The codon usage pattern of genes involved in ovarian cancer

Compositional Features and Codon Usage Pattern of Genes Associated with Parkinson's Disease

Codon usage bias (CUB) is the phenomenon of non-uniform usage of synonymous codons in which some codons are more used than others and it helps in understanding the molecular organization of genome. Bioinformatic approach was used to analyze the protein-coding sequences of genes associated with Parkinson's disease (PD) to explore compositional features and codon usage pattern as no details work was reported yet. The average improved effective number of codons (Nc) and Nc prime were 42.74 and 44.26 respectively, indicated that CUB was low in these genes. In most of the genes, the overall GC content was almost 50% and GC content at the 1st codon position was the highest while GC content at the 2nd codon position was lowest. Relative synonymous codon usage (RSCU) analysis elucidated over-represented (p > 1.6) and under-represented codons (p < 0.6). The GTG (Val) is the only codon over-represented in all genes. Over-represented codons except (GTG) were A or T ending while under-represented codons (except ACT) were G or C ending. The codons namely TTA (Leu), CTA (Leu), ATC (Ile), ATA (Ile), AGT (Ser), AAC (Asn), TGT (Cys), TGC (Cys), CGC (Arg), AGA (Arg), and AGG (Arg) were absent in SNCA1 to SNCA8 genes. The codon TCG (Ser) was absent in all genes except UCHL1 and PINK1. Correspondence analysis (COA) revealed that the pattern of codon usage differs among genes associated with PD. Neutrality plot analysis indicated some of the points are diagonal distribution suggested that mutation pressure influenced the CUB in genes associated with PD.

Molecular insights into codon usage analysis of mitochondrial fission and fusion gene: relevance to neurodegenerative diseases

Mitochondrial dysfunction is the leading cause of neurodegenerative disorders like Alzheimer's disease and Parkinson's disease. Mitochondria is a highly dynamic organelle continuously undergoing the process of fission and fusion for even distribution of components and maintaining proper shape, number, and bioenergetic functionality. A set of genes governs the process of fission and fusion. OPA1, Mfn1, and Mfn2 govern fusion, while Drp1, Fis1, MIEF1, and MIEF2 genes control fission. Determination of specific molecular patterns of transcripts of these genes revealed the impact of compositional constraints on selecting optimal codons. AGA and CCA codons were over-represented, and CCC, GTC, TTC, GGG, ACG were under-represented in the fusion gene set. In contrast, CTG was over-represented, and GCG, CCG, and TCG were under-represented in the fission gene set. Hydropathicity analysis revealed non-polar protein products of both fission and fusion gene set transcripts. AGA codon repeats are an integral part of translational regulation machinery and present a distinct pattern of over-representation and under-representation in different transcripts within the gene sets, suggestive of selective translational force precisely controlling the occurrence of the codon. Out of six synonymous codons, five synonymous codons encoding for leucine were used differently in both gene sets. Hence, forces regulating the occurrence of AGA and five synonymous leucine-encoding codons suggest translational selection. A correlation of mutational bias with gene expression and codon bias and GRAVY and AROMA signifies the selection pressure in both gene sets, while the correlation of compositional bias with gene expression, codon bias, protein properties, and minimum free energy signifies the presence of compositional constraints. More than 25% of codons of both gene sets showed a significant difference in codon usage. The overall analysis shed light on molecular features of gene sets involved in fission and fusion.

Relative synonymous codon usage and codon pair analysis of depression associated genes

Depression negatively impacts mood, behavior, and mental and physical health. It is the third leading cause of suicides worldwide and leads to decreased quality of life. We examined 18 genes available at the genetic testing registry (GTR) from the National Center for Biotechnological Information to investigate molecular patterns present in depression-associated genes. Different genotypes and differential expression of the genes are responsible for ensuing depression. The present study, investigated codon pattern analysis, which might play imperative roles in modulating gene expression of depression-associated genes. Of the 18 genes, seven and two genes tended to up- and down-regulate, respectively, and, for the remaining genes, different genotypes, an outcome of SNPs were responsible alone or in combination with differential expression for different conditions associated with depression. Codon context analysis revealed the abundance of identical GTG-GTG and CTG-CTG pairs, and the rarity of methionine-initiated codon pairs. Information based on codon usage, preferred codons, rare, and codon context might be used in constructing a deliverable synthetic construct to correct the gene expression level of the human body, which is altered in the depressive state. Other molecular signatures also revealed the role of evolutionary forces in shaping codon usage.

Codon usage behavior distinguishes pathogenic Clostridium species from the non-pathogenic species

Genus Clostridium is of the largest genus in class Clostridia. It is comprised of spore-forming, anaerobic, gram-positive organisms. The members of this genus include human pathogens to free-living nitrogen fixing bacteria. In the present study, we have performed a comparison of the choice of preferred codons, codon usage patterns, dinucleotide and amino acid usage pattern of 76 species of Genus Clostridium. We found the pathogenic clostridium species to have smaller AT-rich genomes as compared to opportunistic and non-pathogenic clostridium species. The choice of preferred and optimal codons was also influenced by genomic GC/AT content of the respective clostridium species. The pathogenic clostridium species displayed a strict bias in the codon usage, employing 35 of the 61 codons encoding for 20 amino acids. Comparison of amino acid usage revealed an increased usage of amino acids with lower biosynthetic cost by pathogenic clostridium species as compared to opportunistic and non-pathogenic clostridium species. Smaller genome, strict codon usage bias and amino acid usage lead to lower protein energetic cost for the clostridial pathogens. Overall, we found the pathogenic members of genus Clostridium to prefer small, AT-rich codons to reduce biosynthetic costs and match the cellular environment of its AT-rich human host.

An investigation of codon usage pattern analysis in pancreatitis associated genes

BACKGROUND

Pancreatitis is an inflammatory disorder resulting from the autoactivation of trypsinogen in the pancreas. The genetic basis of the disease is an old phenomenon, and evidence is accumulating for the involvement of synonymous/non-synonymous codon variants in disease initiation and progression.

RESULTS

The present study envisaged a panel of 26 genes involved in pancreatitis for their codon choices, compositional analysis, relative dinucleotide frequency, nucleotide disproportion, protein physical properties, gene expression, codon bias, and interrelated of all these factors. In this set of genes, gene length was positively correlated with nucleotide skews and codon usage bias. Codon usage of any gene is dependent upon its AT and GC component; however, AGG, CGT, and CGA encoding for Arg, TCG for Ser, GTC for Val, and CCA for Pro were independent of nucleotide compositions. In addition, Codon GTC showed a correlation with protein properties, isoelectric point, instability index, and frequency of basic amino acids. We also investigated the effect of various evolutionary forces in shaping the codon usage choices of genes.

CONCLUSIONS

This study will enable us to gain insight into the molecular signatures associated with the disease that might help identify more potential genes contributing to enhanced risk for pancreatitis. All the genes associated with pancreatitis are generally associated with physiological function, and mutations causing loss of function, over or under expression leads to an ailment. Therefore, the present study attempts to envisage the molecular signature in a group of genes that lead to pancreatitis in case of malfunction.

Codon Usage is Influenced by Compositional Constraints in Genes Associated with Dementia

Dementia is a clinical syndrome characterized by progressive cognitive decline, and the symptoms could be gradual, persistent, and progressive. In the present study, we investigated 47 genes that have been linked to dementia. Compositional, selectional, and mutational forces were seen to be involved. Nucleotide components that influenced A- and GC-affected codon usages bias at all three codon positions. The influence of these two compositional constraints on codon usage bias (CUB) was positive for nucleotide A and negative for GC. Nucleotide A also experienced the highest mutational force, and GC-ending codons were preferred over AT-ending codons. A high bias toward GC-ending codons enhances the gene expression level, evidenced by the positive association between CAI- and GC-ending codons. Unusual behavior of the TTG codon showing an inverse relationship with the GC-ending codon and negative influence of gene expression, behavior contrary to all other GC-ending codons, shows an operative selectional force. Furthermore, parity analysis, higher translational selection value, preference of GC-ending codons over AT-ending codons, and association of gene length with gene expression refer to the dominant role of selection pressure with compositional constraint and mutational force-shaping codon usage.

