38 research outputs found

    Defining and Detecting Crossover-Interference Mutants in Yeast

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    The analysis of crossover interference in many creatures is complicated by the presence of two kinds of crossovers, interfering and noninterfering. In such creatures, the values of the traditional indicators of interference are subject not only to the strength of interference but also to the relative frequencies of crossing over contributed by the two kinds. We formalize the relationship among these variables and illustrate the possibilities and limitations of classical interference analysis with meiotic tetrad data from wild-type Saccharomyces cerevisiae and from mlh1 and ndj1 mutants

    The pch2Δ Mutation in Baker's Yeast Alters Meiotic Crossover Levels and Confers a Defect in Crossover Interference

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    Pch2 is a widely conserved protein that is required in baker's yeast for the organization of meiotic chromosome axes into specific domains. We provide four lines of evidence suggesting that it regulates the formation and distribution of crossover events required to promote chromosome segregation at Meiosis I. First, pch2Δ mutants display wild-type crossover levels on a small (III) chromosome, but increased levels on larger (VII, VIII, XV) chromosomes. Second, pch2Δ mutants show defects in crossover interference. Third, crossovers observed in pch2Δ require both Msh4-Msh5 and Mms4-Mus81 functions. Lastly, the pch2Δ mutation decreases spore viability and disrupts crossover interference in spo11 hypomorph strains that have reduced levels of meiosis-induced double-strand breaks. Based on these and previous observations, we propose a model in which Pch2 functions at an early step in crossover control to ensure that every homolog pair receives an obligate crossover

    Cardiovascular disease, chronic kidney disease, and diabetes mortality burden of cardiometabolic risk factors from 1980 to 2010: a comparative risk assessment

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    Background High blood pressure, blood glucose, serum cholesterol, and BMI are risk factors for cardiovascular diseases and some of these factors also increase the risk of chronic kidney disease and diabetes. We estimated mortality from cardiovascular diseases, chronic kidney disease, and diabetes that was attributable to these four cardiometabolic risk factors for all countries and regions from 1980 to 2010. Methods We used data for exposure to risk factors by country, age group, and sex from pooled analyses of populationbased health surveys. We obtained relative risks for the eff ects of risk factors on cause-specifi c mortality from metaanalyses of large prospective studies. We calculated the population attributable fractions for- each risk factor alone, and for the combination of all risk factors, accounting for multicausality and for mediation of the eff ects of BMI by the other three risks. We calculated attributable deaths by multiplying the cause-specifi c population attributable fractions by the number of disease-specifi c deaths. We obtained cause-specifi c mortality from the Global Burden of Diseases, Injuries, and Risk Factors 2010 Study. We propagated the uncertainties of all the inputs to the fi nal estimates. Findings In 2010, high blood pressure was the leading risk factor for deaths due to cardiovascular diseases, chronic kidney disease, and diabetes in every region, causing more than 40% of worldwide deaths from these diseases; high BMI and glucose were each responsible for about 15% of deaths, and high cholesterol for more than 10%. After accounting for multicausality, 63% (10\ub78 million deaths, 95% CI 10\ub71\u201311\ub75) of deaths from these diseases in 2010 were attributable to the combined eff ect of these four metabolic risk factors, compared with 67% (7\ub71 million deaths, 6\ub76\u20137\ub76) in 1980. The mortality burden of high BMI and glucose nearly doubled from 1980 to 2010. At the country level, age-standardised death rates from these diseases attributable to the combined eff ects of these four risk factors surpassed 925 deaths per 100 000 for men in Belarus, Kazakhstan, and Mongolia, but were less than 130 deaths per 100 000 for women and less than 200 for men in some high-income countries including Australia, Canada, France, Japan, the Netherlands, Singapore, South Korea, and Spain. Interpretation The salient features of the cardiometabolic disease and risk factor epidemic at the beginning of the 21st century are high blood pressure and an increasing eff ect of obesity and diabetes. The mortality burden of cardiometabolic risk factors has shifted from high-income to low-income and middle-income countries. Lowering cardiometabolic risks through dietary, behavioural, and pharmacological interventions should be a part of the globalresponse to non-communicable diseases

    Pan-cancer analysis of whole genomes

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    Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

    The neurocognitive functioning in bipolar disorder: a systematic review of data

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