Genetic Trends Estimation in IRRIs Rice Drought Breeding Program and Identification of High Yielding Drought-Tolerant Lines.

Estimating genetic trends using historical data is an important parameter to check the success of the breeding programs. The estimated genetic trends can act as a guideline to target the appropriate breeding strategies and optimize the breeding program for improved genetic gains. In this study, 17 years of historical data from IRRI's rice drought breeding program was used to estimate the genetic trends and assess the breeding program's success. We also identified top-performing lines based on grain yield breeding values as an elite panel for implementing future population improvement-based breeding schemes. A two-stage approach of pedigree-based mixed model analysis was used to analyze the data and extract the breeding values and estimate the genetic trends for grain yield under non-stress, drought, and in combined data of non-stress and drought. Lower grain yield values were observed in all the drought trials. Heritability for grain yield estimates ranged between 0.20 and 0.94 under the drought trials and 0.43-0.83 under non-stress trials. Under non-stress conditions, the genetic gain of 0.21% (10.22 kg/ha/year) for genotypes and 0.17% (7.90 kg/ha/year) for checks was observed. The genetic trend under drought conditions exhibited a positive trend with the genetic gain of 0.13% (2.29 kg/ha/year) for genotypes and 0.55% (9.52 kg/ha/year) for checks. For combined analysis showed a genetic gain of 0.27% (8.32 kg/ha/year) for genotypes and 0.60% (13.69 kg/ha/year) for checks was observed. For elite panel selection, 200 promising lines were selected based on higher breeding values for grain yield and prediction accuracy of > 0.40. The breeding values of the 200 genotypes formulating the core panel ranged between 2366.17 and 4622.59 (kg/ha). A positive genetic rate was observed under all the three conditions; however, the rate of increase was lower than the required rate of 1.5% genetic gain. We propose a recurrent selection breeding strategy within the elite population with the integration of modern tools and technologies to boost the genetic gains in IRRI's drought breeding program. The elite breeding panel identified in this study forms an easily available and highly enriched genetic resource for future recurrent selection programs to boost the genetic gains.

Open-source analytical pipeline for robust data analysis, visualizations and sharing in crop breeding.

BACKGROUND: Developing a systematic phenotypic data analysis pipeline, creating enhanced visualizations, and interpreting the results is crucial to extract meaningful insights from data in making better breeding decisions. Here, we provide an overview of how the Rainfed Rice Breeding (RRB) program at IRRI has leveraged R computational power with open-source resource tools like R Markdown, plotly, LaTeX, and HTML to develop an open-source and end-to-end data analysis workflow and pipeline, and re-designed it to a reproducible document for better interpretations, visualizations and easy sharing with collaborators. RESULTS: We reported the state-of-the-art implementation of the phenotypic data analysis pipeline and workflow embedded into a well-descriptive document. The developed analytical pipeline is open-source, demonstrating how to analyze the phenotypic data in crop breeding programs with step-by-step instructions. The analysis pipeline shows how to pre-process and check the quality of phenotypic data, perform robust data analysis using modern statistical tools and approaches, and convert it into a reproducible document. Explanatory text with R codes, outputs either in text, tables, or graphics, and interpretation of results are integrated into the unified document. The analysis is highly reproducible and can be regenerated at any time. The analytical pipeline source codes and demo data are available at https://github.com/whussain2/Analysis-pipeline . CONCLUSION: The analysis workflow and document presented are not limited to IRRI's RRB program but are applicable to any organization or institute with full-fledged breeding programs. We believe this is a great initiative to modernize the data analysis of IRRI's RRB program. Further, this pipeline can be easily implemented by plant breeders or researchers, helping and guiding them in analyzing the breeding trials data in the best possible way.

Linkages and Interactions Analysis of Major Effect Drought Grain Yield QTLs in Rice.

