Marcin Grzybowski

This study identifies cis-regulatory variants in maize using RNA-seq and genome-wide data, showing that haplotype-rich variants explain most expression diversity and that single-variant summaries are incomplete.

This study identifies spatially distinct heat responses in barley leaves using chlorophyll fluorescence imaging and transcriptomic profiling, revealing region-specific gene expression patterns and potential targets for improving heat resilience.

This study identifies genetic variants associated with photosynthetic traits in maize by controlling environmental and spatial confounders, revealing high-confidence GWAS signals and validating candidate genes through insertion alleles.

This study uses data-driven methods to analyze hyperspectral leaf reflectance data from maize plants, identifying genetic markers correlated with reflectance patterns and chlorophyll content.

This study uses transcriptome-wide association studies in maize to identify flowering time genes, finding TWAS detects more genes than GWAS and links gene expression to function across tissues and environments.

The paper examines genotype-specific responses of non-photochemical quenching (NPQ) to nitrogen deficit in maize, finding correlations between NPQ changes and chlorophyll a/b ratios.

This study investigates how heritable transcriptomic variation contributes to maize adaptation to temperate environments through eQTLs, sQTLs, and gene expression patterns.