Field level evaluation of rice introgression lines for heat tolerance and validation of markers linked to spikelet fertility

Abstract

Rice lines derived from wild species and mutants can serve as a good resource for favorable alleles for heat tolerance. In all, 48 stable lines including 17 KMR3/O. rufipogon introgression lines (KMR3 ILs), 15 Swarna/O. nivara ILs (Swarna ILs) along with their parents, Nagina 22 (N22) and its 4 EMS induced mutants and 7 varieties were evaluated for heat tolerance under irrigated conditions under field in two seasons, wet season 2012 using poly cover house method and dry season 2013 using late sown method. Spikelet fertility (SF), yield per plant (YP) and heat susceptibility index (HSI) for these two traits were considered as criteria to assess heat tolerance compared to control. Four KMR3 ILs and eight Swarna ILs were identified as heat tolerant based on SF and YP and their HSIs in both wet and dry seasons. S-65 and S-70 showed low SF and high YP consistently in response to heat in both seasons. We provide evidence that SF alone may not be the best criterion to assess heat tolerance and including YP is important as lines with low SF but high YP and vice versa were identified under heat stress. Out of 49 SSR markers linked to spikelet fertility, 18 were validated for five traits. RM229 in wet season and RM430 and RM210 in dry season were significantly associated with both SF and its HSI under heat stress. RM430 was also significantly associated with both YP and its HSI in dry season. Thirty two candidate genes were identified close to nine markers associated with traits under heat stress.

Non-Structural Carbohydrates Accumulation in Contrasting Rice Genotypes Subjected to High Night Temperatures

“…Pn, gs, F 0 , F m , F v /F m , YII, NPQ, qP and ETR, suggesting unchanged photosystem II photochemistry, linear electron flux, and CO 2 assimilation, indicating that photosynthesis machinery was not the limiting factor for lower TSC and starch levels found in stem of N22 on seventy day after heading stage when compared to Quer. On the other hand, its higher sink strength when submitted to HNT can originated from its heat tolerance characteristics as reported by different authors (Mutum et al, 2016;Poli et al, 2013;Prasanth et al, 2016). Additionally, was highlighted that N22 had the strongest sink associated to accelerated senescence during stress imposing period.…”

Identification of Major Effect QTLs for Agronomic Traits and CSSLs in Rice from Swarna/Oryza nivara Derived Backcross Inbred Lines

“…Also, three lines 24S, 70S, 14-3S were identified as heat tolerant lines for spikelet fertility and YLDP in both wet and dry seasons (Prasanth et al, 2016). In present study, these five lines 14S, 24S, 70S, 166S and 14-3S were part of the set of CSSLs and they were found to have 11.5–18.6% chromosomal segments from O. nivara .…”

Identifying markers associated with yield traits in Nagina22 rice mutants grown in low phosphorus field or in alternate wet/dry conditions

“…Genetic diversity in rice is usually estimated using either quantitative data such as plant height, number of tillers and panicles, days to flowering, days to maturity and yield traits or molecular marker data such as SSR markers and ISSR markers individually (Prasanth et al, 2016;Nachimuthu et al, 2015 ;Turki et al, 2015;). Both phenotype and molecular data were used to determine genetic diversity and group genotypes using Ward-MLM method in corn (Franco et al, 2005;Ortiz et al, 2008), wheat (Geleta and Heinrich 2012), tomato (Gonçalves et al, 2009), beans (Barbé et al, 2010, capsicum (Sudré et al, 2010), banana (Pestana et al, 2011;Reis et al, 2015) and cassava (Oliveira et al, 2015).…”