Annotation of uORFs in the OMIM genes allows to reveal pathogenic variants in 5′UTRs

Author:

Filatova Alexandra1ORCID,Reveguk Ivan2,Piatkova Maria34,Bessonova Daria5,Kuziakova Olga6,Demakova Victoria5,Romanishin Alexander67,Fishman Veniamin89ORCID,Imanmalik Yerzhan8,Chekanov Nikolay8,Skitchenko Rostislav10ORCID,Barbitoff Yury111213ORCID,Kardymon Olga8,Skoblov Mikhail1ORCID

Affiliation:

1. Research Centre for Medical Genetics , Moscow , Russia

2. Laboratoire de Biologie Structurale de la Cellule , École Polytechnique, Paris , France

3. Institute of Chemistry, Far Eastern Branch of the Russian Academy of Sciences , Vladivostok , Russia

4. Institute of high technologies and advanced materials, Far Eastern Federal University , Vladivostok , Russia

5. Medical Center, Far Eastern Federal University , Vladivostok , Russia

6. Institute of Life Sciences and Biomedicine, Far Eastern Federal University , Vladivostok , Russia

7. Institute of Life Sciences, Immanuel Kant Baltic Federal University , Kaliningrad , Russia

8. Artificial Intelligence Research Institute , Moscow , Russia

9. Molecular Mechanisms of Ontogenesis, Institute of Cytology and Genetics SB RAS , Novosibirsk , Russia

10. Computer Technologies Laboratory, ITMO University , Saint Petersburg , Russia

11. Bioinformatics Institute , St. Petersburg , Russia

12. Department of Genomic Medicine, D.O. Ott Research Institute of Obstetrics , Gynaecology, and Reproductology, St. Petersburg , Russia

13. Dpt. of Genetics and Biotechnology, St. Petersburg State University , St. Petersburg , Russia

Abstract

AbstractAn increasing number of studies emphasize the role of non-coding variants in the development of hereditary diseases. However, the interpretation of such variants in clinical genetic testing still remains a critical challenge due to poor knowledge of their pathogenicity mechanisms. It was previously shown that variants in 5′-untranslated regions (5′UTRs) can lead to hereditary diseases due to disruption of upstream open reading frames (uORFs). Here, we performed a manual annotation of upstream translation initiation sites (TISs) in human disease-associated genes from the OMIM database and revealed ∼4.7 thousand of TISs related to uORFs. We compared our TISs with the previous studies and provided a list of ‘high confidence’ uORFs. Using a luciferase assay, we experimentally validated the translation of uORFs in the ETFDH, PAX9, MAST1, HTT, TTN,GLI2 and COL2A1 genes, as well as existence of N-terminal CDS extension in the ZIC2 gene. Besides, we created a tool to annotate the effects of genetic variants located in uORFs. We revealed the variants from the HGMD and ClinVar databases that disrupt uORFs and thereby could lead to Mendelian disorders. We also showed that the distribution of uORFs-affecting variants differs between pathogenic and population variants. Finally, drawing on manually curated data, we developed a machine-learning algorithm that allows us to predict the TISs in other human genes.

Funder

Artificial Intelligence Research Institute

Ministry of Science and Higher Education of the Russian Federation

Publisher

Oxford University Press (OUP)

Subject

Genetics

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