IU Indianapolis ScholarWorks :: Browsing by Author "Janga, Sarath Chandra"

Browsing by Author "Janga, Sarath Chandra"

Now showing 1 - 10 of 136

A Putative long-range RNA-RNA interaction between ORF8 and Spike of SARS-CoV-2
(Public Library of Science, 2022-09-01) Omoru, Okiemute Beatrice; Pereira, Filipe; Janga, Sarath Chandra; Manzourolajdad, Amirhossein; BioHealth Informatics, School of Informatics and Computing
SARS-CoV-2 has affected people worldwide as the causative agent of COVID-19. The virus is related to the highly lethal SARS-CoV-1 responsible for the 2002-2003 SARS outbreak in Asia. Research is ongoing to understand why both viruses have different spreading capacities and mortality rates. Like other beta coronaviruses, RNA-RNA interactions occur between different parts of the viral genomic RNA, resulting in discontinuous transcription and production of various sub-genomic RNAs. These sub-genomic RNAs are then translated into other viral proteins. In this work, we performed a comparative analysis for novel long-range RNA-RNA interactions that may involve the Spike region. Comparing in-silico fragment-based predictions between reference sequences of SARS-CoV-1 and SARS-CoV-2 revealed several predictions amongst which a thermodynamically stable long-range RNA-RNA interaction between (23660-23703 Spike) and (28025-28060 ORF8) unique to SARS-CoV-2 was observed. The patterns of sequence variation using data gathered worldwide further supported the predicted stability of the sub-interacting region (23679-23690 Spike) and (28031-28042 ORF8). Such RNA-RNA interactions can potentially impact viral life cycle including sub-genomic RNA production rates.
Abundance of Secondary Metabolites in Human Microbiome
Sarsani, Vishal; Kulkarni, Nikhil; Janga, Sarath Chandra
Human body harbors the most complicated microbial ecosystem. Bacteria that have co-evolved within a human context have barely been explored for secondary metabolites. These secondary metabolites are hypothesized to possess biological activities significant within the human host context. In our study, we studied conservation profiles of 203 secondary metabolite gene clusters across 16 human body sites and found that gastrointestinal tract and oral sites show the highest conservation for secondary metabolic gene clusters. We observed that majority of highly conserved metabolites belong to pathway type NRPS. Our phylogenetic analysis of highly conserved stool and oral samples revealed abundance of firmicutes, bacteroidetes and actinobacteria phylum.
Accurate Identification of RNA Editing Events Using Matched RNA and DNA Sequenced Samples Uncovers the Contribution of the Editing Landscape to Disease Progression in Glioblastoma Patients
Hashemikhabir, Seyedsasan; Hundley, Heather A.; Janga, Sarath Chandra
RNA editing event is increasingly appreciated as an important posttranscriptional regulatory mechanism in mammals. Adenosine deaminases that act on RNA (ADARs) are the enzymes that catalyze adenosine (A) to inosine (I) editing events. Human brain RNA is reported to have highest number of editing events. Many neurotransmitter receptors and ion channels undergo editing within exonic regions which generates a different protein than that encoded by the genome. ALU repeats in introns and untranslated regions of brain mRNAs are often targeted by editing events and result in altered splicing and post-transcriptional gene regulation.
Alternative Splicing Profile Comparison of Differentiating I-helper Cells to Dissect the Splicing Signatures of Th1, Th2, 1h17 and Treg Cells
Lakshmipati, Deepak Kumar; Quoseena, Mir; Ulrich, Benjamin; Kaplan, Mark; Janga, Sarath Chandra
This study focuses on the contribution of Alternative Splicing (AS) events in the differentiation and post-differentiation functions of T-helper cells, specifically in Thl, Th2, Th9, Th17 and Treg cells. T cell RNA-seq data from 72hr and 2week post differentiation time points was analyzed using (r-MATS) for alternative splicing events. We observed majority of the significant events are Skipped Exon (SE) events originating from a total of 1,556 genes and lntron Retention (RI) events were the second most abundant event occurring in 1,254 genes at 72 hours post differentiation. These numbers were significantly lower at 2 weeks post differentiation. PCR and qPCR validations confirmed scores of novel splicing event predictions. Results showed several skipped exon (SE) events in KTNl, IL4RA IL27, Hnrmpd, CREM and Arid4b showing different mRNA isoforms across multiple naïve vs differentiated T cell combinations. Overall, RI event associated genes were more prevalent (3,239 genes) than those exhibiting SE (2810 genes). SE events were associated with 10.8% (Th17), 11.2% (Treg), 12.1% (Th2) and 13.9% (Thl) of the genes, a similar trend was observed with RI events with a prevalence of 12.2% (Th17), 12.5% (Treg), 14.2% (Thl) and 14.4% (Th2) of the genes. Gene ontology results showed most of the genes showing SE and RI events are involved in processes like 'mRNA Processing', 'RNA Processing' and 'RNA Binding' and ontology results for retained introns also showed p53 suppression proteins, regulated exocytosis of neurotransmitters and hormones. It was also observed that Introns consistently favored retention at the 3' end of the gene than the 5', with 430 genes showing intron retention events at the 3' end and 21 genes exhibiting them at the 5' end, for the 72 hour time point. Enriched functional ontologies were consistently seen across all cell types to be exclusive for the genes showing RI in the 5' end vs the 3' end.
