A Computational approach to screen, predict and annotate human and chimpanzee PHEX intronic miRNAs, their gene targets, and regulatory interaction networks.
Comput Biol Chem
; 98: 107673, 2022 Jun.
Article
em En
| MEDLINE
| ID: mdl-35460944
ABSTRACT
The knowledge of what separates us genetically from our less-evolved relatives is crucial for gaining new biomedical insight about the human-chimpanzee relatedness that could influence the development of new treatments and diagnostic aids for various ailments. Especially, more than 300 diseases have been mapped to the X chromosome, which has unique and complicated characteristics than other chromosomes in the human genome. Although the genomes of humans and chimpanzees share 99% similarity, significant differences exist between the two species in their non-coding intronic regions. Therefore, this evolutionary-based genome annotation study attempted to computationally compare, contrast, and annotate the homologous miRNAs and their gene regulatory mechanisms in the intronic regions of the PHEX gene on the human X chromosome of the two species. From our results, we identified a total of 1296 human miRNAs and 46, 957 gene targets. Similarly, 30, 563 targets of homologous chimp miRNAs were predicted. miRNAs like hsa-miR-17-5p showed a maximum number of interactions while miRNAs like hsa-miR-107 with the least number of interactions in the human/chimp gene networks. A few top-ranked miRNAs such as hsa-miR-24, hsa-miR-145, hsa-miR-34a, and hsa-miR-378 were observed to be common between the two genera. The cooperativity and multiplicity of certain miRNAs were predicted to regulate the expression of diverse cancer-associated genes such as Cyclin D1, Notch1, CDK-6, E2F3, ALK4, CKDN2A, DHFR, and MAPK14. Nevertheless, further in vitro and in vivo experimental validations of these gene candidates are required before they could be used as potential diagnostic markers and drug targets.
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Texto completo:
1
Bases de dados:
MEDLINE
Assunto principal:
Pan troglodytes
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MicroRNAs
Tipo de estudo:
Prognostic_studies
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Risk_factors_studies
Limite:
Animals
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Humans
Idioma:
En
Revista:
Comput Biol Chem
Assunto da revista:
BIOLOGIA
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INFORMATICA MEDICA
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QUIMICA
Ano de publicação:
2022
Tipo de documento:
Article