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

Leitão, Elsa; Schröder, Christopher; Parenti, Ilaria; Dalle, Carine; Rastetter, Agnès; Kühnel, Theresa; Kuechler, Alma; Kaya, Sabine; Gérard, Bénédicte; Schaefer, Elise; Nava, Caroline; Drouot, Nathalie; Engel, Camille; Piard, Juliette; Duban-Bedu1, Bénédicte; Villard, Laurent; Stegmann, Alexander P. A.; Vanhoutte, Els K.; Verdonschot, Job A. J.; Kaiser, Frank J.; Mau-Them, Frédéric Tran; Scala, Marcello; Striano, Pasquale; Frints, Suzanna G. M.; Argilli, Emanuela; Sherr, Elliott H.; Elder, Fikret; Buratti, Julien; Keren, Boris; Mignot, Cyril; Héron, Delphine; Mandel, Jean-Louis; Gecz, Jozef; Kalscheuer, Vera M.; Horsthemke, Bernhard; Piton, Amélie; Depienne, Christel

doi:10.1038/s41467-022-34264-y

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

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Kalscheuer, Vera M.
Chromosome Rearrangements and Disease (Vera Kalscheuer), Research Group Development & Disease (Head: Stefan Mundlos), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Citation

Leitão, E., Schröder, C., Parenti, I., Dalle, C., Rastetter, A., Kühnel, T., et al. (2022). Systematic analysis and prediction of genes associated with monogenic disorders on human chromosome X. Nature Communications, 13(1): 6570. doi:10.1038/s41467-022-34264-y.

Cite as: https://hdl.handle.net/21.11116/0000-000B-6343-A

Abstract

Disease 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.