Pan-cancer analyses of synonymous mutations based on tissue-specific codon optimality

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Developed tissue-specific codon optimality in 29 human tissues.

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Applied these to analyze synonymous mutations in ∼10,000 tumor and normal samples.

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Synonymous mutations frequently increase optimal codons in most cancer types.

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Synonymous mutations frequently increase optimal codons cell cycle-related genes.

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Frequency of optimal codon gain relates to proliferation, DDR deficiency, and survival.

Codon optimality has been demonstrated to be an important determinant of mRNA stability and expression levels in multiple model organisms and human cell lines. However, tissue-specific codon optimality has not been developed to investigate how codon optimality is usually perturbed by somatic synonymous mutations in human cancers. Here, we determined tissue-specific codon optimality in 29 human tissues based on mRNA expression data from the Genotype-Tissue Expression project. We found that optimal codons were associated with differentiation, whereas non-optimal codons were correlated with proliferation. Furthermore, codons biased toward differentiation displayed greater tissue specificity in codon optimality, and the tissue specificity of codon optimality was primarily present in amino acids with high degeneracy of the genetic code. By applying tissue-specific codon optimality to somatic synonymous mutations in 8532 tumor samples across 24 cancer types and to those in 416 normal cells across six human tissues, we found that synonymous mutations frequently increased optimal codons in tumor cells and cancer-related genes (e.g., genes involved in cell cycle). Furthermore, an elevated frequency of optimal codon gain was found to promote tumor cell proliferation in three cancer types characterized by DNA damage repair deficiency and could act as a prognostic biomarker for patients with triple-negative breast cancer. In summary, this study profiled tissue-specific codon optimality in human tissues, revealed alterations in codon optimality caused by synonymous mutations in human cancers, and highlighted the non-negligible role of optimal codon gain in tumorigenesis and therapeutics.

Binding sites of miRNA on the overexpressed genes of oral cancer using 7mer-seed match

The microRNAs having a length of ~ 19-22 nucleotides are the small, non-coding RNAs. The evolution of microRNAs in many disorders may hold the key to tackle complex challenges. Oral cancer belongs to the group of head and neck cancer. It occurs in the mouth region that appears as an ulcer. In this study, we collected information on the overexpressed genes of oral cancer. The coding sequences of the genes were derived from NCBI and the entire set of human microRNAs present in miRBASE 21 was retrieved. The human microRNAs that can target the overexpressed genes of oral cancer were determined with the aid of our in-house software. The interaction between microRNAs and the overexpressed genes was evaluated with 7mer-m8 model of microRNA targeting. The genes DKK1 and APLN paired with only one miRNA i.e., miR-447 and miR-6087, respectively. But the genes INHBA and MMP1 were found to be targeted by 2 miRNAs, while the genes FN1, FAP, TGFPI, COL4A1, COL4A2, and LOXL2 were found to be targeted by 16, 5, 9, 18, 29, and 11 miRNAs. Subsequently, several measures such as free energy, translation efficiency, and cosine similarity metric were used to estimate the binding process. It was found that the target region's stability was higher than the upstream and downstream zones. The overexpressed genes' GC contents were calculated, revealing that the codons in target miRNA region were overall GC rich as well as GC3 rich. Lastly, gene ontology was performed to better understand each gene's involvement in biological processes, molecular function, and cellular component. Our study showed the role of microRNAs in gene repression, which could possibly aid in the prognosis and diagnosis of oral cancer.

An interplay between compositional constraint and natural selection dictates the codon usage pattern among select Galliformes

