Integrative Computational Genomics Based Approaches to Uncover the Tissue-Specific Regulatory Networks in Development and Disease

Indiana University-Purdue University Indianapolis (IUPUI)Regulatory protein families such as transcription factors (TFs) and RNA Binding Proteins (RBPs) are increasingly being appreciated for their role in regulating the respective targeted genomic/transcriptomic elements resulting in dynamic transcriptional (TRNs) and post-transcriptional regulatory networks (PTRNs) in higher eukaryotes. The mechanistic understanding of these two regulatory network types require a high resolution tissue-specific functional annotation of both the proteins as well as their target sites. This dissertation addresses the need to uncover the tissue-specific regulatory networks in development and disease. This work establishes multiple computational genomics based approaches to further enhance our understanding of regulatory circuits and decipher the associated mechanisms at several layers of biological processes. This study potentially contributes to the research community by providing valuable resources including novel methods, web interfaces and software which transforms our ability to build high-quality regulatory binding maps of RBPs and TFs in a tissue specific manner using multi-omics datasets. The study deciphered the broad spectrum of temporal and evolutionary dynamics of the transcriptome and their regulation at transcriptional and post transcriptional levels. It also advances our ability to functionally annotate hundreds of RBPs and their RNA binding sites across tissues in the human genome which help in decoding the role of RBPs in the context of disease phenotype, networks, and pathways. The approaches developed in this dissertation is scalable and adaptable to further investigate the tissue specific regulators in any biological systems. Overall, this study contributes towards accelerating the progress in molecular diagnostics and drug target identification using regulatory network analysis method in disease and pathophysiology

SARS-CoV-2 contributes to altering the post-transcriptional regulatory networks across human tissues by sponging RNA binding proteins and micro-RNAs

The outbreak of a novel coronavirus SARS-CoV2 responsible for COVID-19 pandemic has caused worldwide public health emergency. Due to the constantly evolving nature of the coronaviruses, SARS-CoV-2 mediated alteration on post-transcriptional gene regulation across human tissues remains elusive. In this study, we systematically dissected the crosstalk and dysregulation of human post-transcriptional regulatory networks governed by RNA binding proteins (RBPs) and micro-RNAs (miRs), due to SARS-CoV-2 infection. We uncovered that 13 out of 29 SARS-CoV- 2 encoded proteins directly interact with 51 human RBPs of which majority of them were abundantly expressed in gonadal tissues and immune cells. We further performed functional analysis of differentially expressed genes in mock treated versus SARS-CoV-2 infected lung cells that revealed an enrichment for immune response, cytokine mediated signaling, and metabolism associated genes. This study also characterized the alternative splicing events in SARS-CoV-2 infected cells compared to control demonstrating that skipped exons and mutually exclusive exons were the most abundant events that potentially contributed to differential outcomes in response to viral infection. Motif enrichment analysis on the RNA genomic sequence of SARS-CoV-2 clearly revealed an enrichment for RBPs such as SRSFs, PCBPs, ELAVs and HNRNPs illustrating the sponging of RBPs by SARS-CoV-2 genome. Similar analysis to study the interactions of miRs with SARS-CoV-2 revealed the potential for several miRs to be sponged, suggesting that these interactions may contribute to altered pos-transcriptional regulation across human tissues. Given the need to understand the interactions of SARS-CoV-2 with key pos-transcriptional regulators in the human genome, this study provides a systematic analysis to dissect the role of dysregulated post-transcriptional regulatory networks controlled by RBPs and miRs, across tissues types during SARS-CoV2 infection.This work was supported by the National Institute of General Medical Sciences of the National Institutes of Health under Award Number R01GM123314 (SCJ). We also thank the lab members for their valuable suggestions and supporting dataset required for completion of this project

Seten: a tool for systematic identification and comparison of processes, phenotypes, and diseases associated with RNA-binding proteins from condition-specific CLIP-seq profiles

