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Comparative Analysis of Genes Associated with Obesity in Humans Using Bioinformatic Data and Tools

Obesity has become a serious global problem that still needs a solution. One of the factors that leads to obesity is genetic predisposition. The identity and characteristics of the genes involved have not yet been fully confirmed. Analyzing the genetic contribution to obesity is a major step towards...

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Autores principales: Musliji, ZS, Pollozhani, AK, Lisichkov, K, Deligios, M, Popovski, ZT
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Sciendo 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8366471/
https://www.ncbi.nlm.nih.gov/pubmed/34447657
http://dx.doi.org/10.2478/bjmg-2021-0012
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author Musliji, ZS
Pollozhani, AK
Lisichkov, K
Deligios, M
Popovski, ZT
author_facet Musliji, ZS
Pollozhani, AK
Lisichkov, K
Deligios, M
Popovski, ZT
author_sort Musliji, ZS
collection PubMed
description Obesity has become a serious global problem that still needs a solution. One of the factors that leads to obesity is genetic predisposition. The identity and characteristics of the genes involved have not yet been fully confirmed. Analyzing the genetic contribution to obesity is a major step towards the solution. In this in silico study, using online bioinformatics tools, we evaluate the role of four genes that are believed to contribute to obesity. Data were collected and analyzed for the sequences of four so-called obesity genes: FTO (fat mass and obesity-associated protein), PPARG (peroxisome proliferator activated receptor γ), ADRB3 (adrenergic receptor β 3) and FABP2 (fatty acid binding protein 2). In the first part of the research, information about the genes was collected and organized and data in FASTA, format are extracted from the National Center for Biotechnology Information (NCBI). In the second part, all genes were analyzed by comparing three species of organisms, Homo sapiens (human), Mus musculus (mouse) and Gallus (chicken). In the third part of this study, phylogenetic trees were constructed for each of the four genes, using blast local alignment search tool (BLAST) and molecular evolutionary genetics analysis (MEGA X) software. Our analysis reveals that the functions of all these genes are associated with overweight and obesity.
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spelling pubmed-83664712021-08-25 Comparative Analysis of Genes Associated with Obesity in Humans Using Bioinformatic Data and Tools Musliji, ZS Pollozhani, AK Lisichkov, K Deligios, M Popovski, ZT Balkan J Med Genet Original Article Obesity has become a serious global problem that still needs a solution. One of the factors that leads to obesity is genetic predisposition. The identity and characteristics of the genes involved have not yet been fully confirmed. Analyzing the genetic contribution to obesity is a major step towards the solution. In this in silico study, using online bioinformatics tools, we evaluate the role of four genes that are believed to contribute to obesity. Data were collected and analyzed for the sequences of four so-called obesity genes: FTO (fat mass and obesity-associated protein), PPARG (peroxisome proliferator activated receptor γ), ADRB3 (adrenergic receptor β 3) and FABP2 (fatty acid binding protein 2). In the first part of the research, information about the genes was collected and organized and data in FASTA, format are extracted from the National Center for Biotechnology Information (NCBI). In the second part, all genes were analyzed by comparing three species of organisms, Homo sapiens (human), Mus musculus (mouse) and Gallus (chicken). In the third part of this study, phylogenetic trees were constructed for each of the four genes, using blast local alignment search tool (BLAST) and molecular evolutionary genetics analysis (MEGA X) software. Our analysis reveals that the functions of all these genes are associated with overweight and obesity. Sciendo 2021-07-27 /pmc/articles/PMC8366471/ /pubmed/34447657 http://dx.doi.org/10.2478/bjmg-2021-0012 Text en © 2021 Musliji ZS, Pollozhani AK, Lisichkov K, Deligios M, Popovski ZT, published by Sciendo https://creativecommons.org/licenses/by-nc-nd/3.0/This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
spellingShingle Original Article
Musliji, ZS
Pollozhani, AK
Lisichkov, K
Deligios, M
Popovski, ZT
Comparative Analysis of Genes Associated with Obesity in Humans Using Bioinformatic Data and Tools
title Comparative Analysis of Genes Associated with Obesity in Humans Using Bioinformatic Data and Tools
title_full Comparative Analysis of Genes Associated with Obesity in Humans Using Bioinformatic Data and Tools
title_fullStr Comparative Analysis of Genes Associated with Obesity in Humans Using Bioinformatic Data and Tools
title_full_unstemmed Comparative Analysis of Genes Associated with Obesity in Humans Using Bioinformatic Data and Tools
title_short Comparative Analysis of Genes Associated with Obesity in Humans Using Bioinformatic Data and Tools
title_sort comparative analysis of genes associated with obesity in humans using bioinformatic data and tools
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8366471/
https://www.ncbi.nlm.nih.gov/pubmed/34447657
http://dx.doi.org/10.2478/bjmg-2021-0012
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