Genomics-assisted breeding for successful development of multiple-stress-tolerant, climate-smart rice for southern and southeastern Asia

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.

Metabolic pathways engineering for drought or/and heat tolerance in cereals

Drought (D) and heat (H) are the two major abiotic stresses hindering cereal crop growth and productivity, either singly or in combination (D/+H), by imposing various negative impacts on plant physiological and biochemical processes. Consequently, this decreases overall cereal crop production and impacts global food availability and human nutrition. To achieve global food and nutrition security vis-a-vis global climate change, deployment of new strategies for enhancing crop D/+H stress tolerance and higher nutritive value in cereals is imperative. This depends on first gaining a mechanistic understanding of the mechanisms underlying D/+H stress response. Meanwhile, functional genomics has revealed several stress-related genes that have been successfully used in target-gene approach to generate stress-tolerant cultivars and sustain crop productivity over the past decades. However, the fast-changing climate, coupled with the complexity and multigenic nature of D/+H tolerance suggest that single-gene/trait targeting may not suffice in improving such traits. Hence, in this review-cum-perspective, we advance that targeted multiple-gene or metabolic pathway manipulation could represent the most effective approach for improving D/+H stress tolerance. First, we highlight the impact of D/+H stress on cereal crops, and the elaborate plant physiological and molecular responses. We then discuss how key primary metabolism- and secondary metabolism-related metabolic pathways, including carbon metabolism, starch metabolism, phenylpropanoid biosynthesis, γ-aminobutyric acid (GABA) biosynthesis, and phytohormone biosynthesis and signaling can be modified using modern molecular biotechnology approaches such as CRISPR-Cas9 system and synthetic biology (Synbio) to enhance D/+H tolerance in cereal crops. Understandably, several bottlenecks hinder metabolic pathway modification, including those related to feedback regulation, gene functional annotation, complex crosstalk between pathways, and metabolomics data and spatiotemporal gene expressions analyses. Nonetheless, recent advances in molecular biotechnology, genome-editing, single-cell metabolomics, and data annotation and analysis approaches, when integrated, offer unprecedented opportunities for pathway engineering for enhancing crop D/+H stress tolerance and improved yield. Especially, Synbio-based strategies will accelerate the development of climate resilient and nutrient-dense cereals, critical for achieving global food security and combating malnutrition.

Genetic mapping identified three hotspot genomic regions and candidate genes controlling heat tolerance-related traits in groundnut

Groundnut productivity and quality have been impeded by rising temperatures in semi-arid environments. Hence, understanding the effects and molecular mechanisms of heat stress tolerance will aid in tackling yield losses. In this context, a recombinant inbred line (RIL) population was developed and phenotyped for eight seasons at three locations for agronomic, phenological, and physiological traits under heat stress. A genetic map was constructed using genotyping-by-sequencing with 478 single-nucleotide polymorphism (SNP) loci spanning a map distance of 1,961.39 cM. Quantitative trait locus (QTL) analysis using phenotypic and genotypic data identified 45 major main-effect QTLs for 21 traits. Intriguingly, three QTL clusters (Cluster-1-Ah03, Cluster-2-Ah12, and Cluster-3-Ah20) harbor more than half of the major QTLs (30/45, 66.6%) for various heat tolerant traits, explaining 10.4%-38.6%, 10.6%-44.6%, and 10.1%-49.5% of phenotypic variance, respectively. Furthermore, important candidate genes encoding DHHC-type zinc finger family protein (arahy.J0Y6Y5), peptide transporter 1 (arahy.8ZMT0C), pentatricopeptide repeat-containing protein (arahy.4A4JE9), Ulp1 protease family (arahy.X568GS), Kelch repeat F-box protein (arahy.I7X4PC), FRIGIDA-like protein (arahy.0C3V8Z), and post-illumination chlorophyll fluorescence increase (arahy.92ZGJC) were the underlying three QTL clusters. The putative functions of these genes suggested their involvement in seed development, regulating plant architecture, yield, genesis and growth of plants, flowering time regulation, and photosynthesis. Our results could provide a platform for further fine mapping, gene discovery, and developing markers for genomics-assisted breeding to develop heat-tolerant groundnut varieties.

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.

Developing Climate-Resilient, Direct-Seeded, Adapted Multiple-Stress-Tolerant Rice Applying Genomics-Assisted Breeding

There is an urgent need to breed dry direct-seeded adapted rice varieties in order to address the emerging scenario of water-labor shortage. The aim of this study was to develop high-yielding, direct-seeded adapted varieties utilizing biparental to multiparental crosses involving as many as six different parents in conventional breeding programs and 12 parents in genomics-assisted breeding programs. The rigorous single plant selections were followed from the F₂ generation onwards utilizing phenotypic selection and quantitative trait locus (QTL)/gene-based/linked markers for tracking the presence of desirable alleles of targeted QTL/genes. In conventional breeding, multiparent lines had significantly higher yields (2,072-6,569 kg ha^-1) than the biparental lines (1,493-6,326 kg ha^-1). GAB lines derived from multiparent crosses had significantly higher (3,293-6,719 kg ha^-1) yields than the multiparent lines from conventional breeding (2,072-6,569 kg ha^-1). Eleven promising lines from genomics-assisted breeding carrying 7-11 QTL/genes and eight lines from conventional breeding with grain-yield improvement from 727 to 1,705 kg ha^-1 and 68 to 902 kg ha^-1, respectively, over the best check were selected. The developed lines may be released as varieties/parental lines to develop better rice varieties for direct-seeded situations or as novel breeding material to study genetic interactions.