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.

Mapping of QTLs associated with yield and related traits under reproductive stage drought stress in rice using SNP linkage map.

BACKGROUND: Drought stress is a major constraint for rice production worldwide. Reproductive stage drought stress (RSDS) leads to heavy yield losses in rice. The prospecting of new donor cultivars for identification and introgression of QTLs of major effect (Quantitative trait locus) for drought tolerance is crucial for the development of drought-resilient rice varieties. METHODS AND RESULTS: Our study aimed to map QTLs associated with yield and its related traits under RSDS conditions. A saturated linkage map was constructed using 3417 GBS (Genotyping by sequencing) derived SNP (Single nucleotide polymorphism) markers spanning 1924.136 cM map length with an average marker density of 0.56 cM, in the F3 mapping population raised via cross made between the traditional ahu rice cultivar, Koniahu (drought tolerant) and a high-yielding variety, Disang (drought susceptible). Using the Inclusive composite interval mapping approach, 35 genomic regions governing yield and related traits were identified in pooled data from 198 F3 and F4 segregating lines evaluated for two consecutive seasons under both RSDS and irrigated control conditions. Of the 35 QTLs, 23 QTLs were identified under RSDS with LOD (Logarithm of odds) values ranging between 2.50 and 7.83 and PVE (phenotypic variance explained) values of 2.95-12.42%. Two major QTLs were found to be linked to plant height (qPH1.29) and number of filled grains per panicle (qNOG5.12) under RSDS. Five putative QTLs for grain yield namely, qGY2.00, qGY5.05, qGY6.16, qGY9.19, and qGY10.20 were identified within drought conditions. Fourteen QTL regions having ≤ 10 Mb QTL interval size were further analysed for candidate gene identification and a total of 4146 genes were detected out of these 2263 (54.63%) genes were annotated to at least one gene ontology (GO) term. CONCLUSION: Several QTLs associated with grain yield and yield components and putative candidate genes were identified. The putative QTLs and candidate genes identified could be employed to augment drought resilience in rice after further validation through MAS strategies.

Genetic analysis for detection of genes associated to drought tolerance in rice accessions belonging to north east India.

INTRODUCTION: The North East (NE) India is rich in biodiversity and also considered as the secondary centre for origin of rice. The NE rice accessions was characterized previously using genetic markers and morphological traits. Simultaneously, genome-wide association studies (GWAS) reveal significant marker-trait associations for the drought tolerance traits. METHODS AND RESULTS: The genetic diversity and population structure of 296 NE rice accessions were studied using 96,712 single nucleotide polymorphism (SNP) markers distributed across 12 chromosomes. The accessions were clustered into two major sub-groups (SG). A total of 91 accessions were assembled as SG1 and 114 accessions as SG2, while the remaining 91 were admixture genotypes. A total of 200 genotypes belonging to different groups were phenotyped for yield component traits under drought and control conditions. The GWAS was performed to identify significant marker-trait associations (MTAs). Consequently, 47 MTAs were detected under drought, exhibiting 0.02-9.95% of phenotypic variance (P.V.). Whereas 58 MTAs were discovered under control conditions, showing a 0.01-9.74% contribution to the phenotype. Through in-silico mining of QTLs, 2999 genes were identified. Among these; only 22 genes were directly associated with stress response. CONCLUSION: These QTLs/genes may be deployed for marker-assisted pyramiding to improve drought tolerance in popular drought susceptible rice varieties.

Molecular mapping of drought-responsive QTLs during the reproductive stage of rice using a GBS (genotyping-by-sequencing) based SNP linkage map.

BACKGROUND: In rice, drought stress at reproductive stage drastically reduces yield, which in turn hampers farmer's efforts towards crop production. The majority of the rice varieties have resistance genes against several abiotic and biotic stresses. Therefore, the traditional landraces were studied to identify QTLs/candidate genes associated with drought tolerance. METHODS AND RESULTS: A high-density SNP-based genetic map was constructed using a Genotyping-by-sequencing (GBS) approach. The recombinant inbred lines (RILs) derived from crossing 'Banglami × Ranjit' were used for QTL analysis. A total map length of 1306.424 cM was constructed, which had an average inter-marker distance of 0.281 cM. The phenotypic evaluation of F6 and F7 RILs were performed under drought stress and control conditions. A total of 42 QTLs were identified under drought stress and control conditions for yield component traits explaining 1.95-13.36% of the total phenotypic variance (PVE). Among these, 19 QTLs were identified under drought stress conditions, whereas 23 QTLs were located under control conditions. A total of 4 QTLs explained a PVE ≥ 10% which are considered as the major QTLs. Moreover, bioinformatics analysis revealed the presence of 6 candidate genes, which showed differential expression under drought and control conditions. CONCLUSION: These QTLs/genes may be deployed for marker-assisted pyramiding to improve drought tolerance in the existing rice varieties.

Identification and characterization of genes for drought tolerance in upland rice cultivar 'Banglami' of North East India.

INTRODUCTION: Rice is a major crop in Assam, North East (NE) India. The rice accessions belonging to NE India possess unique traits of breeder's interest, i.e., tolerant to biotic and abiotic stresses. In the present research programme, the stress responsive genes were identified within the QTLs associated with drought tolerance. The differential expression profiling of genes were performed under drought stress and control conditions. Thus, the 'candidate genes' associated with drought tolerance were recognised and may be deployed in a breeding programme. METHODS AND RESULTS: A drought-tolerant traditional rice cultivar, Banglami, was crossed with a high-yielding, drought-susceptible variety, Ranjit. The mapping population (F4) was raised through the single seed descent (SSD) method and used in QTL analysis. Under drought stress, a total of 4752 genes were identified through in-silico mining of QTLs. Among these, only 21 genes primarily associated with the stress response. The maximum of four stress-responsive genes were located within the QTLs, qNOG12.1 and qGY1.1. However, under control conditions, 2088 genes were identified, out of which, only 15 were categorised as the major stress responsive genes. The functional characterization of genes recognized 24 different types of proteins. Among these, peroxidase and heat shock proteins (Hsp) are the principal proteins encoded during stress. In addition to that, OsbZIP23, inorganic pyrophosphatase, universal stress protein, serine threonine kinase, NADPH oxidoreductase, and proteins belonging to the ABC1 family were also produced during stress condition. The differential expression profiling showed a profound expression pattern of three candidate genes under drought stress condition, i.e., OsI_32199 (Ascorbate peroxidase), OsI_37694 (Universal stress protein) and OsI_32167 (Heat shock protein 81 - 1). CONCLUSION: The novel candidate genes identified for drought tolerance, may be used in the breeding programme for the development of 'climate smart rice varieties'.