The buffering capacity of stems: genetic architecture of nonstructural carbohydrates in cultivated Asian rice, Oryza sativa

Trehalose-6-Phosphate Phosphatase SlTPP1 Adjusts Diurnal Carbohydrate Partitioning in Tomato

Trehalose 6-phosphate phosphatases (TPPs) play essential roles in carbohydrate distribution between source and sink organs in plants. Here, we show that TPPs also participate in regulating diurnal carbohydrate partitioning. In tomato, SlTPP1 exhibited high expression in leaves, particularly in phloem, with distinct diurnal variation. Overexpression of SlTPP1 promoted plant growth and biomass accumulation, whereas its knockout reduced both. Analysis of photosynthesis parameters revealed that overexpression of SlTPP1 accelerated the initiation of photosynthesis at dawn, promoting assimilate production. Additionally, SlTPP1 enhanced the stem's buffering capacity in diurnal carbohydrate partitioning, promoting daytime carbohydrate accumulation and facilitating nocturnal carbohydrate export to the roots, resulting in increased root carbohydrate levels. These results indicate that SlTPP1 regulates diurnal carbohydrate partitioning, establishing a positive feedback loop that promotes plant growth. Notably, overexpression of SlTPP1 reduced T6P concentration, whereas overexpression of SnRK1 (sucrose non-fermenting 1-related protein kinase) α subunit (SNF1) decreased biomass and did not enhance the stem's buffering capacity in carbohydrate partitioning. These findings suggest that SlTPP1's regulation of diurnal carbohydrate partitioning is at least partially independent of the classical T6P-SnRK1 pathway.

Gene Pyramiding Strategies for Sink Size and Source Capacity for High-Yield Japonica Rice Breeding

In Japan, high-yielding indica rice cultivars such as 'Habataki', 'Takanari', and 'Hokuriku 193' have been bred, and many genes related to the high-yield traits have been isolated from these and other indica cultivars. Many such genes are expected to be effective in increasing the yield of japonica rice, including those that increase sink size. It has been expected that high-yielding japonica rice could be bred by introducing sink-size genes into the genetic background of japonica cultivars such as 'Koshihikari', which show strong cold tolerance, have good taste characteristics, and fetch a high price. However, the corresponding near-isogenic lines did not necessarily produce high yields when tested in the field. In this review, we summarize information on the major high-yield-related rice genes and discuss pyramiding strategies to further increase the yield of japonica rice. In parallel with increasing sink size, source capacity needs to be increased by increasing photosynthetic rate per unit leaf area (single leaf photosynthesis), improving canopy structure, and increasing translocation capacity during the ripening stage. To implement these strategies, innovative breeding methodologies that efficiently produce the combinations of desired alleles are required.

Positive effects of public breeding on US rice yields under future climate scenarios

In this study, we model and predict rice yields by integrating molecular marker variation, varietal productivity, and climate, focusing on the Southern U.S. rice-growing region. This region spans the states of Arkansas, Louisiana, Texas, Mississippi, and Missouri and accounts for 85% of total U.S. rice production. By digitizing and combining four decades of county-level variety acreage data (1970 to 2015) with varietal information from genotyping-by-sequencing data, we estimate annual historical county-level allele frequencies. These allele frequencies are used together with county-level weather and yield data to develop ten machine learning models for yield prediction. A two-layer meta-learner ensemble model that combines all ten methods is externally evaluated against observations from historical Uniform Regional Rice Nursery trials (1980 to 2018) conducted in the same states. Finally, the ensemble model is used with forecasted weather from the Coupled Model Intercomparison Project across the 110 rice-growing counties to predict production in the coming decades for Composite Variety Groups assembled based on year of release, breeding program, and several breeding trends. Results indicate positive effects over time of public breeding on rice resilience to future climates, and potential reasons are discussed.

