Version 1
: Received: 1 October 2023 / Approved: 2 October 2023 / Online: 2 October 2023 (04:26:02 CEST)
How to cite:
Iourov, I.Y. Knowledge-Based Prioritization of Genomic Variations: A Quest for Detailed Understanding the Genetic Architecture of Diseases. Preprints2023, 2023100038. https://doi.org/10.20944/preprints202310.0038.v1
Iourov, I.Y. Knowledge-Based Prioritization of Genomic Variations: A Quest for Detailed Understanding the Genetic Architecture of Diseases. Preprints 2023, 2023100038. https://doi.org/10.20944/preprints202310.0038.v1
Iourov, I.Y. Knowledge-Based Prioritization of Genomic Variations: A Quest for Detailed Understanding the Genetic Architecture of Diseases. Preprints2023, 2023100038. https://doi.org/10.20944/preprints202310.0038.v1
APA Style
Iourov, I.Y. (2023). Knowledge-Based Prioritization of Genomic Variations: A Quest for Detailed Understanding the Genetic Architecture of Diseases. Preprints. https://doi.org/10.20944/preprints202310.0038.v1
Chicago/Turabian Style
Iourov, I.Y. 2023 "Knowledge-Based Prioritization of Genomic Variations: A Quest for Detailed Understanding the Genetic Architecture of Diseases" Preprints. https://doi.org/10.20944/preprints202310.0038.v1
Abstract
Understanding the genetic architecture of a disease is crucial for development of valid diagnostic and therapeutic interventions. The analysis of genomic variations associated with pathological conditions is the starting point for uncovering disease-causing pathways (candidate processes). However, the complexity of intergenic and genetic-environmental interactions hinders the identification of pathogenic values of genomic changes. Furthermore, heredity, epigenetics and somatic mosaicism make the interpretation of genomic data even more sophisticated. To succeed, a variety of bioinformatic techniques are applied. Here, reviewing own and literature data, knowledge-based prioritization of genomic variations is described. Theoretical basis of the knowledge-based prioritization is given with a special regard to gene ontology, heuristics, hermeneutics (genomic hermeneutics) and analytics. Practical and methodological issues of prioritization using ontology- or pathway-based systems analysis are considered in the light of optimistic and realistic scenarios of cumulative phenotypic effects of the variome (the whole set of genomic variations in an individual or specific set of genomic variations for a phenotypic outcome). In the present communication, copy number variants (CNVs) in children with neurodevelopmental diseases are used as a practical foundation for the prioritization, inasmuch as these genome variations are systematically overlooked in the so-called NGS era. Nonetheless, it is highly likely that the prioritization is applicable to almost all types of genomic variations (e.g. chromosome abnormalities, gene mutations, functional synonymous variants etc.). The present methodology seems to be a valuable addition to current biomedical science widening the opportunities for medical genomics and genetics.
Keywords
candidate processes; disease; genomic variations; knowledge; medical genomics; ontology; pathways; prioritization; systems analysis; variome
Subject
Biology and Life Sciences, Life Sciences
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
