Tensor decomposition reveals trans-regulated gene modules in maize drought response.

Area of Science:

• Plant genetics
• Genomics
• Bioinformatics

Background:

• Plants exhibit dynamic cellular and gene expression changes under drought stress, often involving trans-regulation.
• Detecting trans-acting genetic variants and gene networks is complex due to the high number of genes and markers.

Purpose of the Study:

• To develop and apply a novel method for identifying trans-acting expression quantitative trait loci (trans-eQTLs) linked to gene modules in maize.
• To associate these gene modules with drought response traits and understand the genetic basis of plant adaptation to drought.

Main Methods:

• Utilized tensor decomposition to identify trans-eQTLs associated with gene modules.
• Performed module-to-trait association analysis to link gene modules to drought-related traits.
• Conducted genome-wide association studies on module expression patterns to identify trans-eQTLs.

Main Results:

• Identified trans-eQTLs linked to gene modules associated with maize drought response.
• Found that half of the analyzed gene modules were relevant to drought-related traits.
• Discovered 286 trans-eQTLs linked to drought-responsive modules, with most undetectable via individual gene expression analysis.
• Observed stronger selection signals in trans-eQTL regions that were selected during maize improvement.

Conclusions:

• Multidimensional reduction techniques, like tensor decomposition, can effectively identify trans-acting variations in gene expression under dynamic environmental conditions.
• This approach offers a promising strategy for processing high-order data in crop breeding, particularly for enhancing drought tolerance.