Saakshi Jalali

Systematic Transcriptome Wide Analysis of lncRNA-miRNA Interactions

Background Long noncoding RNAs (lncRNAs) are a recently discovered class of non-protein coding RNAs, which have now increasingly been shown to be involved in a wide variety of biological processes as regulatory molecules. The functional role of many of the members of this class has been an enigma, except a few of them like Malat and HOTAIR. Little is known regarding the regulatory interactions between noncoding RNA classes. Recent reports have suggested that lncRNAs could potentially interact with other classes of non-coding RNAs including microRNAs (miRNAs) and modulate their regulatory role through interactions. We hypothesized that lncRNAs could participate as a layer of regulatory interactions with miRNAs. The availability of genome-scale datasets for Argonaute targets across human transcriptome has prompted us to reconstruct a genome-scale network of interactions between miRNAs and lncRNAs. Results We used well characterized experimental Photoactivatable-Ribonucleoside-Enhanced Crosslinking and Immunoprecipitation (PAR-CLIP) datasets and the recent genome-wide annotations for lncRNAs in public domain to construct a comprehensive transcriptome-wide map of miRNA regulatory elements. Comparative analysis revealed that in addition to targeting protein-coding transcripts, miRNAs could also potentially target lncRNAs, thus participating in a novel layer of regulatory interactions between noncoding RNA classes. Furthermore, we have modeled one example of miRNA-lncRNA interaction using a zebrafish model. We have also found that the miRNA regulatory elements have a positional preference, clustering towards the mid regions and 3′ ends of the long noncoding transcripts. We also further reconstruct a genome-wide map of miRNA interactions with lncRNAs as well as messenger RNAs. Conclusions This analysis suggests widespread regulatory interactions between noncoding RNAs classes and suggests a novel functional role for lncRNAs. We also present the first transcriptome scale study on miRNA-lncRNA interactions and the first report of a genome-scale reconstruction of a noncoding RNA regulatory interactome involving lncRNAs.

lncRNome: a comprehensive knowledgebase of human long noncoding RNAs

The advent of high-throughput genome scale technologies has enabled us to unravel a large amount of the previously unknown transcriptionally active regions of the genome. Recent genome-wide studies have provided annotations of a large repertoire of various classes of noncoding transcripts. Long noncoding RNAs (lncRNAs) form a major proportion of these novel annotated noncoding transcripts, and presently known to be involved in a number of functionally distinct biological processes. Over 18 000 transcripts are presently annotated as lncRNA, and encompass previously annotated classes of noncoding transcripts including large intergenic noncoding RNA, antisense RNA and processed pseudogenes. There is a significant gap in the resources providing a stable annotation, cross-referencing and biologically relevant information. lncRNome has been envisioned with the aim of filling this gap by integrating annotations on a wide variety of biologically significant information into a comprehensive knowledgebase. To the best of our knowledge, lncRNome is one of the largest and most comprehensive resources for lncRNAs. Database URL: http://genome.igib.res.in/lncRNome

Dynamic expression of long non-coding RNAs (lncRNAs) in adult zebrafish.

Long non-coding RNAs (lncRNA) represent an assorted class of transcripts having little or no protein coding capacity and have recently gained importance for their function as regulators of gene expression. Molecular studies on lncRNA have uncovered multifaceted interactions with protein coding genes. It has been suggested that lncRNAs are an additional layer of regulatory switches involved in gene regulation during development and disease. LncRNAs expressing in specific tissues or cell types during adult stages can have potential roles in form, function, maintenance and repair of tissues and organs. We used RNA sequencing followed by computational analysis to identify tissue restricted lncRNA transcript signatures from five different tissues of adult zebrafish. The present study reports 442 predicted lncRNA transcripts from adult zebrafish tissues out of which 419 were novel lncRNA transcripts. Of these, 77 lncRNAs show predominant tissue restricted expression across the five major tissues investigated. Adult zebrafish brain expressed the largest number of tissue restricted lncRNA transcripts followed by cardiovascular tissue. We also validated the tissue restricted expression of a subset of lncRNAs using independent methods. Our data constitute a useful genomic resource towards understanding the expression of lncRNAs in various tissues in adult zebrafish. Our study is thus a starting point and opens a way towards discovering new molecular interactions of gene expression within the specific adult tissues in the context of maintenance of organ form and function.

