcription-coupled repair, whereas mutation clusters with a unique signature point to a new mutational mechanism. Mutation and recombination rates independently associate with nucleotide diversity, and regional variation in human-chimpanzee divergence is only partly explained by heterogeneity in mutation rate. Finally, we provide a genome-wide mutation rate map for medical and population genetics applications. Our results provide new insights and refine long-standing hypotheses about human mutagenesis.

Extremely High Mutation Rate of HIV-1 In Vivo.

Abstract: Rates of spontaneous mutation critically determine the genetic diversity and evolution of RNA viruses. Although these rates have been characterized in vitro and in cell culture models, they have seldom been determined in vivo for human viruses. Here, we use the intrapatient frequency of premature stop codons to quantify the HIV-1 genome-wide rate of spontaneous mutation in DNA sequences from peripheral blood mononuclear cells. This reveals an extremely high mutation rate of (4.1 ± 1.7) × 10−3 per base per cell, the highest reported for any biological entity. Sequencing of plasma-derived sequences yielded a mutation frequency 44 times lower, indicating that a large fraction of viral genomes are lethally mutated and fail to reach plasma. We show that the HIV-1 reverse transcriptase contributes only 2% of mutations, whereas 98% result from editing by host cytidine deaminases of the A3 family. Hypermutated viral sequences are less abundant in patients showing rapid disease progression compared to normal progressors, highlighting the antiviral role of A3 proteins. However, the amount of A3-mediated editing varies broadly, and we find that low-edited sequences are more abundant among rapid progressors, suggesting that suboptimal A3 activity might enhance HIV-1 genetic diversity and pathogenesis.

A comprehensive assessment of somatic mutation detection in cancer using whole-genome sequencing

Abstract: As whole-genome sequencing for cancer genome analysis becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Here using tumour-normal sample pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, we conduct a benchmarking exercise within the context of the International Cancer Genome Consortium. We compare sequencing methods, analysis pipelines and validation methods. We show that using PCR-free methods and increasing sequencing depth to ∼ 100 × shows benefits, as long as the tumour:control coverage ratio remains balanced. We observe widely varying mutation call rates and low concordance among analysis pipelines, reflecting the artefact-prone nature of the raw data and lack of standards for dealing with the artefacts. However, we show that, using the benchmark mutation set we have created, many issues are in fact easy to remedy and have an immediate positive impact on mutation detection accuracy.

Exome sequencing of osteosarcoma reveals mutation signatures reminiscent of BRCA deficiency

Abstract: Osteosarcomas are aggressive bone tumours with a high degree of genetic heterogeneity, which has historically complicated driver gene discovery. Here we sequence exomes of 31 tumours and decipher their evolutionary landscape by inferring clonality of the individual mutation events. Exome findings are interpreted in the context of mutation and SNP array data from a replication set of 92 tumours. We identify 14 genes as the main drivers, of which some were formerly unknown in the context of osteosarcoma. None of the drivers is clearly responsible for the majority of tumours and even TP53 mutations are frequently mapped into subclones. However, >80% of osteosarcomas exhibit a specific combination of single-base substitutions, LOH, or large-scale genome instability signatures characteristic of BRCA1/2-deficient tumours. Our findings imply that multiple oncogenic pathways drive chromosomal instability during osteosarcoma evolution and result in the acquisition of BRCA-like traits, which could be therapeutically exploited.

Metallaxis-FL: mutation-based fault localization

Abstract: Fault localization methods seek to identify faulty program statements based on the information provided by the failing and passing test executions. Spectrum-based methods are among the most popular ones and assist programmers by assigning suspiciousness values on program statements according to their probability of being faulty. This paper proposes Metallaxis, a fault localization approach based on mutation analysis. The innovative part of Metallaxis is that it uses mutants and links them with the faulty program places. Thus, mutants that are killed mostly by failing tests provide a good indication about the location of a fault. Experimentation using Metallaxis suggests that it is significantly more effective than statement-based approaches. This is true even in the case where mutation cost-reduction techniques, such as mutant sampling, are facilitated. Additionally, results from a controlled experiment show that the use of mutation as a testing technique provides benefits to the fault localization process. Therefore, fault localization is significantly improved by using mutation-based tests instead of block-based or branch-based test suites. Finally, evidence in support of the methods' scalability is also given. Copyright © 2013 John Wiley & Sons, Ltd.

