Flowering response of rice to photoperiod and temperature: a QTL analysis using a phenological model

Abstract

In this study we have attempted to quantify the thermal and photoperiodical responses of rice (Oryza sativa L.) flowering time QTLs jointly by a 'date-of-planting' field experiment of a mapping population, and a 'phenological model' analysis that separately parameterizes the two responses, based on daily temperature, daily photoperiod and flowering date. For this purpose, the 'three-stage Beta model', which parameterizes the sensitivity to temperature (parameter alpha), the sensitivity to photoperiod (parameter beta), and earliness under optimal conditions (10 h photoperiod at 30 degrees C) (parameter G), was applied to 'Nipponbare' x 'Kasalath' backcross inbred lines that were transplanted on five dates. QTLs for the beta value were detected in the four known flowering time QTL (Hd1, Hd2, Hd6 and Hd8) regions, while QTLs for the G value were detected only in the Hd1 and Hd2 regions. This result was consistent with previous reports on near-isogenic lines (NILs) of Hd1, Hd2 and Hd6, where these loci were involved in photoperiod sensitivity, and where Hd1 and Hd2 conferred altered flowering under both 10 and 14 h photoperiods, while Hd6 action was only affected by the 14 h photoperiod. Hd8 was shown to control photoperiod sensitivity for the first time. Interestingly, Hd1 and Hd2 were associated with a QTL for the alpha value, which might support the previous hypothesis that the process of photoinduction depends on temperature. These results demonstrate that our approach can effectively quantify environmental responses of flowering time QTLs without controlled environments or NILs.

Mapping quantitative trait loci for nitrogen uptake and utilization efficiency in rice (Oryza sativa L.) at different nitrogen fertilizer levels

“…With the development of molecular techniques and successful establishment of highdensity molecular genetic linkage map, quantitative trait locus (QTL) analysis has become an important method for genetic research of complex quantitative traits and has been widely used for most agronomic traits in rice (Nakagawa et al, 2005;Yoshinobu et al, 2007;Fujita et al, 2012;Liu et al, 2006;2013). However, there are few reports on its application for investigating nitrogen uptake and utilization characteristics (Senthilvel, 1999;Senthilvel et al, 2001;Fang et al, 2001;Shan et al, 2005).…”

Modelling Gene-Trait-Crop Relationships: Past Experiences and Future Prospects

“…The same approach for QTL-based modelling analyses was applied to crop traits such as leaf elongation rate in maize (Reymond et al, 2003) and flowering time in barley , rice (Nakagawa et al, 2005) and Brassica oleracea (Uptmoor et al, 2008), and fruit quality in peach (Quilot et al, 2004(Quilot et al, , 2005 and tomato (Bertin et al, 2010;Prudent et al, 2011), all relatively simple traits with well-defined influences of some dominant environmental factors (such as vapour pressure deficit, soil moisture content, temperature and photoperiod). In the domain of morphological traits, the phenotypic effects of QTL for culm length, grain number, and grain size in barley have been simulated using morphologically explicit models (Buck-Sorlin, 2002).…”

Genetic studies of transgenic rice plants overproducing an antibacterial peptide show that a high level of transgene expression did not cause inferior effects on host plants

“…No locus affecting flowering time has been found around P0436E04.11 gene based on the search using Gramene database (http://acorn.cshl.org/qtl/help. html) and a recent report on flowering time (Nakagawa et al 2005).…”