Integrative transcriptome analysis suggest processing of a subset of long non-coding RNAs to small RNAs

BackgroundThe availability of sequencing technology has enabled understanding of transcriptomes through genome-wide approaches including RNA-sequencing. Contrary to the previous assumption that large tracts of the eukaryotic genomes are not transcriptionally active, recent evidence from transcriptome sequencing approaches have revealed pervasive transcription in many genomes of higher eukaryotes. Many of these loci encode transcripts that have no obvious protein-coding potential and are designated as non-coding RNA (ncRNA). Non-coding RNAs are classified empirically as small and long non-coding RNAs based on the size of the functional RNAs. Each of these classes is further classified into functional subclasses. Although microRNAs (miRNA), one of the major subclass of ncRNAs, have been extensively studied for their roles in regulation of gene expression and involvement in a large number of patho-physiological processes, the functions of a large proportion of long non-coding RNAs (lncRNA) still remains elusive. We hypothesized that some lncRNAs could potentially be processed to small RNA and thus could have a dual regulatory output.ResultsIntegration of large-scale independent experimental datasets in public domain revealed that certain well studied lncRNAs harbor small RNA clusters. Expression analysis of the small RNA clusters in different tissue and cell types reveal that they are differentially regulated suggesting a regulated biogenesis mechanism.ConclusionsOur analysis suggests existence of a potentially novel pathway for lncRNA processing into small RNAs. Expression analysis, further suggests that this pathway is regulated. We argue that this evidence supports our hypothesis, though limitations of the datasets and analysis cannot completely rule out alternate possibilities. Further in-depth experimental verification of the observation could potentially reveal a novel pathway for biogenesis.ReviewersThis article was reviewed by Dr Rory Johnson (nominated by Fyodor Kondrashov), Dr Raya Khanin (nominated by Dr Yuriy Gusev) and Prof Neil Smalheiser. For full reviews, please go to the Reviewer’s comment section.

Conceptual approaches for lncRNA drug discovery and future strategies

Introduction: Long non-coding RNAs (lncRNAs) are a recently discovered class of non-coding functional RNA which has attracted immense research interest. The growing corpus of literature in the field provides ample evidence to suggest the important role of lncRNAs as regulators in a wide spectrum of biological processes. Recent evidence also suggests the role of lncRNAs in the pathophysiology of disease processes. Areas covered: The authors discuss a conceptual framework for understanding lncRNA-mediated regulation as a function of its interaction with other biomolecules in the cell. They summarize the mechanisms of the known functions of lncRNAs in light of this conceptual framework, and suggest how this insight could help in discovering novel targets for drug discovery. They also argue how certain emerging technologies could be of immense utility, both in discovering potential therapeutic targets as well as in further therapeutic development. Expert opinion: The authors propose how the field could immensely benefit from methodologies and technologies from six emerging fields in molecular and computational biology. They also suggest a futuristic area of lncRNAs design as a potential offshoot of synthetic biology, which would be an attractive field, both for discovery of targets as well as a therapeutic strategy.

Computational approaches towards understanding human long non-coding RNA biology

Long non-coding RNAs (lncRNAs) form the largest class of non-protein coding genes in the human genome. While a small subset of well-characterized lncRNAs has demonstrated their significant role in diverse biological functions like chromatin modifications, post-transcriptional regulation, imprinting etc., the functional significance of a vast majority of them still remains an enigma. Increasing evidence of the implications of lncRNAs in various diseases including cancer and major developmental processes has further enhanced the need to gain mechanistic insights into the lncRNA functions. Here, we present a comprehensive review of the various computational approaches and tools available for the identification and annotation of long non-coding RNAs. We also discuss a conceptual roadmap to systematically explore the functional properties of the lncRNAs using computational approaches.

Distinct Patterns of Genetic Variations in Potential Functional Elements in Long Noncoding RNAs

Non‐protein‐coding RNAs have increasingly been shown to be an important class of regulatory RNAs having significant roles in regulation of gene expression. The long noncoding RNA (lncRNA) gene family presently constitutes a large number of noncoding RNA (ncRNA) loci almost equaling the number of protein‐coding genes. Nevertheless, the biological roles and mechanisms of the majority of lncRNAs are poorly understood, with exceptions of a very few well‐studied candidates. The availability of genome‐scale variation datasets, and increasing number of variant loci from genome‐wide association studies falling in lncRNA loci have motivated us to understand the patterns of genomic variations in lncRNA loci, their potential functional correlates, and selection in populations. In the present study, we have performed a comprehensive analysis of genomic variations in lncRNA loci. We analyzed for patterns and distributions of genomic variations with respect to potential functional domains in lncRNAs. The analysis reveals a distinct distribution of variations in subclasses of long ncRNAs and in potential functional domains of lncRNAs. We further examined signals of selections and allele frequencies of these prioritized set of lncRNAs. To the best of our knowledge, this is the first and comprehensive large‐scale analysis of genetic variations in long ncRNAs.

