1University of Nebraska, Lincoln, USA
ORCiD: [0000-0002-9712-5824]
Keywords: phenome, genome, 3D reconstruction, climate change,
imaging, GWAS
Plant response to environmental stresses varies with time and is not
uniformly manifested across the entire plant or specific organs.
However, in most cases the phenotypic responses are measured at a single
time point and lack spatial resolution. In this study, we aimed to
develop and test a non-destructive approach to capture the dynamic plant
stress responses over a time course and with spatial resolution. We used
the rice panicle as the organ with known spatial heterogeneity and heat
stress as the environmental perturbation. We used a series of 2D RGB
images to reconstruction the rice panicle at high resolution. This
analysis was applied to the rice diversity panel and enabled us to
identify multiple loci regulating heat stress response by combining the
3D-reconstruction derived-approach digital traits with genome-wide
association analysis. We further validated this approach with gene edits
to confirm the role of the identified targets genes in heat stress
response. In summary, our results present a high spatiotemporal
resolution approach to identify digitals traits and underlying genetic
variation that is unlikely to have emerged from conventional image-based
phenotyping.