Integrative phenomics, metabolomics and genomics analysis provides new insights for deciphering the genetic basis of metabolism in polished rice.

ABSTRACT:

Background

Metabolomics is one of the most widely used omics tools for deciphering the functional networks of the metabolites for crop improvement. However, it is technically demanding and costly.

Results

We propose a relatively inexpensive approach for metabolomics analysis in which metabolomics is combined with hyperspectral imaging via machine learning. This approach can be used to target important steps in flavonoid and lipid biosynthesis in rice. We extract 1848 hyperspectral indices and 887 metabolites from polished grains of 533 Oryza sativa accessions. Hyperspectral indices are then linked to metabolites through correlation analysis and modelling. Based on this, a total of 554 metabolites and 1313 hyperspectral indices are identified for further genome-wide associati

SUBMITTER: Feng H 

PROVIDER: S-EPMC11905631 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature