Study Info
INDA Accessions: INRP000189
INSDC Accessions: PRJEB83101, ERP166767
- Title: Fish tales of fatty liver A transcriptomic approach to understanding NAFLD
- Data Type : RNASeq
- Descriptive Title: Fish tales of fatty liver A transcriptomic approach to understanding NAFLD
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Organism:
Scientific Name(Taxon Id): Danio rerio (7955) Common Name: zebrafish
Other Info
- Abstract: Background: Non-alcoholic fatty liver disease is a significant global health concern, affecting millions and characterized by its complexity as a multifaceted disease. Despite its prevalence, the underlying molecular mechanisms remain poorly understood. Methods: Here, we propose a novel diet-induced zebrafish model to investigate NAFLD. We validate this model through a series of histological examinations and molecular assessments, allowing us to explore the intricate pathways involved in the disease. We employ transcriptomic analysis to identify novel players associated with NAFLD progression. Results: Our findings demonstrate that zebrafish subjected to a high-fat diet exhibit weight gain, while Oil Red O staining confirms significant fat deposition in the liver. Quantitative PCR analysis reveals increased expression of lipogenic genes such as acc, fasn, hmgcs1, hmgcra, alongside markers of endoplasmic reticulum stress such as atf6, xbp1, gadd45a, ddit3 and mitochondrial unfolded protein response genes such as hspd1, hspa9, clpp, lonp1, indicating mitochondrial dysfunction which includes increased expression of genes encoding oxphos complexes, uqcrc2, cox4i1, atp5f1b. Transcriptomic profiling uncovers novel markers such as inha, gck, ces2a, id3 and dysregulated pathways related to metabolism, insulin signaling, and cellular stress responses. Conclusions: This study successfully establishes a zebrafish model that replicates key features of NAFLD, including histopathological changes and metabolic dysregulation. The validation of our model allows for a deeper exploration of the molecular landscape of NAFLD. By revealing novel biomarkers and pathways through transcriptomic analysis, our research opens new avenues for understanding the pathogenesis of NAFLD and potential therapeutic targets.
- Linked publications:
- Center Name: Debashruti Bhattacharya, Kusuma School of Biological Sciences, Indian Institute of Technology Delhi Shruti Kaushal Department of Computational Biology, Indraprastha Institute of Information Technology Barsha Chakraborty, Indian Institute of Science Education and Research Bhopal Arnab Raha, Department of Computational Biology, Indraprastha Institute of Information Technology Himanshu Shekhar, Kusuma School of Biological Sciences, Indian Institute of Technology Delhi Apurba Lal Koner, Indian Institute of Science Education and Research Bhopal Saran Kumar, Kusuma School of Biological Sciences, Indian Institute of Technology Delhi Jaspreet Kaur Dhanjal, Department of Computational Biology and Centre of Excellence for Healthcare, Indraprastha Institute of Information Technology Shilpi Minocha, Centre for Integrative Genomics, Genopode, University of Lausanne, Lausanne 1015, Switzerland and Kusuma School of Biological Sciences, Indian Institute of Technology Delhi
- Number of Base(Total) Mbp: 54,917,359,120
- Size in bytes(Total): 27,380,693,767
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