MitoLSDB: A Comprehensive Resource to Study Genotype to Phenotype Correlations in Human Mitochondrial DNA Variations

Human mitochondrial DNA (mtDNA) encodes a set of 37 genes which are essential structural and functional components of the electron transport chain. Variations in these genes have been implicated in a broad spectrum of diseases and are extensively reported in literature and various databases. In this study, we describe MitoLSDB, an integrated platform to catalogue disease association studies on mtDNA (http://mitolsdb.igib.res.in). The main goal of MitoLSDB is to provide a central platform for direct submissions of novel variants that can be curated by the Mitochondrial Research Community. MitoLSDB provides access to standardized and annotated data from literature and databases encompassing information from 5231 individuals, 675 populations and 27 phenotypes. This platform is developed using the Leiden Open (source) Variation Database (LOVD) software. MitoLSDB houses information on all 37 genes in each population amounting to 132397 variants, 5147 unique variants. For each variant its genomic location as per the Revised Cambridge Reference Sequence, codon and amino acid change for variations in protein-coding regions, frequency, disease/phenotype, population, reference and remarks are also listed. MitoLSDB curators have also reported errors documented in literature which includes 94 phantom mutations, 10 NUMTs, six documentation errors and one artefactual recombination. MitoLSDB is the largest repository of mtDNA variants systematically standardized and presented using the LOVD platform. We believe that this is a good starting resource to curate mtDNA variants and will facilitate direct submissions enhancing data coverage, annotation in context of pathogenesis and quality control by ensuring non-redundancy in reporting novel disease associated variants.

Screening Currency Notes for Microbial Pathogens and Antibiotic Resistance Genes Using a Shotgun Metagenomic Approach

Fomites are a well-known source of microbial infections and previous studies have provided insights into the sojourning microbiome of fomites from various sources. Paper currency notes are one of the most commonly exchanged objects and its potential to transmit pathogenic organisms has been well recognized. Approaches to identify the microbiome associated with paper currency notes have been largely limited to culture dependent approaches. Subsequent studies portrayed the use of 16S ribosomal RNA based approaches which provided insights into the taxonomical distribution of the microbiome. However, recent techniques including shotgun sequencing provides resolution at gene level and enable estimation of their copy numbers in the metagenome. We investigated the microbiome of Indian paper currency notes using a shotgun metagenome sequencing approach. Metagenomic DNA isolated from samples of frequently circulated denominations of Indian currency notes were sequenced using Illumina Hiseq sequencer. Analysis of the data revealed presence of species belonging to both eukaryotic and prokaryotic genera. The taxonomic distribution at kingdom level revealed contigs mapping to eukaryota (70%), bacteria (9%), viruses and archae (~1%). We identified 78 pathogens including Staphylococcus aureus, Corynebacterium glutamicum, Enterococcus faecalis, and 75 cellulose degrading organisms including Acidothermus cellulolyticus, Cellulomonas flavigena and Ruminococcus albus. Additionally, 78 antibiotic resistance genes were identified and 18 of these were found in all the samples. Furthermore, six out of 78 pathogens harbored at least one of the 18 common antibiotic resistance genes. To the best of our knowledge, this is the first report of shotgun metagenome sequence dataset of paper currency notes, which can be useful for future applications including as bio-surveillance of exchangeable fomites for infectious agents.

The Zebrafish GenomeWiki: a crowdsourcing approach to connect the long tail for zebrafish gene annotation.

A large repertoire of gene-centric data has been generated in the field of zebrafish biology. Although the bulk of these data are available in the public domain, most of them are not readily accessible or available in nonstandard formats. One major challenge is to unify and integrate these widely scattered data sources. We tested the hypothesis that active community participation could be a viable option to address this challenge. We present here our approach to create standards for assimilation and sharing of information and a system of open standards for database intercommunication. We have attempted to address this challenge by creating a community-centric solution for zebrafish gene annotation. The Zebrafish GenomeWiki is a ‘wiki’-based resource, which aims to provide an altruistic shared environment for collective annotation of the zebrafish genes. The Zebrafish GenomeWiki has features that enable users to comment, annotate, edit and rate this gene-centric information. The credits for contributions can be tracked through a transparent microattribution system. In contrast to other wikis, the Zebrafish GenomeWiki is a ‘structured wiki’ or rather a ‘semantic wiki’. The Zebrafish GenomeWiki implements a semantically linked data structure, which in the future would be amenable to semantic search. Database URL: http://genome.igib.res.in/twiki