Karl A. G. Kremling

This study shows that SPO11-1 localizes dynamically during meiotic recombination initiation in maize, and its loss affects both DSB formation and axial element structural changes.

The paper shows that combining transcriptome-wide association studies (TWAS) with genome-wide association studies (GWAS) improves the detection of genes linked to agronomic and seed quality traits in maize.

The paper uses metabolome-scale GWAS to identify genetic loci controlling maize specialized metabolites, revealing chemical diversity and gene-metabolite associations.

The paper develops deep learning methods that incorporate evolutionary relationships to predict transcript abundance from DNA sequence, achieving auROC values between 0.72 and 0.94.

The paper analyzes Tripsacum transcriptomes to compare gene evolution with maize after a shared polyploidy event, finding similar patterns of gene loss and expression conservation.

This study quantitatively analyzes the heritability of the maize leaf microbiome, finding few bacterial clades and diversity metrics are heritable, while many metabolic functions are, with Methylobacteria playing a key role.