Stable and Novel Quantitative Trait Loci (QTL) Confer Narrow Root Cone Angle in an Aerobic Rice (Oryza sativa L.) Production System

Genome-Wide Association Study of Early Vigour-Related Traits for a Rice (Oryza sativa L.) japonica Diversity Set Grown in Aerobic Conditions

Aerobic rice production is a relatively new system in which rice is direct-seeded and grown in non-flooded but well-watered conditions to improve water productivity. Early vigour-related traits are likely to be important in aerobic conditions. This study aimed to identify quantitative trait loci (QTL) and candidate genes associated with early vigour-related traits in aerobic conditions using a japonica rice diversity set. Field experiments and glasshouse experiments conducted under aerobic conditions revealed significant genotypic variation in early vigour-related traits. Genome-wide association analysis identified 32 QTL associated with early vigour-related traits. Notably, two QTL, qAEV1.5 and qAEV8, associated with both early vigour score and mesocotyl length, explained up to 22.1% of the phenotypic variance. In total, 23 candidate genes related to plant growth development and abiotic stress response were identified in the two regions. This study provides novel insights into the genetic basis of early vigour under aerobic conditions. Validation of identified QTL and candidate genes in different genetic backgrounds is crucial for future studies. Moreover, testing the effect of QTL on yield under different environments would be valuable. After validation, these QTL and genes can be considered for developing markers in marker-assisted selection for aerobic rice production.

Upland rice genomic signatures of adaptation to drought resistance and navigation to molecular design breeding

Upland rice is a distinctive drought-aerobic ecotype of cultivated rice highly resistant to drought stress. However, the genetic and genomic basis for the drought-aerobic adaptation of upland rice remains largely unclear due to the lack of genomic resources. In this study, we identified 25 typical upland rice accessions and assembled a high-quality genome of one of the typical upland rice varieties, IRAT109, comprising 384 Mb with a contig N50 of 19.6 Mb. Phylogenetic analysis revealed upland and lowland rice have distinct ecotype differentiation within the japonica subgroup. Comparative genomic analyses revealed that adaptive differentiation of lowland and upland rice is likely attributable to the natural variation of many genes in promoter regions, formation of specific genes in upland rice, and expansion of gene families. We revealed differentiated gene expression patterns in the leaves and roots of the two ecotypes and found that lignin synthesis mediated by the phenylpropane pathway plays an important role in the adaptive differentiation of upland and lowland rice. We identified 28 selective sweeps that occurred during domestication and validated that the qRT9 gene in selective regions can positively regulate drought resistance in rice. Eighty key genes closely associated with drought resistance were appraised for their appreciable potential in drought resistance breeding. Our study enhances the understanding of the adaptation of upland rice and provides a genome navigation map of drought resistance breeding, which will facilitate the breeding of drought-resistant rice and the "blue revolution" in agriculture.

Genome-wide association studies in rice germplasm reveal significant genomic regions for root and yield-related traits under aerobic and irrigated conditions

The development of nutrient-use efficient rice lines is a priority amidst the changing climate and depleting resources viz., water, land, and labor for achieving sustainability in rice cultivation. Along with the traditional transplanted irrigated system of cultivation, the dry direct-seeded aerobic system is gaining ground nationwide. The root-related traits play a crucial role in nutrient acquisition, adaptation and need to be concentrated along with the yield-attributing traits. We phenotyped an association panel of 118 rice lines for seedling vigour index (SVI) traits at 14 and 21 days after sowing (DAS), root-related traits at panicle initiation (PI) stage in polythene bags under controlled aerobic condition, yield and yield-related traits under the irrigated condition at ICAR-IIRR, Hyderabad, Telangana; irrigated and aerobic conditions at ARS, Dhadesugur, Raichur, Karnataka. The panel was genotyped using simple sequence repeats (SSR) markers and genome-wide association studies were conducted for identifying marker-trait associations (MTAs). Significant correlations were recorded for root length, root dry weight with SVI, root volume at the PI stage, number of productive tillers per plant, spikelet fertility, the total number of grains per panicle with grain yield per plant under irrigated conditions, and the total number of grains per panicle with grain yield per plant under aerobic condition. The panel was divided into three sub-groups (K = 3) and correlated with the principal component analysis. The maximum number of MTAs were found on chromosomes 2, 3, and 12 with considerable phenotypic variability. Consistent MTAs were recorded for SVI traits at 14 and 21 DAS (RM25310, RM80, RM22961, RM1385), yield traits under irrigated conditions (RM2584, RM5179, RM410, RM20698, RM14753) across years at ICAR-IIRR, grain yield per plant (RM22961, RM1146) under the aerobic condition, grain yield per plant at irrigated ICAR-IIRR and SVI (RM5501), root traits at PI stage (RM2584, RM80, RM410, RM1146, RM18472). Functionally relevant genes near the MTAs through in-silico expression analysis in root and panicle tissues viz., HBF2 bZIP transcription factor, WD40 repeat-like domain, OsPILS6a auxin efflux carrier, WRKY108, OsSCP42, OsMADS80, nodulin-like domain-containing protein, amino acid transporter using various rice expression databases were identified. The identified MTAs and rice lines having high SVI traits (Langphou, TI-128, Mouli, TI-124, JBB-631-1), high yield under aerobic (Phouren, NPK-43, JBB-684, Ratnamudi, TI-112), irrigated conditions (KR-209, KR-262, Phouren, Keibi-Phou, TI-17), robust root traits like root length (MoirangPhou-Angouba, Wangoo-Phou, JBB-661, Dissi, NPK-45), root volume (Ratnachudi, KJ-221, Mow, Heimang-Phou, PUP-229) can be further employed in breeding programs for the targeted environments aimed at improving seedling vigour, yield-related traits under irrigated condition, aerobic condition as adaptability to water-saving technology.