Evaluation of Grain-Filling-Related Traits Using Taichung 65 x DV85 Chromosome Segment Substitution Lines (TD-CSSLs) of Rice

Grain yield of rice consists of sink capacity and grain filling. There are some genes known to contribute to sink capacity, but few genes associated with grain filling are known. We conducted a genetic analysis on yield-related traits by using a chromosome segment substitution line population that have introgression from DV85, an aus variety of rice, in the background of T65, a japonica variety. Refined whole-genome genotypes of the 43 TD-CSSLs were obtained by genotyping-by-sequencing. The effects of previously detected quantitative trait loci (QTLs), qNSC1 and qNSC2, were confirmed by the amount of non-structural carbohydrate (NSC) at 5 days after heading (DAH). The CSSL for qSWTR11, the QTL for decrease in shoot weight during the maturity stage, showed the highest NSC at 5 DAH and lowest at 35 DAH. The brown rice yield of these lines were not stably significant. Most of the sink-related traits correlated between the 2 tested years, but most of the grain-filling traits did not show correlation between the 2 years. Correlation analysis revealed that the sink capacity is stable and primarily determines the yield, and grain filling is more affected by the environment. In addition, biomass production before heading and during the maturity stage contributes to higher yield in TD-CSSLs, and the amount of translocation of stem reserve does not affect much to the yield. We conclude that higher NSC at the heading stage and rapid decrease in shoot biomass during the maturity stage did not directly contribute to the yield formation in the japonica genetic background.

Where the wild things are: genetic associations of environmental adaptation in the Oryza rufipogon species complex

Crop wild relatives host unique adaptation strategies that enable them to thrive across a wide range of habitats. As pressures from a changing climate mount, a more complete understanding of the genetic variation that underlies this adaptation could enable broader utilization of wild materials for crop improvement. Here, we carry out environmental association analyses (EAA) in the Oryza rufipogon species complex (ORSC), the wild progenitor of cultivated Asian rice, to identify genomic regions associated with environmental adaptation characterized by variation in bioclimatic and soil variables. We further examine regions for colocalizations with phenotypic associations within the same collection. EAA results indicate that significant regions tend to associate with single environmental variables, although 2 significant loci on chromosomes 3 and 5 are detected as common across multiple variable types (i.e. precipitation, temperature, and/or soil). Distributions of allele frequencies at significant loci across subpopulations of cultivated Oryza sativa indicate that, in some cases, adaptive variation may already be present among cultivars, although evaluation in cultivated populations is needed to empirically test this. This work has implications for the potential utility of wild genetic resources in pre-breeding efforts for rice improvement.

Genome wide association analysis of root hair traits in rice reveals novel genomic regions controlling epidermal cell differentiation

BACKGROUND

Genome wide association (GWA) studies demonstrate linkages between genetic variants and traits of interest. Here, we tested associations between single nucleotide polymorphisms (SNPs) in rice (Oryza sativa) and two root hair traits, root hair length (RHL) and root hair density (RHD). Root hairs are outgrowths of single cells on the root epidermis that aid in nutrient and water acquisition and have also served as a model system to study cell differentiation and tip growth. Using lines from the Rice Diversity Panel-1, we explored the diversity of root hair length and density across four subpopulations of rice (aus, indica, temperate japonica, and tropical japonica). GWA analysis was completed using the high-density rice array (HDRA) and the rice reference panel (RICE-RP) SNP sets.

RESULTS

We identified 18 genomic regions related to root hair traits, 14 of which related to RHD and four to RHL. No genomic regions were significantly associated with both traits. Two regions overlapped with previously identified quantitative trait loci (QTL) associated with root hair density in rice. We identified candidate genes in these regions and present those with previously published expression data relevant to root hair development. We re-phenotyped a subset of lines with extreme RHD phenotypes and found that the variation in RHD was due to differences in cell differentiation, not cell size, indicating genes in an associated genomic region may influence root hair cell fate. The candidate genes that we identified showed little overlap with previously characterized genes in rice and Arabidopsis.

CONCLUSIONS

Root hair length and density are quantitative traits with complex and independent genetic control in rice. The genomic regions described here could be used as the basis for QTL development and further analysis of the genetic control of root hair length and density. We present a list of candidate genes involved in root hair formation and growth in rice, many of which have not been previously identified as having a relation to root hair growth. Since little is known about root hair growth in grasses, these provide a guide for further research and crop improvement.

Insights into carbon and nitrogen metabolism and antioxidant potential during vegetative phase in quinoa (Chenopodium quinoa Willd.)

The present investigation was carried out to understand the impact of carbon and nitrogen metabolism in quinoa genotypes IC411824, IC411825, EC507747 and EC507742 during pre-anthesis stage. It was observed that activities of acid invertase, sucrose synthase (cleavage) and sucrose phosphate synthase (SPS) increased up to 75 days after sowing (DAS) and this might be responsible for providing reducing sugars for the development of vegetative parts. Enhanced activities of nitrate reductase, glutamate synthase, glutamine synthetase during vegetative growth of leaves and stem at 90 DAS assist the fixation of ammonia on glutamate molecule to synthesize amino acids at early stages. However, the glutamate dehydrogenase and nitrite reductase play a central role in the re-assimilation of amides from the amino group of asparaginase. As a result, these photosynthetic products will be responsible for providing both the energy and the C-skeletons for ammonium assimilation during amino acid biosynthesis. Leaves and stem of IC411824 and IC411825 had higher total phenol and total flavonoid content. DPPH (2,2-diphenyl-1-picrylhydrazyl) radical scavenging activity was found to be higher in leaves of IC411825 and in stem of IC411824 and IC411825 indicating their capability to act as natural antioxidants.

Sink Strength Promoting Remobilization of Non-Structural Carbohydrates by Activating Sugar Signaling in Rice Stem during Grain Filling

The remobilization of non-structural carbohydrates (NSCs) in the stem is essential for rice grain filling so as to improve grain yield. We conducted a two-year field experiment to deeply investigate their relationship. Two large-panicle rice varieties with similar spikelet size, CJ03 and W1844, were used to conduct two treatments (removing-spikelet group and control group). Compared to CJ03, W1844 had higher 1000-grain weight, especially for the grain growth of inferior spikelets (IS) after removing the spikelet. These results were mainly ascribed to the stronger sink strength of W1844 than that of CJ03 contrasting in the same group. The remobilization efficiency of NSC in the stem decreased significantly after removing the spikelet for both CJ03 and W1844, and the level of sugar signaling in the T6P-SnRK1 pathway was also significantly changed. However, W1844 outperformed CJ03 in terms of the efficiency of carbon reserve remobilization under the same treatments. More precisely, there was a significant difference during the early grain-filling stage in terms of the conversion of sucrose and starch. Interestingly, the sugar signaling of the T6P and SnRK1 pathways also represented an obvious change. Hence, sugar signaling may be promoted by sink strength to remobilize the NSCs of the rice stem during grain filling to further advance crop yield.

Bottlenecks and opportunities in field-based high-throughput phenotyping for heat and drought stress

Flowering and grain-filling stages are highly sensitive to heat and drought stress exposure, leading to significant loss in crop yields. Therefore, phenotyping to enhance resilience to these abiotic stresses is critical for sustaining genetic gains in crop improvement programs. However, traditional methods for screening traits related to these stresses are slow, laborious, and often expensive. Remote sensing provides opportunities to introduce low-cost, less biased, high-throughput phenotyping methods to capture large genetic diversity to facilitate enhancement of stress resilience in crops. This review focuses on four key physiological traits and processes that are critical in understanding crop responses to drought and heat stress during reproductive and grain-filling periods. Specifically, these traits include: (i) time of day of flowering, to escape these stresses during flowering; (ii) optimizing photosynthetic efficiency; (iii) storage and translocation of water-soluble carbohydrates; and (iv) yield and yield components to provide in-season yield estimates. Moreover, we provide an overview of current advances in remote sensing in capturing these traits, and discuss the limitations with existing technology as well as future direction of research to develop high-throughput phenotyping approaches. In the future, phenotyping these complex traits will require sensor advancement, high-quality imagery combined with machine learning methods, and efforts in transdisciplinary science to foster integration across disciplines.

