Dataset Information

MTR3D: identifying regions within protein tertiary structures under purifying selection.

ABSTRACT: The identification of disease-causal variants is non-trivial. By mapping population variation from over 448,000 exome and genome sequences to over 81,000 experimental structures and homology models of the human proteome, we have calculated both regional intolerance to missense variation (Missense Tolerance Ratio, MTR), using a sliding window of 21-41 codons, and introduce a new 3D spatial intolerance to missense variation score (3D Missense Tolerance Ratio, MTR3D), using spheres of 5-8 Å. We show that the MTR3D is less biased by regions with limited data and more accurately identifies regions under purifying selection than estimates relying on the sequence alone. Intolerant regions were highly enriched for both ClinVar pathogenic and COSMIC somatic missense variants (Mann-Whitney U test P < 2.2 × 10-16). Further, we combine sequence- and spatial-based scores to generate a consensus score, MTRX, which distinguishes pathogenic from benign variants more accurately than either score separately (AUC = 0.85). The MTR3D server enables easy visualisation of population variation, MTR, MTR3D and MTRX scores across the entire gene and protein structure for >17,000 human genes and >42,000 alternative alternate transcripts, including both Ensembl and RefSeq transcripts. MTR3D is freely available by user-friendly web-interface and API at http://biosig.unimelb.edu.au/mtr3d/.

SUBMITTER: Silk M

PROVIDER: S-EPMC8265191 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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MTR3D: identifying regions within protein tertiary structures under purifying selection.

Silk Michael M Pires Douglas E V DEV Rodrigues Carlos H M CHM D'Souza Elston N EN Olshansky Moshe M Thorne Natalie N Ascher David B DB

Nucleic acids research 20210701 W1

The identification of disease-causal variants is non-trivial. By mapping population variation from over 448,000 exome and genome sequences to over 81,000 experimental structures and homology models of the human proteome, we have calculated both regional intolerance to missense variation (Missense Tolerance Ratio, MTR), using a sliding window of 21-41 codons, and introduce a new 3D spatial intolerance to missense variation score (3D Missense Tolerance Ratio, MTR3D), using spheres of 5-8 Å. We sho ...[more]

PMID: 34050760

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Project description:Diverse life forms are driven by the evolution of gene regulatory programs including changes in regulator proteins and cis-regulatory elements. Alterations of cis-regulatory elements are likely to dominate the evolution of the gene regulatory networks, as they are subjected to smaller selective constraints compared with proteins and hence may evolve quickly to adapt the environment. Prior studies on cis-regulatory element evolution focus primarily on sequence substitutions of known transcription factor-binding motifs. However, evolutionary models for the dynamics of motif occurrence are relatively rare, and comprehensive characterization of the evolution of all possible motif sequences has not been pursued. In the present study, we propose an algorithm to estimate the strength of purifying selection of a motif sequence based on an evolutionary model capturing the birth and death of motif occurrences on promoters. We term this measure as the 'evolutionary retention coefficient', as it is related yet distinct from the canonical definition of selection coefficient in population genetics. Using this algorithm, we estimate and report the evolutionary retention coefficients of all possible 10-nucleotide sequences from the aligned promoter sequences of 27 748. orthologous gene families in 34 mammalian species. Intriguingly, the evolutionary retention coefficients of motifs are intimately associated with their functional relevance. Top-ranking motifs (sorted by evolutionary retention coefficients) are significantly enriched with transcription factor-binding sequences according to the curated knowledge from the TRANSFAC database and the ChIP-seq data generated from the ENCODE Consortium. Moreover, genes harbouring high-scoring motifs on their promoters retain significantly coherent expression profiles, and those genes are over-represented in the functional classes involved in gene regulation. The validation results reveal the dependencies between natural selection and functions of cis-regulatory elements and shed light on the evolution of gene regulatory networks.

Dataset Information

MTR3D: identifying regions within protein tertiary structures under purifying selection.

Publications

MTR3D: identifying regions within protein tertiary structures under purifying selection.

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