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密码子使用模式揭示强选择力微调神经疾病相关基因中的CpG含量

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

作者信息

Khandia Rekha, Sharma Anushri, Alqahtani Taha, Alqahtani Ali M, Asiri Yahya I, Alqahtani Saud, Alharbi Ahmed M, Kamal Mohammad Amjad

机构信息

Department of Biochemistry and Genetics, Barkatullah University, Bhopal, India.

Department of Pharmacology, College of Pharmacy, King Khalid University, Abha, Saudi Arabia.

出版信息

Front Neurosci. 2022 Jun 10;16:887929. doi: 10.3389/fnins.2022.887929. eCollection 2022.

DOI:10.3389/fnins.2022.887929
PMID:35757545
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9226491/
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.

摘要

神经退行性疾病会对神经元造成不可逆的损害,并对生活质量产生不利影响。蛋白质错误折叠及其在大脑特定部位的聚集、线粒体功能障碍、钙超载、蛋白水解应激和氧化应激都是神经退行性疾病的病因。此外,代谢改变与神经退行性变有关,这在短暂性全面性遗忘症患者谷氨酰胺和丙氨酸减少、阿尔茨海默病患者血清中同型半胱氨酸 - 半胱氨酸二硫化物升高以及蛋氨酸下降、血清尿素降低中得到了证实。因此,神经退行性变似乎是代谢改变的最终结果。该研究的目的是分析各种属性,如蛋白质的组成、物理性质,以及选择和突变力等因素,这些因素会影响一组直接或间接参与代谢并导致神经退行性变的基因中的密码子使用偏好。计算并分析了各种参数,包括基因组成、二核苷酸分析、相对同义密码子使用(RSCU)、密码子适应指数(CAI)、中性和奇偶性图以及不同的蛋白质指数,以确定密码子使用模式及其影响因素。已发现内在蛋白质特性,如亲水性指数的总平均值(GRAVY)、等电点、疏水性以及酸性、碱性和中性氨基酸含量之间的相关性会影响密码子使用。在长度达800个氨基酸的基因中,GC3含量变化很大,而GC12含量相对恒定。基因中存在最佳的CpG含量,以维持参与代谢的基因所需的高表达水平。还观察到密码子使用偏性较低但蛋白质表达水平较高的情况。组成参数和密码子第二位的核苷酸在解释偏性程度方面起着重要作用。总体分析表明,选择压力、组成限制和突变力的主导作用塑造了密码子使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e2c/9226491/bfca20b8b6a5/fnins-16-887929-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e2c/9226491/d1bdfe6feca9/fnins-16-887929-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e2c/9226491/51848ca6f51c/fnins-16-887929-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e2c/9226491/bfca20b8b6a5/fnins-16-887929-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e2c/9226491/d1bdfe6feca9/fnins-16-887929-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e2c/9226491/2d439ac6545d/fnins-16-887929-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e2c/9226491/96d8079df46a/fnins-16-887929-g003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e2c/9226491/51848ca6f51c/fnins-16-887929-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e2c/9226491/bfca20b8b6a5/fnins-16-887929-g009.jpg

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