Interplay between circular RNA, microRNA, and human diseases.

Circular RNAs (circRNAs) are endogenous RNA formed by the back splicing process. They are ubiquitous, stable, evolutionally conserved, and are tissue-specific. The biochemical and molecular features of circRNAs hold the potential to be used as biomarkers in various diseases to achieve pharmacological goals. CircRNAs have numerous latent modes of action, from acting as sponges for microRNAs and RNA binding proteins to serve as transcriptional regulators, epigenetic alterations, etc. Dysregulated functioning of several circular RNAs lead to the progression of a plethora of diseases. Due to their extremely stable nature and amazing tissue specificity, circRNAs have paved the way for advanced clinical studies as a novel method of early disease detection and treatment efficacy. Therefore, they have been recognized as a latent diagnostic biomarker for neurodegenerative diseases, diabetes, osteoarthritis, and cardiovascular diseases.

Circular RNAs in cancer and diabetes.

Circular RNAs (circRNAs) are a class of noncoding RNA molecules formed by the back splicing process. Compared to linear mRNA molecules they are more stable. CircRNA acts as miRNA sponges, regulates translation, epigenetic alterations, etc. However, the most significant aspect of circRNAs has been its role in regulating the hallmark of cancer and diabetes mellitus. Several circRNAs are extensively expressed in individuals with cancer and diabetics. Dysregulated expression of various circRNAs plays a crucial part in the development of type 2 diabetes mellitus. In the present review, we present the current understanding of cricRNAs biogenesis, regulatory mechanisms, reviews of recent findings and circRNA as potential biomarker.

Analysis of single nucleotide polymorphisms between 2019-nCoV genomes and its impact on codon usage.

The spread of SARS-CoV-2 is a global concern that has taken a toll on entire human health. Researchers across the globe have been working in devising the strategies to combat this dreadful disease. Studies focused on genetic variability help design effective drugs and vaccines. Considering this, the present study entails the information regarding the genome-wide mutations detected in the 108 SARS CoV-2 genomes worldwide. We identified a few hypervariable regions localized in orf1ab, spike, and nucleocapsid gene. These nucleotide polymorphisms demonstrated their effect on both codon usage as well as amino acid usage pattern. Altogether the present study provides valuable information that would be helpful to ongoing research on 2019-nCoV vaccine development.

Linking gut microbiota with the human diseases.

The human gut is rich in microbes. Therefore, it is of interest to document data to link known human diseases with the gut microbiota. Various factors like hormones, metabolites and dietary habitats are responsible for shaping the microbiota of the gut. Imbalance in the gut microbiota is responsible for the pathogenesis of various disease types including rheumatoid arthritis, different types of cancer, diabetes mellitus, obesity, and cardiovascular disease. We report a review of known data for the correction of dysbiosis (imbalance in microbe population) towards improved human health.

Genetic evolution and codon usage analysis of NKX-2.5 gene governing heart development in some mammals.

NKX-2.5 gene is responsible for cardiac development and its targeted disruption apprehends cardiac development at the linear heart tube stage. Bioinformatic analysis was employed to investigate the codon usage pattern and dN/dS of mammalian NKX-2.5 gene. The relative synonymous codon usage analysis revealed variation in codon usage and two synonymous codons namely ATA (Ile) and GTA (Val) were absent in NKX-2.5 gene across selected mammalian species suggesting that these two codons were possibly selected against during evolution. Parity rule 2 analysis of two and four fold amino acids showed CT bias whereas six-fold amino acids revealed GA bias. Neutrality analysis suggests that selection played a prominent role while mutation had a minor role. The dN/dS analysis suggests synonymous substitution played a significant role and it negatively correlated with p-distance of the gene. Purifying natural selection played a dominant role in the genetic evolution of NKX-2.5 gene in mammals.

The significance of gene mutations across eight major cancer types.

Mutations occur spontaneously, which can be induced by either chemicals (e.g. benzene) or biological factors (e.g. virus). Not all mutations cause noticeable changes in cellular functions. However, mutation in key cellular genes leads to developmental disorders. It is one of the main ways in which proto-oncogenes can be changed into their oncogenic state. The progressive accumulation of multiple mutations throughout life leads to cancer. In the past few decades, extensive research on cancer biology has discovered many genes and pathways having role in cancer development. In this review, we tried to summarize the current knowledge of mutational effect on different cancer types and its consequences in brief for future reference and guidance of researchers in cancer biology.

A review on coronary artery disease, its risk factors, and therapeutics.

Coronary artery disease (CAD) is one of the major cardiovascular diseases affecting the global human population. This disease has been proved to be the major cause of death in both the developed and developing countries. Lifestyle, environmental factors, and genetic factors pose as risk factors for the development of cardiovascular disease. The prevalence of risk factors among healthy individuals elucidates the probable occurrence of CAD in near future. Genome-wide association studies have suggested the association of chromosome 9p21.3 in the premature onset of CAD. The risk factors of CAD include diabetes mellitus, hypertension, smoking, hyperlipidemia, obesity, homocystinuria, and psychosocial stress. The eradication and management of CAD has been established through extensive studies and trials. Antiplatelet agents, nitrates, ß-blockers, calcium antagonists, and ranolazine are some of the few therapeutic agents used for the relief of symptomatic angina associated with CAD.

Compositional bias coupled with selection and mutation pressure drives codon usage in Brassica campestris genes.

The plant Brassica campestris includes the vegetables turnip and Chinese cabbage, important plants of economic importance. Here, we have analysed the codon usage bias of B. campestris for 116 protein coding genes. Neutrality analysis showed that B. campestris had a wide range of GC3s, and a significant correlation was observed between GC12 and GC3. Nc versus GC3s plot showed a few genes on or proximate to the expected curve, but the majority of points were found to be scattered distantly from the expected curve. Correspondence analysis on codon usage revealed that the position preference of codons on multidimensional space totally depends on the presence of A and T at synonymous third codon position. These results altogether suggest that composition bias along with selection (major) and mutation pressure (minor) affects the codon usage pattern of the protein coding genes in Brassica campestris.

Codon usage vis-a-vis start and stop codon context analysis of three dicot species.

To understand the variation in genomic composition and its effect on codon usage, we performed the comparative analysis of codon usage and nucleotide usage in the genes of three dicots, Glycine max, Arabidopsis thaliana and Medicago truncatula. The dicot genes were found to be A/T rich and have predominantly A-ending and/or T-ending codons. GC3s directly mimic theusage pattern of global GC content. Relative synonymous codon usage analysis suggests that the high usage frequency of A/T over G/C mononucleotide containing codons in AT-rich dicot genome is due to compositional constraint as a factor of codon usage bias. Odds ratio analysis identified the dinucleotides TpG, TpC, GpA, CpA and CpT as over-represented, where, CpG and TpA as under-represented dinucleotides. The results of (NcExp-NcObs)/NcExp plot suggests that selection pressure other than mutation played a significant role in influencing the pattern of codon usage in these dicots. PR2 analysis revealed the significant role of selection pressure on codon usage. Analysis of varience on codon usage at start and stop site showed variation in codon selection in these sites. This study provides evidence that the dicot genes were subjected to compositional selection pressure.

Interplay between miRNAs and human diseases.

MicroRNAs (miRNAs) are endogenous, non-coding RNAs, which have evoked a great deal of interest due to their importance in many aspects of homeostasis and diseases. MicroRNAs are stable and are essential components of gene regulatory networks. They play a crucial role in healthy individuals and their dysregulations have also been implicated in a wide range of diseases, including diabetes, cardiovascular disease, kidney disease, and cancer. This review summarized the current understanding of interactions between miRNAs and different diseases and their role in disease diagnosis and therapy.

Nasopharyngeal carcinoma: understanding its molecular biology at a fine scale.

Among all cancers, the incidence of nasopharyngeal carcinoma (NPC) is quite high in the endemic regions. NPC is a head and neck cancer with poor survival rate, and is rare throughout most of the world but common in certain geographic areas, like southern Asia and some regions of North East India (Nagaland, Manipur, and Mizoram). A clear understanding of its etiology is still lacking, but NPC is widely suspected to be the result of both genetic susceptibility and exposure to environmental factors or Epstein-Barr virus infection. Diagnosis in the early stages needs a high index of clinical acumen, and, although most cross-sectional imaging investigations show the tumor with precision, confirmation is dependent on histology. This article reviews all related research reports on NPC histopathological classifications worldwide that have been published within the past 20 years. Genome-wide association studies suggested that there might be common disease mechanisms between that disease and NPC. Personalized management rules, quality assessment of life in patients, and an understanding of the essential mechanisms of recurrence could be directed toward research into recurrent NPC. Hence, this literature would offer otolaryngologists a deeper insight into the etiological and management aspects of NPC.

Codon usage and expression level of human mitochondrial 13 protein coding genes across six continents.

The study of codon usage coupled with phylogenetic analysis is an important tool to understand the genetic and evolutionary relationship of a gene. The 13 protein coding genes of human mitochondria are involved in electron transport chain for the generation of energy currency (ATP). However, no work has yet been reported on the codon usage of the mitochondrial protein coding genes across six continents. To understand the patterns of codon usage in mitochondrial genes across six different continents, we used bioinformatic analyses to analyze the protein coding genes. The codon usage bias was low as revealed from high ENC value. Correlation between codon usage and GC3 suggested that all the codons ending with G/C were positively correlated with GC3 but vice versa for A/T ending codons with the exception of ND4L and ND5 genes. Neutrality plot revealed that for the genes ATP6, COI, COIII, CYB, ND4 and ND4L, natural selection might have played a major role while mutation pressure might have played a dominant role in the codon usage bias of ATP8, COII, ND1, ND2, ND3, ND5 and ND6 genes. Phylogenetic analysis indicated that evolutionary relationships in each of 13 protein coding genes of human mitochondria were different across six continents and further suggested that geographical distance was an important factor for the origin and evolution of 13 protein coding genes of human mitochondria.

Codon usage and amino acid usage influence genes expression level.

Highly expressed genes in any species differ in the usage frequency of synonymous codons. The relative recurrence of an event of the favored codon pair (amino acid pairs) varies between gene and genomes due to varying gene expression and different base composition. Here we propose a new measure for predicting the gene expression level, i.e., codon plus amino bias index (CABI). Our approach is based on the relative bias of the favored codon pair inclination among the genes, illustrated by analyzing the CABI score of the Medicago truncatula genes. CABI showed strong correlation with all other widely used measures (CAI, RCBS, SCUO) for gene expression analysis. Surprisingly, CABI outperforms all other measures by showing better correlation with the wet-lab data. This emphasizes the importance of the neighboring codons of the favored codon in a synonymous group while estimating the expression level of a gene.

Cytochrome P450 genes in coronary artery diseases: Codon usage analysis reveals genomic GC adaptation.

Establishing codon usage biases are imperative for understanding the etiology of coronary artery diseases (CAD) as well as the genetic factors associated with these diseases. The aim of this study was to evaluate the contribution of 18 responsible cytochrome P450 (CYP) genes for the risk of CAD. Effective number of codon (Nc) showed a negative correlation with both GC3 and synonymous codon usage order (SCUO) suggesting an antagonistic relationship between codon usage and Nc of genes. The dinucleotide analysis revealed that CG and TA dinucleotides have the lowest odds ratio in these genes. Principal component analysis showed that GC composition has a profound effect in separating the genes along the first major axis. Our findings revealed that mutational pressure and natural selection could possibly be the major factors responsible for codon bias in these genes. The study not only offers an insight into the mechanisms of genomic GC adaptation, but also illustrates the complexity of CYP genes in CAD.

Recombination hotspots: Models and tools for detection.

