A novel miRNA analysis framework to analyze differential biological networks

In silico Identification of miRNAs and Their Targets in Cluster Bean for Their Role in Development and Physiological Responses

Cluster bean popularly known as “guar” is a drought-tolerant, annual legume that has recently emerged as an economically important crop, owing to its high protein and gum content. The guar gum has wide range of applications in food, pharma, and mining industries. India is the leading exporter of various cluster bean-based products all across the globe. Non-coding RNAs (miRNAs) are involved in regulating the expression of the target genes leading to variations in the associated pathways or final protein concentrations. The understanding of miRNAs and their associated targets in cluster bean is yet to be used to its full potential. In the present study, cluster bean EST (Expressed Sequence Tags) database was exploited to identify the miRNA and their predicted targets associated with metabolic and biological processes especially response to diverse biotic and abiotic stimuli using in silico approach. Computational analysis based on cluster bean ESTs led to the identification of 57 miRNAs along with their targets. To the best of our knowledge, this is the first report on identification of miRNAs and their targets using ESTs in cluster bean. The miRNA related to gum metabolism was also identified. Most abundant miRNA families predicted in our study were miR156, miR172, and miR2606. The length of most of the mature miRNAs was found to be 21nt long and the range of minimal folding energy (MFE) was 5.8–177.3 (−kcal/mol) with an average value of 25.4 (−kcal/mol). The identification of cluster bean miRNAs and their targets is predicted to hasten the miRNA discovery, resulting in better knowledge of the role of miRNAs in cluster bean development, physiology, and stress responses.

Plant RNA-mediated gene regulatory network

Not all transcribed RNAs are protein-coding RNAs. Many of them are non-protein-coding RNAs in diverse eukaryotes. However, some of them seem to be non-functional and are resulted from spurious transcription. A lot of non-protein-coding transcripts have a significant function in the translation process. Gene expressions depend on complex networks of diverse gene regulatory pathways. Several non-protein-coding RNAs regulate gene expression in a sequence-specific system either at the transcriptional level or post-transcriptional level. They include a significant part of the gene expression regulatory network. RNA-mediated gene regulation machinery is evolutionarily ancient. They well-evolved during the evolutionary time and are becoming much more complex than had been expected. In this review, we are trying to summarizing the current knowledge in the field of RNA-mediated gene silencing.

MicroRNAs signatures, bioinformatics analysis of miRNAs, miRNA mimics and antagonists, and miRNA therapeutics in osteosarcoma

MicroRNAs (miRNAs) involved in key signaling pathways and aggressive phenotypes of osteosarcoma (OS) was discussed, including PI3K/AKT/MTOR, MTOR AND RAF-1 signaling, tumor suppressor P53- linked miRNAs, NOTCH- related miRNAs, miRNA -15/16 cluster, apoptosis related miRNAs, invasion-metastasis-related miRNAs, and 14Q32-associated miRNAs cluster. Herrin, we discussed insights into the targeted therapies including miRNAs (i.e., tumor-suppressive miRNAs and oncomiRNAs). Using bioinformatics tools, the interaction network of all OS-associated miRNAs and their targets was also depicted.

Identification and Annotation of Potential Function of Regulatory Antisense Long Non-Coding RNAs Related to Feed Efficiency in Bos taurus Bulls

