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Plants, when exposed to sub-lethal stress (induction stress), develop the ability to withstand severe temperatures and this phenomenon is often referred to as acquired thermotolerance. Earlier it was reported that induction stress alters gene expression and brings greater adaptation to heat stress and that the genetic variability in thermotolerance is only seen upon induction stress. Based on this concept, the temperature induction response (TIR) technique has been developed to identify thermotolerant lines. By following the TIR technique, sunflower hybrid KBSH-1 parents were screened for high temperature tolerance. Seedlings of parental lines including CMS 234 A, CMS 234 B and 6 D-1 showed considerable genetic variability for thermotolerance and it was attributed to the expression of existing residual variability for stress responses. Thus, the existing variability forms the basis for identifying thermotolerant lines. The identified parental inbred lines were selected and established in the field and crossed to get F1 hybrid seeds. The KBSH-1 hybrid developed from selected variants of parental lines was compared with the original KBSH-1 for thermotolerance. The selected KBSH-1 was more tolerant compared with the original hybrid both at the seedling as well as at the plant level. The physiological and molecular basis of thermotolerance was studied in the KBSH-1 original and the hybrid developed from selected variants of parental lines. The selected hybrid exhibited high tolerance to Menadione (naphthoquinone)-induced oxidative stress. Even the methyl viologen-induced oxidative stress damage was relatively less in the selected hybrid population. The selected hybrid also showed enhanced expression of the heat shock proteins HSP 90 and HSP 104 and also accumulated higher levels of the heat shock transcription factor HSFA.

journal of experimental botany

Screening of inbred lines to develop a thermotolerant sunflower hybrid using the temperature induction response (TIR) technique: a novel approach by exploiting residual variability