The Mechanism of Manganese Ferrite Nanomaterials Promoting Drought Resistance in Rice

Strategies to reduce the risk of drought damage are urgently needed as intensified climate change threatens agricultural production. One potential strategy was using nanomaterials (NMs) to enhance plant resistance by regulating various physiological and biochemical processes. In the present study, 10 mg kg^-1 manganese ferrite (MnFe₂O₄) NMs had the optimal enhancement to elevate the levels of biomass, photosynthesis, nutrient elements, and polysaccharide in rice by 10.9-525.0%, respectively, under drought stress. The MnFe₂O₄ NMs were internalized by rice plants, which provided the possibility for rice to better cope with drought. Furthermore, as compared with drought control and equivalent ion control, the introduction of MnFe₂O₄ NMs into the roots significantly upregulated the drought-sensing gene CLE25 (29.4%) and the receptor gene NCED3 (59.9%). This activation stimulated downstream abscisic acid, proline, malondialdehyde, and wax biosynthesis by 23.3%, 38.9%, 7.2%, and 26.2%, respectively. In addition, 10 mg·kg^-1 MnFe₂O₄ NMs significantly upregulated the relative expressions of OR1, AUX2, AUX3, PIN1a, and PIN2, and increased IAA content significantly, resulting in an enlarged root angle and a deeper and denser root to help the plant withstand drought stresses. The nutritional quality of rice grains was also improved. Our study provides crucial insight for developing nano-enabled strategies to improve crop productivity and resilience to climate change.

Quantitative trait loci (QTL) for low temperature tolerance at the young microspore stage in rice (Oryza sativa L.) in Australian breeding material

Low temperatures at the young microspore stage (YMS) decreases spikelet fertility and is a major limiting factor to rice production in temperate Australia. Low temperature tolerance is a difficult trait to phenotype, hence there is a strong desire for the identification of quantitative trait loci (QTL) for their use in marker-assisted selection (MAS). Association mapping was used in several breeding populations with a known source of low temperature tolerance, Norin PL8, to identify QTL for low temperature tolerance. A novel QTL for spikelet fertility was identified on chromosome 6, qYMCT6.1, in which the Australian variety, Kyeema, was the donor for increased fertility. Additional five genomics regions were identified that co-located with previously reported QTL, two of which have been previously cloned. Additionally, for the first time a QTL for spikelet fertility qYMCT10.1, has been shown to co-locate with the number of dehisced anthers qYMCTF10.1 which increases the shedding of pollen from the anthers. This study revealed one new QTL for low temperature tolerance at YMS in temperate japonica germplasm and identified an additional five previously reported. These QTL will be utilised for MAS in the Australian rice breeding program and may have merit for temperate breeding programs globally.

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.

Objective Phenotyping of Root System Architecture Using Image Augmentation and Machine Learning in Alfalfa (Medicago sativa L.)

Active breeding programs specifically for root system architecture (RSA) phenotypes remain rare; however, breeding for branch and taproot types in the perennial crop alfalfa is ongoing. Phenotyping in this and other crops for active RSA breeding has mostly used visual scoring of specific traits or subjective classification into different root types. While image-based methods have been developed, translation to applied breeding is limited. This research is aimed at developing and comparing image-based RSA phenotyping methods using machine and deep learning algorithms for objective classification of 617 root images from mature alfalfa plants collected from the field to support the ongoing breeding efforts. Our results show that unsupervised machine learning tends to incorrectly classify roots into a normal distribution with most lines predicted as the intermediate root type. Encouragingly, random forest and TensorFlow-based neural networks can classify the root types into branch-type, taproot-type, and an intermediate taproot-branch type with 86% accuracy. With image augmentation, the prediction accuracy was improved to 97%. Coupling the predicted root type with its prediction probability will give breeders a confidence level for better decisions to advance the best and exclude the worst lines from their breeding program. This machine and deep learning approach enables accurate classification of the RSA phenotypes for genomic breeding of climate-resilient alfalfa.

QTL Validation and Development of SNP-Based High Throughput Molecular Markers Targeting a Genomic Region Conferring Narrow Root Cone Angle in Aerobic Rice Production Systems

Aerobic rice production (AP) provides potential solutions to the global water crisis by consuming less water than traditional permanent water culture. Narrow root cone angle (RCA), development of deeper rooting and associated genomic regions are key for AP adaptation. However, their usefulness depends on validation across genetic backgrounds and development of linked markers. Using three F2 populations derived from IRAT109, qRCA4 was shown to be effective in multiple backgrounds, explaining 9.3-17.3% of the genotypic variation and introgression of the favourable allele resulted in 11.7-15.1° narrower RCA. Novel kompetitive allele specific PCR (KASP) markers were developed targeting narrow RCA and revealed robust quality metrics. Candidate genes related with plant response to abiotic stress and root development were identified along with 178 potential donors across rice subpopulations. This study validated qRCA4's effect in multiple genetic backgrounds further strengthening its value in rice improvement for AP adaptation. Furthermore, the development of novel KASP markers ensured the opportunity for its seamless introgression across pertinent breeding programs. This work provides the tools and opportunity to accelerate development of genotypes with narrow RCA through marker assisted selection in breeding programs targeting AP, which may ultimately contribute to more sustainable rice production where water availability is limited.