Differential Evolution With an Individual-Dependent Mechanism

Abstract: Differential evolution (DE) is a well-known optimization algorithm that utilizes the difference of positions between individuals to perturb base vectors and thus generate new mutant individuals. However, the difference between the fitness values of individuals, which may be helpful to improve the performance of the algorithm, has not been used to tune parameters and choose mutation strategies. In this paper, we propose a novel variant of DE with an individual-dependent mechanism that includes an individual-dependent parameter (IDP) setting and an individual-dependent mutation (IDM) strategy. In the IDP setting, control parameters are set for individuals according to the differences in their fitness values. In the IDM strategy, four mutation operators with different searching characteristics are assigned to the superior and inferior individuals, respectively, at different stages of the evolution process. The performance of the proposed algorithm is then extensively evaluated on a suite of the 28 latest benchmark functions developed for the 2013 Congress on Evolutionary Computation special session. Experimental results demonstrate the algorithm’s outstanding performance.

Estimation of the Spontaneous Mutation Rate in Heliconius melpomene

Abstract: We estimated the spontaneous mutation rate in Heliconius melpomene by genome sequencing of a pair of parents and 30 of their offspring, based on the ratio of number of de novo heterozygotes to the number of callable site-individuals. We detected nine new mutations, each one affecting a single site in a single offspring. This yields an estimated mutation rate of 2.9 × 10−9 (95% confidence interval, 1.3 × 10−9–5.5 × 10−9), which is similar to recent estimates in Drosophila melanogaster, the only other insect species in which the mutation rate has been directly estimated. We infer that recent effective population size of H. melpomene is about 2 million, a substantially lower value than its census size, suggesting a role for natural selection reducing diversity. We estimate that H. melpomene diverged from its Mullerian comimic H. erato about 6 Ma, a somewhat later date than estimates based on a local molecular clock.

Off-target mutations are rare in Cas9-modified mice.

Abstract: We extended our analysis to the remainder of the genome on the basis of the following assumptions. We reasoned that the variants would not be shared with the control inbred strains (C57BL/6J or CBA) and would not be shared in offspring from individual founder animals. Variants associated with repetitive DNA sequence were discarded as these cannot be distinguished from the large number of naturally occurring variants in repetitive DNA sequence in individual mice. These filtering steps (Supplementary Tables 1 and 2) reduced the number of indels to a small set of 120 high-quality variants (Supplementary Data). Twenty-four variants were selected at random, of which 22 were confirmed by experimental validation. On the basis of the ungapped and gapped alignments of the two Ar sgRNAs to genomic sequence at the variant sites, none of the 120 variants appeared to be a true off-target site (Supplementary Fig. 3). We conclude that these variants arose spontaneously and were not the result of unconstrained Cas9 endonuclease activity. Our study is consistent with three recent reports showing negligible genome-wide damage in Cas9-engineered human induced pluripotent stem cells4–6. In contrast to embryonic stem cell technology, where extensive genetic variation arises in culture, undesired mutations induced by the Cas9 endonuclease will be rare in zygotes. Because unlinked mutations will segregate away through breeding, phenotyping of two independent founder animals would be sufficient to establish causality. Alternatively, mutant founder animals generated with two unrelated guide RNAs would rigorously control for any confounding alleles.

Pmx: Automated protein structure and topology generation for alchemical perturbations.

Abstract: Computational protein design requires methods to accurately estimate free energy changes in protein stability or binding upon an amino acid mutation. From the different approaches available, molecular dynamics-based alchemical free energy calculations are unique in their accuracy and solid theoretical basis. The challenge in using these methods lies in the need to generate hybrid structures and topologies representing two physical states of a system. A custom made hybrid topology may prove useful for a particular mutation of interest, however, a high throughput mutation analysis calls for a more general approach. In this work, we present an automated procedure to generate hybrid structures and topologies for the amino acid mutations in all commonly used force fields. The described software is compatible with the Gromacs simulation package. The mutation libraries are readily supported for five force fields, namely Amber99SB, Amber99SB*-ILDN, OPLS-AA/L, Charmm22*, and Charmm36.