Galliformes are believed to be the first avian order that started living in human association and became domesticated. Members of this order ranged from common to rare species. Next-generation sequencing has availed researchers with the whole genome sequences of five Galliformes; chicken, helmeted Guinea fowl, turkey, Japanese quail, and peafowl. Bioinformatic analysis based on codon usage, evolution, and species-specific functional enrichment can provide some crucial information aiding proper understanding of their genomic strategies. In this study, we investigated the genomic features of chicken, helmeted guinea fowl, turkey, and Japanese quail. Their genomes were AT biased although the potentially highly expressed genes contained more GC than AT. Cytosine dominated the third position of frequently used optimal codons. Mutational pressures in the analyzed Galliformes were in the range of 0.2-0.6%. Neutrality plot, translational selection index, and mutational responsive index indicated the dominance of selection pressure over mutational pressure among Galliformes. A pair of di-nucleotides, TpA and CpG, was found to be used less frequently than others in protein-coding genes since both of them are associated with the conversion of euchromatin to heterochromatin. Functional enrichment analysis revealed the dominance of proteins associated with fundamental biological processes. In turkey, chicken and helmeted Guinea fowl proteins with immunity-boosting capacity prevailed along with proteins needed for signal transduction and maintenance of central dogma. Evolutionary analysis indicated a bias towards synonymous substitution than non-synonymous mutation.

Understanding the codon usage patterns of mitochondrial CO genes among Amphibians

A universal phenomenon of using synonymous codons unequally in coding sequences known as codon usage bias (CUB) is observed in all forms of life. Mutation and natural selection drive CUB in many species but the relative role of evolutionary forces varies across species, genes and genomes. We studied the CUB in mitochondrial (mt) CO genes from three orders of Amphibia using bioinformatics approach as no work was reported yet. We observed that CUB of mt CO genes of Amphibians was weak across different orders. Order Caudata had higher CUB followed by Gymnophiona and Anura for all genes and CUB also varied across genes. Nucleotide composition analysis showed that CO genes were AT-rich. The AT content in Caudata was higher than that in Gymnophiona while Anura showed the least content. Multiple investigations namely nucleotide composition, correspondence analysis, parity plot analysis showed that the interplay of mutation pressure and natural selection caused CUB in these genes. Neutrality plot suggested the involvement of natural selection was more than the mutation pressure. The contribution of natural selection was higher in Anura than Gymnophiona and the lowest in Caudata. The codons CGA, TGA, AAA were found to be highly favoured by nature across all genes and orders.

Composition, codon usage pattern, protein properties, and influencing factors in the genomes of members of the family Anelloviridae

The present study was carried out on 62 genome sequences of members of the family Anelloviridae, as there have been no reports of genome analysis of these DNA viruses using a bioinformatics approach. The genes were found to be rich in AC content with low codon usage bias (CUB). Relative synonymous codon usage (RSCU) values identified the preferred codons for each amino acid in the family. The codon AGA was overrepresented, while the codons TCG, TTG, CGG, CGT, ACG, GCG and GAT were underrepresented in all of the genomes. A significant correlation was found between the effective number of codons (ENC) and base constraints, indicating that compositional properties might have influenced the CUB. A highly significant correlation was observed between the overall base content and the base content at the third codon position, indicating that mutations might have affected the CUB. A highly significant positive correlation was observed between GC12 and GC3 (r = 0.904, p < 0.01), which indicated that directional mutation pressure influenced all three codon positions. A neutrality plot revealed that the contribution of mutation and natural selection in determining the CUB was 58.6% and 41.4%, respectively.

Codon bias analyses on thyroid carcinoma genes

BACKGROUND

Thyroid carcinoma is one of the most common cancers in the world. Although the genetics of thyroid carcinoma was intensively studied, new mechanisms could be involved in its development as the codon bias. In this paper, we studied the codon bias of thyroid-cancer genes, considering not only the sequences but also the synonymous mutations.

METHODS

Different measures and statistical analyses were employed to characterize the thyroid-cancer genes. We considered classical measures as RSCU and ENC, the compositional and protein characteristics, but also the codon bias landscape via the %MinMax algorithm.

RESULTS

The compositional analyses highlighted two groups of thyroid cancer genes according to the GC% and GC3% content. The ENC did not show a clear codon bias in the genes. Differently, the RSCU analyses showed interesting codons that could play an important role in the development of thyroid cancer as the codon Ser-tcG. Furthermore, interesting synonymous mutations were detected that could affect the codon bias. The codon bias landscape detected genes enriched in rare codons as AKAP9 and KTN1. A cluster analysis based on %MinMax classified the thyroid cancer genes in four different groups according to the distribution of rare/frequent codons in the sequence.