RNA-binding proteins (RBPs) control the regulation of gene expression in eukaryotic genomes at post-transcriptional level by binding to their cognate RNAs. Although several variants of CLIP (crosslinking and immunoprecipitation) protocols are currently available to study the global protein-RNA interaction landscape at single-nucleotide resolution in a cell, currently there are very few tools that can facilitate understanding and dissecting the functional associations of RBPs from the resulting binding maps. Here, we present Seten, a web-based and command line tool, which can identify and compare processes, phenotypes, and diseases associated with RBPs from condition-specific CLIP-seq profiles. Seten uses BED files resulting from most peak calling algorithms, which include scores reflecting the extent of binding of an RBP on the target transcript, to provide both traditional functional enrichment as well as gene set enrichment results for a number of gene set collections including BioCarta, KEGG, Reactome, Gene Ontology (GO), Human Phenotype Ontology (HPO), and MalaCards Disease Ontology for several organisms including fruit fly, human, mouse, rat, worm, and yeast. It also provides an option to dynamically compare the associated gene sets across data sets as bubble charts, to facilitate comparative analysis. Benchmarking of Seten using eCLIP data for IGF2BP1, SRSF7, and PTBP1 against their corresponding CRISPR RNA-seq in K562 cells as well as randomized negative controls, demonstrated that its gene set enrichment method outperforms functional enrichment, with scores significantly contributing to the discovery of true annotations. Comparative performance analysis using these CRISPR control data sets revealed significantly higher precision and comparable recall to that observed using ChIP-Enrich. Seten's web interface currently provides precomputed results for about 200 CLIP-seq data sets and both command line as well as web interfaces can be used to analyze CLIP-seq data sets. We highlight several examples to show the utility of Seten for rapid profiling of various CLIP-seq data sets

Lantern: a semi-automated pipeline and repository for annotating lncRNAs with ontologies

Digitized for IUPUI ScholarWorks inclusion in 2021.With advancements in in omics technologies, the range of biological processes long non-coding RNAs (lncRNAs) are involved in is expanding extensively [1,2). The accelerating rate of evidence discovery of lncRNAs' role in various critical biochemical, cellular, and physiological processes is necessitating a robust platform of lncRNA annotation resources. Available resources with lncRNA ontology annotations are rare: despite a plethora of resources for annotating genes, and an extensive body of lncRNA literature. Here, we present a lncRNA annotation extractor and repository (Lantern), was developed using PubMed's abstract retrieval engine and NCBO's recommender annotation system [3]. Between 1-150 abstracts were extracted per lncRNA, which were subsequently used for extracting annotations with respect to each ontology by querying NCBO's recommender system via Application Programming Interface (API). To evaluate the quality of annotations in Lantern, benchmarking analysis was performed by deploying Lantern's pipeline over 182 lncRNAs from lncRNAdb [4) and compared the extracted annotations against annotations mapped onto the lncRNAdb's manually curated free text. Benchmarking analysis suggested that Lantern has a recall of 0.62 against lncRNAdb for 182 lncRNAs and precision of 0.8 based on manual verification of ontology annotations for 50 lncRNAs. Additionally, lncRNAs were also annotated with multiple omics information, like: RBP-interaction, tissue specific expression, protein c-expression, coding potential, sub-cellular localization and SNPs for around 11000 lncRNAs; retrieved and analyzed by robust NGS tools and pipelines. The extracted annotations for 11000 lncRNAs are available at http://www.iupui.edu/~sysbio/lantern/

Transcriptome-wide high-throughput mapping of protein–RNA occupancy profiles using POP-seq

Interaction between proteins and RNA is critical for post-transcriptional regulatory processes. Existing high throughput methods based on crosslinking of the protein–RNA complexes and poly-A pull down are reported to contribute to biases and are not readily amenable for identifying interaction sites on non poly-A RNAs. We present Protein Occupancy Profile-Sequencing (POP-seq), a phase separation based method in three versions, one of which does not require crosslinking, thus providing unbiased protein occupancy profiles on whole cell transcriptome without the requirement of poly-A pulldown. Our study demonstrates that ~ 68% of the total POP-seq peaks exhibited an overlap with publicly available protein–RNA interaction profiles of 97 RNA binding proteins (RBPs) in K562 cells. We show that POP-seq variants consistently capture protein–RNA interaction sites across a broad range of genes including on transcripts encoding for transcription factors (TFs), RNA-Binding Proteins (RBPs) and long non-coding RNAs (lncRNAs). POP-seq identified peaks exhibited a significant enrichment (p value < 2.2e−16) for GWAS SNPs, phenotypic, clinically relevant germline as well as somatic variants reported in cancer genomes, suggesting the prevalence of uncharacterized genomic variation in protein occupied sites on RNA. We demonstrate that the abundance of POP-seq peaks increases with an increase in expression of lncRNAs, suggesting that highly expressed lncRNA are likely to act as sponges for RBPs, contributing to the rewiring of protein–RNA interaction network in cancer cells. Overall, our data supports POP-seq as a robust and cost-effective method that could be applied to primary tissues for mapping global protein occupancies

