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      Strong Selectional Forces Fine-Tune CpG Content in Genes Involved in Neurological Disorders as Revealed by Codon Usage Patterns

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          Abstract

          Neurodegenerative disorders cause irreversible damage to the neurons and adversely affect the quality of life. Protein misfolding and their aggregation in specific parts of the brain, mitochondrial dysfunction, calcium load, proteolytic stress, and oxidative stress are among the causes of neurodegenerative disorders. In addition, altered metabolism has been associated with neurodegeneration as evidenced by reductions in glutamine and alanine in transient global amnesia patients, higher homocysteine-cysteine disulfide, and lower methionine decline in serum urea have been observed in Alzheimer’s disease patients. Neurodegeneration thus appears to be a culmination of altered metabolism. The study’s objective is to analyze various attributes like composition, physical properties of the protein, and factors like selectional and mutational forces, influencing codon usage preferences in a panel of genes involved directly or indirectly in metabolism and contributing to neurodegeneration. Various parameters, including gene composition, dinucleotide analysis, Relative synonymous codon usage (RSCU), Codon adaptation index (CAI), neutrality and parity plots, and different protein indices, were computed and analyzed to determine the codon usage pattern and factors affecting it. The correlation of intrinsic protein properties such as the grand average of hydropathicity index (GRAVY), isoelectric point, hydrophobicity, and acidic, basic, and neutral amino acid content has been found to influence codon usage. In genes up to 800 amino acids long, the GC3 content was highly variable, while GC12 content was relatively constant. An optimum CpG content is present in genes to maintain a high expression level as required for genes involved in metabolism. Also observed was a low codon usage bias with a higher protein expression level. Compositional parameters and nucleotides at the second position of codons played essential roles in explaining the extent of bias. Overall analysis indicated that the dominance of selection pressure and compositional constraints and mutational forces shape codon usage.

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          Most cited references58

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          Protein Identification and Analysis Tools on the ExPASy Server

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            A simple method for displaying the hydropathic character of a protein.

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              The codon Adaptation Index--a measure of directional synonymous codon usage bias, and its potential applications.

              P. Sharp, W Li (1987)
              A simple, effective measure of synonymous codon usage bias, the Codon Adaptation Index, is detailed. The index uses a reference set of highly expressed genes from a species to assess the relative merits of each codon, and a score for a gene is calculated from the frequency of use of all codons in that gene. The index assesses the extent to which selection has been effective in moulding the pattern of codon usage. In that respect it is useful for predicting the level of expression of a gene, for assessing the adaptation of viral genes to their hosts, and for making comparisons of codon usage in different organisms. The index may also give an approximate indication of the likely success of heterologous gene expression.
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                Author and article information

                Contributors
                Journal
                Front Neurosci
                Front Neurosci
                Front. Neurosci.
                Frontiers in Neuroscience
                Frontiers Media S.A.
                1662-4548
                1662-453X
                10 June 2022
                2022
                : 16
                : 887929
                Affiliations
                [1] 1Department of Biochemistry and Genetics, Barkatullah University , Bhopal, India
                [2] 2Department of Pharmacology, College of Pharmacy, King Khalid University , Abha, Saudi Arabia
                [3] 3Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, University of Hail , Hail, Saudi Arabia
                [4] 4Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University , Chengdu, China
                [5] 5King Fahd Medical Research Center, King Abdulaziz University , Jeddah, Saudi Arabia
                [6] 6Department of Pharmacy, Faculty of Allied Health Sciences, Daffodil International University , Dhaka, Bangladesh
                [7] 7Enzymoics, Novel Global Community Educational Foundation , Hebersham, NSW, Australia
                Author notes

                Edited by: Wael M. Y. Mohamed, International Islamic University Malaysia, Malaysia

                Reviewed by: Yehuda Ben-Shahar, Washington University in St. Louis, United States; Tarikul Huda Mazumder, EduCare Academy, India

                This article was submitted to Translational Neuroscience, a section of the journal Frontiers in Neuroscience

                Article
                10.3389/fnins.2022.887929
                9226491
                35757545
                062e07b5-a564-46aa-b8d3-cefeea66a67d
                Copyright © 2022 Khandia, Sharma, Alqahtani, Alqahtani, Asiri, Alqahtani, Alharbi and Kamal.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 02 March 2022
                : 04 April 2022
                Page count
                Figures: 9, Tables: 3, Equations: 0, References: 58, Pages: 23, Words: 16750
                Categories
                Neuroscience
                Original Research

                Neurosciences
                neurodegeneration,metabolism-related genes,codon usage,dinucleotide ratio,rscu,fine tuning of cpg dinucleotide

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