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Journal of Experimental Zoology Part B Molecular and Developmental EvolutionSystems BiologyPeer-reviewed journal article

From Genes to Pathways: A Curated Gene Approach to Accurate Pathway Reconstruction in Teleost Fish Transcriptomics

Marcela HerreraiD, Stefano VianelloiD, Laurie J. MitchelliD, Zoé ChamotiD, Catherine Lorin‐NebeliD, Edith BonnelyeiD, Natacha RouxiD, Laurence Besseau AiD, Yann GibertiD, Vincent LaudetiD

PDFDOIPreprint

Abstract

Interpreting the vast amounts of data generated by high-throughput sequencing technologies can often present a significant challenge, particularly for non-model organism. While automated approaches like GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analyses are widely used, they often lack specificity for non-model organisms. To bridge this gap, we present a manually curated gene list tailored for teleost fish transcriptomics. This resource focuses on key biological processes crucial for understanding teleost fish physiology, development, and adaptation, including hormone signaling, various metabolic pathways, appetite regulation, digestion, gastrointestinal function, vision, ossification, osmoregulation, and pigmentation. Developed through collaborative efforts of specialists in diverse fields, the list prioritizes genes with established roles in teleost physiology, experimental evidence, and conservation across species. This curated list aims to provide researchers with a reliable starting point for transcriptomic analyses, offering a carefully evaluated set of genes relevant to current research priorities. By streamlining the process of gene selection and interpretation, this resource supports the broader teleost fish research community in designing and analyzing studies that investigate molecular responses to developmental and environmental changes. We encourage the scientific community to collaboratively expand and refine this list, ensuring its continued relevance and utility for teleost fish research.

Citations
15
FWCI
4.48
Field percentile
top 4%

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