CONCLUSIONS

This is the first study that analyzed the codon bias in thyroid cancer genes based also on synonymous mutations. This study provided different hints that should be further investigated by wet-lab validation and that it could open new scenarios in the understanding the molecular mechanisms involved in thyroid cancer development based on codon bias.

Codon usage signatures in the genus Cryptococcus: A complex interplay of gene expression, translational selection and compositional bias

The fungal genus Cryptococcus comprises of several diverse species. The pathogens forming Cryptococcus neoformans/ Cryptococcus gatti species complex are of immense clinical significance owing to the high frequency of infections and deaths globally. Three closely related non-pathogenic species namely, Cryptococcus amylolentus, Cryptococcus wingfieldii and Cryptococcus depauperatus are the non-pathogenic ancestral species from which pathogenic lineages have diverged. In the current study, a comprehensive analysis of factors influencing the codon and amino acid usage bias in six pathogenic and three non-pathogenic species was performed. Our results revealed that though compositional bias played a crucial role, translational selection and gene expression were the key determinants of codon usage variations. Analysis of relative dinucleotide abundance and codon context signatures revealed strict avoidance of TpA dinucleotide across genomes. Multivariate statistical analysis based on codon usage data resulted in discrete clustering of pathogens and non-pathogens which correlated with previous reports on their phylogenetic distribution.

A Crosstalk on Codon Usage in Genes Associated with Leukemia

Leukemia is the outcome of aggregation of damaged white blood cells. Several genes were reported to be associated with the pathogenesis of leukemia. These genes were computationally analyzed to decipher their codon usage bias (CUB) and to identify the prime factors influencing the codon usage profile as no work was reported yet. The mean values of synonymous codon usage order (SCUO) parameter indicated low CUB of the genes. Significant positive association of SCUO with overall GC and positional GCs might signal the presence of mutational pressure. However, neutrality plot suggested the dominant role of natural selection across the genes. Along with natural selection, the role of mutation pressure was also prominent and that might be responsible for lower CUB (SCUO = 0.19) of genes. Low translational speed might permit accuracy in the process. A strong inverse relationship of translational rate was observed with CUB of genes and folding energy.

Compositional Features and Codon Usage Pattern of Genes Associated with Anxiety in Human

Codon usage bias (CUB) is the unequal usage of synonymous codon; some codons are more preferred than others. CUB analysis has applications in understanding the molecular organization of genome, genetics, gene expression, and molecular evolution. Bioinformatic approach was used to analyze the protein-coding sequences of genes involved in the anxiety to understand the patterns of codon usage as no work was reported yet. The improved effective number of codons (Nc) values ranged from 43.55 to 55.06, with a mean of 44.57, suggested that the overall CUB was low for genes associated with anxiety. The overall GC and AT content was 54.76 and 45.24, respectively. Relative synonymous codon usage (RSCU) analysis revealed that most frequently used codon ended mostly with C or G. The over-represented codons in genes associated with anxiety were CTG, ATC, GTG, AGC, ACC, and GCC, while under-represented codons were TTA, CTT, CTA, ATA, GTT, GTA, TCG, CCG, GCG, CAA, and CGT. Correlation analysis was performed between overall nucleotide composition and its 3rd codon positions, and observed highly significant (p < 0.01) correlation between them suggested that both mutation pressure and natural selection might affect the pattern of CUB. The highly significant correlation (0.598**, p < 0.01) was also observed between GC12 with GC3 suggested that directional mutation pressure might acted on all codon positions for genes associated with anxiety.