Identification of germline genetic mutations in patients with pancreatic cancer

Abstract: BACKGROUND Pancreatic adenocarcinoma (PAC) is part of several cancer predisposition syndromes; however, indications for genetic counseling/testing are not well-defined. In the current study, the authors sought to determine mutation prevalence and characteristics that are predictive of an inherited predisposition for PAC. METHODS A total of 175 consecutive patients with PAC who underwent clinical genetics assessment at Memorial Sloan Kettering Cancer Center between 2011 and 2014 were identified. Clinical data, family history, and germline results were evaluated. RESULTS Among 159 patients with PAC who pursued genetic testing, 24 pathogenic mutations were identified (15.1%; 95% confidence interval, 9.5%-20.7%), including BRCA2 (13 mutations), BRCA1 (4 mutations), p16 (2 mutations), PALB2 (1 mutation), and Lynch syndrome (4 mutations). BRCA1/BRCA2 prevalence was 13.7% in Ashkenazi Jewish (AJ) patients (95 patients) and 7.1% in non-AJ patients (56 patients). In AJ patients with a strong, weak, or absent family history of BRCA-associated cancers, the mutation prevalence was 16.7%, 15.8%, and 7.4%, respectively. The mean age at the time of diagnosis in all mutation carriers was 58.5 years (range, 45-75 years) compared with 64 years (range, 27-87 years) in those not carrying a mutation (P = .02). Although BRCA2 was the most common mutation identified, no patients with early-onset PAC (diagnosed at age ≤ 50 years) harbored a BRCA2 mutation and the mean age at diagnosis in BRCA2 carriers was equivalent to that of individuals who were not mutation carriers (P = .34). Mutation prevalence in patients with early-onset disease (21 patients) was 28.6%, including BRCA1 (2 mutations), p16 (2 mutations), MSH2 (1 mutation), and MLH1 (1 mutation). CONCLUSIONS Mutations in BRCA2 account for > 50% of patients with PAC with an identified susceptibility syndrome. AJ patients were found to have high BRCA1/BRCA2 prevalence regardless of personal/family history, suggesting that ancestry alone indicates a need for genetic evaluation. With the exception of BRCA2-associated PAC, an inherited predisposition for PAC is associated with an earlier age at PAC diagnosis, suggesting that this subset of patients may also represent a population warranting further evaluation. Cancer 2015;121:4382–8. © 2015 American Cancer Society.

Defining “mutation” and “polymorphism” in the era of personal genomics

Abstract: The growing advances in DNA sequencing tools have made analyzing the human genome cheaper and faster While such analyses are intended to identify complex variants, related to disease susceptibility and efficacy of drug responses, they have blurred the definitions of mutation and polymorphism In the era of personal genomics, it is critical to establish clear guidelines regarding the use of a reference genome Nowadays DNA variants are called as differences in comparison to a reference In a sequencing project Single Nucleotide Polymorphisms (SNPs) and DNA mutations are defined as DNA variants detectable in >1 % or <1 % of the population, respectively The alternative use of the two terms mutation or polymorphism for the same event (a difference as compared with a reference) can lead to problems of classification These problems can impact the accuracy of the interpretation and the functional relationship between a disease state and a genomic sequence We propose to solve this nomenclature dilemma by defining mutations as DNA variants obtained in a paired sequencing project including the germline DNA of the same individual as a reference Moreover, the term mutation should be accompanied by a qualifying prefix indicating whether the mutation occurs only in somatic cells (somatic mutation) or also in the germline (germline mutation) We believe this distinction in definition will help avoid confusion among researchers and support the practice of sequencing the germline and somatic tissues in parallel to classify the DNA variants thus defined as mutations

Parent–progeny sequencing indicates higher mutation rates in heterozygotes

Abstract: Mutation rates vary within genomes, but the causes of this remain unclear. As many prior inferences rely on methods that assume an absence of selection, potentially leading to artefactual results, we call mutation events directly using a parent-offspring sequencing strategy focusing on Arabidopsis and using rice and honey bee for replication. Here we show that mutation rates are higher in heterozygotes and in proximity to crossover events. A correlation between recombination rate and intraspecific diversity is in part owing to a higher mutation rate in domains of high recombination/diversity. Implicating diversity per se as a cause, we find an ∼3.5-fold higher mutation rate in heterozygotes than in homozygotes, with mutations occurring in closer proximity to heterozygous sites than expected by chance. In a genome that is a patchwork of heterozygous and homozygous domains, mutations occur disproportionately more often in the heterozygous domains. If segregating mutations predispose to a higher local mutation rate, clusters of genes dominantly under purifying selection (more commonly homozygous) and under balancing selection (more commonly heterozygous), might have low and high mutation rates, respectively. Our results are consistent with this, there being a ten times higher mutation rate in pathogen resistance genes, expected to be under positive or balancing selection. Consequently, we do not necessarily need to evoke extremely weak selection on the mutation rate to explain why mutational hot and cold spots might correspond to regions under positive/balancing and purifying selection, respectively.