Quantitative trait loci conferring high grain yield under drought in rice are important genomic resources for climate resilient breeding. Major and consistent drought grain yield QTLs usually co-locate with flowering and/or plant height QTLs, which could be due to either linkage or pleiotropy. Five mapping populations used for the identification of major and consistent drought grain yield QTLs underwent multiple-trait, multiple-interval mapping test (MT-MIM) to estimate the significance of pleiotropy effects. Results indicated towards possible linkages between the drought grain yield QTLs with co-locating flowering and/or plant height QTLs. Linkages of days to flowering and plant height were eliminated through a marker-assisted breeding approach. Drought grain yield QTLs also showed interaction effects with flowering QTLs. Drought responsiveness of the flowering locus on chromosome 3 (qDTY3.2) has been revealed through allelic analysis. Considering linkage and interaction effects associated with drought QTLs, a comprehensive marker-assisted breeding strategy was followed to develop rice genotypes with improved grain yield under drought stress.

Traits and QTLs for development of dry direct-seeded rainfed rice varieties.

The development of rice varieties for dry direct-seeded conditions can be accelerated by selecting suitable traits. In the present investigation, traits hypothesized to be important for direct-seeded conditions in rainfed systems, including seedling emergence, early vegetative vigour, nutrient uptake, nodal root number, and root hair length and density, were characterized to study the genetic control of these traits and their relationship with grain yield under seedling- and reproductive-stage drought stress. Two BC2F4 mapping populations derived from crosses of Aus276, a drought-tolerant aus variety, with MTU1010 and IR64, high-yielding indica mega-varieties, were developed and studied to identify quantitative trait loci (QTLs) that showed large and consistent effects. A total of 26 QTLs associated with 23 traits and 20 QTLs associated with 13 traits were mapped in the Aus276/3*IR64 and Aus276/3*MTU1010 populations, respectively. qGY6.1, qGY10.1, qGY1.1, and qEVV9.1 were found to be effective in both populations under a wide range of conditions. QTLs for several seedling-stage traits co-located with QTLs for grain yield, including early vegetative vigour and root hair length. On chromosome 5, several QTLs for nutrient uptake co-located with QTLs for root hair density and nematode gall rating. Six lines were selected from both populations based on grain yield and the presence of QTLs, and these lines typically showed improved seedling-stage traits (nodal root number, dry shoot weight, and root hair length and density). The co-located QTLs identified here can be used in research aimed at increasing the yield and adaptability of rainfed rice to direct-seeded conditions.

QTLs for tolerance of drought and breeding for tolerance of abiotic and biotic stress: an integrated approach.

BACKGROUND: The coupling of biotic and abiotic stresses leads to high yield losses in rainfed rice (Oryza sativa L.) growing areas. While several studies target these stresses independently, breeding strategies to combat multiple stresses seldom exist. This study reports an integrated strategy that combines QTL mapping and phenotypic selection to develop rice lines with high grain yield (GY) under drought stress and non-stress conditions, and tolerance of rice blast. METHODOLOGY: A blast-tolerant BC2F3-derived population was developed from the cross of tropical japonica cultivar Moroberekan (blast- and drought-tolerant) and high-yielding indica variety Swarna (blast- and drought-susceptible) through phenotypic selection for blast tolerance at the BC2F2 generation. The population was studied for segregation distortion patterns and QTLs for GY under drought were identified along with study of epistatic interactions for the trait. RESULTS: Segregation distortion, in favour of Moroberekan, was observed at 50 of the 59 loci. Majority of these marker loci co-localized with known QTLs for blast tolerance or NBS-LRR disease resistance genes. Despite the presence of segregation distortion, high variation for DTF, PH and GY was observed and several QTLs were identified under drought stress and non-stress conditions for the three traits. Epistatic interactions were also detected for GY which explained a large proportion of phenotypic variance observed in the population. CONCLUSIONS: This strategy allowed us to identify QTLs for GY along with rapid development of high-yielding purelines tolerant to blast and drought with considerably reduced efforts. Apart from this, it also allowed us to study the effects of the selection cycle for blast tolerance. The developed lines were screened at IRRI and in the target environment, and drought and blast tolerant lines with high yield were identified. With tolerance to two major stresses and high yield potential, these lines may provide yield stability in rainfed rice areas.