Long non-coding RNAs (lncRNAs) can influence transcriptional and translational processes in mammalian cells and are associated with various developmental, physiological and phenotypic conditions. However, they remain poorly understood and annotated in livestock species. We combined phenotypic, metabolomics and liver transcriptomic data of bulls divergent for residual feed intake (RFI) and fat accretion. Based on a project-specific transcriptome annotation for the bovine reference genome ARS-UCD.1.2 and multiple-tissue total RNA sequencing data, we predicted 3590 loci to be lncRNAs. To identify lncRNAs with potential regulatory influence on phenotype and gene expression, we applied the regulatory impact factor algorithm on a functionally prioritized set of loci (n = 4666). Applying the algorithm of partial correlation and information theory, significant and independent pairwise correlations were calculated and co-expression networks were established, including plasma metabolites correlated with lncRNAs. The network hub lncRNAs were assessed for potential cis-actions and subjected to biological pathway enrichment analyses. Our results reveal a prevalence of antisense lncRNAs positively correlated with adjacent protein-coding genes and suggest their participation in mitochondrial function, acute phase response signalling, TCA-cycle, fatty acid β-oxidation and presumably gluconeogenesis. These antisense lncRNAs indicate a stabilizing function for their cis-correlated genes and a putative regulatory role in gene expression.

Legionnaires’ Disease: State of the Art Knowledge of Pathogenesis Mechanisms of Legionella

Legionella species are environmental gram-negative bacteria able to cause a severe form of pneumonia in humans known as Legionnaires’ disease. Since the identification of Legionella pneumophila in 1977, four decades of research on Legionella biology and Legionnaires’ disease have brought important insights into the biology of the bacteria and the molecular mechanisms that these intracellular pathogens use to cause disease in humans. Nowadays, Legionella species constitute a remarkable model of bacterial adaptation, with a genus genome shaped by their close coevolution with amoebae and an ability to exploit many hosts and signaling pathways through the secretion of a myriad of effector proteins, many of which have a eukaryotic origin. This review aims to discuss current knowledge of Legionella infection mechanisms and future research directions to be taken that might answer the many remaining open questions. This research will without a doubt be a terrific scientific journey worth taking.

An integrative approach to develop computational pipeline for drug-target interaction network analysis

Understanding the general principles governing the functioning of biological networks is a major challenge of the current era. Functionality of biological networks can be observed from drug and target interaction perspective. All possible modes of operations of biological networks are confined by the interaction analysis. Several of the existing approaches in this direction, however, are data-driven and thus lack potential to be generalized and extrapolated to different species. In this paper, we demonstrate a systems pharmacology pipeline and discuss how the network theory, along with gene ontology (GO) analysis, co-expression analysis, module re-construction, pathway mapping and structure level analysis can be used to decipher important properties of biological networks with the aim to propose lead molecule for the therapeutic interventions of various diseases.

Comparative de novo transcriptome analysis of male and female Sea buckthorn

Sea buckthorn is a dioecious medicinal plant found at high altitude. The plant has both male and female reproductive organs in separate individuals. In this article, whole transcriptome de novo assemblies of male and female flower bud samples were carried out using Illumina NextSeq 500 platform to determine the role of the genes involved in sex determination. Moreover, genes with differential expression in male and female transcriptomes were identified to understand the underlying sex determination mechanism. The current study showed 63,904 and 62,272 coding sequences (CDS) in female and male transcriptome data sets, respectively. 16,831 common CDS were screened out from both transcriptomes, out of which 625 were upregulated and 491 were found to be downregulated. To understand the potential regulatory roles of differentially expressed genes in metabolic networks and biosynthetic pathways: KEGG mapping, gene ontology, and co-expression network analysis were performed. Comparison with Flowering Interactive Database (FLOR-ID) resulted in eight differentially expressed genes viz. CHD3-type chromatin-remodeling factor PICKLE (PKL), phytochrome-associated serine/threonine-protein phosphatase (FYPP), protein TOPLESS (TPL), sensitive to freezing 6 (SFR6), lysine-specific histone demethylase 1 homolog 1 (LDL1), pre-mRNA-processing-splicing factor 8A (PRP8A), sucrose synthase 4 (SUS4), ubiquitin carboxyl-terminal hydrolase 12 (UBP12), known to be broadly involved in flowering, photoperiodism, embryo development, and cold response pathways. Male and female flower bud transcriptome data of Sea buckthorn may provide comprehensive information at genomic level for the identification of genetic regulation involved in sex determination.