Identification of novel regulatory pathways across normal human bronchial epithelial cell lines (NHBEs) and peripheral blood mononuclear cell lines (PBMCs) in COVID-19 patients using transcriptome analysis

Lavanya, C; Upadhyaya, Aajnaa; Neogi, Arpita Guha; Niranjan, Vidya

doi:10.1016/j.imu.2022.100979

Cited by 4 publications

(1 citation statement)

References 31 publications

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“…Primarily, transcriptome analysis unveils fresh insights into biomarker exploration, establishing gene-centric benchmarks for personalized medicine and therapies [6]. Furthermore, transcriptome analysis plays a significant role in advancing research on long-term effects of COVID-19 [7]. By scrutinizing genome-wide differential RNA expression, researchers can gain a deeper understanding of the biological processes and molecular mechanisms governing cell fate, development, and the progression of diseases.…”

Section: Introductionmentioning

confidence: 99%

Recent Advancement on In-Silico Tools for Whole Transcriptome Analysis

Niranjan,

Chandramouli,

SureshKumar

et al. 2024

Genetics

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Delving into the intricate world of transcriptome analysis, this chapter unfolds the story of gene expression in organisms. The classic DNA microarray and RNA-seq methods have long been the pillars, with RNA-seq taking the spotlight for its superior resolution in understanding dynamic aspects. Yet, tools like Hisat2 and DESeq2, while effective, come with the drawback of being time-consuming and reliant on powerful GPUs. The need for quicker, less resource-intensive techniques has sparked a shift toward simpler R and Python-based tools that not only sidestep GPU dependence but also offer enhanced graphical representations. As we navigate through the content, the chapter draws a vivid comparison between the established tools and the emerging ones, highlighting the pressing need for innovative approaches in transcriptome analysis. The narrative guides readers through the fundamentals, from the Central Dogma’s backstory to the pivotal role of RNA in gene expression and disease. It uncovers the nuances between RNA-Seq and microarray technologies, providing a comprehensive overview of tools for data collection and interpreting changes in gene expression. Our journey extends to the latest breakthroughs, such as the TACITuS platform and the TALON pipeline, tailored for in-depth analysis of transcriptomes using long-read data. The chapter concludes by emphasizing the ever-growing significance of transcriptomics in unraveling complex biological phenomena, with a spotlight on the promising applications of next-generation sequencing. A comprehensive summary ties it all together, detailing the step-by-step protocol of transcriptome analysis, along with insights into current tools, their advantages, and limitations, providing readers with a holistic understanding of their practical application and outcomes.

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Section: Introductionmentioning

confidence: 99%

Recent Advancement on In-Silico Tools for Whole Transcriptome Analysis

Niranjan,

Chandramouli,

SureshKumar

et al. 2024

Genetics

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Scope of repurposed drugs against the potential targets of the latest variants of SARS-CoV-2

Niranjan¹,

Setlur²,

Karunakaran³

et al. 2022

Struct Chem

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The unprecedented outbreak of the severe acute respiratory syndrome (SARS) Coronavirus-2, across the globe, triggered a worldwide uproar in the search for immediate treatment strategies. With no specific drug and not much data available, alternative approaches such as drug repurposing came to the limelight. To date, extensive research on the repositioning of drugs has led to the identification of numerous drugs against various important protein targets of the coronavirus strains, with hopes of the drugs working against the major variants of concerns (alpha, beta, gamma, delta, omicron) of the virus. Advancements in computational sciences have led to improved scope of repurposing via techniques such as structure-based approaches including molecular docking, molecular dynamic simulations and quantitative structure activity relationships, network-based approaches, and artificial intelligence-based approaches with other core machine and deep learning algorithms. This review highlights the various approaches to repurposing drugs from a computational biological perspective, with various mechanisms of action of the drugs against some of the major protein targets of SARS-CoV-2. Additionally, clinical trials data on potential COVID-19 repurposed drugs are also highlighted with stress on the major SARS-CoV-2 targets and the structural effect of variants on these targets. The interaction modelling of some important repurposed drugs has also been elucidated. Furthermore, the merits and demerits of drug repurposing are also discussed, with a focus on the scope and applications of the latest advancements in repurposing.

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