Integrating Image-Based Phenomics and Association Analysis to Dissect the Genetic Architecture of Temporal Salinity Responses in Rice

Abstract

Salinity affects a significant portion of arable land and is particularly detrimental for irrigated agriculture, which provides onethird of the global food supply. Rice (Oryza sativa), the most important food crop, is salt sensitive. The genetic resources for salt tolerance in rice germplasm exist but are underutilized 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 d 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 was 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, to our knowledge, 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.

Salinity tolerance loci revealed in rice using high-throughput non-invasive phenotyping

“…1). Comparing the percentage decrease in salt-treated plants relative to control plants at each interval, consistent with the results of Campbell et al 16, we found that indica lines maintained better growth than aus lines (Fig. 1c,d; Supplementary Table 1); for example, in the interval 2–6 days after treatment, growth of indica due to salinity decreased by 21%, while that of aus decreased by 29%.…”

“…To date, few genetic studies have used high time- and spatial-resolution non-destructive image-based phenotyping to address the complex response of plants to abiotic stresses1316. In this work, we have demonstrated the effectiveness of high-throughput phenotyping for dissecting the genetic architecture of complex traits such as RGR, TR and TUE, and the effects of salinity on these parameters.…”

Dynamic Quantitative Trait Locus Analysis of Plant Phenomic Data

“…Recently, Campbell et al [32] conducted an association analysis on 360 rice lines with 26 258 SNPs to understand the genetic mechanism of the dynamics of rice responses to salt stress. The…”

3D sorghum reconstructions from depth images identify QTL regulating shoot architecture

“…A variety of noncommercial platforms and methods developed by the research community also exist and have been demonstrated to perform well (White et al, 2012;Fiorani and Schurr, 2013;Sirault et al, 2013;Pound et al, 2014). Several platforms have been deployed at sufficiently large scale to examine genomic loci underlying complex traits in crop plants such as barley (Hordeum vulgare; Honsdorf et al, 2014), pepper (Capsicum annuum; van der Heijden et al, 2012), maize (Zea mays; Liu et al, 2011), rice (Oryza sativa; Campbell et al, 2015), and wheat (Triticum aestivum; Rasheed et al, 2014). These successful applications of image-based phenotyping to understand the genetic bases of complex crop traits represent only a small fraction of the imaging modalities and crop species available for study.…”