In infertile women, cells from Chlamydia trachomatis infected site release higher levels of interferon-gamma, interleukin-10 and tumor necrosis factor-alpha upon heat shock protein stimulation than fertile women

<p>Abstract</p> <p>Background</p> <p>The magnitude of reproductive morbidity associated with sexually transmitted Chlamydia trachomatis infection is enormous. Association of antibodies to chlamydial heat shock proteins (cHSP) 60 and 10 with various disease sequelae such as infertility or ectopic pregnancy has been reported. Cell-mediated immunity is essential in resolution and in protection to Chlamydia as well as is involved in the immunopathogenesis of chlamydial diseases. To date only peripheral cell mediated immune responses have been evaluated for cHSP60. These studies suggest cHSPs as important factors involved in immunopathological condition associated with infection. Hence study of specific cytokine responses of mononuclear cells from the infectious site to cHSP60 and cHSP10 may elucidate their actual role in the cause of immunopathogenesis and the disease outcome.</p> <p>Methods</p> <p>Female patients (n = 368) attending the gynecology out patient department of Safdarjung hospital, New Delhi were enrolled for the study and were clinically characterized into two groups; chlamydia positive fertile women (n = 63) and chlamydia positive infertile women (n = 70). Uninfected healthy women with no infertility problem were enrolled as controls (n = 39). cHSP60 and cHSP10 specific cytokine responses (Interferon (IFN)-gamma, Interleukin (IL)-10, Tumor Necrosis Factor (TNF)-alpha, IL-13 and IL-4) were assessed by ELISA in stimulated cervical mononuclear cell supernatants.</p> <p>Results</p> <p>cHSP60 and cHSP10 stimulation results in significant increase in IFN-gamma (P = 0.006 and P = 0.04 respectively) and IL-10 levels (P = 0.04) in infertile group as compared to fertile group. A significant cHSP60 specific increase in TNF-alpha levels (P = 0.0008) was observed in infertile group as compared to fertile group. cHSP60 and cHSP10 specific IFN-gamma and IL-10 levels were significantly correlated (P < 0.0001, r = 0.54 and P = 0.004, r = 0.33 respectively) in infertile group.</p> <p>Conclusion</p> <p>Our results suggest that exposure to chlamydial heat shock proteins (cHSP60 and cHSP10) could significantly affect mucosal immune function by increasing the release of IFN-gamma, IL-10 and TNF-alpha by cervical mononuclear cells.</p

ELECTROLUMINESCENCE STUDY OF ZnS: Sm, Li PHOSPHOR USING SOLID STATE REACTION METHOD

In the present work we have attempted to study the electroluminescent (EL) properties of ZnS: Sm, Li luminophor.The phosphor is synthesized using solid state reaction method. A comparative study has been made for electroluminescent emission characteristics of five samples viz ZnS:Cu,Li, ZnS:Sm, ZnS:Sm,Cl; ZnS:Sm,Li; ZnS:Cu,Sm,Li. It is observed that the intensity of brightness varies with the applied voltage and excitation frequency according to the universal laws and color of emission is found to be greenish. Li is found to enhance the EL intensity of ZnS: Sm phosphor. Structural studies using XRD have also been performed. The average grain size of ZnS: Sm, Li is estimated to be 38.9µ

Express: A database of transcriptome profiles encompassing known and novel transcripts across multiple development stages in eye tissues

