Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

A novel approach to identify genes that determine grain protein deviation in cereals


ABSTRACT: Grain yield and protein content were determined for six wheat cultivars grown over three years at multiple sites and at multiple N-fertilizer inputs. Although grain protein was negatively correlated with yield, some grain samples had higher protein contents than expected based on their yields, a trait referred to as grain protein deviation (GPD). We used novel statistical approaches to calculate GPD across environment and to correlate gene expression in the developing caryopsis with this trait. The yield and protein content were initially adjusted for nitrogen fertilizer inputs, and then adjusted for yield (to remove the negative correlation) resulting in environmental corrected GPD. The transcriptome data for all samples were subjected to Principal Component Analysis (PCA) and ANOVA to id

ORGANISM(S): Triticum aestivum

SUBMITTER: Artem Lysenko 

PROVIDER: E-GEOD-59056 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

Similar Datasets