Systematic analysis and prediction of genes associated with monogenic disorders on human chromosome X.

Simple item page
dc.contributor.authorLeitão, E.
dc.contributor.authorSchröder, C.
dc.contributor.authorParenti, I.
dc.contributor.authorDalle, C.
dc.contributor.authorRastetter, A.
dc.contributor.authorKühnel, T.
dc.contributor.authorKuechler, A.
dc.contributor.authorKaya, S.
dc.contributor.authorGérard, B.
dc.contributor.authorSchaefer, E.
dc.contributor.authorNava, C.
dc.contributor.authorDrouot, N.
dc.contributor.authorEngel, C.
dc.contributor.authorPiard, J.
dc.contributor.authorDuban-Bedu, B.
dc.contributor.authorVillard, L.
dc.contributor.authorStegmann, A.P.A.
dc.contributor.authorVanhoutte, E.K.
dc.contributor.authorVerdonschot, J.A.J.
dc.contributor.authorKaiser, F.J.
dc.contributor.authoret al.
dc.date.issued2022
dc.description.abstractDisease gene discovery on chromosome (chr) X is challenging owing to its unique modes of inheritance. We undertook a systematic analysis of human chrX genes. We observe a higher proportion of disorder-associated genes and an enrichment of genes involved in cognition, language, and seizures on chrX compared to autosomes. We analyze gene constraints, exon and promoter conservation, expression, and paralogues, and report 127 genes sharing one or more attributes with known chrX disorder genes. Using machine learning classifiers trained to distinguish disease-associated from dispensable genes, we classify 247 genes, including 115 of the 127, as having high probability of being disease-associated. We provide evidence of an excess of variants in predicted genes in existing databases. Finally, we report damaging variants in CDK16 and TRPC5 in patients with intellectual disability or autism spectrum disorders. This study predicts large-scale gene-disease associations that could be used for prioritization of X-linked pathogenic variants.
dc.identifier.citationNature Communications, 2022; 13(1):6570-1-6570-17
dc.identifier.doi10.1038/s41467-022-34264-y
dc.identifier.issn2041-1723
dc.identifier.issn2041-1723
dc.identifier.orcidGecz, J. [0000-0002-7884-6861]
dc.identifier.urihttps://hdl.handle.net/2440/146075
dc.language.isoen
dc.publisherSpringer Science and Business Media LLC
dc.rights© The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/.
dc.source.urihttps://doi.org/10.1038/s41467-022-34264-y
dc.subjectGenetics; Neurodevelopmental disorders
dc.subject.meshChromosomes, Human, X
dc.subject.meshHumans
dc.subject.meshDatabases, Genetic
dc.subject.meshGenes, X-Linked
dc.subject.meshIntellectual Disability
dc.subject.meshAutism Spectrum Disorder
dc.titleSystematic analysis and prediction of genes associated with monogenic disorders on human chromosome X.
dc.typeJournal article
pubs.publication-statusPublished

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
hdl_146075.pdf
Size:
3.3 MB
Format:
Adobe Portable Document Format
Description:
Published version
Download

Collections

Research Outputs