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Genomic prediction can be a powerful tool to achieve greater rates of genetic gain for quantitative traits if thoroughly integrated into a breeding strategy. In rice as in other crops, the interest in genomic prediction is very strong with a number of studies addressing multiple aspects of its use, ranging from the more conceptual to the more practical. There are important considerations for the integration of genomic prediction in public breeding programs especially while integrating rice regional testing network partners for phenotyping the training sets in the partner locations. The irrigated breeding program at the International Rice Research Institute is used as a concrete example on which we provide data and R scripts to reproduce the analysis but also to highlight practical challenges regarding the use of predictions. The adage: "To someone with a hammer, everything looks like a nail" describes a common psychological pitfall that sometimes plagues the integration and application of new technologies to a discipline. In here we try to outline the benefits and bottlenecks of applying genomic prediction in an active breeding program.

Genomic prediction can be a powerful tool to achieve greater rates of genetic gain for quantitative traits if thoroughly integrated into a breeding strategy. In rice as in other crops, the interest in genomic prediction is very strong with a number of studies addressing multiple aspects of its use, ranging from the more conceptual to the more practical. In this chapter, we review the literature on rice (Oryza sativa) and summarize important considerations for the integration of genomic prediction in breeding programs. The irrigated breeding program at the International Rice Research Institute is used as a concrete example on which we provide data and R scripts to reproduce the analysis but also to highlight practical challenges regarding the use of predictions. The adage “To someone with a hammer, everything looks like a nail” describes a common psychological pitfall that sometimes plagues the integration and application of new technologies to a discipline. We have designed this chapter to help rice breeders avoid that pitfall and appreciate the benefits and limitations of applying genomic prediction, as it is not always the best approach nor the first step to increasing the rate of genetic gain in every context.

Rice 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

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.