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A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

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Tracking difference in gene expression in a time-course experiment using gene set enrichment analysis.

Pui Shan Wong¹, Michihiro Tanaka², Yoshihiko Sunaga³

¹CBRC, National Institute of AIST, Tokyo, Japan.

|October 1, 2014

Summary

This study explores lipid accumulation in the diatom Fistulifera sp. JPCC DA0580, identifying key metabolic pathways for biofuel production. Gene expression analysis reveals distinct temporal gene upregulation during growth and oil accumulation.

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Area of Science:

Biotechnology
Marine Biology
Metabolic Engineering

Background:

Fistulifera sp. strain JPCC DA0580 is a unique pennate diatom capable of simultaneous growth and high-level lipid accumulation (40-60% cell weight).
This trait makes it a promising candidate for sustainable biofuel production.
Understanding the genetic and metabolic basis of this lipid accumulation is crucial for optimizing its application.

Purpose of the Study:

To investigate the relationship between gene expression and metabolic functions during lipid accumulation in Fistulifera sp. strain JPCC DA0580.
To identify key metabolic pathways involved in growth and lipid synthesis using transcriptomic data.
To develop and apply novel analytical methods for time-course gene expression data in microalgae.

Main Methods:

RNA-Seq was performed on Fistulifera sp. strain JPCC DA0580 at four time points under oil-accumulating and non-oil-accumulating conditions.
Gene Set Enrichment Analysis (GSEA) was adapted using KEGG pathways and resampling to analyze 7,822 genes.
Network visualization of metabolic pathways combined with expression data was used to identify key reactions and pathways.

Main Results:

GSEA identified photosynthesis, lipid synthesis, and amino acid synthesis pathways as significant for oil production and growth.
Network analysis revealed a distinct, non-concerted temporal upregulation of genes.
Two novel, more efficient metabolic pathways for triacylglycerol (TAG) production were identified and shown to be upregulated.

Conclusions:

The study successfully analyzed time-course transcriptomic data to understand lipid accumulation in Fistulifera sp. strain JPCC DA0580.
Key metabolic pathways and temporal gene expression patterns influencing biofuel precursor synthesis were elucidated.
Novel metabolic pathways offer new hypotheses for enhancing lipid production in microalgae.