What happens at night? Physiological mechanisms related to maintaining grain yield under high night temperature in rice

High night temperature (HNT) causes substantial yield loss in rice (Oryza sativa L.). In this study, the physiological processes related to flag leaf dark respiration (Rn) and grain filling under HNT were explored in a multi-parent advanced generation intercross population developed for heat tolerance (MAGIC^heat ) along with selected high temperature tolerant breeding lines developed with heat-tolerant parents. Within a subset of lines, flag leaf Rn under HNT treatment was related to lower spikelet number per panicle and thus reduced yield. HNT enhanced the nighttime reduction of non-structural carbohydrates (NSC) in stem tissue, but not in leaves, and stem nighttime NSC reduction was negatively correlated with yield. Between heading and harvest, the major difference in NSC concentration was found for starch, but not for soluble sugar. HNT weakened the relationship between NSC remobilization and harvest index at both the phenotypic and genetic level. By using genome-wide association studies, an invertase inhibitor, MADS box transcription factors and a UDP-glycosyltransferase that were identified as candidate genes orchestrating stem NSC remobilization in the control treatment were lost under HNT. With the identification of physiological and genetic components related to rice HNT response, this study offers promising prebreeding materials and trait targets to sustain yield stability under climate change.

Drought tolerance in selected aerobic and upland rice varieties is driven by different metabolic and antioxidative responses

Sugar-mediated osmotic acclimation and a strong antioxidative response reduce drought-induced biomass loss at the vegetative stage in rice. A clear understanding of the physiological and biochemical adaptations to water limitation in upland and aerobic rice can help to identify the mechanisms underlying their tolerance to low water availability. In this study, three indica rice varieties-IR64 (lowland), Apo (aerobic), and UPL Ri-7 (upland)-, that are characterized by contrasting levels of drought tolerance, were exposed to drought at the vegetative stage. Drought-induced changes in biomass, leaf metabolites and oxidative stress markers/enzyme activities were analyzed in each variety at multiple time points. The two drought-tolerant varieties, Apo and UPL Ri-7 displayed a reduced water use in contrast to the susceptible variety IR64 that displayed high water consumption and consequent strong leaf dehydration upon drought treatment. A sugar-mediated osmotic acclimation in UPL Ri-7 and a strong antioxidative response in Apo were both effective in limiting the drought-induced biomass loss in these two varieties, while biomass loss was high in IR64, also after recovery. A qualitative comparison of these results with the ones of a similar experiment conducted in the field at the reproductive stage showed that only Apo, which also in this stage showed the highest antioxidant power, was able to maintain a stable grain yield under stress. Our results show that different metabolic and antioxidant adaptations confer drought tolerance to aerobic and upland rice varieties in the vegetative stage. The effectiveness of these adaptations differs between developmental stages. Unraveling the genetic control of these mechanisms might be exploited in breeding for new rice varieties adapted to water-limited environments.

Sucrose transport and metabolism control carbon partitioning between stem and grain in rice

Source-sink relationships are key to overall crop performance. Detailed understanding of the factors that determine source-sink dynamics is imperative for the balance of biomass and grain yield in crop plants. We investigated the differences in source-sink relationships between a cultivated rice, Oryza sativa cv. Nipponbare, and a wild rice, Oryza australiensis, which show striking differences in biomass and grain yield. Oryza australiensis, which accumulates a higher biomass, not only showed higher photosynthesis per unit leaf area but also exported more sucrose from leaves compared with Nipponbare. However, grain features and sugar content suggested limited sucrose mobilization to grains in the wild rice due to vasculature and sucrose transporter functions. Low cell wall invertase activity and high sucrose synthase cleavage activity followed by higher expression of cellulose synthase genes in O. australiensis stem indicated that it utilized photosynthates preferentially for the synthesis of structural carbohydrates, resulting in high biomass. In contrast, source-sink relationships favored high grain yield in Nipponbare via accumulation of transitory starch in the stem, due to higher expression of starch biosynthetic genes, which is mobilized to panicles at the grain filling stage. Thus, vascular features, sucrose transport, and functions of sugar metabolic enzymes explained the differences in source-sink relationships between Nipponbare and O. australiensis.

