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.

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.

The basic sequence features were analysed that influence gene expression via codon usage bias of the selected forty coding sequences of Homo sapiens in a simple prokaryotic model i.e. E. coli K-12 genome. The prime objective was to elucidate the interrelationships among tRNA gene copy numbers, synonymous codons, amino acids and translational efficiency using tRNA adaptation index. It was evident from RSCU scores and principal component analysis, that only those preferred codons were used by the isoacceptor tRNAs that had G and C base at their third codon position. Relationship between tRNA adaptation index and amino acids, revealed that valine, arginine, serine and isoleucine showed significant positive correlation with gene expression. Therefore, it could be inferred that GC content in these genes might have the major role in shaping the codon bias and affecting the translational efficiency of the coding sequences.

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.