Managing Global Resources for a Secure Future

2017 Annual Meeting | Oct. 22-25 | Tampa, FL

106-1 Heat Stress Tolerance in Rice (Oryza sativa L.): Identification of Quantitative Trait Loci for Seedling Growth Under Heat Stress.

See more from this Division: C07 Genomics, Molecular Genetics and Biotechnology
See more from this Session: Genomics, Molecular Genetics and Biotechnology General Oral

Monday, October 23, 2017: 1:35 PM
Marriott Tampa Waterside, Florida Salon VI

Newton Kilasi1, Jugpreet Singh1, Qingyuan Xiang2, Tongjun Gu3, Carlos Vallejos2, Changrong Ye4, Krishna Jagadish S.V.5, Paul Kusolwa6 and Bala Rathinasabapathi7, (1)Horticultural Sciences, University of Florida, Gainesville, Gainesville, FL
(2)Horticultural Sciences, University of Florida, Gainesville, FL
(3)ICBR, University of Florida,, Gainesville, FL
(4)IRRI, Manila, Philippines
(5)Department of Agronomy, Kansas State University, Manhattan, KS
(6)Crop Science, Sokoine University of Agriculture, Morogoro, Tanzania, United Republic of
(7)University of Florida, Gainesville, Gainesville, FL
Abstract:
Productivity of rice, world’s most important cereal is threatened by high temperature stress, intensified by climate change. Development of heat stress-tolerant varieties is one of the best strategies to maintain its productivity. However, heat stress tolerance is a multigenic trait and the candidate genes are poorly known. Therefore, we aimed to identify quantitative trait loci (QTLs) for vegetative stage tolerance to heat stress in rice and prioritize candidate genes using RNA sequencing. We used genotyping-by-sequencing to generate single nucleotide polymorphic (SNP) markers for 150 F8 recombinant inbred lines obtained by crossing heat tolerant ‘N22’ and heat susceptible ‘IR64’ varieties. A linkage map was constructed using 689 recombinationally unique SNP markers in this mapping population. Heat stress tolerance was assessed by measuring shoot and root length of germinating seedlings under dark, incubated at control (28°C) and heat stress (37°C) conditions. Mapping analysis revealed a total of 15 QTL, out of which two were responsible for both root and shoot stress tolerance. These QTL contributed between 5.3 and 20.4% effect on the parameters measured. We used RNA Sequencing analysis of ‘N22’ and ‘IR64’ roots under control and stress conditions to identify potential candidate genes for heat stress tolerance.

See more from this Division: C07 Genomics, Molecular Genetics and Biotechnology
See more from this Session: Genomics, Molecular Genetics and Biotechnology General Oral

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