Rice Functional Genomics Research: Past Decade and Future

Amand P, Rupp J, Pumphrey M, Fritz A, Zhang G, Jordan KW, Bai G. A novel quantitative trait locus for barley yellow dwarf virus resistance and kernel traits on chromosome 2D of a wheat cultivar Jagger

Barley yellow dwarf (BYD) is one of the most serious viral diseases in cereal crops worldwide. Identification of quantitative trait loci (QTLs) underlining wheat resistance to barley yellow dwarf virus (BYDV) is essential for breeding BYDV-tolerant wheat cultivars. In this study, a recombinant inbred line (RIL) population was developed from the cross between Jagger (PI 593688) and a Jagger mutant (JagMut1095). A linkage map of 3106 cM consisting of 21 wheat chromosomes was developed using 1003 unique single nucleotide polymorphisms (SNPs) from the RIL population and was used to identify QTLs for BYDV resistance and yield-related traits, including 1000-kernel weight (TKW), kernel area (KA), kernel width (KW), and kernel length (KL). QByd.hwwg-2DL, a QTL on chromosome arm 2DL for BYDV resistance, was consistently identified in three field experiments and explained 11.6%-44.5% of the phenotypic variation. For yield-related traits, six major and repeatable QTLs were identified on 1AS (QKa.hwwg-1AS), 2DL (QTkw.hwwg-2DL, QKa.hwwg-2DL, QKw.hwwg-2DL, and QKl.hwwg-2DL), and 5AL (QKw.hwwg-5AL). The major QTLs on chromosome 2DL for TKW, KA, KW, and KL were mapped between 621 and 643 Mb, overlapping with QByd.hwwg-2DL with all the favorable alleles from Jagger. This study reports the first native BYDV resistance QTL (QByd.hwwg-2DL) originating from common wheat and tightly linked markers to the QTL for improvement of wheat BYDV resistance in wheat breeding.

Genome-wide identification and characterization of cation-proton antiporter (CPA) gene family in rice (Oryza sativa L.) and their expression profiles in response to phytohormones

The cation-proton antiporter (CPA) superfamily plays pivotal roles in regulating cellular ion and pH homeostasis in plants. To date, the regulatory functions of CPA family members in rice (Oryza sativa L.) have not been elucidated. In this study, we use rice public data and information techniques, 29 OsCPA candidate genes were identified in the rice japonica variety (referred to as OsCPA) and phylogenetically categorized into K+ efflux antiporter (KEA), Na+/H+ exchanger (NHX), and cation/H+ exchanger (CHX) groups containing 4, 7, and 18 OsCPA genes. The OsCPA proteins were predominantly localized in the plasma membrane and unevenly scattered on 11 chromosomes. The structural analysis of OsCPA proteins revealed higher similarities within groups. Prediction of selection pressure, collinearity, and synteny analysis indicated that all duplicated OsCPA genes had undergone strong purifying selection throughout their evolution. The cis-acting regulatory elements (CAREs) analysis identified 56 CARE motifs responsive to light, tissue, hormones, and stresses. Additionally, 124 miRNA families were identified in the gene promoters, and OsNHX7 was targeted by the highest number of miRNAs (43 miRNAs). Gene Ontology analysis demonstrated the numerous functions of OsCPA genes associated with biological processes (57.14%), cellular components (7.94%), and molecular functions (34.92%). A total of 12 transcription factor families (TFFs), including 40 TFs were identified in gene promoters, with the highest numbers of TFFs (5TFFs) linked to OsCHX13, and OsCHX15. Protein-protein interaction analysis suggested maximum functional similarities between rice and Arabidopsis CPA proteins. Based on expression analysis, OsKEA1, OsKEA2, OsNHX3, and OsNHX7 were frequently expressed in rice tissues. Furthermore, OsNHX3, OsNHX4, OsNHX6, OsNHX7, OsCHX8, and OsCHX17 in abscisic acid, OsKEA1, OsNHX3, and OsCHX8 in gibberellic acid, OsKEA1, OsKEA3, OsNHX1, and OsNHX3 in indole-3-acetic acid treatment were demonstrated as potential candidates in response to hormone. These findings highlight potential candidates for further characterization of OsCPA genes, which may aid in the development of rice varieties.

Sludge-derived biostimulants promote glycosylation of tricin and luteolin in the flavone and flavonol biosynthesis to enhance anti-inflammatory activities of rice

Alkaline thermal hydrolysis of sewage sludge produces nutrients and biostimulants that enhance plant growth, attracting considerable interest in agriculture. However, the metabolic differences and regulatory mechanisms of sewage sludge-derived biostimulants (SS-BS) on the phenotypic traits, nutritional quality, and safety indicators of harvested crops remain unclear. This study investigates the impact of SS-BS on rice quality on an agricultural production scale. The research reveals that rice treated with SS-BS complies with safety standards comparable to premium rice. SS-BS significantly enhances nutrient enrichment in the endosperm, increasing protein, vitamin B1, dietary fiber, and vitamin E content by 7%, 7.2%, 23.2%, and 42.2%, respectively. Furthermore SS-BS upregulates the FG2 gene,leading to increased Nictoflorin content and activation of the gene expression of UGT73C6 and CYP75A, which catalyze O-glycosylation and promot glycosyl transfer. By inhibiting the synthesis of Trifolin, Scolymoside, and Swertiajaponin, SS-BS favors the synthesis of glycosylated derivatives of Tricin and Luteolin, which exhibit higher anti-inflammatory activity. Additionally, two novel genes, novel.2100 and novel.1300, and an uncharacterized gene, LOC9269295, are closely associated with the production of anti-inflammatory and antioxidant compounds. This study provides new evidence for SS-BS application and insights into their regulatory mechanisms affecting crop quality, contributing to the development of functional foods and sustainable agriculture.

A Simple Narrative Review of Progress on the Processing and Utilization of Functional Rice

This paper aims to review the research progress on the processing and utilization of functional rice and explore its potential to enhance human health. The research progress in the processing and utilization of colored rice, low-protein rice, high-resistant starch rice, micronutrient-enriched rice, and bioreactor rice was systematically analyzed through a comprehensive literature review. The impact of various processing techniques on the retention of nutritional components in functional rice was also discussed. This study found that functional rice exhibits great potential in terms of nutritional value, health effects, and market demand. However, issues such as the loss of bioactive components during processing, the maintenance of specific agronomic traits, and market acceptance still need to be addressed. The research and development of functional rice are significant for enriching people's dietary choices and addressing global malnutrition and chronic disease problems. Future efforts should focus on further optimizing processing techniques and utilizing genetic engineering and molecular breeding technologies to enhance the nutritional value and agronomic traits of functional rice, thus meeting market demands and health objectives.

Rapid and dynamic detection of endogenous proteins through in locus tagging in rice

Understanding the behavior of endogenous proteins is crucial for functional genomics, yet their dynamic characterization in plants presents substantial challenges. Whereas mammalian studies have leveraged in locus tagging with the luminescent HiBiT peptide and genome editing for rapid quantification of native proteins, this approach remains unexplored in plants. Here, we introduce the in locus HiBiT tagging of rice proteins and demonstrate its feasibility in plants. We found that although traditional HiBiT blotting works in rice, it failed to detect two of the three tagged proteins, a result attributable to low luminescence activity in plants. To overcome this limitation, we engaged in extensive optimization, culminating in a new luciferin substrate coupled with a refined reaction protocol that enhanced luminescence up to 6.9 fold. This innovation led to the development of TagBIT (tagging with HiBiT), a robust method for high-sensitivity protein characterization in plants. Our application of TagBIT to seven rice genes illustrates its versatility on endogenous proteins, enabling antibody-free protein blotting, real-time protein quantification via luminescence, in situ visualization using a cross-breeding strategy, and effective immunoprecipitation for analysis of protein interactions. The heritable nature of this system, confirmed across T1 to T3 generations, positions TagBIT as a powerful tool for protein study in plant biology.

Community metagenomics reveals the processes of cadmium resistance regulated by microbial functions in soils with Oryza sativa root exudate input

Plants exert a profound influence on their rhizosphere microbiome through the secretion of root exudates, thereby imparting critical effects on their growth and overall health. The results unveil that japonica rice showcases a remarkable augmentation in its antioxidative stress mechanisms under Cd stress. This augmentation is characterized by the sequestration of heavy metal ions within the root system and the prodigious secretion of a spectrum of flavonoids, including Quercetin, Luteolin, Apigenin, Kaempferide, and Sakuranetin. These flavonoids operate as formidable guardians, shielding the plant from oxidative damage instigated by Cd-induced stress. Furthermore, the metagenomic analyses divulge the transformative potential of flavonoids, as they induce profound alterations in the composition and structural dynamics of plant rhizosphere microbial communities. These alterations manifest through the recruitment of plant growth-promoting bacteria, effectively engineering a conducive milieu for japonica rice. In addition, our symbiotic network analysis discerns that flavonoid compounds significantly improved the positive correlations among dominant species within the rhizosphere of japonica rice. This, in turn, bolsters the stability and intricacy of the microenvironmental ecological network. KEGG functional analyses reveal a notable upregulation in the expression of flavonoid functional genes, specifically cadA, cznA, nccC, and czrB, alongside an array of transporters, encompassing RND, ABC, MIT, and P-ATPase. These molecular orchestrations distinctly demarcated the rhizosphere microbiome of japonica rice, markedly enhancing its tolerance to Cd-induced stress. These findings not only shed light on the establishment of Cd-resistant bacterial consortia in rice but also herald a promising avenue for the precise modulation of plant rhizosphere microbiomes, thereby fortifying the safety and efficiency of crop production.

The OsGAPC3 mutation significantly affects grain quality traits and improves the nutritional quality of rice

The glycolytic enzyme cytoplasmic glyceraldehyde-3-phosphate dehydrogenase (GAPC3) is involved in multiple biological processes in plants, including transcriptional regulation, and material metabolism. However, the relationship between OsGAPC3 and the quality traits of rice is poorly understood. Here we identify OsGAPC3 mutations that enhance the protein content and grain nutritional quality of rice by regulating the OsAAP6 gene expression. The number and volume of type-II protein bodies in the endosperm of the OsGAPC3 mutants, and GPC increase significantly. We report significant increases in chalkiness area and degree, and decreases for starch content, gel consistency, and taste value. Results of proteomic detection and analysis reveal that OsGAPC3 affects the major storage substances (proteins and starch) metabolism in rice, and the accumulation of proteins and starch in the endosperm. Additionally, the OsGAPC3 mutation significantly decreases the rice-seedling salt tolerance. Therefore, OsGAPC3 affects multiple quality traits of rice, participates in regulating rice-seedling salt-stress response. These data can be used to design better-quality and stronger salt-resistant rice varieties.

Exploring Lignin Biosynthesis Genes in Rice: Evolution, Function, and Expression

Lignin is nature's second most abundant vascular plant biopolymer, playing significant roles in mechanical support, water transport, and stress responses. This study identified 90 lignin biosynthesis genes in rice based on phylogeny and motif constitution, and they belong to PAL, C4H, 4CL, HCT, C3H, CCoAOMT, CCR, F5H, COMT, and CAD families. Duplication events contributed largely to the expansion of these gene families, such as PAL, CCoAOMT, CCR, and CAD families, mainly attributed to tandem and segmental duplication. Microarray data of 33 tissue samples covering the entire life cycle of rice suggested fairly high PAL, HCT, C3H, CCoAOMT, CCR, COMT, and CAD gene expressions and rather variable C4H, 4CL, and F5H expressions. Some members of lignin-related genes (OsCCRL11, OsHCT1/2/5, OsCCoAOMT1/3/5, OsCOMT, OsC3H, OsCAD2, and OsPAL1/6) were expressed in all tissues examined. The expression patterns of lignin-related genes can be divided into two major groups with eight subgroups, each showing a distinct co-expression in tissues representing typically primary and secondary cell wall constitutions. Some lignin-related genes were strongly co-expressed in tissues typical of secondary cell walls. Combined HPLC analysis showed increased lignin monomer (H, G, and S) contents from young to old growth stages in five genotypes. Based on 90 genes' microarray data, 27 genes were selected for qRT-PCR gene expression analysis. Four genes (OsPAL9, OsCAD8C, OsCCR8, and OsCOMTL4) were significantly negatively correlated with lignin monomers. Furthermore, eleven genes were co-expressed in certain genotypes during secondary growth stages. Among them, six genes (OsC3H, OsCAD2, OsCCR2, OsCOMT, OsPAL2, and OsPAL8) were overlapped with microarray gene expressions, highlighting their importance in lignin biosynthesis.

Bayesian Lookahead Perturbation Policy for Inference of Regulatory Networks

The complexity, scale, and uncertainty in regulatory networks (e.g., gene regulatory networks and microbial networks) regularly pose a huge uncertainty in their models. These uncertainties often cannot be entirely reduced using limited and costly data acquired from the normal condition of systems. Meanwhile, regulatory networks often suffer from the non-identifiability issue, which refers to scenarios where the true underlying network model cannot be clearly distinguished from other possible models. Perturbation or excitation is a well-known process in systems biology for acquiring targeted data to reveal the complex underlying mechanisms of regulatory networks and overcome the non-identifiability issue. We consider a general class of Boolean network models for capturing the activation and inactivation of components and their complex interactions. Assuming partial available knowledge about the interactions between components of the networks, this paper formulates the inference process through the maximum aposteriori (MAP) criterion. We develop a Bayesian lookahead policy that systematically perturbs regulatory networks to maximize the performance of MAP inference under the perturbed data. This is achieved by optimally formulating the perturbation process in a reinforcement learning context and deriving a scalable deep reinforcement learning perturbation policy to compute near-optimal Bayesian policy. The proposed method learns the perturbation policy through planning without the need for any real data. The high performance of the proposed approach is demonstrated by comprehensive numerical experiments using the well-known mammalian cell cycle and gut microbial community networks.

Comprehensive mapping and modelling of the rice regulome landscape unveils the regulatory architecture underlying complex traits

Unraveling the regulatory mechanisms that govern complex traits is pivotal for advancing crop improvement. Here we present a comprehensive regulome atlas for rice (Oryza sativa), charting the chromatin accessibility across 23 distinct tissues from three representative varieties. Our study uncovers 117,176 unique open chromatin regions (OCRs), accounting for ~15% of the rice genome, a notably higher proportion compared to previous reports in plants. Integrating RNA-seq data from matched tissues, we confidently predict 59,075 OCR-to-gene links, with enhancers constituting 69.54% of these associations, including many known enhancer-to-gene links. Leveraging this resource, we re-evaluate genome-wide association study results and discover a previously unknown function of OsbZIP06 in seed germination, which we subsequently confirm through experimental validation. We optimize deep learning models to decode regulatory grammar, achieving robust modeling of tissue-specific chromatin accessibility. This approach allows to predict cross-variety regulatory dynamics from genomic sequences, shedding light on the genetic underpinnings of cis-regulatory divergence and morphological disparities between varieties. Overall, our study establishes a foundational resource for rice functional genomics and precision molecular breeding, providing valuable insights into regulatory mechanisms governing complex traits.

OsG6PGH1 affects various grain quality traits and participates in the salt stress response of rice

Cytoplasmic 6-phosphogluconate dehydrogenase (G6PGH) is a key enzyme in the pentose phosphate pathway that is involved in regulating various biological processes such as material metabolism, and growth and development in plants. However, it was unclear if OsG6PGH1 affected rice grain quality traits. We perform yeast one-hybrid experiments and reveal that OsG6PGH1 may interact with OsAAP6. Subsequently, yeast in vivo point-to-point experiments and local surface plasmon resonance experiments verified that OsG6PGH1 can bind to OsAAP6. OsG6PGH1 in rice is a constitutive expressed gene that may be localized in the cytoplasm. OsAAP6 and protein-synthesis metabolism-related genes are significantly upregulated in OsG6PGH1 overexpressing transgenic positive endosperm, corresponding to a significant increase in the number of protein bodies II, promoting accumulation of related storage proteins, a significant increase in grain protein content (GPC), and improved rice nutritional quality. OsG6PGH1 positively regulates amylose content, negatively regulates chalkiness rate and taste value, significantly affects grain quality traits such as appearance, cooking, and eating qualities of rice, and is involved in regulating the expression of salt stress related genes, thereby enhancing the salt-stress tolerance of rice. Therefore, OsG6PGH1 represents an important genetic resource to assist in the design of high-quality and multi-resistant rice varieties.

Comprehensive physiology and proteomics analysis revealed the molecular toxicological mechanism of Se stress on indica and japonica rice

Selenium pollution can lead to a decrease in crop yield and quality. However, the toxicological mechanisms of high Se concentrations on crops remain unclear. This study aimed to elucidate the physiological and proteomic molecular responses to Se stress in Oryza sativa. The results showed that under selenium stress, enzymatic activities of catalase, peroxidase, and superoxide dismutase in indica rice decreased by 61%, 28%, and 68%, respectively. The contents of non-enzymatic antioxidant substances ascorbic acid, glutathione, cysteine, proline, anthocyanidin, and flavonoids were decreased by 13%, 39%, 46%, 32%, 20%, and 5%, respectively, which significantly inhibited the antioxidant stress process of plants. At the same time, the results of proteomics analysis showed that rice seedlings, under Se stress, are involved in photosynthesis, photosynthesis-antenna proteins, carbon fixation, porphyrin metabolism, glyoxylate, and dicarboxylate. The differentially expressed proteins in metabolism and glutathione metabolism pathways showed a downward trend. It significantly inhibited the anti-oxidative stress, photosynthesis, and energy cycling process in plant cells, destroyed the homeostasis balance of rice plants, and inhibited the growth and development of rice. This finding reveals the molecular toxicological mechanism of Se stress on rice seedlings and provides a possible way to improve Se-resistant rice seedlings.

Utilizing transcriptomics and proteomics to unravel key genes and proteins of Oryza sativa seedlings mediated by selenium in response to cadmium stress

BACKGROUND

Cadmium (Cd) pollution has declined crop yields and quality. Selenium (Se) is a beneficial mineral element that protects plants from oxidative damage, thereby improving crop tolerance to heavy metals. The molecular mechanism of Se-induced Cd tolerance in rice (Oryza sativa) is not yet understood. This study aimed to elucidate the beneficial mechanism of Se (1 mg/kg) in alleviating Cd toxicity in rice seedlings.

RESULTS

Exogenous selenium addition significantly improved the toxic effect of cadmium stress on rice seedlings, increasing plant height and fresh weight by 20.53% and 34.48%, respectively, and increasing chlorophyll and carotenoid content by 16.68% and 15.26%, respectively. Moreover, the MDA, ·OH, and protein carbonyl levels induced by cadmium stress were reduced by 47.65%, 67.57%, and 56.43%, respectively. Cell wall metabolism, energy cycling, and enzymatic and non-enzymatic antioxidant systems in rice seedlings were significantly enhanced. Transcriptome analysis showed that the expressions of key functional genes psbQ, psbO, psaG, psaD, atpG, and PetH were significantly up-regulated under low-concentration Se treatment, which enhanced the energy metabolism process of photosystem I and photosystem II in rice seedlings. At the same time, the up-regulation of LHCA, LHCB family, and C4H1, PRX, and atp6 functional genes improved the ability of photon capture and heavy metal ion binding in plants. Combined with proteome analysis, the expression of functional proteins OsGSTF1, OsGSTU11, OsG6PDH4, OsDHAB1, CP29, and CabE was significantly up-regulated under Se, which enhanced photosynthesis and anti-oxidative stress mechanism in rice seedlings. At the same time, it regulates the plant hormone signal transduction pathway. It up-regulates the expression response process of IAA, ABA, and JAZ to activate the synergistic effect between each cell rapidly and jointly maintain the homeostasis balance.

CONCLUSION

Our results revealed the regulation process of Se-mediated critical metabolic pathways, functional genes, and proteins in rice under cadmium stress. They provided insights into the expression rules and dynamic response process of the Se-mediated plant resistance mechanism. This study provided the theoretical basis and technical support for crop safety in cropland ecosystems and cadmium-contaminated areas.

Plant Functional Genomics Based on High-Throughput CRISPR Library Knockout Screening: A Perspective

Plant biology studies in the post-genome era have been focused on annotating genome sequences' functions. The established plant mutant collections have greatly accelerated functional genomics research in the past few decades. However, most plant genome sequences' roles and the underlying regulatory networks remain substantially unknown. Clustered, regularly interspaced short palindromic repeat (CRISPR)-associated systems are robust, versatile tools for manipulating plant genomes with various targeted DNA perturbations, providing an excellent opportunity for high-throughput interrogation of DNA elements' roles. This study compares methods frequently used for plant functional genomics and then discusses different DNA multi-targeted strategies to overcome gene redundancy using the CRISPR-Cas9 system. Next, this work summarizes recent reports using CRISPR libraries for high-throughput gene knockout and function discoveries in plants. Finally, this work envisions the future perspective of optimizing and leveraging CRISPR library screening in plant genomes' other uncharacterized DNA sequences.

Genetic dissection of monosaccharides contents in rice whole grain using genome-wide association study

The simplest form of carbohydrates are monosaccharides which are the building blocks for the synthesis of polymers or complex carbohydrates. Monosaccharide contents of 197 rice accessions were quantified by HPAEC-PAD in rice (Oryza sativa L.) whole grain (RWG). A genome-wide association study (GWAS) was carried out using 33,812 single nucleotide polymorphisms (SNPs) to identify corresponding genomic regions influencing neutral monosaccharides contents. In total, 49 GWAS signals contained in 17 genomic regions (quantitative trait loci [QTLs]) on seven chromosomes of rice were determined to be associated with monosaccharides contents of whole grain. The QTLs were found for fucose (1), mannose (1), xylose (2), arabinose (2), galactose (4), and rhamnose (7) contents, all of which are novel. Based on co-location of annotated rice genes in the vicinity of GWAS signals, the constituents of the whole grain were associated with the following candidate genes: arabinose content with α-N-arabinofuranosidase, pectinesterase inhibitor, and glucosamine-fructose-6-phosphate aminotransferase 1; xylose content with ZOS1-10 (a C2H2 zinc finger transcription factor [TF]); mannose content with aldose 1-epimerase-like protein and a MYB family TF; galactose content with a GT8 family member (galacturonosyltransferase-like 3), a GRAS family TF, and a GH16 family member (xyloglucan endotransglucosylase/hydrolase xyloglucan 23); fucose content with gibberellin 20 oxidase and a lysine-rich arabinogalactan protein 19, and finally rhamnose content with myo-inositol-1-phosphate synthase, UDP-arabinopyranose mutase, and COBRA-like protein precursor. The results of this study should improve our understanding of the genetic basis of the factors that might be involved in the biosynthesis, regulation, and turnover of monosaccharides in RWG, aiming to enhance the nutritional value of rice grain and impact the related industries.

Multiple insights into lignin-mediated cadmium detoxification in rice (Oryza sativa)

Cadmium (Cd) is readily absorbed by rice and enters the food chain, posing a health risk to humans. A better understanding of the mechanisms of Cd-induced responses in rice will help in developing solutions to reduce Cd uptake in rice. Therefore, this research attempted to reveal the detoxification mechanisms of rice in response to Cd through physiological, transcriptomic and molecular approaches. The results showed that Cd stress restricted rice growth, led to Cd accumulation and H2O2 production, and resulted cell death. Transcriptomic sequencing revealed glutathione and phenylpropanoid were the major metabolic pathways under Cd stress. Physiological studies showed that antioxidant enzyme activities, glutathione and lignin contents were significantly increased under Cd stress. In response to Cd stress, q-PCR results showed that genes related to lignin and glutathione biosynthesis were upregulated, whereas metal transporter genes were downregulated. Further pot experiment with rice cultivars with increased and decreased lignin content confirmed the causal relationship between increased lignin and reduced Cd in rice. This study provides a comprehensive understanding of lignin-mediated detoxification mechanism in rice under Cd stress and explains the function of lignin in production of low-Cd rice to ensure human health and food safety.

Weighted gene co-expression network analysis of nitrogen (N)-responsive genes and the putative role of G-quadruplexes in N use efficiency (NUE) in rice

Rice is an important target to improve crop nitrogen (N) use efficiency (NUE), and the identification and shortlisting of the candidate genes are still in progress. We analyzed data from 16 published N-responsive transcriptomes/microarrays to identify, eight datasets that contained the maximum number of 3020 common genes, referred to as N-responsive genes. These include different classes of transcription factors, transporters, miRNA targets, kinases and events of post-translational modifications. A Weighted gene co-expression network analysis (WGCNA) with all the 3020 N-responsive genes revealed 15 co-expression modules and their annotated biological roles. Protein-protein interaction network analysis of the main module revealed the hub genes and their functional annotation revealed their involvement in the ubiquitin process. Further, the occurrences of G-quadruplex sequences were examined, which are known to play important roles in epigenetic regulation but are hitherto unknown in N-response/NUE. Out of the 3020 N-responsive genes studied, 2298 contained G-quadruplex sequences. We compared these N-responsive genes containing G-quadruplex sequences with the 3601 genes we previously identified as NUE-related (for being both N-responsive and yield-associated). This analysis revealed 389 (17%) NUE-related genes containing G-quadruplex sequences. These genes may be involved in the epigenetic regulation of NUE, while the rest of the 83% (1811) genes may regulate NUE through genetic mechanisms and/or other epigenetic means besides G-quadruplexes. A few potentially important genes/processes identified as associated with NUE were experimentally validated in a pair of rice genotypes contrasting for NUE. The results from the WGCNA and G4 sequence analysis of N-responsive genes helped identify and shortlist six genes as candidates to improve NUE. Further, the hitherto unavailable segregation of genetic and epigenetic gene targets could aid in informed interventions through genetic and epigenetic means of crop improvement.

Genome-Wide Association Study Identified Candidate Genes for Alkalinity Tolerance in Rice

Alkalinity stress is a major hindrance to enhancing rice production globally due to its damaging effect on plants' growth and development compared with salinity stress. However, understanding of the physiological and molecular mechanisms of alkalinity tolerance is limited. Therefore, a panel of indica and japonica rice genotypes was evaluated for alkalinity tolerance at the seedling stage in a genome-wide association study to identify tolerant genotypes and candidate genes. Principal component analysis revealed that traits such as alkalinity tolerance score, shoot dry weight, and shoot fresh weight had the highest contribution to variations in tolerance, while shoot Na⁺ concentration, shoot Na⁺:K⁺ ratio, and root-to-shoot ratio had moderate contributions. Phenotypic clustering and population structure analysis grouped the genotypes into five subgroups. Several salt-susceptible genotypes such as IR29, Cocodrie, and Cheniere placed in the highly tolerant cluster suggesting different underlying tolerance mechanisms for salinity and alkalinity tolerance. Twenty-nine significant SNPs associated with alkalinity tolerance were identified. In addition to three alkalinity tolerance QTLs, qSNK4, qSNC9, and qSKC10, which co-localized with the earlier reported QTLs, a novel QTL, qSNC7, was identified. Six candidate genes that were differentially expressed between tolerant and susceptible genotypes were selected: LOC_Os04g50090 (Helix-loop-helix DNA-binding protein), LOC_Os08g23440 (amino acid permease family protein), LOC_Os09g32972 (MYB protein), LOC_Os08g25480 (Cytochrome P450), LOC_Os08g25390 (Bifunctional homoserine dehydrogenase), and LOC_Os09g38340 (C2H2 zinc finger protein). The genomic and genetic resources such as tolerant genotypes and candidate genes would be valuable for investigating the alkalinity tolerance mechanisms and for marker-assisted pyramiding of the favorable alleles for improving alkalinity tolerance at the seedling stage in rice.

Structure-Based Inverse Reinforcement Learning for Quantification of Biological Knowledge

Gene regulatory networks (GRNs) play crucial roles in various cellular processes, including stress response, DNA repair, and the mechanisms involved in complex diseases such as cancer. Biologists are involved in most biological analyses. Thus, quantifying their policies reflected in available biological data can significantly help us to better understand these complex systems. The primary challenges preventing the utilization of existing machine learning, particularly inverse reinforcement learning techniques, to quantify biologists' knowledge are the limitations and huge amount of uncertainty in biological data. This paper leverages the network-like structure of GRNs to define expert reward functions that contain exponentially fewer parameters than regular reward models. Numerical experiments using mammalian cell cycle and synthetic gene-expression data demonstrate the superior performance of the proposed method in quantifying biologists' policies.

The power of retrotransposons in high-throughput genotyping and sequencing

The use of molecular markers has become an essential part of molecular genetics through their application in numerous fields, which includes identification of genes associated with targeted traits, operation of backcrossing programs, modern plant breeding, genetic characterization, and marker-assisted selection. Transposable elements are a core component of all eukaryotic genomes, making them suitable as molecular markers. Most of the large plant genomes consist primarily of transposable elements; variations in their abundance contribute to most of the variation in genome size. Retrotransposons are widely present throughout plant genomes, and replicative transposition enables them to insert into the genome without removing the original elements. Various applications of molecular markers have been developed that exploit the fact that these genetic elements are present everywhere and their ability to stably integrate into dispersed chromosomal localities that are polymorphic within a species. The ongoing development of molecular marker technologies is directly related to the deployment of high-throughput genotype sequencing platforms, and this research is of considerable significance. In this review, the practical application to molecular markers, which is a use of technology of interspersed repeats in the plant genome were examined using genomic sources from the past to the present. Prospects and possibilities are also presented.

Cytological, transcriptome and miRNome temporal landscapes decode enhancement of rice grain size

BACKGROUND

Rice grain size (GS) is an essential agronomic trait. Though several genes and miRNA modules influencing GS are known and seed development transcriptomes analyzed, a comprehensive compendium connecting all possible players is lacking. This study utilizes two contrasting GS indica rice genotypes (small-grained SN and large-grained LGR). Rice seed development involves five stages (S1-S5). Comparative transcriptome and miRNome atlases, substantiated with morphological and cytological studies, from S1-S5 stages and flag leaf have been analyzed to identify GS proponents.

RESULTS

Histology shows prolonged endosperm development and cell enlargement in LGR. Stand-alone and comparative RNAseq analyses manifest S3 (5-10 days after pollination) stage as crucial for GS enhancement, coherently with cell cycle, endoreduplication, and programmed cell death participating genes. Seed storage protein and carbohydrate accumulation, cytologically and by RNAseq, is shown to be delayed in LGR. Fourteen transcription factor families influence GS. Pathway genes for four phytohormones display opposite patterns of higher expression. A total of 186 genes generated from the transcriptome analyses are located within GS trait-related QTLs deciphered by a cross between SN and LGR. Fourteen miRNA families express specifically in SN or LGR seeds. Eight miRNA-target modules display contrasting expressions amongst SN and LGR, while 26 (SN) and 43 (LGR) modules are differentially expressed in all stages.

CONCLUSIONS

Integration of all analyses concludes in a "Domino effect" model for GS regulation highlighting chronology and fruition of each event. This study delineates the essence of GS regulation, providing scope for future exploits. The rice grain development database (RGDD) ( www.nipgr.ac.in/RGDD/index.php ; https://doi.org/10.5281/zenodo.7762870 ) has been developed for easy access of data generated in this paper.

Genome-Wide Urea Response in Rice Genotypes Contrasting for Nitrogen Use Efficiency

Rice is an ideal crop for improvement of nitrogen use efficiency (NUE), especially with urea, its predominant fertilizer. There is a paucity of studies on rice genotypes contrasting for NUE. We compared low urea-responsive transcriptomes of contrasting rice genotypes, namely Nidhi (low NUE) and Panvel1 (high NUE). Transcriptomes of whole plants grown with media containing normal (15 mM) and low urea (1.5 mM) revealed 1497 and 2819 differentially expressed genes (DEGs) in Nidhi and Panvel1, respectively, of which 271 were common. Though 1226 DEGs were genotype-specific in Nidhi and 2548 in Panvel1, there was far higher commonality in underlying processes. High NUE is associated with the urea-responsive regulation of other nutrient transporters, miRNAs, transcription factors (TFs) and better photosynthesis, water use efficiency and post-translational modifications. Many of their genes co-localized to NUE-QTLs on chromosomes 1, 3 and 9. A field evaluation under different doses of urea revealed better agronomic performance including grain yield, transport/uptake efficiencies and NUE of Panvel1. Comparison of our urea-based transcriptomes with our previous nitrate-based transcriptomes revealed many common processes despite large differences in their expression profiles. Our model proposes that differential involvement of transporters and TFs, among others, contributes to better urea uptake, translocation, utilization, flower development and yield for high NUE.

Designing rice panicle architecture via developmental regulatory genes

Rice panicle architecture displays remarkable diversity in branch number, branch length, and grain arrangement; however, much remains unknown about how such diversity in patterns is generated. Although several genes related to panicle branch number and panicle length have been identified, how panicle branch number and panicle length are coordinately regulated is unclear. Here, we show that panicle length and panicle branch number are independently regulated by the genes Prl5/OsGA20ox4, Pbl6/APO1, and Gn1a/OsCKX2. We produced near-isogenic lines (NILs) in the Koshihikari genetic background harboring the elite alleles for Prl5, regulating panicle rachis length; Pbl6, regulating primary branch length; and Gn1a, regulating panicle branching in various combinations. A pyramiding line carrying Prl5, Pbl6, and Gn1a showed increased panicle length and branching without any trade-off relationship between branch length or number. We successfully produced various arrangement patterns of grains by changing the combination of alleles at these three loci. Improvement of panicle architecture raised yield without associated negative effects on yield-related traits except for panicle number. Three-dimensional (3D) analyses by X-ray computed tomography (CT) of panicles revealed that differences in panicle architecture affect grain filling. Importantly, we determined that Prl5 improves grain filling without affecting grain number.

Lost genome segments associate with trait diversity during rice domestication

BACKGROUND

DNA mutations of diverse types provide the raw material required for phenotypic variation and evolution. In the case of crop species, previous research aimed to elucidate the changing patterns of repetitive sequences, single-nucleotide polymorphisms (SNPs), and small InDels during domestication to explain morphological evolution and adaptation to different environments. Additionally, structural variations (SVs) encompassing larger stretches of DNA are more likely to alter gene expression levels leading to phenotypic variation affecting plant phenotypes and stress resistance. Previous studies on SVs in rice were hampered by reliance on short-read sequencing limiting the quantity and quality of SV identification, while SV data are currently only available for cultivated rice, with wild rice largely uncharacterized. Here, we generated two genome assemblies for O. rufipogon using long-read sequencing and provide insights on the evolutionary pattern and effect of SVs on morphological traits during rice domestication.

RESULTS

In this study, we identified 318,589 SVs in cultivated and wild rice populations through a comprehensive analysis of 13 high-quality rice genomes and found that wild rice genomes contain 49% of unique SVs and an average of 1.76% of genes were lost during rice domestication. These SVs were further genotyped for 649 rice accessions, their evolutionary pattern during rice domestication and potential association with the diversity of important agronomic traits were examined. Genome-wide association studies between these SVs and nine agronomic traits identified 413 candidate causal variants, which together affect 361 genes. An 824-bp deletion in japonica rice, which encodes a serine carboxypeptidase family protein, is shown to be associated with grain length.

CONCLUSIONS

We provide relatively accurate and complete SV datasets for cultivated and wild rice accessions, especially in TE-rich regions, by comparing long-read sequencing data for 13 representative varieties. The integrated rice SV map and the identified candidate genes and variants represent valuable resources for future genomic research and breeding in rice.

The Pyramiding of Elite Allelic Genes Related to Grain Number Increases Grain Number per Panicle Using the Recombinant Lines Derived from Indica-japonica Cross in Rice

Indica(xian)-japonica(geng) hybrid rice has many heterosis traits that can improve rice yield. However, the traditional hybrid technology will struggle to meet future needs for the development of higher-yield rice. Available genomics resources can be used to efficiently understand the gene-trait association trait for rice breeding. Based on the previously constructed high-density genetic map of 272 high-generation recombinant inbred lines (RILs) originating from the cross of Luohui 9 (indica, as female) and RPY geng (japonica, as male) and high-quality genomes of parents, here, we further explore the genetic basis for an important complex trait: possible causes of grain number per panicle (GNPP). A total of 20 genes related to grains number per panicle (GNPP) with the differences of protein amino acid between LH9 and RPY were used to analyze genotype combinations, and PCA results showed a combination of PLY1, LAX1, DTH8 and OSH1 from the RPY geng with PYL4, SP1, DST and GNP1 from Luohui 9 increases GNPP. In addition, we also found that the combination of LAX1-T2 and GNP1-T3 had the most significant increase in GNPP. Notably, Molecular Breeding Knowledgebase (MBK) showed a few aggregated rice cultivars, LAX1-T2 and GNP1-T3, which may be a result of the natural geographic isolation between the two gene haplotypes. Therefore, we speculate that the pyramiding of japonica-type LAX-T2 with indica-type GNP1-T3 via hybridization can significantly improve rice yield by increasing GNPP.

Conventional and Omics Approaches for Understanding the Abiotic Stress Response in Cereal Crops-An Updated Overview

Cereals have evolved various tolerance mechanisms to cope with abiotic stress. Understanding the abiotic stress response mechanism of cereal crops at the molecular level offers a path to high-yielding and stress-tolerant cultivars to sustain food and nutritional security. In this regard, enormous progress has been made in the omics field in the areas of genomics, transcriptomics, and proteomics. Omics approaches generate a massive amount of data, and adequate advancements in computational tools have been achieved for effective analysis. The combination of integrated omics and bioinformatics approaches has been recognized as vital to generating insights into genome-wide stress-regulation mechanisms. In this review, we have described the self-driven drought, heat, and salt stress-responsive mechanisms that are highlighted by the integration of stress-manipulating components, including transcription factors, co-expressed genes, proteins, etc. This review also provides a comprehensive catalog of available online omics resources for cereal crops and their effective utilization. Thus, the details provided in the review will enable us to choose the appropriate tools and techniques to reduce the negative impacts and limit the failures in the intensive crop improvement study.

Genomics and transcriptomics to protect rice (Oryza sativa. L.) from abiotic stressors: -pathways to achieving zero hunger

More over half of the world's population depends on rice as a major food crop. Rice (Oryza sativa L.) is vulnerable to abiotic challenges including drought, cold, and salinity since it grown in semi-aquatic, tropical, or subtropical settings. Abiotic stress resistance has bred into rice plants since the earliest rice cultivation techniques. Prior to the discovery of the genome, abiotic stress-related genes were identified using forward genetic methods, and abiotic stress-tolerant lines have developed using traditional breeding methods. Dynamic transcriptome expression represents the degree of gene expression in a specific cell, tissue, or organ of an individual organism at a specific point in its growth and development. Transcriptomics can reveal the expression at the entire genome level during stressful conditions from the entire transcriptional level, which can be helpful in understanding the intricate regulatory network relating to the stress tolerance and adaptability of plants. Rice (Oryza sativa L.) gene families found comparatively using the reference genome sequences of other plant species, allowing for genome-wide identification. Transcriptomics via gene expression profiling which have recently dominated by RNA-seq complements genomic techniques. The identification of numerous important qtl,s genes, promoter elements, transcription factors and miRNAs involved in rice response to abiotic stress was made possible by all of these genomic and transcriptomic techniques. The use of several genomes and transcriptome methodologies to comprehend rice (Oryza sativa, L.) ability to withstand abiotic stress have been discussed in this review.

Improving Yield and Yield Stability in Winter Rye by Hybrid Breeding

Rye is the only cross-pollinating small-grain cereal. The unique reproduction biology results in an exceptional complexity concerning genetic improvement of rye by breeding. Rye is a close relative of wheat and has a strong adaptation potential that refers to its mating system, making this overlooked cereal readily adjustable to a changing environment. Rye breeding addresses the emerging challenges of food security associated with climate change. The systematic identification, management, and use of its valuable natural diversity became a feasible option in outbreeding rye only following the establishment of hybrid breeding late in the 20th century. In this article, we review the most recent technological advances to improve yield and yield stability in winter rye. Based on recently released reference genome sequences, SMART breeding approaches are described to counterbalance undesired linkage drag effects of major restorer genes on grain yield. We present the development of gibberellin-sensitive semidwarf hybrids as a novel plant breeding innovation based on an approach that is different from current methods of increasing productivity in rye and wheat. Breeding of new rye cultivars with improved performance and resilience is indispensable for a renaissance of this healthy minor cereal as a homogeneous commodity with cultural relevance in Europe that allows for comparatively smooth but substantial complementation of wheat with rye-based diets, supporting the necessary restoration of the balance between human action and nature.

Rice co-expression network analysis identifies gene modules associated with agronomic traits

Identifying trait-associated genes is critical for rice (Oryza sativa) improvement, which usually relies on map-based cloning, quantitative trait locus analysis, or genome-wide association studies. Here we show that trait-associated genes tend to form modules within rice gene co-expression networks, a feature that can be exploited to discover additional trait-associated genes using reverse genetics. We constructed a rice gene co-expression network based on the graphical Gaussian model using 8,456 RNA-seq transcriptomes, which assembled into 1,286 gene co-expression modules functioning in diverse pathways. A number of the modules were enriched with genes associated with agronomic traits, such as grain size, grain number, tiller number, grain quality, leaf angle, stem strength, and anthocyanin content, and these modules are considered to be trait-associated gene modules. These trait-associated gene modules can be used to dissect the genetic basis of rice agronomic traits and to facilitate the identification of trait genes. As an example, we identified a candidate gene, OCTOPUS-LIKE 1 (OsOPL1), a homolog of the Arabidopsis (Arabidopsis thaliana) OCTOPUS gene, from a grain size module and verified it as a regulator of grain size via functional studies. Thus, our network represents a valuable resource for studying trait-associated genes in rice.

Heat Stress Decreases Rice Grain Weight: Evidence and Physiological Mechanisms of Heat Effects Prior to Flowering

Heat stress during the preflowering panicle initiation stage seriously decreases rice grain weight in an invisible way and has not been given enough attention. The current review aims to (i) specify the heat effects on rice grain weight during the panicle initiation stage compared with the most important grain-filling stage; and (ii) discuss the physiological mechanisms of the decreased rice grain weight induced by heat during panicle initiation in terms of assimilate supply and phytohormone regulation, which are key physiological processes directly regulating rice grain weight. We emphasize that the effect of heat during the panicle initiation stage on rice grain weight is more serious than that during the grain-filling stage. Heat stress during the panicle initiation stage induces alterations in endogenous phytohormones, leading to the inhibition of the photosynthesis of functional leaves (source) and the formation of vascular bundles (flow), thus reducing the accumulation and transport of nonstructural carbohydrates and the growth of lemmata and paleae. The disruptions in the "flow" and restrictions in the preanthesis "source" tissue reduce grain size directly and decrease grain plumpness indirectly, resulting in a reduction in the final grain weight, which could be the direct physiological causes of the lower rice grain weight induced by heat during the panicle initiation stage. We highlight the seriousness of preflowering heat stress on rice grain weight, which can be regarded as an invisible disaster. The physiological mechanisms underlying the lower grain weight induced by heat during panicle initiation show a certain novelty because they distinguish this stage from the grain-filling stage. Additionally, a number of genes that control grain size through phytohormones have been summarized, but their functions have not yet been fully tested under heat conditions, except for the Grain Size and Abiotic stress tolerance 1 (GSA1) and BRASSINOSTEROID INSENSITIVE1 (OsBRI1) genes, which are reported to respond rapidly to heat stress. The mechanisms of reduced rice grain weight induced by heat during the panicle initiation stage should be studied in more depth in terms of molecular pathways.

Comparative Transcriptomic Analyses of Nitrate-Response in Rice Genotypes With Contrasting Nitrogen Use Efficiency Reveals Common and Genotype-Specific Processes, Molecular Targets and Nitrogen Use Efficiency-Candidates

The genetic basis for nitrogen (N)-response and N use efficiency (NUE) must be found in N-responsive gene expression or protein regulation. Our transcriptomic analysis of nitrate response in two contrasting rice genotypes of Oryza sativa ssp. Indica (Nidhi with low NUE and Panvel1 with high NUE) revealed the processes/functions underlying differential N-response/NUE. The microarray analysis of low nitrate response (1.5 mM) relative to normal nitrate control (15 mM) used potted 21-days old whole plants. It revealed 1,327 differentially expressed genes (DEGs) exclusive to Nidhi and 666 exclusive to Panvel1, apart from 70 common DEGs, of which 10 were either oppositely expressed or regulated to different extents. Gene ontology analyses revealed that photosynthetic processes were among the very few processes common to both the genotypes in low N response. Those unique to Nidhi include cell division, nitrogen utilization, cytoskeleton, etc. in low N-response, whereas those unique to Panvel1 include signal transduction, protein import into the nucleus, and mitochondria. This trend of a few common but mostly unique categories was also true for transporters, transcription factors, microRNAs, and post-translational modifications, indicating their differential involvement in Nidhi and Panvel1. Protein-protein interaction networks constructed using DEG-associated experimentally validated interactors revealed subnetworks involved in cytoskeleton organization, cell wall, etc. in Nidhi, whereas in Panvel1, it was chloroplast development. NUE genes were identified by selecting yield-related genes from N-responsive DEGs and their co-localization on NUE-QTLs revealed the differential distribution of NUE-genes between genotypes but on the same chromosomes 1 and 3. Such hotspots are important for NUE breeders.

Reverse genetic approaches for breeding nutrient-rich and climate-resilient cereal and food legume crops

In the last decade, advancements in genomics tools and techniques have led to the discovery of many genes. Most of these genes still need to be characterized for their associated function and therefore, such genes remain underutilized for breeding the next generation of improved crop varieties. The recent developments in different reverse genetic approaches have made it possible to identify the function of genes controlling nutritional, biochemical, and metabolic traits imparting drought, heat, cold, salinity tolerance as well as diseases and insect-pests. This article focuses on reviewing the current status and prospects of using reverse genetic approaches to breed nutrient-rich and climate resilient cereal and food legume crops.

Increase Crop Resilience to Heat Stress Using Omic Strategies

Varieties of various crops with high resilience are urgently needed to feed the increased population in climate change conditions. Human activities and climate change have led to frequent and strong weather fluctuation, which cause various abiotic stresses to crops. The understanding of crops' responses to abiotic stresses in different aspects including genes, RNAs, proteins, metabolites, and phenotypes can facilitate crop breeding. Using multi-omics methods, mainly genomics, transcriptomics, proteomics, metabolomics, and phenomics, to study crops' responses to abiotic stresses will generate a better, deeper, and more comprehensive understanding. More importantly, multi-omics can provide multiple layers of information on biological data to understand plant biology, which will open windows for new opportunities to improve crop resilience and tolerance. However, the opportunities and challenges coexist. Interpretation of the multidimensional data from multi-omics and translation of the data into biological meaningful context remained a challenge. More reasonable experimental designs starting from sowing seed, cultivating the plant, and collecting and extracting samples were necessary for a multi-omics study as the first step. The normalization, transformation, and scaling of single-omics data should consider the integration of multi-omics. This review reports the current study of crops at abiotic stresses in particular heat stress using omics, which will help to accelerate crop improvement to better tolerate and adapt to climate change.

Introgression Lines: Valuable Resources for Functional Genomics Research and Breeding in Rice (Oryza sativa L.)

The narrow base of genetic diversity of modern rice varieties is mainly attributed to the overuse of the common backbone parents that leads to the lack of varied favorable alleles in the process of breeding new varieties. Introgression lines (ILs) developed by a backcross strategy combined with marker-assisted selection (MAS) are powerful prebreeding tools for broadening the genetic base of existing cultivars. They have high power for mapping quantitative trait loci (QTLs) either with major or minor effects, and are used for precisely evaluating the genetic effects of QTLs and detecting the gene-by-gene or gene-by-environment interactions due to their low genetic background noise. ILs developed from multiple donors in a fixed background can be used as an IL platform to identify the best alleles or allele combinations for breeding by design. In the present paper, we reviewed the recent achievements from ILs in rice functional genomics research and breeding, including the genetic dissection of complex traits, identification of elite alleles and background-independent and epistatic QTLs, analysis of genetic interaction, and genetic improvement of single and multiple target traits. We also discussed how to develop ILs for further identification of new elite alleles, and how to utilize IL platforms for rice genetic improvement.

Twenty years of rice genomics research: From sequencing and functional genomics to quantitative genomics

Since the completion of the rice genome sequencing project in 2005, we have entered the era of rice genomics, which is still in its ascendancy. Rice genomics studies can be classified into three stages: structural genomics, functional genomics, and quantitative genomics. Structural genomics refers primarily to genome sequencing for the construction of a complete map of rice genome sequence. This is fundamental for rice genetics and molecular biology research. Functional genomics aims to decode the functions of rice genes. Quantitative genomics is large-scale sequence- and statistics-based research to define the quantitative traits and genetic features of rice populations. Rice genomics has been a transformative influence on rice biological research and contributes significantly to rice breeding, making rice a good model plant for studying crop sciences.

Assembly of yield heterosis of an elite rice hybrid is promising by manipulating dominant quantitative trait loci

In the past, rice hybrids with strong heterosis have been obtained empirically, by developing and testing thousands of combinations. Here, we aimed to determine whether heterosis of an elite hybrid could be achieved by manipulating major quantitative trait loci. We used 202 chromosome segment substitution lines from the elite hybrid Shanyou 63 to evaluate single segment heterosis (SSH) of yield per plant and identify heterotic loci. All nine detected heterotic loci acted in a dominant fashion, and no SSH exhibited overdominance. Functional alleles of key yield-related genes Ghd7, Ghd7.1, Hd1, and GS3 were dispersed in both parents. No functional alleles of three investigated genes were expressed at higher levels in the hybrids than in the more desirable parents. A hybrid pyramiding eight heterotic loci in the female parent Zhenshan 97 background had a comparable yield to Shanyou 63 and much higher yield than Zhenshan 97. Five hybrids pyramiding eight or nine heterotic loci in the combined parental genome background showed similar yield performance to that of Shanyou 63. These results suggest that dominance underlying functional complementation is an important contributor to yield heterosis and that heterosis assembly might be successfully promised by manipulating several major dominant heterotic loci.

Physiological and Multi-Omics Approaches for Explaining Drought Stress Tolerance and Supporting Sustainable Production of Rice

Drought differs from other natural disasters in several respects, largely because of the complexity of a crop's response to it and also because we have the least understanding of a crop's inductive mechanism for addressing drought tolerance among all abiotic stressors. Overall, the growth and productivity of crops at a global level is now thought to be an issue that is more severe and arises more frequently due to climatic change-induced drought stress. Among the major crops, rice is a frontline staple cereal crop of the developing world and is critical to sustaining populations on a daily basis. Worldwide, studies have reported a reduction in rice productivity over the years as a consequence of drought. Plants are evolutionarily primed to withstand a substantial number of environmental cues by undergoing a wide range of changes at the molecular level, involving gene, protein and metabolite interactions to protect the growing plant. Currently, an in-depth, precise and systemic understanding of fundamental biological and cellular mechanisms activated by crop plants during stress is accomplished by an umbrella of -omics technologies, such as transcriptomics, metabolomics and proteomics. This combination of multi-omics approaches provides a comprehensive understanding of cellular dynamics during drought or other stress conditions in comparison to a single -omics approach. Thus a greater need to utilize information (big-omics data) from various molecular pathways to develop drought-resilient crop varieties for cultivation in ever-changing climatic conditions. This review article is focused on assembling current peer-reviewed published knowledge on the use of multi-omics approaches toward expediting the development of drought-tolerant rice plants for sustainable rice production and realizing global food security.

Nitrate-responsive transcriptome analysis reveals additional genes/processes and associated traits viz. height, tillering, heading date, stomatal density and yield in japonica rice

Our transcriptomic analysis expanded the repertoire of nitrate-responsive genes/processes in rice and revealed their phenotypic association with root/shoot, stomata, tiller, panicle/flowering and yield, with agronomic implications for nitrogen use efficiency. Nitrogen use efficiency (NUE) is a multigenic quantitative trait, involving many N-responsive genes/processes that are yet to be fully characterized. Microarray analysis of early nitrate response in excised leaves of japonica rice revealed 6688 differentially expressed genes (DEGs), including 2640 hitherto unreported across multiple functional categories. They include transporters, enzymes involved in primary/secondary metabolism, transcription factors (TFs), EF-hand containing calcium binding proteins, hormone metabolism/signaling and methytransferases. Some DEGs belonged to hitherto unreported processes viz. alcohol, lipid and trehalose metabolism, mitochondrial membrane organization, protein targeting and stomatal opening. 1158 DEGs were associated with growth physiology and grain yield or phenotypic traits for NUE. We identified seven DEGs for shoot apical meristem, 66 for leaf/culm/root, 31 for tiller, 70 for heading date/inflorescence/spikelet/panicle, 144 for seed and 78 for yield. RT-qPCR validated nitrate regulation of 31 DEGs belonging to various important functional categories/traits. Physiological validation of N-dose responsive changes in plant development revealed that relative to 1.5 mM, 15 mM nitrate significantly increased stomatal density, stomatal conductance and transpiration rate. Further, root/shoot growth, number of tillers and grain yield declined and panicle emergence/heading date delayed, despite increased photosynthetic rate. We report the binding sites of diverse classes of TFs such as WRKY, MYB, HMG etc., in the 1 kb up-stream regions of 6676 nitrate-responsive DEGs indicating their role in regulating nitrate response/NUE. Together, these findings expand the repertoire of genes and processes involved in genomewide nitrate response in rice and reveal their physiological, phenotypic and agronomic implications for NUE.

From Green Super Rice to green agriculture: Reaping the promise of functional genomics research

Producing sufficient food with finite resources to feed the growing global population while having a smaller impact on the environment has always been a great challenge. Here, we review the concept and practices of Green Super Rice (GSR) that have led to a paradigm shift in goals for crop genetic improvement and models of food production for promoting sustainable agriculture. The momentous achievements and global deliveries of GSR have been fueled by the integration of abundant genetic resources, functional gene discoveries, and innovative breeding techniques with precise gene and whole-genome selection and efficient agronomic management to promote resource-saving, environmentally friendly crop production systems. We also provide perspectives on new horizons in genomic breeding technologies geared toward delivering green and nutritious crop varieties to further enhance the development of green agriculture and better nourish the world population.

Advanced high-throughput plant phenotyping techniques for genome-wide association studies: A review

Linking phenotypes and genotypes to identify genetic architectures that regulate important traits is crucial for plant breeding and the development of plant genomics. In recent years, genome-wide association studies (GWASs) have been applied extensively to interpret relationships between genes and traits. Successful GWAS application requires comprehensive genomic and phenotypic data from large populations. Although multiple high-throughput DNA sequencing approaches are available for the generation of genomics data, the capacity to generate high-quality phenotypic data is lagging far behind. Traditional methods for plant phenotyping mostly rely on manual measurements, which are laborious, inaccurate, and time-consuming, greatly impairing the acquisition of phenotypic data from large populations. In contrast, high-throughput phenotyping has unique advantages, facilitating rapid, non-destructive, and high-throughput detection, and, in turn, addressing the shortcomings of traditional methods. Aim of Review: This review summarizes the current status with regard to the integration of high-throughput phenotyping and GWAS in plants, in addition to discussing the inherent challenges and future prospects. Key Scientific Concepts of Review: High-throughput phenotyping, which facilitates non-contact and dynamic measurements, has the potential to offer high-quality trait data for GWAS and, in turn, to enhance the unraveling of genetic structures of complex plant traits. In conclusion, high-throughput phenotyping integration with GWAS could facilitate the revealing of coding information in plant genomes.

A Genome-Wide Association Study Pinpoints Quantitative Trait Genes for Plant Height, Heading Date, Grain Quality, and Yield in Rye (Secale cereale L.)

Rye is the only cross-pollinating Triticeae crop species. Knowledge of rye genes controlling complex-inherited traits is scarce, which, currently, largely disables the genomics assisted introgression of untapped genetic variation from self-incompatible germplasm collections in elite inbred lines for hybrid breeding. We report on the first genome-wide association study (GWAS) in rye based on the phenotypic evaluation of 526 experimental hybrids for plant height, heading date, grain quality, and yield in 2 years and up to 19 environments. We established a cross-validated NIRS calibration model as a fast, effective, and robust analytical method to determine grain quality parameters. We observed phenotypic plasticity in plant height and tiller number as a resource use strategy of rye under drought and identified increased grain arabinoxylan content as a striking phenotype in osmotically stressed rye. We used DArTseq™ as a genotyping-by-sequencing technology to reduce the complexity of the rye genome. We established a novel high-density genetic linkage map that describes the position of almost 19k markers and that allowed us to estimate a low genome-wide LD based on the assessed genetic diversity in elite germplasm. We analyzed the relationship between plant height, heading date, agronomic, as well as grain quality traits, and genotype based on 20k novel single-nucleotide polymorphism markers. In addition, we integrated the DArTseq™ markers in the recently established 'Lo7' reference genome assembly. We identified cross-validated SNPs in 'Lo7' protein-coding genes associated with all traits studied. These include associations of the WUSCHEL-related homeobox transcription factor DWT1 and grain yield, the DELLA protein gene SLR1 and heading date, the Ethylene overproducer 1-like protein gene ETOL1 and thousand-grain weight, protein and starch content, as well as the Lectin receptor kinase SIT2 and plant height. A Leucine-rich repeat receptor protein kinase and a Xyloglucan alpha-1,6-xylosyltransferase count among the cross-validated genes associated with water-extractable arabinoxylan content. This study demonstrates the power of GWAS, hybrid breeding, and the reference genome sequence in rye genetics research to dissect and identify the function of genes shaping genetic diversity in agronomic and grain quality traits of rye. The described links between genetic causes and phenotypic variation will accelerate genomics-enabled rye improvement.

The landscape of gene-CDS-haplotype diversity in rice: Properties, population organization, footprints of domestication and breeding, and implications for genetic improvement

Polymorphisms within gene coding regions represent the most important part of the overall genetic diversity of rice. We characterized the gene-coding sequence-haplotype (gcHap) diversity of 45 963 rice genes in 3010 rice accessions. With an average of 226 ± 390 gcHaps per gene in rice populations, rice genes could be classified into three main categories: 12 865 conserved genes, 10 254 subspecific differentiating genes, and 22 844 remaining genes. We found that 39 218 rice genes carry >255 179 major gcHaps of potential functional importance. Most (87.5%) of the detected gcHaps were specific to subspecies or populations. The inferred proto-ancestors of local landrace populations reconstructed from conserved predominant (ancient) gcHaps correlated strongly with wild rice accessions from the same geographic regions, supporting a multiorigin (domestication) model of Oryza sativa. Past breeding efforts generally increased the gcHap diversity of modern varieties and caused significant frequency shifts in predominant gcHaps of 14 266 genes due to independent selection in the two subspecies. Low frequencies of "favorable" gcHaps at most known genes related to rice yield in modern varieties suggest huge potential for rice improvement by mining and pyramiding of favorable gcHaps. The gcHap data were demonstrated to have greater power than SNPs for the detection of causal genes that affect complex traits. The rice gcHap diversity dataset generated in this study would facilitate rice basic research and improvement in the future.

Transcriptomic Analysis of Rice Plants Overexpressing PsGAPDH in Response to Salinity Stress

In plants, glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is a main enzyme in the glycolytic pathway. It plays an essential role in glycerolipid metabolism and response to various stresses. To examine the function of PsGAPDH (Pleurotus sajor-caju GAPDH) in response to abiotic stress, we generated transgenic rice plants with single-copy/intergenic/homozygous overexpression PsGAPDH (PsGAPDH-OX) and investigated their responses to salinity stress. Seedling growth and germination rates of PsGAPDH-OX were significantly increased under salt stress conditions compared to those of the wild type. To elucidate the role of PsGAPDH-OX in salt stress tolerance of rice, an Illumina HiSeq 2000 platform was used to analyze transcriptome profiles of leaves under salt stress. Analysis results of sequencing data showed that 1124 transcripts were differentially expressed. Using the list of differentially expressed genes (DEGs), functional enrichment analyses of DEGs such as Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were performed. KEGG pathway enrichment analysis revealed that unigenes exhibiting differential expression were involved in starch and sucrose metabolism. Interestingly, trehalose-6-phosphate synthase (TPS) genes, of which expression was enhanced by abiotic stress, showed a significant difference in PsGAPDH-OX. Findings of this study suggest that PsGAPDH plays a role in the adaptation of rice plants to salt stress.

QTL Mapping and Favorable Allele Mining of Nitrogen Deficiency Tolerance Using an Interconnected Breeding Population in Rice

Nitrogen is one of the most important nutrients for rice growth and development. Breeding of nitrogen deficiency tolerance (NDT) variety is considered to be the most economic measure to solve the constrain of low nitrogen stress on grain yield in rice. An interconnected breeding (IB) population of 497 lines developed using Huanghuazhan (HHZ) as the recurrent parent and eight elite lines as the donor parents were tested for five traits including grain yield, biomass, harvest index, thousand grain weight, and spikelet fertility under two nitrogen treatments in three growing seasons. Association analysis using 7,388 bins generated by sequencing identified a total of 14, 14, and 12 QTLs for the five traits under low nitrogen (LN), normal nitrogen (NN), and LN/NN conditions, respectively, across three seasons. Favorable alleles were dissected for the 40 QTLs at the 10 NDT regions, and OM1723 was considered as the most important parent with the highest frequency of favorable alleles contributing to NDT-related traits. Six superior lines all showed significantly higher GY in LN environments and similar GY under NN environments except for H10. Substitution mapping using near-isogenic introgression lines delimited the qTGW2-1, which was identified on chromosome 2 under LN, NN, and LN/NN conditions into two QTLs, which were located in the two regions of about 200 and 350 kb with different favorable alleles. The bins 16, 1301, 1465, 1486, 3464, and 6249 harbored the QTLs for NDT detected in this study, and the QTLs/genes previously identified for NDT or nitrogen use efficiency (NUE) could be used for enhancing NDT and NUE by marker-assisted selection (MAS).

A quantitative genomics map of rice provides genetic insights and guides breeding

Extensive allelic variation in agronomically important genes serves as the basis of rice breeding. Here, we present a comprehensive map of rice quantitative trait nucleotides (QTNs) and inferred QTN effects based on eight genome-wide association study cohorts. Population genetic analyses revealed that domestication, local adaptation and heterosis are all associated with QTN allele frequency changes. A genome navigation system, RiceNavi, was developed for QTN pyramiding and breeding route optimization, and implemented in the improvement of a widely cultivated indica variety. This work presents an efficient platform that bridges ever-increasing genomic knowledge and diverse improvement needs in rice.

Incorporation of parental phenotypic data into multi-omic models improves prediction of yield-related traits in hybrid rice

Hybrid breeding has been shown to effectively increase rice productivity. However, identifying desirable hybrids out of numerous potential combinations is a daunting challenge. Genomic selection holds great promise for accelerating hybrid breeding by enabling early selection before phenotypes are measured. With the recent advances in multi-omic technologies, hybrid prediction based on transcriptomic and metabolomic data has received increasing attention. However, the current omic-based hybrid prediction has ignored parental phenotypic information, which is of fundamental importance in plant breeding. In this study, we integrated parental phenotypic information into various multi-omic prediction models applied in hybrid breeding of rice and compared the predictabilities of 15 combinations from four sets of predictors from the parents, that is genome, transcriptome, metabolome and phenome. The predictability for each combination was evaluated using the best linear unbiased prediction and a modified fast HAT method. We found significant interactions between predictors and traits in predictability, but joint prediction with various combinations of the predictors significantly improved predictability relative to prediction of any single source omic data for each trait investigated. Incorporation of parental phenotypic data into various omic predictors increased the predictability, averagely by 13.6%, 54.5%, 19.9% and 8.3%, for grain yield, number of tillers per plant, number of grains per panicle and 1000 grain weight, respectively. Among nine models of incorporating parental traits, the AD-All model was the most effective one. This novel strategy of incorporating parental phenotypic data into multi-omic prediction is expected to improve hybrid breeding progress, especially with the development of high-throughput phenotyping technologies.

Discovery of new genetic determinants of morphological plasticity in rice roots and shoots under phosphate starvation using GWAS

Phosphorus is an essential nutrient for plants that is often in short supply. In rice (Oryza sativa L.), inorganic phosphate (P_i) deficiency leads to various physiological disorders that consequently affect plant productivity. In this study, a large-scale phenotyping experiment using 160 Vietnamese rice landraces was performed under greenhouse conditions, by employing an alpha lattice design with three replicates, to identify quantitative trait loci (QTLs) associated with plant growth inhibition caused by P_i deficiency. Rice plantlets were grown for six weeks in the PVC sand column (16 cm diameter × 80 cm height) supplied with P_i-deficient medium (10 μM P) or full-P_i Yoshida medium (320 μM P). The effects of P_i deficiency on the number of crown roots, root length, shoot length, root weight, shoot weight and total weight were studied. From 36 significant markers identified using a genome-wide association study, 21 QTLs associated with plant growth inhibition under P_i starvation were defined. In total, 158 candidate genes co-located with the defined QTLs were identified. Interestingly, one QTL (qRST9.14) was associated with all three weight-traits. The co-located gene GLYCEROPHOSPHODIESTER PHOSPHODIESTERASE 13 was found to be potentially involved in P_i transport. Understanding the molecular mechanisms of Pi-starvation responses, and identifying the potential QTLs responsible for low-P_i stress tolerance, will provide valuable information for developing new varieties tolerant of low-P_i conditions.

Assessing Rice Salinity Tolerance: From Phenomics to Association Mapping

Rice is the most salt-sensitive cereal, suffering yield losses above 50% with soil salinity of 6 dS/m. Thus, understanding the mechanisms of rice salinity tolerance is key to address food security. In this chapter, we provide guidelines to assess rice salinity tolerance using a high-throughput phenotyping platform (HTP) with digital imaging at seedling/early tillering stage and suggest improved analysis methods using stress indices. The protocols described here also include computer scripts for users to improve their experimental design, run genome-wide association studies (GWAS), perform multi-testing corrections, and obtain the Manhattan plots, enabling the identification of loci associated with salinity tolerance. Notably, the computer scripts provided here can be used for any stress or GWAS experiment and independently of HTP.