Recombination hotspots are the regions within the genome where the rate, and the frequency of recombination are optimum with a size varying from 1 to 2kb. The recombination event is mediated by the double-stranded break formation, guided by the combined enzymatic action of DNA topoisomerase and Spo 11 endonuclease. These regions are distributed non-uniformly throughout the human genome and cause distortions in the genetic map. Numerous lines of evidence suggest that the number of hotspots known in humans has increased manifold in recent years. A few facts about the hotspot evolutions were also put forward, indicating the differences in the hotspot position between chimpanzees and humans. In mice, recombination hot spots were found to be clustered within the major histocompatibility complex (MHC) region. Several models, that help explain meiotic recombination has been proposed. Moreover, scientists also developed some computational tools to locate the hotspot position and estimate their recombination rate in humans is of great interest to population and medical geneticists. Here we reviewed the molecular mechanisms, models and in silico prediction techniques of hot spot residues.

Allele frequency for Cystic fibrosis in Indians vis-a/-vis global populations.

Cystic fibrosis (CF) is an autosomal recessive disease caused by mutations in the cystic fibrosis transmembrane conductance regulator gene. This gene encodes a protein involved in epithelial anion channel. Cystic fibrosis is the most common life-limiting genetic disorder in Caucasians; it also affects other ethnic groups like the Blacks and the Native Americans. Cystic fibrosis is considered to be rare among individuals from the Indian subcontinent. We analyzed a total of 29 world׳s populations for cystic fibrosis on the basis of gene frequency and heterozygosity. Among 29 countries Switzerland revealed the highest gene frequency and heterozygosity for CF (0.022, 0.043) whereas Japan recorded the lowest values (0.002, 0.004) followed by India (0.004, 0.008). Our analysis suggests that the prevalence of cystic fibrosis is very low in India.

A cross talk between codon usage bias in human oncogenes.

BACKGROUND: Oncogenes are the genes that have the potential to induce cancer. The extent and origin of codon usage bias is an important indicator of the forces shaping genome evolution in living organisms. RESULTS: We observed moderate correlations between gene expression as measured by CAI and GC content at any codon site. The findings of our results showed that there is a significant positive correlation (Spearman's r= 0.45, P<0.01) between GC content at first and second codon position with that of third codon position. Further, striking negative correlation (r = -0.771, P < 0.01) between ENC with the GC3s values of each gene and positive correlation (r=0.644, P<0.01) in between CAI and ENC was also observed. CONCLUSIONS: The mutation pressure is the major determining factor in shaping the codon usage pattern of oncogenes rather than natural selection since its effects are present at all codon positions. The results revealed that codon usage bias determines the level of oncogene expression in human. Highly expressed oncogenes had rich GC contents with high degree of codon usage bias.

Computational prediction of submergence responsive microRNA and their binding position within the genome of Oryza sativa.

BACKGROUND: MicroRNAs (miRNAs) are small noncoding RNAs which play crucial role in response to the adverse biotic and abiotic stress conditions at the post transcriptional level. The functions of the miRNAs are generally based on complementarity to their target region. RESULTS: We used the online tool psRNA Target for the identification of submergence responsive miRNA using the gene expression profile related to the submergence condition. We wrote a perl script for the prediction of miRNA target gene. The position based feature of the script increases the overall specificity of the program. Our perl script performed well on the genomic data of Oryza sativa and produced significant results with their positions. These results were analyzed on the basis of complementarity and the statistical scores are used to find out the most probable binding regions. These predicted binding regions are aligned with their respective miRNAs to find out the consensus sequence. We scored the alignment using a position dependent, mismatch penalty system. We also identified the rate of conservation of bases at a particular position for all the predicted binding regions and it was found that all the predicted binding regions maintain above 70% rate of conservation of bases. CONCLUSION: Our approach provides a novel framework for screening the genome of Oryza sativa. It can be broadly applied to identify complementarity specific miRNA targets computationally by doing a little modification of the script depending on the type of the miRNA.