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

SpeedFlower: a comprehensive speed breeding protocol for indica and japonica rice

To increase rice yields and feed billions of people, it is essential to enhance genetic gains. However, the development of new varieties is hindered by longer generation times and seasonal constraints. To address these limitations, a speed breeding facility has been established and a robust speed breeding protocol, SpeedFlower is developed that allows growing 4-5 generations of indica and/or japonica rice in a year. Our findings reveal that a high red-to-blue (2R > 1B) spectrum ratio, followed by green, yellow and far-red (FR) light, along with a 24-h long day (LD) photoperiod for the initial 15 days of the vegetative phase, facilitated early flowering. This is further enhanced by 10-h short day (SD) photoperiod in the later stage and day and night temperatures of 32/30 °C, along with 65% humidity facilitated early flowering ranging from 52 to 60 days at high light intensity (800 μmol m-2 s-1). Additionally, the use of prematurely harvested seeds and gibberellic acid treatment reduced the maturity duration by 50%. Further, SpeedFlower was validated on a diverse subset of 198 rice accessions from 3K RGP panel encompassing all 12 distinct groups of Oryza sativa L. classes. Our results confirmed that using SpeedFlower one generation can be achieved within 58-71 days resulting in 5.1-6.3 generations per year across the 12 sub-groups. This breakthrough enables us to enhance genetic gain, which could feed half of the world's population dependent on rice.

Genetic gains in IRRI's rice salinity breeding and elite panel development as a future breeding resource

KEY MESSAGE

Estimating genetic gains and formulating a future salinity elite breeding panel for rice pave the way for developing better high-yielding salinity tolerant lines with enhanced genetic gains. Genetic gain is a crucial parameter to check the breeding program's success and help optimize future breeding strategies for enhanced genetic gains. To estimate the genetic gains in IRRI's salinity breeding program and identify the best genotypes based on high breeding values for grain yield (kg/ha), we analyzed the historical data from the trials conducted in the IRRI, Philippines and Bangladesh. A two-stage mixed-model approach accounting for experimental design factors and a relationship matrix was fitted to obtain the breeding values for grain yield and estimate genetic trends. A positive genetic trend of 0.1% per annum with a yield advantage of 1.52 kg/ha was observed in IRRI, Philippines. In Bangladesh, we observed a genetic gain of 0.31% per annum with a yield advantage of 14.02 kg/ha. In the released varieties, we observed a genetic gain of 0.12% per annum with a 2.2 kg/ha/year yield advantage in the IRRI, Philippines. For the Bangladesh dataset, a genetic gain of 0.14% per annum with a yield advantage of 5.9 kg/ha/year was observed in the released varieties. Based on breeding values for grain yield, a core set of the top 145 genotypes with higher breeding values of > 2400 kg/ha in the IRRI, Philippines, and > 3500 kg/ha in Bangladesh with a reliability of > 0.4 were selected to develop the elite breeding panel. Conclusively, a recurrent selection breeding strategy integrated with novel technologies like genomic selection and speed breeding is highly required to achieve higher genetic gains in IRRI's salinity breeding programs.

Realized Genetic Gain in Rice: Achievements from Breeding Programs

Genetic improvement is crucial for ensuring food security globally. Indeed, plant breeding has contributed significantly to increasing the productivity of major crops, including rice, over the last century. Evaluating the efficiency of breeding strategies necessitates a quantification of this progress. One approach involves assessing the genetic gain achieved through breeding programs based on quantitative traits. This study aims to provide a theoretical understanding of genetic gain, summarize the major results of genetic gain studies in rice breeding, and suggest ways of improving breeding program strategies and future studies on genetic gain. To achieve this, we present the concept of genetic gain and the essential aspects of its estimation. We also provide an extensive literature review of genetic gain studies in rice (Oryza sativa L.) breeding programs to understand the advances made to date. We reviewed 29 studies conducted between 1999 and 2023, covering different regions, traits, periods, and estimation methods. The genetic gain for grain yield, in particular, showed significant variation, ranging from 1.5 to 167.6 kg/ha/year, with a mean value of 36.3 kg/ha/year. This translated into a rate of genetic gain for grain yield ranging from 0.1% to over 3.0%. The impact of multi-trait selection on grain yield was clarified by studies that reported genetic gains for other traits, such as plant height, days to flowering, and grain quality. These findings reveal that while breeding programs have achieved significant gains, further improvements are necessary to meet the growing demand for rice. We also highlight the limitations of these studies, which hinder accurate estimations of genetic gain. In conclusion, we offer suggestions for improving the estimation of genetic gain based on quantitative genetic principles and computer simulations to optimize rice breeding strategies.

Population improvement via recurrent selection drives genetic gain in upland rice breeding

One of the main challenges of breeding programs is to identify superior genotypes from a large number of candidates. By gradually increasing the frequency of favorable alleles in the breeding population, recurrent selection improves the population mean for target traits, increasing the chance to identify promising genotypes. In rice, population improvement through recurrent selection has been used very little to date, except in Latin America. At Embrapa (Brazilian Agricultural Research Corporation), the upland rice breeding program is conducted in two phases: population improvement followed by product development. In this study, the CNA6 population, evaluated over five cycles (3 to 7) of selection, including 20 field trials, was used to assess the realized genetic gain. A high rate of genetic gain was observed for grain yield, at 215 kg.ha-1 per cycle or 67.8 kg.ha-1 per year (3.08%). The CNA6 population outperformed the controls only for the last cycle, with a yield difference of 1128 kg.ha-1. An analysis of the product development pipeline, based on 29 advanced yield trials with lines derived from cycles 3 to 6, showed that lines derived from the CNA6 population had high grain yield, but did not outperform the controls. These results demonstrate that the application of recurrent selection to a breeding population with sufficient genetic variability can result in significant genetic gains for quantitative traits, such as grain yield. The integration of this strategy into a two-phase breeding program also makes it possible to increase quantitative traits while selecting for other traits of interest.

Tools for using the International Rice Genebank to breed for climate-resilient varieties

Traditional rice varieties have been critical for developing improved stress-tolerant rice varieties. Tools to analyze the genome sequences of traditional varieties are accelerating the identification and deployment of genes conferring climate change resilience.

Improving blast resistance of maintainer line DRR 9B by transferring broad spectrum resistance gene Pi2 by marker assisted selection in rice

Hybrid rice technology offers great promise to further enhance rice production and productivity for global food security. Improving hybrid rice parental lines is the first step in developing heterotic rice hybrids. To improve resistance against blast disease, a maintainer line DRR 9B was fortified with a major broad-spectrum blast resistance gene Pi2 through marker-assisted selection. The rice blast caused by Magnaporthe oryzae is a major disease and can cause severe yield losses upto 100%. The NILs of Samba Mahsuri namely BA-23-11-89-12-168 possessing Pi2 was utilized as a donor parent. The PCR-based molecular marker tightly linked to Pi2 gene was used for the foreground selection at BC₁F₁ generation. The molecular marker tightly linked to the major fertility restorer gene Rf4 was used for negative selection (i.e., selection of plants possessing non fertility restoring alleles) at BC₁F₁ generation to identify maintainer lines. The positive plants with Rf4 gene were added to the restorer pool for restorer line development. At each stage, MAS for Pi2 coupled with stringent phenotypic selection for agro-morphological and grain quality traits were exercised. At BC₁F₃ generation, one hundred families were screened against blast disease at uniform blast nursery (UBN) and selected resistant lines were advanced to next generations. In the BC₁F₅ generation plants were subjected to agro-morphological evaluation for yield and yield-contributing traits. The selected plants at BC₁F₅ generation were crossed with DRR 9A to assess the maintainer ability of blast resistance lines and for further CMS line conversion for hybrid rice breeding for developing blast resistance rice hybrids.

