DOI: 10.37421/1747-0862.2022.16.562
Endogenous tiny non-coding RNAs called microRNAs (miRNAs) control the expression of genes. Several mechanisms, including miRNA gene amplification or deletion, improper miRNA transcriptional control, dysregulated epigenetic alterations, and flaws in the miRNA biogenesis machinery, have been shown to contribute to the dysregulation of miRNA expression in human cancer. Under specific circumstances, miRNAs can act as tumour suppressors or oncogenes. The hallmarks of cancer, such as maintaining proliferative signalling, dodging growth inhibitors, resisting cell death, triggering invasion and metastasis, and generating angiogenesis, have been linked to the dysregulated miRNAs. MiRNAs have been implicated in an increasing number of studies as possible biomarkers for human cancer diagnosis, prognosis, and treatment targets or tools; nevertheless, further research and validation are required. In this review, we emphasise how miRNAs function as tumour suppressors or oncogenes to control the emergence of human cancers.
DOI: 10.37421/1747-0862.2022.16.563
DOI: 10.37421/1747-0862.2022.16.564
Mutations are crucial building blocks for evolution, and population genetics is key to our knowledge of it. This overview is meant to serve as a preface to the subsequent, more in-depth papers. We review the state-of-the-art understanding of mutation rates and both their detrimental and advantageous effects on fitness, and we then take a look at ideas that forecast the outcome of specific mutations or the effects of mutation accumulation for quantitative features. Numerous advancements in the past relied on models that treated the evolution of mutations at each DNA site separately, ignoring how sites on chromosomes are linked together and how effects from different sites interact (epistasis). This study examines previous research that attempts to forecast how mutations may interact. Many fundamental and practical problems can be answered by having a solid understanding of the population genetics of both individual locus mutations and features influenced by multiple loci.
DOI: 10.37421/1747-0862.2022.16.565
DOI: 10.37421/1747-0862.2022.16.566
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