We determined various forces involved in shaping codon usage of the genes linked to brain iron accumulation and infantile neuroaxonal dystrophy. The analysis paved the way for determining the forces responsible for composition, expression level, physical properties and codon bias of a gene. An interesting observation related to composition was that, on all the three codon positions, any two of the four nucleotides had similar compositions. CpG, TpA, and GpT dinucleotides were underrepresented with the overrepresentation of TpG dinucleotide. CpG and TpA containing codons ATA, CTA, TCG, and GCG were underrepresented, while TpG dinucleotide containing codon CTG was overrepresented, indicative of compositional constraints importance. GC ending codons were favored when the genome is GC rich, except leucine encoding codon TTG, which exhibits an inverse relationship with GC content. Nucleotide disproportions are found associated with the physical properties of proteins. The values of CAI and ENc are suggestive of low codon bias in genes. Considering the results of neutrality analysis, parity analysis, underrepresentation of TpA and CpG codons, and over-representation of TpG codons, the correlation between the compositional constraints and skew relationships with protein properties suggested the role of all the three selectional, mutational and compositional forces in shaping codon usage with the dominance of selectional pressure.
Cite this article
Leucine encoding codon TTG shows an inverse relationship with GC content in genes involved in neurodegeneration with iron accumulation
Taha Alqahtani1, Rekha Khandia2,*, Nidhi Puranik2, Ali M Alqahtani1, Mohannad A. Almikhlafi3, Mubarak Ali Algahtany4
1 Department of Pharmacology, College of Pharmacy, King Khalid University, 62529 Abha, Saudi Arabia
2 Department of Biochemistry and Genetics, Barkatullah University, 462026 MP Bhopal, India
3 Department of Pharmacology and Toxicology, Taibah University, 42311 Madinah, Saudi Arabia
4 Division of Neurosurgery, Department of Surgery, College of Medicine, King Khalid University, 62529 Abha, Saudi Arabia
J. Integr. Neurosci. 2021, 20(4), 905–918; https://doi.org/10.31083/j.jin2004092
Submitted: 19 August 2021 | Revised: 29 September 2021 | Accepted: 1 November 2021 | Published: 30 December 2021
(This article belongs to the Special Issue Biomedical informatics in neuroscience)
Copyright: © 2021 The Author(s). Published by IMR Press.
This is an open access article under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/).