ArticleBioinformatics (Oxford, England)2017
When loss-of-function is loss of function: assessing mutational signatures and impact of loss-of-function genetic variants.
Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.
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Who cites it
49 citing papers in PubMed.
- The relationship between genomic variation and genetic load: insights from small island populations.Heredity · 2026Article
- Clinico-genetic heterogeneity in Pakistani families affected with muscular dystrophies.Molecular biology reports · 2026Article
- NEDAMSS syndrome-related truncating and missense mutations are associated with aberrant liquid-liquid phase separation of IRF2BPL.Nature communications · 2026Article
- Literature-driven extraction and computational prediction of causal statements linking genetic variants to biological processes, pathways and phenotypes.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2026Article
- A novel frameshift variant in ALS2 associated with segmental axonopathy in Merino sheep.Genetics, selection, evolution : GSE · 2025Article
- Exon disruptive variants in Populus trichocarpa associated with wood properties exhibit distinct gene expression patterns.The plant genome · 2025Article
- Article
- Review
- Variant Impact Predictor database (VIPdb), version 2: trends from three decades of genetic variant impact predictors.Human genomics · 2024Article
- Contributions of Germline and Somatic Mosaic Genetics to Thoracic Aortic Aneurysms in Nonsyndromic Individuals.Journal of the American Heart Association · 2024Article
- Variant Impact Predictor database (VIPdb), version 2: Trends from 25 years of genetic variant impact predictors.bioRxiv : the preprint server for biology · 2024Article
- Exome sequencing improves the molecular diagnostics of paediatric unexplained neurodevelopmental disorders.Orphanet journal of rare diseases · 2024Article
- Prediction of cancer driver genes and mutations: the potential of integrative computational frameworks.Briefings in bioinformatics · 2024Review
- Bioinformatics of germline variant discovery for rare disease diagnostics: current approaches and remaining challenges.Briefings in bioinformatics · 2024Review
- Review of Computational Methods and Database Sources for Predicting the Effects of Coding Frameshift Small Insertion and Deletion Variations.ACS omega · 2024Review
- Development and validation of animal variant classification guidelines to objectively evaluate genetic variant pathogenicity in domestic animals.Frontiers in veterinary science · 2024Article
- Structural Dynamics Predominantly Determine the Adaptability of Proteins to Amino Acid Deletions.International journal of molecular sciences · 2023Article
- Characterization of RNA polymerase II trigger loop mutations using molecular dynamics simulations and machine learning.PLoS computational biology · 2023Article
- Whole genome sequencing reveals population diversity and variation in HIV-1 specific host genes.Frontiers in genetics · 2023Article
- Case report: Novel frameshift mutation inFrontiers in genetics · 2023Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
motivationLoss-of-function genetic variants are frequently associated with severe clinical phenotypes, yet many are present in the genomes of healthy individuals. The available methods to assess the impact of these variants rely primarily upon evolutionary conservation with little to no consideration of the structural and functional implications for the protein. They further do not provide information to the user regarding specific molecular alterations potentially causative of disease.
resultsTo address this, we investigate protein features underlying loss-of-function genetic variation and develop a machine learning method, MutPred-LOF, for the discrimination of pathogenic and tolerated variants that can also generate hypotheses on specific molecular events disrupted by the variant. We investigate a large set of human variants derived from the Human Gene Mutation Database, ClinVar and the Exome Aggregation Consortium. Our prediction method shows an area under the Receiver Operating Characteristic curve of 0.85 for all loss-of-function variants and 0.75 for proteins in which both pathogenic and neutral variants have been observed. We applied MutPred-LOF to a set of 1142 de novo vari3ants from neurodevelopmental disorders and find enrichment of pathogenic variants in affected individuals. Overall, our results highlight the potential of computational tools to elucidate causal mechanisms underlying loss of protein function in loss-of-function variants. AVAILABILITY AND IMPLEMENTATION: http://mutpred.mutdb.org. CONTACT: predrag@indiana.edu.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.