TLE6 mutation causes the earliest known human embryonic lethality

Abstract: Embryonic lethality is a recognized phenotypic expression of individual gene mutations in model organisms. However, identifying embryonic lethal genes in humans is challenging, especially when the phenotype is manifested at the preimplantation stage. In an ongoing effort to exploit the highly consanguineous nature of the Saudi population to catalog recessively acting embryonic lethal genes in humans, we have identified two families with a female-limited infertility phenotype. Using autozygosity mapping and whole exome sequencing, we map this phenotype to a single mutation in TLE6, a maternal effect gene that encodes a member of the subcortical maternal complex in mammalian oocytes. Consistent with the published phenotype of mouse Tle6 mutants, embryos from female patients who are homozygous for the TLE6 mutation fail to undergo early cleavage, with resulting sterility. The human mutation abrogates TLE6 phosphorylation, a step that is reported to be critical for the PKA-mediated progression of oocyte meiosis II. Furthermore, the TLE6 mutation impairs its binding to components of the subcortical maternal complex. In this first report of a human defect in a member of the subcortical maternal subcritical maternal complex, we show that the TLE6 mutation is gender-specific and leads to the earliest known human embryonic lethality phenotype.

Asymmetric Context-Dependent Mutation Patterns Revealed through Mutation–Accumulation Experiments

Abstract: Despite the general assumption that site-specific mutation rates are independent of the local sequence context, a growing body of evidence suggests otherwise. To further examine context-dependent patterns of mutation, we amassed 5,645 spontaneous mutations in wild- type (WT) and mismatch-repair deficient (MMR(-)) mutation-accumulation (MA) lines of the gram-positive model organism Bacillus subtilis. We then analyzed>7,500 spontaneous base-substitution mutations across B. subtilis, Escherichia coli, and Mesoplasma florum WT and MMR(-) MA lines, finding a context-dependent mutation pattern that is asymmetric around the origin of replication. Different neighboring nucleotides can alter site-specific mutation rates by as much as 75-fold, with sites neighboring G:C base pairs or dimers involving alternating pyrimidine-purine and purine-pyrimidine nucleotides having significantly elevated mutation rates. The influence of context-dependent mutation on genome architecture is strongest in M. florum, consistent with the reduced efficiency of selection in organisms with low effective population size. If not properly accounted for, the disparities arising from patterns of context-dependent mutation can significantly influence interpretations of positive and purifying selection.

Multi-population differential evolution with balanced ensemble of mutation strategies for large-scale global optimization

Abstract: Differential evolution (DE) is a simple, yet very effective, population-based search technique. However, it is challenging to maintain a balance between exploration and exploitation behaviors of the DE algorithm. In this paper, we boost the population diversity while preserving simplicity by introducing a multi-population DE to solve large-scale global optimization problems. In the proposed algorithm, called mDE-bES, the population is divided into independent subgroups, each with different mutation and update strategies. A novel mutation strategy that uses information from either the best individual or a randomly selected one is used to produce quality solutions to balance exploration and exploitation. Selection of individuals for some of the tested mutation strategies utilizes fitness-based ranks of these individuals. Function evaluations are divided into epochs. At the end of each epoch, individuals between the subgroups are exchanged to facilitate information exchange at a slow pace. The performance of the algorithm is evaluated on a set of 19 large-scale continuous optimization problems. A comparative study is carried out with other state-of-the-art optimization techniques. The results show that mDE-bES has a competitive performance and scalability behavior compared to the contestant algorithms.

A mutation in the POT1 gene is responsible for cardiac angiosarcoma in TP53-negative Li-Fraumeni-like families.

Abstract: Cardiac angiosarcoma (CAS) is a rare malignant tumour whose genetic basis is unknown. Here we show, by whole-exome sequencing of a TP53-negative Li–Fraumeni-like (LFL) family including CAS cases, that a missense variant (p.R117C) in POT1 (protection of telomeres 1) gene is responsible for CAS. The same gene alteration is found in two other LFL families with CAS, supporting the causal effect of the identified mutation. We extend the analysis to TP53-negative LFL families with no CAS and find the same mutation in a breast AS family. The mutation is recently found once in 121,324 studied alleles in ExAC server but it is not described in any other database or found in 1,520 Spanish controls. In silico structural analysis suggests how the mutation disrupts POT1 structure. Functional and in vitro studies demonstrate that carriers of the mutation show reduced telomere-bound POT1 levels, abnormally long telomeres and increased telomere fragility.

