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Ahmad, M.

Publications and source records attributed to Ahmad, M..

38 records · Page 3Linked to original sources

Dynamic Kinetochore Size Regulation Promotes Microtubule Capture And Chromosome Biorientation In Mitosis

Faithful chromosome segregation depends on the ability of sister kinetochores to attach to spindle microtubules. An outer layer of the kinetochore known as the fibrous corona transiently expands in early mitosis and disassembles upon microtubule capture. Neither the functional importance nor the mechanistic basis for this are known. Here we show that the dynein adaptor Spindly and the RZZ kinetochore complex drive fibrous corona formation in a dynein-independent manner. C-terminal farnesylation and MPS1 kinase activity cause conformational changes of Spindly that promote oligomerization of RZZ:Spindly complexes into a corona-like meshwork in cells and in vitro. Concurrent with corona expansion, Spindly potentiates corona shedding by recruiting dynein via three conserved short linear motifs. Expanded, non-sheddable fibrous coronas engage in extensive, long-lived lateral microtubule interactions that persist to metaphase and result in fused sister kinetochores, formation of merotelic attachments and chromosome segregation errors in anaphase. Thus, dynamic kinetochore size regulation in mitosis is coordinated by a single, Spindly-based mechanism that promotes initial microtubule capture and subsequent correct maturation of attachments.

cell biology↗

CardioClassifier: demonstrating the power of disease- and gene-specific computational decision support for clinical genome interpretation

PurposeInternationally-adopted variant interpretation guidelines from the American College of Medical Genetics and Genomics (ACMG) are generic and require disease-specific refinement. Here we developed CardioClassifier (www.cardioclassifier.org), a semi-automated decision-support tool for inherited cardiac conditions (ICCs).\n\nMethodsCardioClassifier integrates data retrieved from multiple sources with user-input case-specific information, through an interactive interface, to support variant interpretation. Combining disease- and gene-specific knowledge with variant observations in large cohorts of cases and controls, we refined 14 computational ACMG criteria and created three ICC-specific rules.\n\nResultsWe benchmarked CardioClassifier on 57 expertly-curated variants and show full retrieval of all computational data, concordantly activating 87.3% of rules. A generic annotation tool identified fewer than half as many clinically-actionable variants (64/219 vs 156/219, Fishers P=1.1x10-18), with important false positives; illustrating the critical importance of disease and gene-specific annotations.\n\nCardioClassifier identified putatively disease-causing variants in 33.7% of 327 cardiomyopathy cases, comparable with leading ICC laboratories. Through addition of manually-curated data, variants found in over 40% of cardiomyopathy cases are fully annotated, without requiring additional user-input data.\n\nConclusionCardioClassifier is an ICC-specific decision-support tool that integrates expertly curated computational annotations with case-specific data to generate fast, reproducible and interactive variant pathogenicity reports, according to best practice guidelines.

genomics↗