Target Identification Using Single Cell RNA-Seq: Algorithms and Applications

Abstract

Target identification is a crucial step in the drug development process, significantly affecting the success rate and efficiency of bringing new therapies to market. Recent advancements in single-cell RNA sequencing and computational tools have accelerated the identification and validation of therapeutic targets by enabling a deeper understanding of disease mechanisms at the cellular level. However, challenges such as inadequate understanding of the molecular basis of certain diseases and limitations in current single-cell data analysis methods, particularly in capturing gene regulatory relationships, continue to hinder the full exploitation of these technologies in precision medicine. To this end, we aim to enhance target identification in scRNA-seq, crucial for unraveling cellular differentiation and disease mechanisms. Firstly, we develop ���scInTime���, a computational method that capitalizes on single-cell trajectory data and gene regulatory networks to accurately identify master regulators of cellular differentiation. This algorithm aims to overcome the existing challenges in mapping cell fate decisions, a critical step in advancing personalized medicine. Secondly, we propose to undertake an integrated scRNA-seq data analysis to investigate the association between pyroptosis and the severity of COVID-19. This research is expected to shed light on the immune response to SARS-CoV-2 and identify potential targets for therapeutic intervention. By focusing on the mechanisms underlying severe COVID-19 cases, we anticipate contributing to the global effort in combating the pandemic. Thirdly, we address metabolic diseases, specifically investigating the role of hepatocyte adenosine kinase in fat deposition and liver inflammation. Here, we aim to elucidate the molecular pathways that lead to excessive fat storage and inflammation in the liver, offering targets for the treatment of metabolic syndromes. Finally, we conduct a sex-based study on the role of RSPO3 in estrogen-mediated sex differences. Understanding the molecular bases of sex differences in diseases is critical for the development of gender-specific therapies and this study will contribute to that knowledge base. Overall, our goal is to leverage scRNA-seq for precise target identification, addressing significant gaps in the understanding of cellular differentiation and disease. This thesis is designed to set the stage for a series of investigations that will collectively advance our knowledge in the field and lead to novel therapeutic strategies