TP53 mutations in de novo acute myeloid leukemia patients: longitudinal follow-ups show the mutation is stable during disease evolution

Abstract: The TP53 mutation is frequently detected in acute myeloid leukemia (AML) patients with complex karyotype (CK), but the stability of this mutation during the clinical course remains unclear. In this study, TP53 mutations were identified in 7% of 500 patients with de novo AML and 58.8% of patients with CK. TP53 mutations were closely associated with older age, lower white blood cell (WBC) and platelet counts, FAB M6 subtype, unfavorable-risk cytogenetics and CK, but negatively associated with NPM1 mutation, FLT3/ITD and DNMT3A mutation. Multivariate analysis demonstrated that TP53 mutation was an independent poor prognostic factor for overall survival and disease-free survival among the total cohort and the subgroup of patients with CK. A scoring system incorporating TP53 mutation and nine other prognostic factors, including age, WBC counts, cytogenetics and gene mutations, into survival analysis proved to be very useful to stratify AML patients. Sequential study of 420 samples showed that TP53 mutations were stable during AML evolution, whereas the mutation was acquired only in 1 of the 126 TP53 wild-type patients when therapy-related AML originated from different clone emerged. In conclusion, TP53 mutations are associated with distinct clinic-biological features and poor prognosis in de novo AML patients and are rather stable during disease progression.

Achieving scalable mutation-based generation of whole test suites

Abstract: Without complete formal specification, automatically generated software tests need to be manually checked in order to detect faults. This makes it desirable to produce the strongest possible test set while keeping the number of tests as small as possible. As commonly applied coverage criteria like branch coverage are potentially weak, mutation testing has been proposed as a stronger criterion. However, mutation based test generation is hampered because usually there are simply too many mutants, and too many of these are either trivially killed or equivalent. On such mutants, any effort spent on test generation would per definition be wasted. To overcome this problem, our search-based EvoSuite test generation tool integrates two novel optimizations: First, we avoid redundant test executions on mutants by monitoring state infection conditions, and second we use whole test suite generation to optimize test suites towards killing the highest number of mutants, rather than selecting individual mutants. These optimizations allowed us to apply EvoSuite to a random sample of 100 open source projects, consisting of a total of 8,963 classes and more than two million lines of code, leading to a total of 1,380,302 mutants. The experiment demonstrates that our approach scales well, making mutation testing a viable test criterion for automated test case generation tools, and allowing us to analyze the relationship of branch coverage and mutation testing in detail.

Evolving New Protein-Protein Interaction Specificity through Promiscuous Intermediates

Abstract: Interacting proteins typically coevolve, and the identification of coevolving amino acids can pinpoint residues required for interaction specificity. This approach often assumes that an interface-disrupting mutation in one protein drives selection of a compensatory mutation in its partner during evolution. However, this model requires a non-functional intermediate state prior to the compensatory change. Alternatively, a mutation in one protein could first broaden its specificity, allowing changes in its partner, followed by a specificity-restricting mutation. Using bacterial toxin-antitoxin systems, we demonstrate the plausibility of this second, promiscuity-based model. By screening large libraries of interface mutants, we show that toxins and antitoxins with high specificity are frequently connected in sequence space to more promiscuous variants that can serve as intermediates during a reprogramming of interaction specificity. We propose that the abundance of promiscuous variants promotes the expansion and diversification of toxin-antitoxin systems and other paralogous protein families during evolution.

NCI-MATCH Launch Highlights New Trial Design in Precision-Medicine Era

Abstract: In July, oncologists will start enrolling patients in a clinical trial with 20 or more arms, each testing different agents against different molecular targets and each including patients with different cancers. In design, the trial itself couldn’t be more different from the classic clinical trial. Instead of focusing on one cancer, as trials have for decades, the National Cancer Institute’s NCI-MATCH (Molecular Analysis for Therapy Choice) trial will include patients with any solid tumor or lymphoma who have one of many genomic abnormalities known to drive cancer. Patients will be matched with a targeted agent that has shown promise against their abnormality, regardless of what cancer they have. Known as a basket trial, the new design highlights the rapidly growing number of potential targets and agents in oncology and the urgency of finding more efficient ways to evaluate them in trials. NCI-MATCH is not the first clinical trial of targeted agents to depart from classic design, but it is the most ambitious—“the largest and most rigorous precision oncology trial in history,” said Clifford Hudis, M.D., immediate past president of the American Society for Clinical Oncology, speaking at the society’s annual meeting in June. MATCH will enroll about 1,000 patients, be accessible around the country, and eventually include at least 20 genomic alterations with as many targeted therapies. The protocol directs, and will yield valuable data on, all stages of the process, including biopsy and genomic analysis. One result will be a trove of new data on alterations in advanced cancers. Investigators estimate they will screen about 3,000 tumor samples to find 1,000 patients with alterations that are eligible for the trial. But 3,000 is only a best guess at this point, said trial cochair Barbara A. Conley, M.D., associate director of NCI’s Cancer Diagnosis Program. “We have a lot to learn about the prevalence of variants,” she said.

