To study complex biological processes holistically, it is imperative to take an integrative approach that combines multi-omics data to highlight the interrelationships of the involved biomolecules and their functions. With the advent of high-throughput techniques and availability of multi-omics data generated from a large set of samples, several promising tools and methods have been developed for data integration and interpretation. In this review, we collected the tools and methods that adopt integrative approach to analyze multiple omics data and summarized their ability to address applications such as disease subtyping, biomarker prediction, and deriving insights into the data. We provide the methodology, use-cases, and limitations of these tools; brief account of multi-omics data repositories and visualization portals; and challenges associated with multi-omics data integration.

Graphical Abstract Highlights d Anticipatory hepatic fed miRNAs are essential to attenuating fasting response d RISC association of miRNA-mRNA pairs oscillates during fed-fast cycles in the liver d Convergent additive action of miRNAs governs metabolic and mitochondrial homeostasis d Scavenging fed miRNAs impairs refed transition and affects whole-body energetics SUMMARY Inability to mediate fed-fast transitions in the liver is known to cause metabolic dysfunctions and diseases. Intuitively, a failure to inhibit futile translation of state-specific transcripts during fed-fast cycles would abrogate dynamic physiological transitions.Here, we have discovered hepatic fed microRNAs that target fasting-induced genes and are essential for a refed transition. Our findings highlight the role of these fed microRNAs in orchestrating system-level control over liver physiology and whole-body energetics. By targeting SIRT1, PGC1a, and their downstream genes, fed microRNAs regulate metabolic and mitochondrial pathways. MicroRNA expression, processing, and RISC loading oscillate during these cycles and possibly constitute an anticipatory mechanism. Fed-microRNA oscillations are deregulated during aging. Scavenging of hepatic fed microRNAs causes uncontrolled gluconeogenesis and failure in the catabolic-to-anabolic switching upon feeding, which are hallmarks of metabolic diseases. Besides identifying mechanisms that enable efficient physiological toggling, our study highlights fed microRNAs as candidate therapeutic targets.

Transcriptome, the functional element of the genome, is comprised of different kinds of RNA molecules such as mRNA, miRNA, ncRNA, rRNA, and tRNA to name a few. Each of these RNA molecules plays a vital role in the physiological response, and understanding the regulation of these molecules is extremely critical for the better understanding of the functional genome. RNA Sequencing (RNASeq) is one of the latest techniques applied to study genome-wide transcriptome characterization and profiling using high-throughput sequenced data. As compared to array-based methods, RNASeq provides in-depth and more precise information on transcriptome characterization and quantification. Based upon availability of reference genome, transcriptome assembly can be referenceguided or de novo. Once transcripts are assembled, downstream analysis such as expression profiling, gene ontology, and pathway enrichment analyses can give more insight into gene regulation. This chapter describes the significance of RNASeq study over arraybased traditional methods, approach to analyze RNASeq data, available methods and tools, challenges associated with the data analysis, application areas, some of the recent advancement made in the area of transcriptome study and its application.

We have carried out weighted gene co-expression network analysis of Mycobacterium tuberculosis to gain insights into gene expression architecture during log phase growth. The differentially expressed genes between at least one pair of 11 different M. tuberculosis strains as source of biological variability were used for co-expression network analysis. This data included genes with highest coefficient of variation in expression. Five distinct modules were identified using topological overlap based clustering. All the modules together showed significant enrichment in biological processes: fatty acid biosynthesis, cell membrane, intracellular membrane bound organelle, DNA replication, Quinone biosynthesis, cell shape and peptidoglycan biosynthesis, ribosome and structural constituents of ribosome and transposition. We then extracted the co-expressed connections which were supported either by transcriptional regulatory network or STRING database or high edge weight of topological overlap. The genes trpC, nadC, pitA, Rv3404c, atpA, pknA, Rv0996, purB, Rv2106 and Rv0796 emerged as top hub genes. After overlaying this network on the iNJ661 metabolic network, the reactions catalyzed by 15 highly connected metabolic genes were knocked down in silico and evaluated by Flux Balance Analysis. The results showed that in 12 out of 15 cases, in 11 more than 50% of reactions catalyzed by genes connected through co-expressed connections also had altered fluxes. The modules 'Turquoise', 'Blue' and 'Red' also showed enrichment in essential genes. We could map 152 of the previously known or proposed drug targets in these modules and identified 15 new potential drug targets based on their high degree of co-expressed connections and strong correlation with module eigengenes.

Background: The molecular mechanisms of transcriptional regulation are poorly understood in Plasmodium falciparum. In addition, most of the genes in Plasmodium falciparum are transcriptionally poised and only a handful of cis-regulatory elements are known to operate in transcriptional regulation. Here, we employed an epigenetic signature based approach to identify significance of previously uncharacterised intergenic regions enriched with histone modification marks leading to discovery of enhancer-like elements. Results: We found that enhancer-like elements are significantly enriched with H3K4me1, generate unique noncoding bi-directional RNAs and majority of them can function as cis-regulators. Furthermore, functional enhancer reporter assay demonstrates that the enhancer-like elements regulate transcription of target genes in Plasmodium falciparum. Our study also suggests that the Plasmodium genome segregates functionally related genes into discrete housekeeping and pathogenicity/virulence clusters, presumably for robust transcriptional control of virulence/pathogenicity genes.