Genetic Analysis of Drought Resistance in Rice by Molecular Markers

Abstract

Drought stress is the major constraint to rice (Oryza sativa L.) production and yield stability in rainfed ecosystems. Identifying genomic regions contributing to drought resistance will help develop rice cultivars suitable for rainfed regions through molecular marker assisted breeding. Quantitative trait loci (QTLs) linked to plant water stress indicators, phenology and production traits under irrigated and drought stress conditions were mapped by means of a doubled‐haploid (DH) population of 154 rice lines from the cross CT9993‐5‐10‐1‐M/IR62266‐42‐6‐2. The DH lines were subjected to water stress before anthesis in three field experiments at two locations. The DH lines showed significant variation for plant water stress indicators, phenology, plant biomass, yield and yield components under irrigated control and water stress. A total of 47 QTLs were identified for various plant water stress indicators, phenology, and production traits under control and water stress conditions in the field, which individually explained 5 to 59% of the phenotype variation. A region was identified on chromosome 4 that harbored major QTLs for plant height, grain yield, and number of grains per panicle under drought stress. By comparing the coincidence of QTLs with specific traits, we also genetically dissected the nature of association of root traits and capacity for osmotic adjustment with rice production under drought. Root traits had positive correlations with yield and yield components under drought stress. This study demonstrated that the region RG939‐RG476‐RG214 on chromosome 4 identified for root‐related drought resistance component QTLs also had pleiotropic effects on yield traits under stress. Consistent QTLs for drought resistance traits and yield under stress were detected and might be useful for marker‐assisted selection for rainfed rice improvement.

Plant drought stress: effects, mechanisms and management

“…However, this approach is far from being optimal, since yield is a quantitative trait and characterized by a low heritability and a high genotype × environment interaction (Babu et al, 2003). It is strongly believed that understanding of a physiological and molecular basis may help target the key traits that limit yield.…”

“…Selection response in the target population of environments under natural stress can be considered a correlated response to selection in the managed stress environment (Venuprasad et al, 2007). On the other hand, classical breeding is a good approach for developing drought tolerance, which relies upon multi-location testing of progenies in environments representing a random selection of the variation in drought stress in the target environment (Babu et al, 2003). A modification to this strategy involves selection for putative drought-adaptive secondary traits (Ludlow and Muchow, 1990), either alone or as part of a selection index.…”

Drought-tolerance QTLs commonly detected in two sets of reciprocal introgression lines in rice

“…The QTL QSnp3a governing SpNP was localised in the region of 3502670-4681740 on chromosome 3 and was mapped together with the rn3 for root number in PVC-pipe at mature stage (Qu et al 2008), QRvd3 for root volume, and QRgvd3 for root growth rate in volume under drought conditions (Yue et al 2006), as well as the QTL for leaf rolling score in paddy soil condition (Yue et al 2005). The QTL QSf8 influencing SF detected in the region of 19556500-20662759 on chromosome 8 was mapped together with QTLs for several DT related traits in rice across a variety of genetic backgrounds and environments, such as oa8.1 for osmotic adjustment (Nguyen et al 2004), the QTL for relative water content (Price et al 2002a), the QTL for leaf drying (Babu et al 2003), the QTL for drought response index (DRI) (Yue et al 2005), and QGy8 for grain yield under stress. The QTL QSnp11 affecting SpNP, which was located in the region of 749467-1767997 on chromosome 11, was mapped together with the QMrdd11 affecting maximum root depth and QDrvd11 for deep root rate in volume under drought conditions (Yue et al 2006) and QTLs for panicle number, filled grains per panicle, seed fertility and grain yield per plant simultaneously detected under drought and irrigated conditions at reproductive stage (Wang et al 2013).…”

“…The use of quantitative trait locus (QTL) mapping has contributed to a better understanding of the genetic basis of DT-related traits. An increasing number of QTLs related to drought response have been reported, and these include QTLs for osmotic adjustment (Robin et al 2003), grain yield and yield components (Lanceras et al 2004;Xu et al 2005;Wang et al 2013), stay-green (Jiang et al 2004), canopy temperature, leaf rolling and leaf drying (Yue et al 2005), carbon isotope discrimination (D 13 C) (Takai et al 2009;Xu et al 2009), photosynthesis parameters (Gu et al 2012), and root morphology and other root-related traits such as root penetration ability (Price et al 2002a;Babu et al 2003). The earlier approach to improve grain yield under reproductive-stage drought stress through selection based on secondary traits such as root architecture, leaf water potential, panicle water potential, osmotic adjustment, relative water content, etc.…”

Características de tolerância à seca em genótipos de uma coleção nuclear de arroz de terras altas

“…A melhoria na estabilidade da produção dos genótipos em ambientes propensos ao deficit hídrico é de grande importância para a cultura do arroz de sequeiro e pode ser feita por meio do melhoramento, pela identificação das características que possam contribuir para a tolerância à seca (Babu et al, 2003). A busca por cultivares de arroz de terras altas tolerantes à seca é reconhecida como a estratégia mais eficiente para aliviar a insegurança alimentar causada pela escassez de água (Huang et al, 2007).…”