Allele frequency analysis of GALC gene causing Krabbe disease in human and its codon usage

Krabbe disease is one of the rarest autosomal recessive disorders in human, caused by mutation in the GALC (β-galactosylceramidase) gene, resulting in several mental and physical health issues. Due to its rarity and phenotypic heterogeneity, diagnosis rate of this disease is very low. This study generated information on the recessive allele frequency dynamics of GALC gene across 15 global populations, with the highest frequency detected in Druze (Israel) population and the lowest frequency in Turkey and the United States. The recessive allele would take more time period (about 24,975 years) to be completely removed from the population having the lowest frequency and vice versa. The codon usage patterns of four isoforms of GALC gene revealed that a few synonymous codons were used more frequently than others in the isoforms. The codon AGA (arginine) was found to be overrepresented in GALC gene, except for galactocerebrosidase isoform a precursor. Further, GALC gene showed low codon usage bias (CUB) as evident from high ENC values (55.7-58.2), with A/T ending codons more preferred to G/C ending codons. CUB analysis elucidated the dual role of mutational pressure (major role) and natural selection (minor role) in GALC gene evolution.

Synonymous codon usage and context analysis of genes associated with pancreatic cancer

Pancreatic cancer is a fatal disorder which originates in pancreas. Its mortality rate is increasing with time. Some studies also reported that pancreatic cancer would be ranked 2nd by the year 2030. Codon usage bias (CUB) arises when synonymous codons for each amino acid are not used randomly in the coding sequences of genes. We used bioinformatic methods to analyze the compositional properties, codon context and codon usage trend of the genes associated with pancreatic cancer as no work was reported yet. From the base composition analysis, the pancreatic cancer genes were found to be GC-rich and at the 3rd codon position the G/C ending codons were more preferred to A/T ending ones. The CUB was low in genes associated with pancreatic cancer. Correspondence analysis proposed that other than base constraints, CUB might also be affected by some other factors such as natural selection. Moreover, results of correlation analysis indicated that CUB and various GC contents i.e. GC, GC1, GC2, GC3 played important role in the release of free energy by transcripts of the genes associated with pancreatic cancer. The low compAI values of coding sequences suggested a low translation rate of the genes.

Insights into the nucleotide composition and codon usage pattern of human tumor suppressor genes

Tumor suppressor genes encode different proteins that inhibit the uncontrolled proliferation of cell growth and tumor development. To acquire clues for predicting gene expression level, it is essential to understand the codon usage bias (CUB) of genes to characterize genome which possesses its own compositional characteristics and unique coding sequences. We used bioinformatic tools to analyze the codon usage patterns of 637 human tumor suppressor genes as no work was reported earlier. The mean effective number of codons of these genes was 48, indicating low CUB. Our results exhibited a significant positive correlation among different nucleotide compositions and the codons ending with C base was most frequently used along with the most over-represented codon CTG and GTG codifying leucine and valine amino acid, respectively, in human tumor suppressor genes. The neutrality plot showed a significant positive correlation (Pearson, r = 0. 646; P < .01) suggesting that mutation on GC bias might affect the CUB. However, the linear regression coefficient of GC₁₂ on GC₃ in human tumor suppressor genes suggested that natural selection played a major role while mutation pressure played a minor role in the codon usage patterns of tumor suppressor genes in human. Our study would throw light into the factors that affect CUB and the codon usage patterns in the human tumor suppressor genes.

Compositional features and codon usage pattern of TP63 gene

The tumor protein p63encoded by the gene TP63 acts as a homologue of p53 protein. TP63 gene is the transformation factor with two initiation sites for transcriptional process and is related with stress, signal transduction and cell cycle control. The biasness in the preference of a few codons more frequently over other synonymous codons is the codon usage bias (CUB). Natural selection and mutational pressure are the two prime evolutionary forces acting on CUB. Here, the bioinformatic based analysis was performed to investigate the base distribution and CUB of TP63transcript variants (isoforms) as no work was performed earlier. Analysis of compositional features revealed variation in base content across TP63 gene isoforms and the GC content was more than 50%, indicating GC richness of its isoforms. The mean effective number of codons (ENC), a measure of CUB, was 51.83, i.e. overall CUB of TP63 gene was low. Among 13 isoforms of TP63 gene, nature selected against the CTA codon in 8 isoforms and favored five over-represented (RSCU > 1.6) codons namely CTG, CAG, ATC, AAC and GCC during evolution. Correlation between overall nucleotide composition and its 3rd codon position revealed that both mutational pressure and natural selection moulded its CUB. Further, the correlation between ENC and aromaticity depicted that variation of CUB was related to the degree of aromaticity of p63 protein.