Catalog of genetic variants within mature microRNA seed regions in chicken

Comparative Analysis of Published Database Predicting MicroRNA Binding in 3'UTR of mRNA in Diverse Species

BACKGROUND

Micro-RNAs are endogenous non-coding RNA moieties of 22-27 nucleotides that play a crucial role in the regulation of various biological processes and make them useful prognostic and diagnostic biomarkers. Discovery and experimental validation of miRNA is a laborious and time-consuming process. For early prediction, multiple bioinformatics databases are available for miRNA target prediction; however, their utility can confuse amateur researchers in selecting the most appropriate tools for their study.

OBJECTIVE

This descriptive review aimed to analyse the usability of the existing database based on the following criteria: accessibility, efficiency, interpretability, updatability, and flexibility for miRNA target prediction of 3'UTR of mRNA in diverse species so that the researchers can utilize the database most appropriate to their research.

METHODS

A systematic literature search was performed in PubMed, Google Scholar and Scopus databases up to November 2022. ≥10,000 articles found online, including ⁓130 miRNA tools, which contain various information on miRNA. Out of them, 31 databases that provide information on validated 3'UTR miRNAs target databases were included and analysed in this review.

RESULTS

These miRNA database tools are being used in varied areas of biological research to select the most suitable miRNA for their experimental validation. These databases, updated until the year 2021, consist of miRNA-related data from humans, animals, mice, plants, viruses etc. They contain 525-29806351 data entries, and information from most databases is freely available on the online platform.

CONCLUSION

Reviewed databases provide significant information, but not all information is accurate or up-to-date. Therefore, Diana-TarBase and miRWalk are the most comprehensive and up-to-date databases.

Clinical Implications of Necroptosis Genes Expression for Cancer Immunity and Prognosis: A Pan-Cancer Analysis

Background

Necroptosis, a form of programmed cell death, is increasingly being investigated for its controversial role in tumorigenesis and progression. Necroptosis suppresses tumor formation and tumor development by killing tumor cells; however, the necrotic cells also promote tumor formation and tumor development via the immunosuppressive effect of necroptosis and inflammatory response caused by cytokine release. Thus, the exact mechanism of necroptosis in pan-cancer remains unknown.

Methods

The data of 11,057 cancer samples were downloaded from the TCGA database, along with clinical information, tumor mutation burden, and microsatellite instability information of the corresponding patients. We used the TCGA data in a pan-cancer analysis to identify differences in mRNA level as well as single nucleotide variants, copy number variants, methylation profiles, and genomic signatures of miRNA-mRNA interactions. Two drug datasets (from GDSC, CTRP) were used to evaluate drug sensitivity and resistance against necroptosis genes.

Results

Necroptosis genes were aberrantly expressed in various cancers. The frequency of necroptosis gene mutations was highest in lung squamous cell carcinoma. Furthermore, the correlation between necroptosis gene expression in the tumor microenvironment and immune cell infiltration varied for different cancers. High necroptosis gene expression was found to correlate with NK, Tfh, Th1, CD8_T, and DC cells. These can therefore be used as biomarkers to predict prognosis. By matching gene targets with drugs, we identified potential candidate drugs.

Conclusion

Our study showed the genomic alterations and clinical features of necroptosis genes in 33 cancers. This may help clarify the link between necroptosis and tumorigenesis. Our findings may also provide new approaches for the clinical treatment of cancer.

Muscle transcriptome signature and gene regulatory network analysis in two divergent lines of a hilly bovine species Mithun (Bos frontalis)

A massive bovine, Bos frontalis, also known as Mithun or Gayal, found at higher altitude is very promising meat and milk animal. For candidate gene and marker discovery, RNA-seq data was generated from longissimus dorsi muscle tissues with Illumina-HiSeq. Such markers can be used in future for genetic gain of traits like feed conversion efficiency (FCE) and average daily gain (ADG). Analysis revealed 297differentially expressed genes (DEGs) having 173 up and 124 down-regulated unigenes. Extensive conservation was found in genic region while comparing with Bos taurus. Analysis revealed 57 pathways having 112 enzymes, 72 transcriptional factors and cofactors, 212 miRNAs regulating 71 DEGs, 25,855 SSRs, mithun-specific 104,822 variants and 7288 indels, gene regulatory network (GRN) having 24 hub-genes and transcriptional factors regulating cell proliferation, immune tolerance and myogenesis. This is first report of muscle transcriptome depicting candidate genes with GRN controlling FCE and ADG. Reported putative molecular markers, candidate genes and hub proteins can be valuable genomic resources for association studies in genetic improvement programme.

MicroRNA Polymorphisms in Cancer: A Literature Analysis

Single nucleotide polymorphisms (SNPs) located in microRNA (miRNA) genes (miR-SNPs) have attracted increasing attention in recent years due to their involvement in the development of various types of cancer. Therefore, a systematic review on this topic was needed. From 55 scientific publications we collected 20 SNPs, which are located within 18 miRNA encoding genes and have been associated with 16 types of cancer. Among 20 miRNA gene polymorphisms 13 are located within the premature miRNA region, five within mature, and two within mature seed miRNA region. We graphically visualized a network of miRNA-cancer associations which revealed miRNA genes and cancer types with the highest number of connections. Our study showed that, despite a large number of variations currently known to be located within miRNA genes in humans, most of them have not yet been tested for association with cancer. MicroRNA SNPs collected in this study represent only 0.43% of known miRNA gene variations (20/4687). Results of the present study will be useful to researchers investigating the clinical use of miRNAs, such as the roles of miRNAs as diagnostic markers and therapeutic targets.