Multi-environment genomic selection in rice elite breeding lines

Abstract Background: Assessing the performance of elite lines in target environments is essential for breeding programs to select the most relevant genotypes. One of the main complexities in this task resides in accounting for the genotype by environment interactions. Genomic prediction models that integrate information from multi-environment trials and environmental covariates can be efficient tools in this context. The objective of this study was to assess the predictive ability of different genomic prediction models to optimize the use of multi- environment information. We used 111 elite breeding lines representing the diversity of the International Rice Research Institute (IRRI) breeding program for irrigated ecosystems. The lines were evaluated for three traits (days to flowering, plant height, and grain yield) in 15 environments in Asia and Africa and genotyped with 882 SNP markers. We evaluated the efficiency of genomic prediction to predict untested environments using seven multi-environment models and three cross-validation scenarios. Results: The elite lines were found to belong to the indica group and more specifically the indica-1B subgroup which gathered improved material originating from the Green Revolution. Phenotypic correlations between environments were high for days to flowering and plant height (33% and 54% of pairwise correlation greater than 0.5 ) but low for grain yield (lower than 0.2 in most cases). Clustering analyses based on environmental covariates separated Asia’s and Africa's environments into different clusters or subclusters. The predictive abilities ranged from 0.06 to 0.79 for days to flowering, 0.25 to 0.88 for plant height, and -0.29 to 0.62 for grain yield. We found that models integrating genotype-by-environment interaction effects did not perform significantly better than models integrating only main effects (genotypes and environment or environmental covariates). The different cross-validation scenarios showed that, in most cases, the use of all available environments gave better results than a subset. Conclusion: Multi-environment genomic prediction models with main effects were sufficient for accurate phenotypic prediction of elite lines in targeted environments. The recommendation for the breeders is to use simple multi-environment models with all available information for routine application in breeding programs

Synthesis beyond limit

<p>Rice production needs to increase in the future in order to meet increasing demands. The development of new improved and higher yielding varieties more quickly will be needed to meet this demand. However, most rice breeding programmes in the world have not changed in several decades. In this article, we revisit the evidence in favour of using rapid generation advance (RGA) as a routine breeding method. We describe preliminary activities at the International Rice Research Institute (IRRI) to re-establish RGA on a large scale as the main breeding method for irrigated rice breeding. We also describe experiences from the early adoption at the Bangladesh Rice Research Institute. Evaluation of RGA breeding lines at IRRI for yield, flowering time and plant height indicated transgressive segregation for all traits. Some RGA lines were also higher yielding than the check varieties. The cost advantages of using RGA compared to the pedigree method were also empirically determined by performing an economic analysis. This indicated that RGA is several times more cost effective and advantages will be realized after 1 year even if facilities need to be built. Based on our experience, and previous independent research empirically testing the RGA method in rice, we recommend that this method should be implemented for routine rice breeding in order to improve breeding efficiency.</p

Association mapping in rice: basic concepts and perspectives for molecular breeding

In the last decade, association mapping (AM) has become a well-established method to detect genes and quantitative trait loci (QTLs) associated with agronomically important traits. The identification of a large number of single nucleotide polymorphisms (SNPs) from genome sequencing and concurrent development of high-throughput genotyping platforms has led to AM being widely used for a range of crops. These technologies have been used in rice (Oryza sativa) to explore the abundant diversity and there is enormous potential to identify novel QTLs for traits of interest. Due to the availability of cost-effective high-throughput SNP genotyping methods and rapid developments in rice genomics, it is inevitable that these AM approaches will become more popular in the future, especially in the context of genome-wide association studies (GWASs). In this paper, we review the fundamental concepts, critical considerations and limitations of AM focusing on rice, and reiterate the importance of accurate phenotypic data. We also include a section about connecting GWAS to molecular breeding, covering practical consideration for breeders, which is required to use GWAS results in actual rice molecular breeding programs and which has not received adequate attention in the scientific literature

The Development and Characterization of Near-Isogenic and Pyramided Lines Carrying Resistance Genes to Brown Planthopper with the Genetic Background of Japonica Rice (Oryza sativa L.)

