Integrating image-based phenomics and association analysis to dissect the genetic architecture of temporal salinity responses in rice

Authors
Campbell MT1, Knecht AC2, Berger B3, Brien CJ4, Wang D5, Walia H6

Author Affiliations
1University of Nebraska CITY: Lincoln STATE: Nebraska United States Of America [US]
2University of Nebraska CITY: Lincoln United States Of America [US]
3University of Adelaide CITY: Adelaide Australia [AU]
4University of South Australia CITY: Adelaide Australia [AU]
5University of Nebraska CITY: Lincoln United States Of America [US]
6University of Nebraska CITY: Lincoln POSTAL_CODE: 68583 United States Of America [US]

Published online before print June 2015. doi: http:/​/​dx.​doi.​org/​10.​1104/​pp.​15.​00450
Plant Physiology June 2015 pp.00450.2015

Salinity affects a significant portion of arable land and is particularly detrimental for irrigated agriculture, which provides a third of the global food supply. Rice, the most important food crop is salt-sensitive. The genetic resources for salt tolerance in rice germplasm exist but are under-utilized due to the difficulty in capturing the dynamic nature of physiological responses to salt stress. The genetic basis of these physiological responses is predicted to be polygenic. In an effort to address this challenge, we generated temporal imaging data from 378 diverse rice genotypes across 14 days of 90 mM NaCl stress and developed a statistical model to assess the genetic architecture of dynamic salinity-induced growth responses in rice germplasm. A genomic region on Chromosome 3 strongly associated with the early growth response and was captured using visible range imaging. Fluorescence imaging identified four genomic regions linked to salinity-induced fluorescence responses. A region on chromosome 1 regulates both the fluorescence shift indicative of the longer-term ionic stress and the early growth rate decline during salinity stress. We present a new approach to capture the dynamic plant responses to its environment and elucidate the genetic basis of these responses using a longitudinal genome-wide association model. More