Bacterial regulatory networks are extremely flexible in evolution
(2006-05) Lozada-Chávez, Irma; Janga, Sarath Chandra; Collado-Vides, Julio
Over millions of years the structure and complexity of the transcriptional regulatory network (TRN) in bacteria has changed, reorganized and enabled them to adapt to almost every environmental niche on earth. In order to understand the plasticity of TRNs in bacteria, we studied the conservation of currently known TRNs of the two model organisms Escherichia coli K12 and Bacillus subtilis across complete genomes including Bacteria, Archaea and Eukarya at three different levels: individual components of the TRN, pairs of interactions and regulons. We found that transcription factors (TFs) evolve much faster than the target genes (TGs) across phyla. We show that global regulators are poorly conserved across the phylogenetic spectrum and hence TFs could be the major players responsible for the plasticity and evolvability of the TRNs. We also found that there is only a small fraction of significantly conserved transcriptional regulatory interactions among different phyla of bacteria and that there is no constraint on the elements of the interaction to co-evolve. Finally our results suggest that majority of the regulons in bacteria are rapidly lost implying a high-order flexibility in the TRNs. We hypothesize that during the divergence of bacteria certain essential cellular processes like the synthesis of arginine, biotine and ribose, transport of amino acids and iron, availability of phosphate, replication process and the SOS response are well conserved in evolution. From our comparative analysis, it is possible to infer that transcriptional regulation is more flexible than the genetic component of the organisms and its complexity and structure plays an important role in the phenotypic adaptation.
Bcl6 and Blimp1 reciprocally regulate ST2+ Treg-cell development in the context of allergic airway inflammation
(Elsevier, 2020) Koh, Byunghee; Ulrich, Benjamin J.; Nelson, Andrew S.; Panangipalli, Gayathri; Kharwadkar, Rakshin; Wu, Wenting; Xie, Markus M.; Fu, Yongyao; Turner, Matthew J.; Paczesny, Sophie; Janga, Sarath Chandra; Dent, Alexander L.; Kaplan, Mark H.; Pediatrics, School of Medicine
Background Bcl6 is required for the development of T follicular helper cells and T follicular regulatory (Tfr) cells that regulate germinal center responses. Bcl6 also affects the function of regulatory T (Treg) cells. Objective The goal of this study was to define the functions of Bcl6 in Treg cells, including Tfr cells, in the context of allergic airway inflammation. Methods We used a model of house dust mite sensitization to challenge wild-type, Bcl6fl/fl Foxp3-Cre, and Prdm1 (Blimp1)fl/fl Foxp3-Cre mice to study the reciprocal roles of Bcl6 and Blimp1 in allergic airway inflammation. Results In the house dust mite model, Tfr cells repress the production of IgE and Bcl6+ Treg cells suppress the generation of type 2 cytokine–producing cells in the lungs. In mice with Bcl6-deficient Treg cells, twice as many ST2+ (IL-33R+) Treg cells develop as are observed in wild-type mice. ST2+ Treg cells in the context of allergic airway inflammation are Blimp1 dependent, express type 2 cytokines, and share features of visceral adipose tissue Treg cells. Bcl6-deficient Treg cells are more susceptible, and Blimp1-deficient Treg cells are resistant, to acquiring the ST2+ Treg–cell phenotype in vitro and in vivo in response to IL-33. Bcl6-deficient ST2+ Treg cells, but not Bcl6-deficient ST2+ conventional T cells, strongly promote allergic airway inflammation when transferred into recipient mice. Lastly, ST2 is required for the exacerbated allergic airway inflammation in Bcl6fl/fl Foxp3-Cre mice. Conclusions During allergic airway inflammation, Bcl6 and Blimp1 play dual roles in regulating Tfr-cell activity in the germinal center and in the development of ST2+ Treg cells that promote type 2 cytokine responses.
Benchmarking of de novo assembly algorithms for Nanopore data reveals optimal performance of OLC approaches
(Biomed Central, 2016) Cherukuri, Yesesri; Janga, Sarath Chandra; Department of Biohealth Informatics, School of Informatics and Computing
Improved DNA sequencing methods have transformed the field of genomics over the last decade. This has become possible due to the development of inexpensive short read sequencing technologies which have now resulted in three generations of sequencing platforms. More recently, a new fourth generation of Nanopore based single molecule sequencing technology, was developed based on MinION® sequencer which is portable, inexpensive and fast. It is capable of generating reads of length greater than 100 kb. Though it has many specific advantages, the two major limitations of the MinION reads are high error rates and the need for the development of downstream pipelines. The algorithms for error correction have already emerged, while development of pipelines is still at nascent stage.
Building Integrated Ontological Knowledge Structures with Efficient Approximation Algorithms
(2015) Xiang, Yang; Janga, Sarath Chandra
The integration of ontologies builds knowledge structures which brings new understanding on existing terminologies and their associations. With the steady increase in the number of ontologies, automatic integration of ontologies is preferable over manual solutions in many applications. However, available works on ontology integration are largely heuristic without guarantees on the quality of the integration results. In this work, we focus on the integration of ontologies with hierarchical structures. We identified optimal structures in this problem and proposed optimal and efficient approximation algorithms for integrating a pair of ontologies. Furthermore, we extend the basic problem to address the integration of a large number of ontologies, and correspondingly we proposed an efficient approximation algorithm for integrating multiple ontologies. The empirical study on both real ontologies and synthetic data demonstrates the effectiveness of our proposed approaches. In addition, the results of integration between gene ontology and National Drug File Reference Terminology suggest that our method provides a novel way to perform association studies between biomedical terms.
CASowary: CRISPR-Cas13 guide RNA predictor for transcript depletion
(BMC, 2022) Krohannon, Alexander; Srivastava, Mansi; Rauch, Simone; Srivastava, Rajneesh; Dickinson, Bryan C.; Janga, Sarath Chandra; BioHealth Informatics, School of Informatics and Computing
Background: Recent discovery of the gene editing system - CRISPR (Clustered Regularly Interspersed Short Palindromic Repeats) associated proteins (Cas), has resulted in its widespread use for improved understanding of a variety of biological systems. Cas13, a lesser studied Cas protein, has been repurposed to allow for efficient and precise editing of RNA molecules. The Cas13 system utilizes base complementarity between a crRNA/sgRNA (crispr RNA or single guide RNA) and a target RNA transcript, to preferentially bind to only the target transcript. Unlike targeting the upstream regulatory regions of protein coding genes on the genome, the transcriptome is significantly more redundant, leading to many transcripts having wide stretches of identical nucleotide sequences. Transcripts also exhibit complex three-dimensional structures and interact with an array of RBPs (RNA Binding Proteins), both of which may impact the effectiveness of transcript depletion of target sequences. However, our understanding of the features and corresponding methods which can predict whether a specific sgRNA will effectively knockdown a transcript is very limited. Results: Here we present a novel machine learning and computational tool, CASowary, to predict the efficacy of a sgRNA. We used publicly available RNA knockdown data from Cas13 characterization experiments for 555 sgRNAs targeting the transcriptome in HEK293 cells, in conjunction with transcriptome-wide protein occupancy information. Our model utilizes a Decision Tree architecture with a set of 112 sequence and target availability features, to classify sgRNA efficacy into one of four classes, based upon expected level of target transcript knockdown. After accounting for noise in the training data set, the noise-normalized accuracy exceeds 70%. Additionally, highly effective sgRNA predictions have been experimentally validated using an independent RNA targeting Cas system - CIRTS, confirming the robustness and reproducibility of our model's sgRNA predictions. Utilizing transcriptome wide protein occupancy map generated using POP-seq in HeLa cells against publicly available protein-RNA interaction map in Hek293 cells, we show that CASowary can predict high quality guides for numerous transcripts in a cell line specific manner. Conclusions: Application of CASowary to whole transcriptomes should enable rapid deployment of CRISPR/Cas13 systems, facilitating the development of therapeutic interventions linked with aberrations in RNA regulatory processes.
Charting the Unexplored RNA-binding Protein Atlas of the Human Genome
(Office of the Vice Chancellor for Research, 2012-04-13) Zhao, Huiying; Yang, Yuedong; Janga, Sarath Chandra; Chen, Jason; Zhu, Heng; Kao, Cheng; Zhou, Yaoqi
Detecting protein-RNA interactions is challenging–both experimentally and computationally– because RNAs are large in number, diverse in cellular location and function, and flexible in structure. As a result, many RNA-binding proteins (RBPs) remain to be identified and characterized. Recently, we developed a bioinformatics tool called SPOT-Seq that integrates template-based structure prediction with RNA-binding affinity prediction to predict RBPs. Application of SPOT-Seq to human genome leads to doubling of RBPs from 2115 to 4296. Half of novel (>2000) RBPs are poorly or not annotated. The other half possesses Gene Ontology leaf IDs that are associated with known RBPs. In particular, we identified 36 novel RBPs in cancer, cardiovascular, diabetes and neurodegenerative pathways and 26 novel RBPs associated with disease-causing SNPs. Half of these disease-associating, predicted novel RBPs are annotated to interact with known RBPs. Accuracy of predicted novel RBPs is further validated by same confirmation rate of novel and annotated RBPs in human proteome microarrays experiments. The large number of predicted novel RBPs and their abundance in disease pathways and disease-causing SNPs are useful for hypothesis generation. These predicted novel human RBPs (>2000) with confidence level and their predicted complex structures with RNA can be downloaded from http://sparks.informatics.iupui.edu (yqzhou@iupui.edu)

Browsing by Author "Janga, Sarath Chandra"

Results Per Page

Sort Options