Systematic Review on Local Ancestor Inference From a Mathematical and Algorithmic Perspective

Genotypic data provide deep insights into the population history and medical genetics. The local ancestry inference (LAI) (also termed local ancestry deconvolution) method uses the hidden Markov model (HMM) to solve the mathematical problem of ancestry reconstruction based on genomic data. HMM is combined with other statistical models and machine learning techniques for particular genetic tasks in a series of computer tools. In this article, we surveyed the mathematical structure, application characteristics, historical development, and benchmark analysis of the LAI method in detail, which will help researchers better understand and further develop LAI methods. Firstly, we extensively explore the mathematical structure of each model and its characteristic applications. Next, we use bibliometrics to show detailed model application fields and list articles to elaborate on the historical development. LAI publications had experienced a peak period during 2006-2016 and had kept on moving in the following years. The efficiency, accuracy, and stability of the existing models were evaluated by the benchmark. We find that phased data had higher accuracy in comparison with unphased data. We summarize these models with their distinct advantages and disadvantages. The Loter model uses dynamic programming to obtain a globally optimal solution with its parameter-free advantage. Aligned bases can be used directly in the Seqmix model if the genotype is hard to call. This research may help model developers to realize current challenges, develop more advanced models, and enable scholars to select appropriate models according to given populations and datasets.

A Coordinated Suite of Wild-Introgression Lines in Indica and Japonica Elite Backgrounds

Rice, Oryza sativa L., is a cultivated, inbreeding species that serves as the staple food for the largest number of people on earth. It has two strongly diverged varietal groups, Indica and Japonica, which result from a combination of natural and human selection. The genetic divergence of these groups reflects the underlying population structure of their wild ancestors, and suggests that a pre-breeding strategy designed to take advantage of existing genetic, geographic and ecological substructure may provide a rational approach to the utilization of crop wild ancestors in plant improvement. Here we describe the coordinated development of six introgression libraries (n = 63 to 81 lines per library) in both Indica (cv. IR64) and Japonica (cv. Cybonnet) backgrounds using three bio-geographically diverse wild donors representing the Oryza rufipogon Species Complex from China, Laos and Indonesia. The final libraries were genotyped using an Infinium 7K rice SNP array (C7AIR) and analyzed under greenhouse conditions for several simply inherited (Mendelian) traits. These six interspecific populations can be used as individual Chromosome Segment Substitution Line libraries and, when considered together, serve as a powerful genetic resource for systematic genetic dissection of agronomic, physiological and developmental traits in rice.

Genome-wide association analysis of stem water-soluble carbohydrate content in bread wheat

GWAS identified 36 potentially new loci for wheat stem water-soluble carbohydrate (WSC) contents and 13 pleiotropic loci affecting WSC and thousand-kernel weight. Five KASP markers were developed and validated. Water-soluble carbohydrates (WSC) reserved in stems contribute significantly to grain yield (GY) in wheat. However, knowledge of the genetic architecture underlying stem WSC content (SWSCC) is limited. In the present study, 166 diverse wheat accessions from the Yellow and Huai Valleys Winter Wheat Zone of China and five other countries were grown in four well-watered environments. SWSCC at 10 days post-anthesis (10DPA), 20DPA and 30DPA, referred as WSC10, WSC20 and WSC30, respectively, and thousand-kernel weight (TKW) were assessed. Correlation analysis showed that TKW was significantly and positively correlated with WSC10 and WSC20. Genome-wide association study was performed on SWSCC and TKW with 373,106 markers from the wheat 660 K and 90 K SNP arrays. Totally, 62 stable loci were detected for SWSCC, with 36, 24 and 19 loci for WSC10, WSC20 and WSC30, respectively; among these, 36 are potentially new, 16 affected SWSCC at two or three time-points, and 13 showed pleiotropic effects on both SWSCC and TKW. Linear regression showed clear cumulative effects of favorable alleles for increasing SWSCC and TKW. Genetic gain analyses indicated that pyramiding favorable alleles of SWSCC had simultaneously improved TKW. Kompetitive allele-specific PCR markers for five pleiotropic loci associated with both SWSCC and TKW were developed and validated. This study provided a genome-wide landscape of the genetic architecture of SWSCC, gave a perspective for understanding the relationship between WSC and GY and explored the theoretical basis for co-improvement of WSC and GY. It also provided valuable loci and markers for future breeding.