The brown planthopper (BPH: Nilaparvata lugens St&aring;l.) is a major pest of rice, Oryza sativa, in Asia. Host plant resistance has tremendous potential to reduce the damage caused to rice by the planthopper. However, the effectiveness of resistance genes varies spatially and temporally according to BPH virulence. Understanding patterns in BPH virulence against resistance genes is necessary to efficiently and sustainably deploy resistant rice varieties. To survey BPH virulence patterns, seven near-isogenic lines (NILs), each with a single BPH resistance gene (BPH2-NIL, BPH3-NIL, BPH17-NIL, BPH20-NIL, BPH21-NIL, BPH32-NIL and BPH17-ptb-NIL) and fifteen pyramided lines (PYLs) carrying multiple resistance genes were developed with the genetic background of the japonica rice variety, Taichung 65 (T65), and assessed for resistance levels against two BPH populations (Hadano-66 and Koshi-2013 collected in Japan in 1966 and 2013, respectively). Many of the NILs and PYLs were resistant against the Hadano-66 population but were less effective against the Koshi-2013 population. Among PYLs, BPH20+BPH32-PYL and BPH2+BPH3+BPH17-PYL granted relatively high BPH resistance against Koshi-2013. The NILs and PYLs developed in this research will be useful to monitor BPH virulence prior to deploying resistant rice varieties and improve rice&rsquo;s resistance to BPH in the context of regionally increasing levels of virulence

Identification of an Elite Core Panel as a Key Breeding Resource to Accelerate the Rate of Genetic Improvement for Irrigated Rice

International audienceRice genetic improvement is a key component of achieving and maintaining food security in Asia and Africa in the face of growing populations and climate change. In this effort, the International Rice Research Institute (IRRI) continues to play a critical role in creating and disseminating rice varieties with higher productivity. Due to increasing demand for rice, especially in Africa, there is a strong need to accelerate the rate of genetic improvement for grain yield. In an effort to identify and characterize the elite breeding pool of IRRI’s irrigated rice breeding program, we analyzed 102 historical yield trials conducted in the Philippines during the period 2012–2016 and representing 15,286 breeding lines (including released varieties). A mixed model approach based on the pedigree relationship matrix was used to estimate breeding values for grain yield, which ranged from 2.12 to 6.27 t·ha −1 . The rate of genetic gain for grain yield was estimated at 8.75 kg·ha −1 year −1 (0.23%) for crosses made in the period from 1964 to 2014. Reducing the data to only IRRI released varieties, the rate doubled to 17.36 kg·ha −1 year −1 (0.46%). Regressed against breeding cycle the rate of gain for grain yield was 185 kg·ha −1 cycle −1 (4.95%). We selected 72 top performing lines based on breeding values for grain yield to create an elite core panel (ECP) representing the genetic diversity in the breeding program with the highest heritable yield values from which new products can be derived. The ECP closely aligns with the indica 1B sub-group of Oryza sativa that includes most modern varieties for irrigated systems. Agronomic performance of the ECP under multiple environments in Asia and Africa confirmed its high yield potential. We found that the rate of genetic gain for grain yield found in this study was limited primarily by long cycle times and the direct introduction of non-improved material into the elite pool. Consequently, the current breeding scheme for irrigated rice at IRRI is based on rapid recurrent selection among highly elite lines. In this context, the ECP constitutes an important resource for IRRI and NAREs breeders to carefully characterize and manage that elite diversity

Revisiting rice breeding methods – evaluating the use of rapid generation advance (RGA) for routine rice breeding

Rice production needs to increase in the future in order to meet increasing demands. The development of new improved and higher yielding varieties more quickly will be needed to meet this demand. However, most rice breeding programmes in the world have not changed in several decades. In this article, we revisit the evidence in favour of using rapid generation advance (RGA) as a routine breeding method. We describe preliminary activities at the International Rice Research Institute (IRRI) to re-establish RGA on a large scale as the main breeding method for irrigated rice breeding. We also describe experiences from the early adoption at the Bangladesh Rice Research Institute. Evaluation of RGA breeding lines at IRRI for yield, flowering time and plant height indicated transgressive segregation for all traits. Some RGA lines were also higher yielding than the check varieties. The cost advantages of using RGA compared to the pedigree method were also empirically determined by performing an economic analysis. This indicated that RGA is several times more cost effective and advantages will be realized after 1 year even if facilities need to be built. Based on our experience, and previous independent research empirically testing the RGA method in rice, we recommend that this method should be implemented for routine rice breeding in order to improve breeding efficiency