Peter A. Crisp

This study compares how genomic and epigenomic relationships contribute to genotype-by-environment interaction in grapevine clones, finding that epigenomic factors capture more GEI variance than genomic factors.

UMR-seq reveals epigenetic variation in plant hypomethylomes, showing UMRs are enriched in regulatory loci and improve genomic prediction and trait association mapping in wheat.

This study shows that knocking out PIN2 in barley alters root gravitropism and architecture without affecting shoot growth.

The paper identifies and characterizes PDI family members in sorghum to explore their domain architecture, structure, and functionality, highlighting structural differences from human PDIs.

The paper trains deep learning models on ATAC-seq and DNA methylation data from 12 and 10 angiosperm species to predict chromatin accessibility and methylation across species, finding strong conservation of chromatin mechanisms.

The paper applies machine learning to predict transcription factor-DNA interactions in maize and soybean, achieving high accuracy in maize but high false positives in soybean.

The paper uses DNA methylation profiles from a single tissue to identify unmethylated regions (UMRs) that mark expressed genes and cis-regulatory elements in plant genomes.

This study characterizes sRNA variation and inheritance in maize inbreds and F1 hybrids, revealing genotype and developmental influences on sRNA expression and non-additive inheritance patterns.

The paper describes a transgenerational epigenetic decline in vigor and viability in maize-teosinte backcross populations, termed 'hybrid decay', characterized by genomic instability and altered gene expression.