Genetic gain for rice yield in rainfed environments in India.

The complexity of genotype × environment interactions under drought reduces heritability, which determines the effectiveness of selection for drought tolerance and development of drought tolerant varieties. Genetic progress measured through changes in yield performance over time is important in determining the efficiency of breeding programmes in which test cultivars are replaced each year on the assumption that the new cultivars will surpass the older cultivars. The goal of our study was to determine the annual rate of genetic gain for rice grain yield in a drought-prone rainfed system in a series of multi-environment trials conducted from 2005 to 2014 under the Drought Breeding Network of Indian sites in collaboration with the International Rice Research Institute (IRRI). Our results show a positive trend in grain yield with an annual genetic yield increase of about 0.68 % under irrigated control, 0.87 % under moderate reproductive stage drought stress and 1.9 % under severe reproductive stage drought stress due to breeding efforts. The study also demonstrates the effectiveness of direct selection for grain yield under both irrigated control as well as managed drought stress screening to improve yield in typical rainfed systems. IRRI's drought breeding programme has exhibited a significant positive trend in genetic gain for grain yield over the years under both drought stress as well as favorable irrigated control conditions. Several drought tolerant varieties released from the programme have outperformed the currently grown varieties under varied conditions in the rainfed environments on farmers' fields.

QTL x environment interactions in rice. I. heading date and plant height.

One hundred twenty six doubled-haploid (DH) rice lines were evaluated in nine diverse Asian environments to reveal the genetic basis of genotype x environment interactions (GEI) for plant height (PH) and heading date (HD). A subset of lines was also evaluated in four water-limited environments, where the environmental basis of G x E could be more precisely defined. Responses to the environments were resolved into individual QTL x environment interactions using replicated phenotyping and the mixed linear-model approach. A total of 37 main-effect QTLs and 29 epistatic QTLs were identified. On average, these QTLs were detectable in 56% of the environments. When detected in multiple environments, the main effects of most QTLs were consistent in direction but varied considerably in magnitude across environments. Some QTLs had opposite effects in different environments, particularly in water-limited environments, indicating that they responded to the environments differently. Inconsistent QTL detection across environments was due primarily to non- or weak-expression of the QTL, and in part to significant QTL x environment interaction effects in the opposite direction to QTL main effects, and to pronounced epistasis. QTL x environment interactions were trait- and gene-specific. The greater GEI for HD than for PH in rice were reflected by more environment-specific QTLs, greater frequency and magnitude of QTL x environment interaction effects, and more pronounced epistasis for HD than for PH. Our results demonstrated that QTL x environment interaction is an important property of many QTLs, even for highly heritable traits such as height and maturity. Information about QTL x environment interaction is essential if marker-assisted selection is to be applied to the manipulation of quantitative traits.

Development of a PCR-based marker to identify rice blast resistance gene, Pi-2(t), in a segregating population.

The genomic clone RG64, which is tightly linked to the blast resistance gene Pi-2(t) in rice, provides means to perform marker-aided selection in a rice breeding program. The objective of this study was to investigate the possibility of generating a polymerase chain reaction (PCR)-based polymorphic marker that can distinguish the blast resistant gene, Pi-2(t), and susceptible genotypes within cultivated rice. RG64 was sequenced, and the sequence data was used to design pairs of specific primers for (PCR) amplification of genomic DNA from rice varieties differing in their blast disease responsiveness. The amplified products, known as sequenced-tagged-sites (STSs), were not polymorphic between the three varieties examined. However, cleavage of the amplified products with the restriction enzyme HaeIII generated a polymorphic fragment, known as specific amplicon polymorphism (SAP), between the resistant and the susceptible genotypes. To examine the power of the identified SAP marker in predicting the genotype of the Pi-2 (t) locus, we determined the genotypes of the F2 individuals at this locus by performing progeny testing for the disease response in the F3 generation. The results indicated an accuracy of more than 95% in identifying the resistant plants, which was similar to that using RG64 as the hybridization probe. The identification of the resistant homozygous plants increased to 100% when the markers flanking the genes were considered simultaneously. These results demonstrate the utility of SAP markers as simple and yet reliable landmarks for use in marker-assisted selection and breeding within cultivated rice.