Di Wu

Leveraging prior biological knowledge improves prediction of tocochromanols in maize grain

This study evaluates prediction models for tocochromanol content in maize grain using genomic and transcriptomic data, finding that incorporating biological knowledge improves predictive ability.

Combining GWAS and TWAS to identify candidate causal genes for tocochromanol levels in maize grain

The paper combines GWAS and TWAS to identify 13 candidate causal genes for tocochromanol levels in maize grain, including five previously unassociated genes.

Transcriptome-wide association and prediction for carotenoids and tocochromanols in fresh sweet corn kernels

This study uses transcriptome-wide association and prediction to identify genes related to carotenoid and tocochromanol levels in sweet corn and shows transcriptomic data improve predictive models.

Genome-wide association study suggests an independent genetic basis of zinc and cadmium concentrations in fresh sweet corn kernels

This study identifies genetic factors influencing zinc and cadmium concentrations in sweet corn kernels through genome-wide association analysis.

Elemental Accumulation in Kernels of the Maize Nested Association Mapping Panel Reveals Signals of Gene by Environment Interactions

The paper measures elemental accumulation in maize kernels across environments and identifies genetic loci associated with elemental traits using QTL and GWAS.