Merging Genomics and Transcriptomics for Predicting Fusarium Head Blight Resistance in Wheat

Area of Science:

• Plant breeding
• Genomics
• Transcriptomics
• Pathology

Background:

• Genomic selection using molecular markers is established in wheat breeding.
• Fusarium head blight (FHB) resistance in wheat is a well-studied genomic selection target.
• Transcriptomic data's potential for predictive breeding in the FHB-wheat pathosystem is unexplored.

Purpose of the Study:

• Compare genomic versus transcriptomic prediction for FHB resistance.
• Evaluate blending genomic and transcriptomic data using a single-step method.
• Assess the utility of transcriptomics in wheat breeding for FHB resistance.

Main Methods:

• Utilized a diversity panel of wheat breeding lines and cultivars.
• Performed genomic prediction using genome-wide molecular markers.
• Conducted transcriptomic prediction using gene expression data.
• Applied a single-step method to combine genomic and transcriptomic data.

Main Results:

• Gene expression data showed a substantial advantage over molecular markers for predicting FHB resistance.
• Single-step predictions improved prediction ability, primarily due to enhanced accuracy in RNA-sequenced genotypes.
• Transcriptomic data offers complementary value to existing predictive breeding pipelines.

Conclusions:

• Transcriptomics is a valuable complement to genomic and pedigree data in predictive breeding.
• Gene expression data enhances the prediction of Fusarium head blight resistance in wheat.
• Future cost-efficient RNA-sequencing techniques will increase the accessibility of transcriptomic data for breeding programs.