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7月10日,国际植物表型学会系列webinar第5期将由顶级大牛Mark Tester的学生Nadia Al-Tamimi博士介绍其博士期间在澳大利亚国家植物表型平台植物加速器筛选水稻耐盐QTL的工作。
题目:Identification of QTLs associated with growth and transpiration under controlled conditions at The Plant Accelerator
报告人:Nadia Al-Tamimi
时间:7月10日(周五)20:00-21:00
直播平台:百博智慧直播间植物表型频道
报告内容:
High-throughput phenotyping (HTP) 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.
The contents of this work were published as a research article in Nature Communications.
The full citation is: Nadia Al-Tamimi, Chris Brien, Helena Oakey, Bettina Berger, Stephanie Saade, Yung Shwen Ho, Sandra M. Schmöckel, Mark Tester & Sónia Negrão. Salinity tolerance loci revealed in rice using high-throughput non- invasive phenotyping. (2016)Nature Communications, volume7, Article number: 13342. https://www.ncbi.nlm.nih.gov/pubmed/27853175.
报告人介绍:
Dr. Nadia Al-Tamimi is a recent PhD graduate in Plant Science Professor Mark Tester’s lab at King Abdullah University of Science &Technology (KAUST) in Saudi Arabia where she studied “The genetics of salinity tolerance in rice”. During her studies, she gained experience in high-throughput phenotyping, data collection and interpretation in addition to big data management and data visualization. She has made collaborations with various institutions such as AfricaRice in Senegal and International Rice Research Institute (IRRI) in the Philippines. She currently works as Postdoctoral researcher at University College Dublin, Dublin Ireland and has gained additional experience in field phenotyping, mentoring, data management planning and big data processing.
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