Potassium deficiency aggravates yield loss in rice by restricting the translocation of non-structural carbohydrates under Sarocladium oryzae infection condition

Sheath rot disease (ShR) caused by Sarocladium oryzae (S. oryzae) infection is an emerging disease that causes severe yield loss by restricting the translocation of non-structural carbohydrates (NSC). Potassium (K) nutrition plays a critical role in disease resistance and the exportation of NSC. However, the physiological mechanisms of K with respect to ShR have not been thoroughly elucidated to date. The objectives of this study were to reveal the mechanisms by which K increases ShR resistance by regulating NSC translocation of rice, therefore, a field experiment combined with an inoculation experiment was conducted. We demonstrate that ShR disease incidence and disease index decreased dramatically with an increasing K application. K deficiency sharply induced the accumulation of NSC in the flag leaf (FL) and flag leaf sheath (FLS) under S. oryzae infection condition, which reduced the contribution of transferred NSC to final yield. A permutational multivariate analysis showed that K deficiency had a greater (49.0%, P < 0.001) effect on the NSC content variation in FL than that of S. oryzae infection (15.0%, P < 0.001). S. oryzae infection dramatically increased the difference in apparent transferred mass of NSC and cell membrane injury of diseased organs between K-deficient and K-sufficient rice. Finally, we demonstrate that cell membrane injury was a limiting factor imposed by K deficiency, which restricts the export of NSC from source organs. This work highlights the importance of K in improving ShR resistance by regulating NSC translocation (particularly the stem NSC).

QTL analysis for carbon assimilate translocation-related traits during maturity in rice (Oryza sativa L.)

Problems with carbon assimilate translocation from source organs to sink (grains) during ripening cause yield losses in rice (Oryza sativa L.), especially in high-sink-capacity varieties. We conducted a genetic analysis of traits related to such translocation by using recombinant inbred lines. Shoot weight (SW) of T65, a japonica parent, was retained from heading to late maturity, whereas that of DV85, an aus parent, was greater than that of T65 at 5 days after heading (DAH) and then decreased until 20 DAH. This difference was observed clearly under standard-fertilizer but not low-fertilizer conditions. Non-structural carbohydrate (NSC) contents in the parents showed a tendency similar to that for SW. QTL analysis revealed pleiotropic QTLs on chromosomes 5 and 10, probably by associations with heading date QTLs. A QTL associated with harvest index and NSC at 5 DAH was detected on chromosome 1. By considering the temporal changes of the traits, we found a QTL for decrease in SW on chromosome 11; the DV85 allele of this QTL facilitated assimilate translocation and suppressed biomass growth. A suggestive QTL for NSC decrease was located on chromosome 2. These QTLs could represent potential targets for controlling carbon assimilate translocation in breeding programs.

An imputation platform to enhance integration of rice genetic resources

As sequencing and genotyping technologies evolve, crop genetics researchers accumulate increasing numbers of genomic data sets from various genotyping platforms on different germplasm panels. Imputation is an effective approach to increase marker density of existing data sets toward the goal of integrating resources for downstream applications. While a number of imputation software packages are available, the limitations to utilization for the rice community include high computational demand and lack of a reference panel. To address these challenges, we develop the Rice Imputation Server, a publicly available web application leveraging genetic information from a globally diverse rice reference panel assembled here. This resource allows researchers to benefit from increased marker density without needing to perform imputation on their own machines. We demonstrate improvements that imputed data provide to rice genome-wide association (GWA) results of grain amylose content and show that the major functional nucleotide polymorphism is tagged only in the imputed data set.