Climate change challenges, plant science solutions

Climate change is a defining challenge of the 21st century, and this decade is a critical time for action to mitigate the worst effects on human populations and ecosystems. Plant science can play an important role in developing crops with enhanced resilience to harsh conditions (e.g. heat, drought, salt stress, flooding, disease outbreaks) and engineering efficient carbon-capturing and carbon-sequestering plants. Here, we present examples of research being conducted in these areas and discuss challenges and open questions as a call to action for the plant science community.

Enhancing genetic gain through the application of genomic selection in developing irrigated rice for the favorable ecosystem in Bangladesh

Increasing selection differential and decreasing cycle time, the rate of genetic improvement can be accelerated. Creating and capturing higher genetic with higher accuracy within the shortest possible time is the prerequisite for enhancing genetic gain for any trait. Comprehensive yield testing at multi-locations at early generations together with the shortest line fixation time can expedite the rapid recycling of parents in the breeding program through recurrent selection. Genomic selection is efficient in capturing high breeding value individuals taking additive genetic effects of all genes into account with and without extensive field testing, thus reducing breeding cycle time enhances genetic gain. In the Bangladesh Rice Research Institute, GS technology together with the trait-specific marker-assisted selection at the early generation of RGA-derived breeding lines showed a prediction accuracy of 0.454-0.701 with 0.989-2.623 relative efficiency over the four consecutive years of exercise. This study reports that the application of GS together with trait-specific MAS has expedited the yield improvement by 117 kg ha^-1·year^-1, which is around seven-fold larger than the baseline annual genetic gain and shortened the breeding cycle by around 1.5 years from the existing 4.5 years.

50 years of rice breeding in Bangladesh: genetic yield trends

To assess the efficiency of genetic improvement programs, it is essential to assess the genetic trend in long-term data. The present study estimates the genetic trends for grain yield of rice varieties released between 1970 and 2020 by the Bangladesh Rice Research Institute. The yield of the varieties was assessed from 2001-2002 to 2020-2021 in multi-locations trials. In such a series of trials, yield may increase over time due to (i) genetic improvement (genetic trend) and (ii) improved management or favorable climate change (agronomic/non-genetic trend). In both the winter and monsoon seasons, we observed positive genetic and non-genetic trends. The annual genetic trend for grain yield in both winter and monsoon rice varieties was 0.01 t ha^-1, while the non-genetic trend for both seasons was 0.02 t ha^-1, corresponding to yearly genetic gains of 0.28% and 0.18% in winter and monsoon seasons, respectively. The overall percentage yield change from 1970 until 2020 for winter rice was 40.96%, of which 13.91% was genetic trend and 27.05% was non-genetic. For the monsoon season, the overall percentage change from 1973 until 2020 was 38.39%, of which genetic and non-genetic increases were 8.36% and 30.03%, respectively. Overall, the contribution of non-genetic trend is larger than genetic trend both for winter and monsoon seasons. These results suggest that limited progress has been made in improving yield in Bangladeshi rice breeding programs over the last 50 years. Breeding programs need to be modernized to deliver sufficient genetic gains in the future to sustain Bangladeshi food security.

Introgression of tsv1 improves tungro disease resistance of a rice variety BRRI dhan71

Rice Tungro disease poses a threat to rice production in Asia. Marker assisted backcross breeding is the most feasible approach to address the tungro disease. We targeted to introgress tungro resistance locus tsv1 from Matatag 1 into a popular but tungro susceptible rice variety of Bangladesh, BRRI dhan71. The tsv1 locus was traced using two tightly linked markers RM336 and RM21801, and background genotyping was carried out using 7 K SNPs. A series of three back crosses followed by selfing resulted in identification of plants similar to BRRI dhan71. The background recovery varied at 91-95% with most of the lines having 95%. The disease screening of the lines showed moderate to high level of tungro resistance with a disease index score of ≤ 5. Introgression Lines (ILs) had medium slender grain type, and head rice recovery (59.2%), amylose content (20.1%), gel consistency (40.1 mm) and gelatinization temperature were within the acceptable range. AMMI and Kang's stability analysis based on multi-location data revealed that multiple selected ILs outperformed BRRI dhan71 across the locations. IR144480-2-2-5, IR144483-1-2-4, IR144484-1-2-2 and IR144484-1-2-5 are the most promising lines. These lines will be further evaluated and nominated for varietal testing in Bangladesh.

