Big data, integrative omics and network biology.

A cell integrates various signals through a network of biomolecules that crosstalk to synergistically regulate the replication, transcription, translation and other metabolic activities of a cell. These networks regulate signal perception and processing that drives biological functions. The biological complexity cannot be fully captured by a single -omics discipline. The holistic study of an organism-in health, perturbation, exposure to environment and disease, is studied under systems biology. The bottom-up molecular approaches (genes, mRNA, protein, metabolite, etc.) have laid the foundation of current biological knowledge covering the horizon from viruses, bacteria, fungi, plants and animals. Yet, these techniques provide a rather myopic view of biology at the molecular level. To understand how the interconnected molecular components are formed and rewired in disease or exposure to environmental stimuli is the holy grail of modern biology. The omics era was heralded by the genomics revolution but advanced sequencing techniques are now also ubiquitous in transcriptomics, proteomics, metabolomics and lipidomics. Multi-omics data analysis and integration techniques are driving the quest for deeper insights into how the different layers of biomolecules talk to each other in diverse contexts.

Posttranslational modifications in systems biology.

The biological complexity cannot be captured by genes or proteins alone. The protein posttranslational modifications (PTMs) impart functional diversity to the proteome and regulate protein structure, activity, localization and interactions. Their dynamics drive cellular signaling, growth and development while their dysregulation causes many diseases. Mass spectrometry based quantitative profiling of PTMs and bioinformatics analysis tools allow systems level insights into their network architecture. High-resolution profiling of PTM networks will advance disease understanding and precision medicine. It can accelerate the discovery of biomarkers and drug targets. This requires better tools for unbiased, high-throughput and accurate PTM identification, site localization and automated annotation on a systems level.

Global Transcriptome Profiling Identified Transcription Factors, Biological Process, and Associated Pathways for Pre-Harvest Aflatoxin Contamination in Groundnut.

Pre-harvest aflatoxin contamination (PAC) in groundnut is a serious quality concern globally, and drought stress before harvest further exacerbate its intensity, leading to the deterioration of produce quality. Understanding the host-pathogen interaction and identifying the candidate genes responsible for resistance to PAC will provide insights into the defense mechanism of the groundnut. In this context, about 971.63 million reads have been generated from 16 RNA samples under controlled and Aspergillus flavus infected conditions, from one susceptible and seven resistant genotypes. The RNA-seq analysis identified 45,336 genome-wide transcripts under control and infected conditions. This study identified 57 transcription factor (TF) families with major contributions from 6570 genes coding for bHLH (719), MYB-related (479), NAC (437), FAR1 family protein (320), and a few other families. In the host (groundnut), defense-related genes such as senescence-associated proteins, resveratrol synthase, seed linoleate, pathogenesis-related proteins, peroxidases, glutathione-S-transferases, chalcone synthase, ABA-responsive gene, and chitinases were found to be differentially expressed among resistant genotypes as compared to susceptible genotypes. This study also indicated the vital role of ABA-responsive ABR17, which co-regulates the genes of ABA responsive elements during drought stress, while providing resistance against A. flavus infection. It belongs to the PR-10 class and is also present in several plant-pathogen interactions.

Molecular and Physiological Alterations in Chickpea under Elevated CO2 Concentrations.

The present study reports profiling of the elevated carbon dioxide (CO2) concentration responsive global transcriptome in chickpea, along with a combinatorial approach for exploring interlinks between physiological and transcriptional changes, important for the climate change scenario. Various physiological parameters were recorded in two chickpea cultivars (JG 11 and KAK 2) grown in open top chambers under ambient [380 parts per million (ppm)] and two stressed/elevated CO2 concentrations (550 and 700 ppm), at different stages of plant growth. The elevated CO2 concentrations altered shoot and root length, nodulation (number of nodules), total chlorophyll content and nitrogen balance index, significantly. RNA-Seq from 12 tissues representing vegetative and reproductive growth stages of both cultivars under ambient and elevated CO2 concentrations identified 18,644 differentially expressed genes including 9,687 transcription factors (TF). The differential regulations in genes, gene networks and quantitative real-time polymerase chain reaction (qRT-PCR) -derived expression dynamics of stress-responsive TFs were observed in both cultivars studied. A total of 138 pathways, mainly involved in sugar/starch metabolism, chlorophyll and secondary metabolites biosynthesis, deciphered the crosstalk operating behind the responses of chickpea to elevated CO2 concentration.

Investigating Coronary Artery Disease methylome through targeted bisulfite sequencing.

BACKGROUND: Gene environment interactions leading to epigenetic alterations play pivotal role in the pathogenesis of Coronary Artery Disease (CAD). Altered DNA methylation is one such epigenetic factor that could lead to altered disease etiology. In this study, we comprehensively identified methylation sites in several genes that have been previously associated with young CAD patients. METHODS: The study population consisted of 42 healthy controls and 33 young CAD patients (age group <50 years). We performed targeted bisulfite sequencing of promoter as well as gene body regions of several genes in various pathways like cholesterol synthesis and metabolism, endothelial dysfunction, apoptosis, which are implicated in the development of CAD. RESULTS: We observed that the genes like GALNT2, HMGCR were hypermethylated in the promoter whereas LDLR gene promoter was hypomethylated indicating that intracellular LDL uptake was higher in CAD patients. Although APOA1 did not show significant change in methylation but APOC3 and APOA5 showed variation in methylation in promoter and exonic regions. Glucokinase (GCK) and endothelial nitric oxide synthase 3 (NOS3) were hyper methylated in the promoter. Genes involved in apoptosis (BAX/BCL2/AKT2) and inflammation (PHACTR1/LCK) also showed differential methylation between controls and CAD patients. A combined analysis of the methylated CpG sites using machine learning tool revealed 14 CpGs in 11 genes that could discriminate CAD cases from controls with over 93% accuracy. CONCLUSIONS: This study is unique because it highlights important gene methylation alterations which might predict the risk of young CAD in Indian population. Large scale studies in different populations would be important for validating our findings and understanding the epigenetic events associated with CAD.

MitoepigenomeKB a comprehensive resource for human mitochondrial epigenetic data.

Epigenetic modifications in the mitochondrial genome has been an emerging area of interest in the recent years in the field of mitochondrial biology. The renewed interest in the area has been largely fueled by a number of reports in the recent years suggesting the presence of epigenetic modifications in human mitochondrial genome and their associations with exposure to environmental factors and human diseases and or traits. Nevertheless there has been no systematic effort to curate, organize this information to enable cross-comparison between studies and datasets. We compiled 62 datasets from 9 studies on the epigenetic modifications in human mitochondrial genome to create a comprehensive catalog. This catalog is available as a user friendly interface - mitoepigenomeKB, where the data could be searched, browsed or visualized. The resource is available at URL: http://clingen.igib.res.in/mitoepigenome/. We hope mitoepigenomeKB would emerge as a central resource for datasets on epigenetic modifications in human mitochondria and would serve as the starting point to understanding the biology of human mitochondrial epigenome.