Salinity tolerance loci revealed in rice using high-throughput non-invasive phenotyping
Microsoft Excel 2007
AuthorsAl Tamimi, Nadia
Schmöckel, Sandra M.
Tester, Mark A.
KAUST DepartmentBiological and Environmental Sciences and Engineering (BESE) Division
Computational Bioscience Research Center (CBRC)
Desert Agriculture Initiative
Online Publication Date2016-11-17
Print Publication Date2016-12
Permanent link to this recordhttp://hdl.handle.net/10754/621845
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AbstractHigh-throughput phenotyping produces multiple measurements over time, which require new methods of analyses that are flexible in their quantification of plant growth and transpiration, yet are computationally economic. Here we develop such analyses and apply this to a rice population genotyped with a 700k SNP high-density array. Two rice diversity panels, indica and aus, containing a total of 553 genotypes, are phenotyped in waterlogged conditions. Using cubic smoothing splines to estimate plant growth and transpiration, we identify four time intervals that characterize the early responses of rice to salinity. Relative growth rate, transpiration rate and transpiration use efficiency (TUE) are analysed using a new association model that takes into account the interaction between treatment (control and salt) and genetic marker. This model allows the identification of previously undetected loci affecting TUE on chromosome 11, providing insights into the early responses of rice to salinity, in particular into the effects of salinity on plant growth and transpiration.
CitationAl-Tamimi N, Brien C, Oakey H, Berger B, Saade S, et al. (2016) Salinity tolerance loci revealed in rice using high-throughput non-invasive phenotyping. Nature Communications 7: 13342. Available: http://dx.doi.org/10.1038/ncomms13342.
SponsorsThe research reported in this publication was supported by funding from King Abdullah University of Science and Technology. We thank Michael Dingkuhn, Brigitte Courtois, Kenneth McNally and Julie Mae Pasuquin from the Global Rice Phenotyping Network. All seed material was kindly provided by the International Rice Genebank (International Rice Research Institute, Philippines). We thank Professor Susan McCouch (Cornell University) for providing the ‘HDRA 700kK SNPs’ data for the GWAS and analytical comments. We thank all members at The Plant Accelerator: Dr Rachel Burton, Helli Meinecke, Dr Trevor Garnett, Dr Alex Garcia, Richard Norrish, Dr Guntur Tanjung, George Sainsbury, Evi Guidolin, Robin Hosking, Lidia Mischis, Nicky Bond, Sepideh Azizi Taramsary, Kate Dowling and Fiona Groskreutz for providing technical support in the collection of phenotypic data. The Plant Accelerator, Australian Plant Phenomics Facility, is supported under the National Collaborative Research Infrastructure Strategy of the Australian Government. We thank Heno Hwang for scientific illustrations of the Smarthouses illustration of pot design. We also thank Bo Li and Inês Silva Pires for critical comments.
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