Integrative Transcriptomic and Proteomic Analysis Reveals an Alternative Molecular Network of Glutamine Synthetase 2 Corresponding to Nitrogen Deficiency in Rice (Oryza sativa L.).

Nitrogen (N) is an essential nutrient for plant growth and development. The root system architecture is a highly regulated morphological system, which is sensitive to the availability of nutrients, such as N. Phenotypic characterization of roots from LY9348 (a rice variety with high nitrogen use efficiency (NUE)) treated with 0.725 mM NH4NO3 (1/4N) was remarkable, especially primary root (PR) elongation, which was the highest. A comprehensive analysis was performed for transcriptome and proteome profiling of LY9348 roots between 1/4N and 2.9 mM NH4NO3 (1N) treatments. The results indicated 3908 differential expression genes (DEGs; 2569 upregulated and 1339 downregulated) and 411 differential abundance proteins (DAPs; 192 upregulated and 219 downregulated). Among all DAPs in the proteome, glutamine synthetase (GS2), a chloroplastic ammonium assimilation protein, was the most upregulated protein identified. The unexpected concentration of GS2 from the shoot to the root in the 1/4N treatment indicated that the presence of an alternative pathway of N assimilation regulated by GS2 in LY9348 corresponded to the low N signal, which was supported by GS enzyme activity and glutamine/glutamate (Gln/Glu) contents analysis. In addition, N transporters (NRT2.1, NRT2.2, NRT2.3, NRT2.4, NAR2.1, AMT1.3, AMT1.2, and putative AMT3.3) and N assimilators (NR2, GS1;1, GS1;2, GS1;3, NADH-GOGAT2, and AS2) were significantly induced during the long-term N-deficiency response at the transcription level (14 days). Moreover, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis demonstrated that phenylpropanoid biosynthesis and glutathione metabolism were significantly modulated by N deficiency. Notably, many transcription factors and plant hormones were found to participate in root morphological adaptation. In conclusion, our study provides valuable information to further understand the response of rice roots to N-deficiency stress.

Novel and Automatic Rice Thickness Extraction Based on Photogrammetry Using Rice Edge Features.

The dimensions of phenotyping parameters such as the thickness of rice play an important role in rice quality assessment and phenotyping research. The objective of this study was to propose an automatic method for extracting rice thickness. This method was based on the principle of binocular stereovision but avoiding the problem that it was difficult to directly match the corresponding points for 3D reconstruction due to the lack of texture of rice. Firstly, the shape features of edge, instead of texture, was used to match the corresponding points of the rice edge. Secondly, the height of the rice edge was obtained by way of space intersection. Finally, the thickness of rice was extracted based on the assumption that the average height of the edges of multiple rice is half of the thickness of rice. According to the results of the experiments on six kinds of rice or grain, errors of thickness extraction were no more than the upper limit of 0.1 mm specified in the national industry standard. The results proved that edge features could be used to extract rice thickness and validated the effectiveness of the thickness extraction algorithm we proposed, which provided technical support for the extraction of phenotyping parameters for crop researchers.

Pentatricopeptide-repeat family protein RF6 functions with hexokinase 6 to rescue rice cytoplasmic male sterility.

Cytoplasmic male sterility (CMS) has been extensively used for hybrid seed production in many major crops. Honglian CMS (HL-CMS) is one of the three major types of CMS in rice and has contributed greatly to food security worldwide. The HL-CMS trait is associated with an aberrant chimeric mitochondrial transcript, atp6-orfH79, which causes pollen sterility and can be rescued by two nonallelic restorer-of-fertility (Rf) genes, Rf5 or Rf6. Here, we report the identification of Rf6, which encodes a novel pentatricopeptide repeat (PPR) family protein with a characteristic duplication of PPR motifs 3-5. RF6 is targeted to mitochondria, where it physically associates with hexokinase 6 (OsHXK6) and promotes the processing of the aberrant CMS-associated transcript atp6-orfH79 at nucleotide 1238, which ensures normal pollen development and restores fertility. The duplicated motif 3 of RF6 is essential for RF6-OsHXK6 interactions, processing of the aberrant transcript, and restoration of fertility. Furthermore, reductions in the level of OsHXK6 result in atp6-orfH79 transcript accumulation and male sterility. Together these results reveal a novel mechanism for CMS restoration by which RF6 functions with OsHXK6 to restore HL-CMS fertility. The present study also provides insight into the function of hexokinase 6 in regulating mitochondrial RNA metabolism and may facilitate further exploitation of heterosis in rice.

The rice pentatricopeptide repeat protein RF5 restores fertility in Hong-Lian cytoplasmic male-sterile lines via a complex with the glycine-rich protein GRP162.

The cytoplasmic male sterility (CMS) phenotype in plants can be reversed by the action of nuclear-encoded fertility restorer (Rf) genes. The molecular mechanism involved in Rf gene-mediated processing of CMS-associated transcripts is unclear, as are the identities of other proteins that may be involved in the CMS-Rf interaction. In this study, we cloned the restorer gene Rf5 for Hong-Lian CMS in rice and studied its fertility restoration mechanism with respect to the processing of the CMS-associated transcript atp6-orfH79. RF5, a pentatricopeptide repeat (PPR) protein, was unable to bind to this CMS-associated transcript; however, a partner protein of RF5 (GRP162, a Gly-rich protein encoding 162 amino acids) was identified to bind to atp6-orfH79. GRP162 was found to physically interact with RF5 and to bind to atp6-orfH79 via an RNA recognition motif. Furthermore, we found that RF5 and GRP162 are both components of a restoration of fertility complex (RFC) that is 400 to 500 kD in size and can cleave CMS-associated transcripts in vitro. Evidence that a PPR protein interacts directly with a Gly-rich protein to form a subunit of the RFC provides a new perspective on the molecular mechanisms underlying fertility restoration.

Interaction with Cu²âº disrupts the RNA binding affinities of RNA recognition motif containing protein.

The glycine-rich proteins (GRP) containing RNA recognition motifs (RRM) are involved in the regulation of transcriptional and/or post-transcriptional events. Previous studies have established that GRP162 plays an important role in the restoration of fertility in Honglian cytoplasmic male sterile (HL-CMS) rice. In this study, the ion binding properties of rGRP162 were tested by isothermal titration calorimetry (ITC) and electrophoretic mobility shift assay (EMSA) was performed to test the interaction. Circular dichroism (CD) was carried out to detect the alteration of secondary structure in the presence and absence of Cu(2+). Furthermore, two RRM containing proteins, AtRBP45A and AtRBP47A, were expressed to validate the interaction. Results showed Cu(2+) and Fe(3+) bound GRP162, whereas Ca(2+), Mn(2+), Mg(2+) and K(+) did not. EMSA confirmed that interaction with Cu(2+) interrupted the biological activity of GRP162 by disrupting the secondary structure of the protein based on the results of CD. Moreover, the RNA binding activities of rAtRBP45A and rAtRBP47A were also impaired in the presence of Cu(2+). Data suggest that Cu(2+) in excess may disrupt RNA-binding proteins containing RRM that are essential for post-transcriptional regulation and may impair the development of plants or animals.

The mechanism of ORFH79 suppression with the artificial restorer fertility gene Mt-GRP162.

The restoration fertility complex (RFC) was previously identified in Honglian (HL)-cytoplasmic male sterility (CMS) rice (Oryza sativa), and glycine-rich protein 162 (GRP162) is responsible for binding to the CMS-associated transcript atp6-orfH79. Here, we engineered a recombinant GRP162 containing the mitochondrial transit peptide, termed Mt-GRP162, as an artificial restorer of fertility (Rf) gene. Mt-GRP162 was confirmed to bind to CMS-associated RNA and to localize to the mitochondria. The transgenic plants showed restored fertility with partially functional pollen. We found that the expression of ORFH79 decreased in transgenic plants, while the expression of atp6-orfH79 was not changed. These findings indicate that Mt-GRP162 restores fertility by suppressing the expression of the cytotoxic protein ORFH79 at the post-transcriptional level rather than via the cleavage of atp6-orfH79 in the presence of RFC. These findings contribute to our understanding of the mechanisms of restoration through diverse pathways.

Genome-Wide Association Mapping for Yield and Yield-Related Traits in Rice (Oryza Sativa L.) Using SNPs Markers.

Rice (Oryza sativa L.) is a staple food for more than 50% of the world's population. Rice cultivar improvement is critical in order to feed the world's growing population. Improving yield is one of the main aims of rice breeders. However, yield is a complex quantitative trait controlled by many genes. The presence of genetic diversity is the key factor to improve the yield hence, the presence of diversity in any germplasm is important for yield improvement. In the current study, the rice germplasm was collected from Pakistan and the United States of America and a panel of 100 diverse genotypes was utilized to identify important yield and yield-related traits. For this, a genome-wide association study (GWAS) was performed to identify the genetic loci related to yield. The GWAS on the diverse germplasm will lead to the identification of new genes which can be utilized in the breeding program for improvement of yield. For this reason, firstly, the germplasm was phenotypically evaluated in two growing seasons for yield and yield-related traits. The analysis of variance results showed significant differences among traits which showed the presence of diversity in the current germplasm. Secondly, the germplasm was also genotypically evaluated using 10K SNP. Genetic structure analysis showed the presence of four groups which showed that enough genetic diversity was present in the rice germplasm to be used for association mapping analysis. The results of GWAS identified 201 significant marker trait associations (MTAs. 16 MTAs were identified for plant height, 49 for days to flowering, three for days to maturity, four for tillers per plant, four for panicle length, eight for grains per panicle, 20 unfilled grains per panicle, 81 for seed setting %, four for thousand-grain weight, five for yield per plot and seven for yield per hectare. Apart from this, some pleiotropic loci were also identified. The results showed that panicle length (PL) and thousand-grain weight (TGW) were controlled by a pleiotropic locus OsGRb23906 on chromosome 1 at 10,116,371 cM. The loci OsGRb25803 and OsGRb15974 on chromosomes 4 and 8 at the position of 14,321,111 cM and 6,205,816 cM respectively, showed pleiotropic effects for seed setting % (SS) and unfilled grain per panicle (UG/P). A locus OsGRb09180 on chromosome 4 at 19,850,601 cM was significantly linked with SS and yield/ha. Furthermore, gene annotation was performed, and results indicated that the 190 candidate genes or QTLs that closely linked with studied traits. These candidate genes and novel significant markers could be useful in marker-assisted gene selection and QTL pyramiding to improve rice yield and the selection of potential parents, recombinants and MTAs which could be used in rice breeding programs to develop high-yielding rice varieties for sustainable food security.

Estimation of Rice Aboveground Biomass by UAV Imagery with Photosynthetic Accumulation Models.

The effective and accurate aboveground biomass (AGB) estimation facilitates evaluating crop growth and site-specific crop management. Considering that rice accumulates AGB mainly through green leaf photosynthesis, we proposed the photosynthetic accumulation model (PAM) and its simplified version and compared them for estimating AGB. These methods estimate the AGB of various rice cultivars throughout the growing season by integrating vegetation index (VI) and canopy height based on images acquired by unmanned aerial vehicles (UAV). The results indicated that the correlation of VI and AGB was weak for the whole growing season of rice and the accuracy of the height model was also limited for the whole growing season. In comparison with the NDVI-based rice AGB estimation model in 2019 data (R2 = 0.03, RMSE = 603.33 g/m2) and canopy height (R2 = 0.79, RMSE = 283.33 g/m2), the PAM calculated by NDVI and canopy height could provide a better estimate of AGB of rice (R2 = 0.95, RMSE = 136.81 g/m2). Then, based on the time-series analysis of the accumulative model, a simplified photosynthetic accumulation model (SPAM) was proposed that only needs limited observations to achieve R2 above 0.8. The PAM and SPAM models built by using 2 years of samples successfully predicted the third year of samples and also demonstrated the robustness and generalization ability of the models. In conclusion, these methods can be easily and efficiently applied to the UAV estimation of rice AGB over the entire growing season, which has great potential to serve for large-scale field management and also for breeding.

Two non-allelic nuclear genes restore fertility in a gametophytic pattern and enhance abiotic stress tolerance in the hybrid rice plant.

In indica rice, the HongLian (HL)-type combination of cytoplasmic male sterility (CMS) and fertility restoration (Rf) is widely used for the production of commercial hybrid seeds in China, Laos, Vietnam and other Southeast Asian countries. Generally, any member of the gametophytic fertility restoration system, 50% of the pollen in hybrid F(1) plants displays recovered sterility. In this study, however, a HL-type hybrid variety named HongLian You6 had approximately 75% normal (viable) pollen rather than the expected 50%. To resolve this discrepancy, several fertility segregation populations, including F(2) and BC(1)F(1) derived from the HL-CMS line Yuetai A crossed with the restorer line 9311, were constructed and subjected to genetic analysis. A gametophytic restoration model was discovered to involve two non-allelic nuclear restorer genes, Rf5 and Rf6. The Rf5 had been previously identified using a positional clone strategy. The Rf6 gene represents a new restorer gene locus, which was mapped to the short arm of chromosome 8. The hybrid F(1) plants containing one restorer gene, either Rf5 or Rf6, displayed 50% normal pollen grains with I(2)-KI solution; however, those with both Rf5 and Rf6 displayed 75% normal pollens. We also established that the hybrid F(1) plants including both non-allelic restorer genes exhibited an increased stable seed setting when subjected to stress versus the F(1) plants with only one restorer gene. Finally, we discuss the breeding scheme for the plant gametophytic CMS/Rf system.

Combining spectral and wavelet texture features for unmanned aerial vehicles remote estimation of rice leaf area index.

Estimating the crop leaf area index (LAI) accurately is very critical in agricultural remote sensing, especially in monitoring crop growth and yield prediction. The development of unmanned aerial vehicles (UAVs) has been significant in recent years and has been extensively applied in agricultural remote sensing (RS). The vegetation index (VI), which reflects spectral information, is a commonly used RS method for estimating LAI. Texture features can reflect the differences in the canopy structure of rice at different growth stages. In this research, a method was developed to improve the accuracy of rice LAI estimation during the whole growing season by combining texture information based on wavelet transform and spectral information derived from the VI. During the whole growth period, we obtained UAV images of two study areas using a 12-band Mini-MCA system and performed corresponding ground measurements. Several VI values were calculated, and the texture analysis was carried out. New indices were constructed by mathematically combining the wavelet texture and spectral information. Compared with the corresponding VIs, the new indices reduced the saturation effect and were less sensitive to the emergence of panicles. The determination coefficient (R2) increased for most VIs used in this study throughout the whole growth period. The results indicated that the estimation accuracy of LAI by combining spectral information and texture information was higher than that of VIs. The method proposed in this study used the spectral and wavelet texture features extracted from UAV images to establish a model of the whole growth period of rice, which was easy to operate and had great potential for large-scale auxiliary rice breeding and field management research.

Remote estimation of leaf area index (LAI) with unmanned aerial vehicle (UAV) imaging for different rice cultivars throughout the entire growing season.

BACKGROUND: Rice is one of the most important grain crops worldwide. The accurate and dynamic monitoring of Leaf Area Index (LAI) provides important information to evaluate rice growth and production. METHODS: This study explores a simple method to remotely estimate LAI with Unmanned Aerial Vehicle (UAV) imaging for a variety of rice cultivars throughout the entire growing season. Forty eight different rice cultivars were planted in the study site and field campaigns were conducted once a week. For each campaign, several widely used vegetation indices (VI) were calculated from canopy reflectance obtained by 12-band UAV images, canopy height was derived from UAV RGB images and LAI was destructively measured by plant sampling. RESULTS: The results showed the correlation of VI and LAI in rice throughout the entire growing season was weak, and for all tested indices there existed significant hysteresis of VI vs. LAI relationship between rice pre-heading and post-heading stages. The model based on the product of VI and canopy height could reduce such hysteresis and estimate rice LAI of the whole season with estimation errors under 24%, not requiring algorithm re-parameterization for different phenology stages. CONCLUSIONS: The progressing phenology can affect VI vs. LAI relationship in crops, especially for rice having quite different canopy spectra and structure after its panicle exsertion. Thus the models solely using VI to estimate rice LAI are phenology-specific and have high uncertainties for post-heading stages. The model developed in this study combines both remotely sensed canopy height and VI information, considerably improving rice LAI estimation at both pre- and post-heading stages. This method can be easily and efficiently implemented in UAV platforms for various rice cultivars during the entire growing season with no rice phenology and cultivar pre-knowledge, which has great potential for assisting rice breeding and field management studies at a large scale.

Identification of High Nitrogen Use Efficiency Phenotype in Rice (Oryza sativa L.) Through Entire Growth Duration by Unmanned Aerial Vehicle Multispectral Imagery.

Identification of high Nitrogen Use Efficiency (NUE) phenotypes has been a long-standing challenge in breeding rice and sustainable agriculture to reduce the costs of nitrogen (N) fertilizers. There are two main challenges: (1) high NUE genetic sources are biologically scarce and (2) on the technical side, few easy, non-destructive, and reliable methodologies are available to evaluate plant N variations through the entire growth duration (GD). To overcome the challenges, we captured a unique higher NUE phenotype in rice as a dynamic time-series N variation curve through the entire GD analysis by canopy reflectance data collected by Unmanned Aerial Vehicle Remote Sensing Platform (UAV-RSP) for the first time. LY9348 was a high NUE rice variety with high Nitrogen Uptake Efficiency (NUpE) and high Nitrogen Utilization Efficiency (NUtE) shown in nitrogen dosage field analysis. Its canopy nitrogen content (CNC) was analyzed by the high-throughput UAV-RSP to screen two mixed categories (51 versus 42 varieties) selected from representative higher NUE indica rice collections. Five Vegetation Indices (VIs) were compared, and the Normalized Difference Red Edge Index (NDRE) showed the highest correlation with CNC (r = 0.80). Six key developmental stages of rice varieties were compared from transplantation to maturation, and the high NUE phenotype of LY9348 was shown as a dynamic N accumulation curve, where it was moderately high during the vegetative developmental stages but considerably higher in the reproductive developmental stages with a slower reduction rate. CNC curves of different rice varieties were analyzed to construct two non-linear regression models between N% or N% × leaf area index (LAI) with NDRE separately. Both models could determine the specific phenotype with the coefficient of determination (R 2) above 0.61 (Model I) and 0.86 (Model II). Parameters influencing the correlation accuracy between NDRE and N% were found to be better by removing the tillering stage data, separating the short and long GD varieties for the analysis and adding canopy structures, such as LAI, into consideration. The high NUE phenotype of LY9348 could be traced and reidentified across different years, locations, and genetic germplasm groups. Therefore, an effective and reliable high-throughput method was proposed for assisting the selection of the high NUE breeding phenotype.

Genome-Wide Identification and Expansion Patterns of SULTR Gene Family in Gramineae Crops and Their Expression Profiles under Abiotic Stress in Oryza sativa.

Sulfate transporters (SULTRs), also known as H+/SO42- symporters, play a key role in sulfate transport, plant growth and stress responses. However, the evolutionary relationships and functional differentiation of SULTRs in Gramineae crops are rarely reported. Here, 111 SULTRs were retrieved from the genomes of 10 Gramineae species, including Brachypodium disachyon, Hordeum vulgare, Setaria italica, Sorghum bicolor, Zea mays, Oryza barthii, Oryza rufipogon, Oryza glabbermia and Oryza sativa (Oryza sativa ssp. indica and Oryza sativa ssp. japonica). The SULTRs were clustered into five clades based on a phylogenetic analysis. Syntheny analysis indicates that whole-genome duplication/segmental duplication and tandem duplication events were essential in the SULTRs family expansion. We further found that different clades and orthologous groups of SULTRs were under a strong purifying selective force. Expression analysis showed that rice SULTRs with high-affinity transporters are associated with the functions of sulfate uptake and transport during rice seedling development. Furthermore, using Oryza sativa ssp. indica as a model species, we found that OsiSULTR10 was significantly upregulated under salt stress, while OsiSULTR3 and OsiSULTR12 showed remarkable upregulation under high temperature, low-selenium and drought stresses. OsiSULTR3 and OsiSULTR9 were upregulated under both low-selenium and high-selenium stresses. This study illustrates the expression and evolutionary patterns of the SULTRs family in Gramineae species, which will facilitate further studies of SULTR in other Gramineae species.

Resequencing of 1,143 indica rice accessions reveals important genetic variations and different heterosis patterns.

Obtaining genetic variation information from indica rice hybrid parents and identification of loci associated with heterosis are important for hybrid rice breeding. Here, we resequence 1,143 indica accessions mostly selected from the parents of superior hybrid rice cultivars of China, identify genetic variations, and perform kinship analysis. We find different hybrid rice crossing patterns between 3- and 2-line superior hybrid lines. By calculating frequencies of parental variation differences (FPVDs), a more direct approach for studying rice heterosis, we identify loci that are linked to heterosis, which include 98 in superior 3-line hybrids and 36 in superior 2-line hybrids. As a proof of concept, we find two accessions harboring a deletion in OsNramp5, a previously reported gene functioning in cadmium absorption, which can be used to mitigate rice grain cadmium levels through hybrid breeding. Resource of indica rice genetic variation reported in this study will be valuable to geneticists and breeders.

Remote estimation of rice LAI based on Fourier spectrum texture from UAV image.

BACKGROUND: The accurate estimation of rice LAI is particularly important to monitor rice growth status. Remote sensing, as a non-destructive measurement technology, has been proved to be useful for estimating vegetation growth parameters, especially at large scale. With the development of unmanned aerial vehicles (UAVs), this novel remote sensing platform has been widely used to provide remote sensing images which have much higher spatial resolution. Previous reports have shown that the spectral feature of remote sensing images could be an effective indicator to estimate vegetation growth parameters. However, the texture feature of high-resolution remote sensing images is rarely employed for this purpose. Besides, the physical mechanism between the texture feature and vegetation growth parameters is still unclear. RESULTS: In this study, a Fourier spectrum texture based on the UAV Image was developed to estimate rice LAI. And the relationship between Fourier spectrum texture and rice LAI was also analyzed. The results showed that Fourier spectrum texture could improve the accuracy of rice LAI estimation. CONCLUSIONS: In conclusion, the texture feature of high-resolution remote sensing images may be more effective in rice LAI estimation than the spectral feature.

Remote Estimation of Rice Yield With Unmanned Aerial Vehicle (UAV) Data and Spectral Mixture Analysis.

The accurate assessment of rice yield is crucially important for China's food security and sustainable development. Remote sensing (RS), as an emerging technology, is expected to be useful for rice yield estimation especially at regional scales. With the development of unmanned aerial vehicles (UAVs), a novel approach for RS has been provided, and it is possible to acquire high spatio-temporal resolution imagery on a regional scale. Previous reports have shown that the predictive ability of vegetation index (VI) decreased under the influence of panicle emergence during the later stages of rice growth. In this study, a new approach which integrated UAV-based VI and abundance information obtained from spectral mixture analysis (SMA) was established to improve the estimation accuracy of rice yield at heading stage. The six-band image of all studied rice plots was collected by a camera system mounted on an UAV at booting stage and heading stage respectively. And the corresponding ground measured data was also acquired at the same time. The relationship of several widely-used VIs and Rice Yield was tested at these two stages and a relatively weaker correlation between VI and yield was found at heading stage. In order to improve the estimation accuracy of rice yield at heading stage, the plot-level abundance of panicle, leaf and soil, indicating the fraction of different components within the plot, was derived from SMA on the six-band image and in situ endmember spectra collected for different components. The results showed that VI incorporated with abundance information exhibited a better predictive ability for yield than VI alone. And the product of VI and the difference of leaf abundance and panicle abundance was the most accurate index to reliably estimate yield for rice under different nitrogen treatments at heading stage with the coefficient of determination reaching 0.6 and estimation error below 10%.

Remote estimation of rapeseed yield with unmanned aerial vehicle (UAV) imaging and spectral mixture analysis.

BACKGROUND: The accurate quantification of yield in rapeseed is important for evaluating the supply of vegetable oil, especially at regional scales. METHODS: This study developed an approach to estimate rapeseed yield with remotely sensed canopy spectra and abundance data by spectral mixture analysis. A six-band image of the studied rapeseed plots was obtained by an unmanned aerial vehicle (UAV) system during the rapeseed flowering stage. Several widely used vegetation indices (VIs) were calculated from canopy reflectance derived from the UAV image. And the plot-level abundance of flower, leaf and soil, indicating the fraction of different components within the plot, was retrieved based on spectral mixture analysis on the six-band image and endmember spectra collected in situ for different components. RESULTS: The results showed that for all tested indices VI multiplied by leaf-related abundance closely related to rapeseed yield. The product of Normalized Difference Vegetation Index and short-stalk-leaf abundance was the most accurate for estimating yield in rapeseed under different nitrogen treatments with the estimation errors below 13%. CONCLUSION: This study gives an important indication that spectral mixture analysis needs to be considered when estimating yield by remotely sensed VI, especially for the image containing obviously spectral different components or for crops which have conspicuous flowers or fruits with significantly different spectra from their leave.

Metabolic prediction of important agronomic traits in hybrid rice (Oryza sativa L.).

Hybrid crops have contributed greatly to improvements in global food and fodder production over the past several decades. Nevertheless, the growing population and changing climate have produced food crises and energy shortages. Breeding new elite hybrid varieties is currently an urgent task, but present breeding procedures are time-consuming and labour-intensive. In this study, parental metabolic information was utilized to predict three polygenic traits in hybrid rice. A complete diallel cross population consisting of eighteen rice inbred lines was constructed, and the hybrids' plant height, heading date and grain yield per plant were predicted using 525 metabolites. Metabolic prediction models were built using the partial least square regression method, with predictive abilities ranging from 0.858 to 0.977 for the hybrid phenotypes, relative heterosis, and specific combining ability. Only slight changes in predictive ability were observed between hybrid populations, and nearly no changes were detected between reciprocal hybrids. The outcomes of prediction of the three highly polygenic traits demonstrated that metabolic prediction was an accurate (high predictive abilities) and efficient (unaffected by population genetic structures) strategy for screening promising superior hybrid rice. Exploitation of this pre-hybridization strategy may contribute to rice production improvement and accelerate breeding programs.

Hierarchical additive effects on heterosis in rice (Oryza sativa L.).

Exploitation of heterosis in crops has contributed greatly to improvement in global food and energy production. In spite of the pervasive importance of heterosis, a complete understanding of its mechanisms has remained elusive. In this study, a small test-crossed rice population was constructed to investigate the formation mechanism of heterosis for 13 traits. The results of the relative mid-parent heterosis and modes of inheritance of all investigated traits demonstrated that additive effects were the foundation of heterosis for complex traits in a hierarchical structure, and multiplicative interactions among the component traits were the framework of heterosis in complex traits. Furthermore, new balances between unit traits and related component traits provided hybrids with the opportunity to achieve an optimal degree of heterosis for complex traits. This study dissected heterosis of both reproductive and vegetative traits from the perspective of hierarchical structure for the first time. Additive multiplicative interactions of component traits were proven to be the origin of heterosis in complex traits. Meanwhile, more attention should be paid to component traits, rather than complex traits, in the process of revealing the mechanism of heterosis.

Cytological and transcriptional dynamics analysis of host plant revealed stage-specific biological processes related to compatible rice-Ustilaginoidea virens interaction.

Rice false smut, a fungal disease caused by Ustilaginoidea virens is becoming a severe detriment to rice production worldwide. However, little is known about the molecular response of rice to attacks by the smut pathogen. In this article, we define the initial infection process as having three stages: initial colonization on the pistil (stage 1, S1), amplification on the anther (stage 2, S2) and sporulation in the anther chambers (stage 3, S3). Based on the transcriptome of rice hosts in response to U. virens in two separate years, we identified 126, 204, and 580 specific regulated genes in their respective stages S1, S2, and S3, respectively, by excluding common expression patterns in other openly biotic/abiotic databases using bioinformatics. As the disease progresses, several stage-specific biological processes (BP) terms were distinctively enriched: "Phosphorylation" in stage S1, "PCD" in S2, and "Cell wall biogenesis" in S3, implying a concise signal cascade indicative of the tactics that smut pathogens use to control host rice cells during infection. 113 regulated genes were coexpressed among the three stages. They shared highly conserved promoter cis-element in the promoters in response to the regulation of WRKY and Myb for up-regulation, and ABA and Ca2+ for down regulation, indicating their potentially critical roles in signal transduction during rice-U. virens interaction. We further analyzed seven highly regulated unique genes; four were specific to pollen development, implying that pollen-related genes play critical roles in the establishment of rice susceptibility to U. virens. To my knowledge, this is the first report about probing of molecular response of rice to smut pathogen infection, which will greatly expand our understanding of the molecular events surrounding infection by rice false smut.