Advances in sequencing have facilitated nucleotide-resolution genome-wide transcriptomic profiles across multiple mouse eye tissues. However, these RNA sequencing (RNA-seq) based eye developmental transcriptomes are not organized for easy public access, making any further analysis challenging. Here, we present a new database “Express” (http://www.iupui.edu/∼sysbio/express/) that unifies various mouse lens and retina RNA-seq data and provides user-friendly visualization of the transcriptome to facilitate gene discovery in the eye. We obtained RNA-seq data encompassing 7 developmental stages of lens in addition to that on isolated lens epithelial and fibers, as well as on 11 developmental stages of retina/isolated retinal rod photoreceptor cells from publicly available wild-type mouse datasets. These datasets were pre-processed, aligned, quantified and normalized for expression levels of known and novel transcripts using a unified expression quantification framework. Express provides heatmap and browser view allowing easy navigation of the genomic organization of transcripts or gene loci. Further, it allows users to search candidate genes and export both the visualizations and the embedded data to facilitate downstream analysis. We identified total of >81,000 transcripts in the lens and >178,000 transcripts in the retina across all the included developmental stages. This analysis revealed that a significant number of the retina-expressed transcripts are novel. Expression of several transcripts in the lens and retina across multiple developmental stages was independently validated by RT-qPCR for established genes such as Pax6 and Lhx2 as well as for new candidates such as Elavl4, Rbm5, Pabpc1, Tia1 and Tubb2b. Thus, Express serves as an effective portal for analyzing pruned RNA-seq expression datasets presently collected for the lens and retina. It will allow a wild-type context for the detailed analysis of targeted gene-knockout mouse ocular defect models and facilitate the prioritization of candidate genes from Exome-seq data of eye disease patients

Role of SARS-CoV-2 in Altering the RNA-Binding Protein and miRNA-Directed Post-Transcriptional Regulatory Networks in Humans

The outbreak of a novel coronavirus SARS-CoV-2 responsible for the COVID-19 pandemic has caused a worldwide public health emergency. Due to the constantly evolving nature of the coronaviruses, SARS-CoV-2-mediated alterations on post-transcriptional gene regulations across human tissues remain elusive. In this study, we analyzed publicly available genomic datasets to systematically dissect the crosstalk and dysregulation of the human post-transcriptional regulatory networks governed by RNA-binding proteins (RBPs) and micro-RNAs (miRs) due to SARS-CoV-2 infection. We uncovered that 13 out of 29 SARS-CoV-2-encoded proteins directly interacted with 51 human RBPs, of which the majority of them were abundantly expressed in gonadal tissues and immune cells. We further performed a functional analysis of differentially expressed genes in mock-treated versus SARS-CoV-2-infected lung cells that revealed enrichment for the immune response, cytokine-mediated signaling, and metabolism-associated genes. This study also characterized the alternative splicing events in SARS-CoV-2-infected cells compared to the control, demonstrating that skipped exons and mutually exclusive exons were the most abundant events that potentially contributed to differential outcomes in response to the viral infection. A motif enrichment analysis on the RNA genomic sequence of SARS-CoV-2 clearly revealed the enrichment for RBPs such as SRSFs, PCBPs, ELAVs, and HNRNPs, suggesting the sponging of RBPs by the SARS-CoV-2 genome. A similar analysis to study the interactions of miRs with SARS-CoV-2 revealed functionally important miRs that were highly expressed in immune cells, suggesting that these interactions may contribute to the progression of the viral infection and modulate the host immune response across other human tissues. Given the need to understand the interactions of SARS-CoV-2 with key post-transcriptional regulators in the human genome, this study provided a systematic computational analysis to dissect the role of dysregulated post-transcriptional regulatory networks controlled by RBPs and miRs across tissue types during a SARS-CoV-2 infection

Lantern: an integrative repository of functional annotations for lncRNAs in the human genome

Background: With advancements in omics technologies, the range of biological processes where long non-coding RNAs (lncRNAs) are involved, is expanding extensively, thereby generating the need to develop lncRNA annotation resources. Although, there are a plethora of resources for annotating genes, despite the extensive corpus of lncRNA literature, the available resources with lncRNA ontology annotations are rare. Results: We present a lncRNA annotation extractor and repository (Lantern), developed using PubMed's abstract retrieval engine and NCBO's recommender annotation system. Lantern's annotations were benchmarked against lncRNAdb's manually curated free text. Benchmarking analysis suggested that Lantern has a recall of 0.62 against lncRNAdb for 182 lncRNAs and precision of 0.8. Additionally, we also annotated lncRNAs with multiple omics annotations, including predicted cis-regulatory TFs, interactions with RBPs, tissue-specific expression profiles, protein co-expression networks, coding potential, sub-cellular localization, and SNPs for ~ 11,000 lncRNAs in the human genome, providing a one-stop dynamic visualization platform. Conclusions: Lantern integrates a novel, accurate semi-automatic ontology annotation engine derived annotations combined with a variety of multi-omics annotations for lncRNAs, to provide a central web resource for dissecting the functional dynamics of long non-coding RNAs and to facilitate future hypothesis-driven experiments. The annotation pipeline and a web resource with current annotations for human lncRNAs are freely available on sysbio.lab.iupui.edu/lantern