Branching Process Models of Cancer

Abstract: In this chapter, we will use multitype branching processes with mutation to model cancer. With cancer progression, resistance to therapy, and metastasis in mind, we will investigate τ k , the time of the first type k mutation, and σ k , the time of the first type k mutation that founds a family line that does not die out, as well as the growth of the number of type k cells. The last three sections apply these results to metastasis, ovarian cancer, and tumor heterogeneity. Even though martingales and stable laws are mentioned, these notes should be accessible to a student who is familiar with Poisson processes and continuous time Markov chains.

Late onset spinal motor neuronopathy is caused by mutation in CHCHD10

Abstract: Objective A study was undertaken to identify the responsible gene defect underlying late onset spinal motor neuronopathy (LOSMoN/SMAJ; Online Mendelian Inheritance in Man #615048), an autosomal dominant disease mapped to chromosome 22q11.2. Methods The previous genetic linkage approach by microsatellite haplotyping was continued in new families. A whole genome sequencing was performed to find all possibly pathogenic mutations in the linked area. The detected variations were verified by Sanger sequencing. Results Six new SMAJ families were identified based on the unique founder haplotype. A critical recombination in 1 family restricted the linked area to 727kb between markers SHGC-106816 and D22S345. In whole genome sequencing a previously unknown mutation c.197G>T p.G66V in CHCHD10 was identified. The mutation was shown to segregate with the disease in 55 patients from 17 families. Interpretation Mutation c.197G>T p.G66V in CHCHD10 is the cause of the lower motor neuron syndrome LOSMoN/SMAJ. During the preparation of this article other mutations were reported to cause frontotemporal dementia–amyotrophic lateral sclerosis syndrome, indicating that the CHCHD10 gene is largely important for the motor and cognitive neuronal systems. ANN NEUROL 2015;77:163–172

Exploring the Relationships between Mutation Rates, Life History, Genome Size, Environment, and Species Richness in Flowering Plants

Abstract: A new view is emerging of the interplay between mutation at the genomic level, substitution at the population level, and diversification at the lineage level. Many studies have suggested that rate of molecular evolution is linked to rate of diversification, but few have evaluated competing hypotheses. By analyzing sequences from 130 families of angiosperms, we show that variation in the synonymous substitution rate is correlated among genes from the mitochondrial, chloroplast, and nuclear genomes and linked to differences in traits among families (average height and genome size). Within each genome, synonymous rates are correlated to nonsynonymous substitution rates, suggesting that increasing the mutation rate results in a faster rate of genome evolution. Substitution rates are correlated with species richness in protein-coding sequences from the chloroplast and nuclear genomes. These data suggest that species traits contribute to lineage-specific differences in the mutation rate that drive both synonymous and nonsynonymous rates of change across all three genomes, which in turn contribute to greater rates of divergence between populations, generating higher rates of diversification. These observations link mutation in individuals to population-level processes and to patterns of lineage divergence.

Self-adaptive differential evolution algorithm with discrete mutation control parameters

Abstract: In DMPSADE, control parameters and mutation strategies could be automatically adjusted.We first proposed a new encoding for parameter control in DE algorithm.Roulette wheel is used to implement the selection of mutation strategies. Generally, the optimization problem has different relationships (i.e., linear, approximately linear, non-linear, or highly non-linear) with different optimized variables. The choices of control parameters and mutation strategies would directly affect the performance of differential evolution (DE) algorithm in satisfying the evolution requirement of each optimized variable and balancing its exploitation and exploration capabilities. Therefore, a self-adaptive DE algorithm with discrete mutation control parameters (DMPSADE) is proposed. In DMPSADE, each variable of each individual has its own mutation control parameter, and each individual has its own crossover control parameter and mutation strategy. DMPSADE was compared with 8 state-of-the-art DE variants and 3 non-DE algorithms by using 25 benchmark functions. The statistical results indicate that the average performance of DMPSADE is better than those of all other competitors.