Approaches for the Search and Analysis of Pathogenic Variants of Nucleotide Sequence in Non-coding Gene Regions Were Developed

Joint article of the laboratory of functional genomics at the Research Centre for Medical Genetics, devoted to the development of an algorithm that allows the detection of pathogenic variants of nucleotide sequence in 5 non-translated gene regions, was published in Nucleic Acids Research (Q1, IF 19.16). 

To date, in the DNA diagnostics of patients with hereditary diseases, researchers focus on the part of the gene with which the translation of the main protein encoded by the given genome directly occurs. However, in addition to the described protein coding part, human genes include sequences that are not involved in protein coding. One such sequence is the 5 ī non-translated region in front of the protein-coding part of the gene. These domains play an important role in regulating gene expression through various mechanisms, including the presence of special sequences called small open reading frames - upstream ORFs (uORFs).

According to literary estimates, more than half of human genes may have such a reading frame, but they describe pathogenic variants only in isolated cases. This is due to the lack of qualitative annotation of uORFs in human genes, on the one hand, and to the lack of accessible tools for searching and interpreting variants in these genes, on the other hand.

The work devoted to solving these problems was carried out by employees of the functional genomics laboratory at RCMG together with colleagues from the Far Eastern Federal University (FEFU), Artificial Intelligence Research Institute (AIRI)and the Bio-information Science and Polytechnic Institute in Paris. Researchers have analyzed in detail about 3,600 genes associated with hereditary diseases, which are mentioned in the OMIM database. As a result, 4.7 thousand. sites of initiation of translation of small open reading frames in 1782 genes associated with the development of hereditary diseases were described.

“One of the most important results was the confirmation that half of the genes associated with hereditary diseases have small open reading frames. To date, there has not been a high-quality list of the coordinates of uORF in human genes, making it difficult to find pathogenic variants in these genes. Our research is important for improving the quality of DNA diagnostics of patients with hereditary diseases. We have created our own bio-information technology tool that allows us to find pathogenic variants in uORF. With its help, we analyzed the options in the open databases HGMD and ClinVar and found such options that lead to the development of the disease at the expense of breaking small open frames of reading. Some small open reading frames and variants found with the help of bio-information technology tools have been experimentally tested to confirm our hypothesis. In addition, based on our detailed analysis of uORF in a small part of the human genes associated with the development of hereditary diseases, we have worked together to create a model of machine learning, which predicted small open reading frames in all other human genes, which is of interest to basic science”, - said PhB  Alexandra Filatova, the researcher of the laboratory of functional genomics at RCMG.

The work was performed within the state assignment of the Ministry of Science and Higher Education of the Russian Federation with the support of the Research Institute for Artificial Intelligence (AIRI) and is of great practical importance. The created programme of search of pathogenic variants of nucleotide sequence in small open frame of reading will allow to increase efficiency of diagnostics. In cases where standard DNA diagnostic methods fail, doctors will be able to use a bio-information technology tool to search for pathogenic variants in the 5 bacterial non-translatable gene regions. The programme will be applied in the research practice of RCMG, as well as open to specialists of other scientific and medical organizations.  

For more details of the report follow the link: Alexandra Filatova, Ivan Reveguk, Maria Piatkova, Daria Bessonova, Olga Kuziakova, Victoria Demakova, Alexander Romanishin, Veniamin Fishman, Yerzhan Imanmalik, Nikolay Chekanov, Rostislav Skitchenko, Yury Barbitoff, Olga Kardymon, Mikhail Skoblov. Annotation of uORFs in the OMIM genes allows to reveal pathogenic variants in 5′UTRs. Nucleic Acids Research, gkac1247 https://doi.org/10.1093/nar/gkac1247