Identification and mapping of stable QTL with main and epistasis effect on rice grain yield under upland drought stress.

BACKGROUND: Drought is one of the most important abiotic stresses that cause drastic reduction in rice grain yield (GY) in rainfed environments. The identification and introgression of QTL leading to high GY under drought have been advocated to be the preferred breeding strategy to improve drought tolerance of popular rice varieties. Genetic control of GY under reproductive-stage drought stress (RS) was studied in two BC1F4 mapping populations derived from crosses of Kali Aus, a drought-tolerant aus cultivar, with high-yielding popular varieties MTU1010 and IR64. The aim was to identify QTL for GY under RS that show a large and consistent effect for the trait. Bulk segregant analysis (BSA) was used to identify significant markers putatively linked with high GY under drought. RESULTS: QTL analysis revealed major-effect GY QTL: qDTY1.2, qDTY2.2 and qDTY1.3, qDTY2.3 (DTY; Drought grain yield) under drought consistently over two seasons in Kali Aus/2*MTU1010 and Kali Aus/2*IR64 populations, respectively. qDTY1.2 and qDTY2.2 explained an additive effect of 288 kg ha-1 and 567 kg ha-1 in Kali Aus/2*MTU1010, whereas qDTY1.3 and qDTY2.3 explained an additive effect of 198 kg ha-1 and 147 kg ha-1 in Kali Aus/2*IR64 populations, respectively.Epistatic interaction was observed for DTF (days to flowering) between regions on chromosome 2 flanked by markers RM154-RM324 and RM263-RM573 and major epistatic QTL for GY showing interaction between genomic locations on chromosome 1 at marker interval RM488-RM315 and chromosome 2 at RM324-RM263 in 2012 DS and 2013 DS RS in Kali Aus/2*IR64 mapping populations. CONCLUSION: The QTL, qDTY1.2, qDTY1.3, qDTY2.2, and qDTY2.3, identified in this study can be used to improve GY of mega varieties MTU1010 and IR64 under different degrees of severity of drought stress through marker-aided backcrossing and provide farmers with improved varieties that effectively combine high yield potential with good yield under drought. The observed epistatic interaction for GY and DTF will contribute to our understanding of the genetic basis of agronomically important traits and enhance predictive ability at an individualized level in agriculture.

Multiple major QTL lead to stable yield performance of rice cultivars across varying drought intensities.

BACKGROUND: Availability of irrigation water is becoming a major limiting factor in rice cultivation. Production in rainfed areas is affected in particular by drought events, as these areas are commonly planted to high-yielding drought-susceptible rice (Oryza sativa L.) varieties. The use of bulk segregant analysis (BSA), taking grain yield (GY) as a selection criterion, has resulted in the identification of several large-effect QTL. A QTL mapping study was undertaken on a BC1F3:4 population developed from the cross IR55419-04/2*TDK1 with the aim of identifying large-effect QTL in the background of TDK1, a popular variety from Lao PDR. RESULTS: The study identified three QTL-qDTY3.1 (RM168-RM468), qDTY6.1 (RM586-RM217), and qDTY6.2 (RM121-RM541)-for grain yield under drought. qDTY3.1 and qDTY6.1, showed consistent effect across seasons under lowland drought-stress conditions while qDTY6.1 and qDTY6.2 showed effect under both upland and lowland drought conditions. The test of QTL effect, conducted through a QTL class analysis, showed the complimentary nature of qDTY3.1 and qDTY6.1. Both QTL showed specific patterns of effect across different maturity groups within the mapping population and higher stability for grain yield was seen across stress levels for lines with both QTLs as compared to those with single or no QTL. CONCLUSIONS: The study offers a clear understanding of large-effect QTL for grain yield under drought and their effect as individual QTL and in various combinations. The study also opens up an opportunity to develop a drought-tolerant version of TDK1 through marker-assisted backcross breeding and has led to a large-scale QTL pyramiding program aiming to combine these QTL with Sub1 in the background of TDK1 as recipient variety.