Optimizing predictions in IRRI's rice drought breeding program by leveraging 17 years of historical data and pedigree information

Prediction models based on pedigree and/or molecular marker information are now an inextricable part of the crop breeding programs and have led to increased genetic gains in many crops. Optimization of IRRI's rice drought breeding program is crucial for better implementation of selections based on predictions. Historical datasets with precise and robust pedigree information have been a great resource to help optimize the prediction models in the breeding programs. Here, we leveraged 17 years of historical drought data along with the pedigree information to predict the new lines or environments and dissect the G × E interactions. Seven models ranging from basic to proposed higher advanced models incorporating interactions, and genotypic specific effects were used. These models were tested with three cross-validation schemes (CV1, CV2, and CV0) to assess the predictive ability of tested and untested lines in already observed environments and tested lines in novel or new environments. In general, the highest prediction abilities were obtained when the model accounting interactions between pedigrees (additive) and environment were included. The CV0 scheme (predicting unobserved or novel environments) reveals very low predictive abilities among the three schemes. CV1 and CV2 schemes that borrow information from the target and correlated environments have much higher predictive abilities. Further, predictive ability was lower when predicting lines in non-stress conditions using drought data as training set and/or vice-versa. When predicting the lines using the data sets under the same conditions (stress or non-stress data sets), much better prediction accuracy was obtained. These results provide conclusive evidence that modeling G × E interactions are important in predictions. Thus, considering G × E interactions would help to build enhanced genomic or pedigree-based prediction models in the rice breeding program. Further, it is crucial to borrow the correlated information from other environments to improve prediction accuracy.

Genomic Regions and Floral Traits Contributing to Low Temperature Tolerance at Young Microspore Stage in a Rice (Oryza sativa L.) Recombinant Inbred Line Population of Sherpa/IRAT109

Aerobic rice production (AP) consumes less water compared to flooded systems. Developing genotypes and identifying genomic regions associated with low temperature (LT) tolerance at the young microspore stage (YMS) is imperative for AP, particularly for temperate regions. Using a recombinant inbred line population derived from the Australian LT tolerant variety Sherpa, experiments were conducted to map and dissect quantitative trait loci (QTL) associated with spikelet sterility (SS) after exposure to LT and to investigate floral traits contributing to the development of lower SS. Significant genotypic variation for SS was observed in the population after exposure to LT at YMS. Three genomic regions associated with SS, qYMCT3, qYMCT4, and qYMCT8.1 were identified in chromosomes 3, 4, and 8 respectively, using multiple QTL models explaining 22.4% of the genotypic variation. Introgression of the favorable allele from qYMCT3 was estimated to reduce SS by up to 15.4%. A co-locating genomic region with qYMCT3, qDTHW3.1 was identified as the major QTL affecting days to heading and explained as much as 44.7% of the genotypic variation. Whole-genome sequence and bioinformatic analyses demonstrated OsMADS50 as the candidate gene for qYMCT3/qDTHW3.1 and to our knowledge, this was the first attempt in connecting the role of OsMADS50 in both LT and flowering in rice. Differential sets selected for extreme SS showed LT tolerant genotype group produced higher total pollen per spikelet resulting in a higher number of dehisced anthers and pollen on stigma and eventually, lower SS than THE sensitive group. The relationship between these key floral traits with SS was induced only after exposure to LT and was not observed in warm ideal temperature conditions. Identification of elite germplasm with favorable QTL allele and combinations, gene cloning, and pyramiding with additional high-value QTL for key traits should empower breeders to develop AP adapted genotypes for temperate growing regions, and ultimately produce climate-resilient rice.