An integrated hyperspectral imaging and genome-wide association analysis platform provides spectral and genetic insights into the natural variation in rice.

ABSTRACT: With progress of genetic sequencing technology, plant genomics has experienced rapid development and subsequently triggered the progress of plant phenomics. In this study, a high-throughput hyperspectral imaging system (HHIS) was developed to obtain 1,540 hyperspectral indices at whole-plant level during tillering, heading, and ripening stages. These indices were used to quantify traditional agronomic traits and to explore genetic variation. We performed genome-wide association study (GWAS) of these indices and traditional agronomic traits in a global rice collection of 529 accessions. With the genome-level suggestive P-value threshold, 989 loci were identified. Of the 1,540 indices, we detected 502 significant indices (designated as hyper-traits) that exhibited phenotypic and genetic rela

SUBMITTER: Feng H 

PROVIDER: S-EPMC5493659 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature