Genes and Diseases: Insights from Transcriptomics Studies

Dmitry S Kolobkov; Darya A Sviridova; Serikbai K Abilev; Artem N Kuzovlev; Lyubov E Salnikova

doi:10.3390/genes13071168

Genes and Diseases: Insights from Transcriptomics Studies

Genes (Basel). 2022 Jun 28;13(7):1168. doi: 10.3390/genes13071168.

Authors

Dmitry S Kolobkov¹, Darya A Sviridova¹, Serikbai K Abilev¹, Artem N Kuzovlev², Lyubov E Salnikova^{1

2

3}

Affiliations

¹ The Laboratory of Ecological Genetics, Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow 119991, Russia.
² The Laboratory of Clinical Pathophysiology of Critical Conditions, Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow 107031, Russia.
³ The Laboratory of Molecular Immunology, Rogachev National Research Center of Pediatric Hematology, Oncology and Immunology, Moscow 117997, Russia.

Abstract

Results of expression studies can be useful to clarify the genotype-phenotype relationship. However, according to data from recent literature, there is a large group of genes that are revealed as differentially expressed (DE) in many studies, regardless of the biological context. Additional analyses could shed more light on the relationships between genes, their differential expression, and diseases. We generated a set of 9972 disease genes from five gene-phenotype databases (OMIM, ORPHANET, DDG2P, DisGeNet and MalaCards) and a report of the International Union of Immunological Societies. To study transcriptomics of disease and non-disease genes in healthy tissues, we obtained data from the Human Protein Atlas (HPA) website. We analyzed the dependency between expression in healthy tissues and gene occurrence in Gene Expression Omnibus series using tools within the Enrichr libraries. The results of expression studies were annotated with Gene Ontology (GO) and Human Phenotype Ontology (HPO) terms. Using transcriptomics analysis of healthy tissues, we validated the previous findings of higher expression levels of disease genes in pathologically linked tissues compared to other tissues. Preferentially DE genes were generally highly expressed in one or multiple tissues and were enriched for disease genes. According to the results of GO enrichment analyses, both down- and up-regulated DE genes most often took part in immune response, translation and tissue-specific processes. A connection between DE-related pathology and the diversity of HPO terms was found. Investigating a link between expression and phenotype contributes to understanding the mode of development and progression of human diseases.

Keywords: differential expression (DE); disease genes; gene expression omnibus (GEO); gene ontology (GO); human phenotype ontology (HPO); transcriptomics analysis of healthy tissues.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Gene Expression Profiling*
Gene Ontology
Humans
Phenotype
Transcriptome* / genetics

Grants and funding

This work was supported by the state assignments of the Ministry of Education and Science of Russia (No. 0112-2019-0002 “Genetic technologies in biology, medicine, agriculture and environmental management activities” and No. FGWS-2022-0001 “Multiple organ dysfunction and insufficiency in critical conditions: leading mechanisms of development, new methods of diagnosis and treatment”).