Rice Functional Genomics Research: Past Decade and Future

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.

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.

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.

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.

Meta-Analysis of Yield-Related and N-Responsive Genes Reveals Chromosomal Hotspots, Key Processes and Candidate Genes for Nitrogen-Use Efficiency in Rice

Nitrogen-use efficiency (NUE) is a function of N-response and yield that is controlled by many genes and phenotypic parameters that are poorly characterized. This study compiled all known yield-related genes in rice and mined them from the N-responsive microarray data to find 1,064 NUE-related genes. Many of them are novel genes hitherto unreported as related to NUE, including 80 transporters, 235 transcription factors (TFs), 44 MicroRNAs (miRNAs), 91 kinases, and 8 phosphatases. They were further shortlisted to 62 NUE-candidate genes following hierarchical methods, including quantitative trait locus (QTL) co-localization, functional evaluation in the literature, and protein-protein interactions (PPIs). They were localized to chromosomes 1, 3, 5, and 9, of which chromosome 1 with 26 genes emerged as a hotspot for NUE spanning 81% of the chromosomes. Further, co-localization of the NUE genes on NUE-QTLs resolved differences in the earlier studies that relied mainly on N-responsive genes regardless of their role in yield. Functional annotations and PPIs for all the 1,064 NUE-related genes and also the shortlisted 62 candidates revealed transcription, redox, phosphorylation, transport, development, metabolism, photosynthesis, water deprivation, and hormonal and stomatal function among the prominent processes. In silico expression analysis confirmed differential expression of the 62 NUE-candidate genes in a tissue/stage-specific manner. Experimental validation in two contrasting genotypes revealed that high NUE rice shows better photosynthetic performance, transpiration efficiency and internal water-use efficiency in comparison to low NUE rice. Feature Selection Analysis independently identified one-third of the common genes at every stage of hierarchical shortlisting, offering 6 priority targets to validate for improving the crop NUE.

Genetic mapping for agronomic traits in a MAGIC population of common bean (Phaseolus vulgaris L.) under drought conditions

BACKGROUND

Common bean is an important staple crop in the tropics of Africa, Asia and the Americas. Particularly smallholder farmers rely on bean as a source for calories, protein and micronutrients. Drought is a major production constraint for common bean, a situation that will be aggravated with current climate change scenarios. In this context, new tools designed to understand the genetic basis governing the phenotypic responses to abiotic stress are required to improve transfer of desirable traits into cultivated beans.

RESULTS

A multiparent advanced generation intercross (MAGIC) population of common bean was generated from eight Mesoamerican breeding lines representing the phenotypic and genotypic diversity of the CIAT Mesoamerican breeding program. This population was assessed under drought conditions in two field trials for yield, 100 seed weight, iron and zinc accumulation, phenology and pod harvest index. Transgressive segregation was observed for most of these traits. Yield was positively correlated with yield components and pod harvest index (PHI), and negative correlations were found with phenology traits and micromineral contents. Founder haplotypes in the population were identified using Genotyping by Sequencing (GBS). No major population structure was observed in the population. Whole Genome Sequencing (WGS) data from the founder lines was used to impute genotyping data for GWAS. Genetic mapping was carried out with two methods, using association mapping with GWAS, and linkage mapping with haplotype-based interval screening. Thirteen high confidence QTL were identified using both methods and several QTL hotspots were found controlling multiple traits. A major QTL hotspot located on chromosome Pv01 for phenology traits and yield was identified. Further hotspots affecting several traits were observed on chromosomes Pv03 and Pv08. A major QTL for seed Fe content was contributed by MIB778, the founder line with highest micromineral accumulation. Based on imputed WGS data, candidate genes are reported for the identified major QTL, and sequence changes were identified that could cause the phenotypic variation.

CONCLUSIONS

This work demonstrates the importance of this common bean MAGIC population for genetic mapping of agronomic traits, to identify trait associations for molecular breeding tool design and as a new genetic resource for the bean research community.

Decoding the plant genome: From epigenome to 3D organization

The linear genome of eukaryotes is partitioned into diverse chromatin states and packaged into a three-dimensional (3D) structure, which has functional implications in DNA replication, DNA repair, and transcriptional regulation. Over the past decades, research on plant functional genomics and epigenomics has made great progress, with thousands of genes cloned and molecular mechanisms of diverse biological processes elucidated. Recently, 3D genome research has gradually attracted great attention of many plant researchers. Herein, we briefly review the progress in genomic and epigenomic research in plants, with a focus on Arabidopsis and rice, and summarize the currently used technologies and advances in plant 3D genome organization studies. We also discuss the relationships between one-dimensional linear genome sequences, epigenomic states, and the 3D chromatin architecture. This review provides basis for future research on plant 3D genomics.

CAFRI-Rice: CRISPR applicable functional redundancy inspector to accelerate functional genomics in rice

Rice (Oryza sativa L.) is a staple crop with agricultural traits that have been intensively investigated. However, despite the variety of mutant population and multi-omics data that have been generated, rice functional genomic research has been bottlenecked due to the functional redundancy in the genome. This phenomenon has masked the phenotypes of knockout mutants by functional compensation and redundancy. Here, we present an intuitive tool, CRISPR applicable functional redundancy inspector to accelerate functional genomics in rice (CAFRI-Rice; cafri-rice.khu.ac.kr). To create this tool, we generated a phylogenetic heatmap that can estimate the similarity between protein sequences and expression patterns, based on 2,617 phylogenetic trees and eight tissue RNA-sequencing datasets. In this study, 33,483 genes were sorted into 2,617 families, and about 24,980 genes were tested for functional redundancy using a phylogenetic heatmap approach. It was predicted that 7,075 genes would have functional redundancy, according to the threshold value validated by an analysis of 111 known genes functionally characterized using knockout mutants and 5,170 duplicated genes. In addition, our analysis demonstrated that an anther/pollen-preferred gene cluster has more functional redundancy than other clusters. Finally, we showed the usefulness of the CAFRI-Rice-based approach by overcoming the functional redundancy between two root-preferred genes via loss-of-function analyses as well as confirming the functional dominancy of three genes through a literature search. This CAFRI-Rice-based target selection for CRISPR/Cas9-mediated mutagenesis will not only accelerate functional genomic studies in rice but can also be straightforwardly expanded to other plant species.

5Gs for crop genetic improvement

Here we propose a 5G breeding approach for bringing much-needed disruptive changes to crop improvement. These 5Gs are Genome assembly, Germplasm characterization, Gene function identification, Genomic breeding (GB), and Gene editing (GE). In our view, it is important to have genome assemblies available for each crop and a deep collection of germplasm characterized at sequencing and agronomic levels for identification of marker-trait associations and superior haplotypes. Systems biology and sequencing-based mapping approaches can be used to identify genes involved in pathways leading to the expression of a trait, thereby providing diagnostic markers for target traits. These genes, markers, haplotypes, and genome-wide sequencing data may be utilized in GB and GE methodologies in combination with a rapid cycle breeding strategy.

Rice OsLHT1 Functions in Leaf-to-Panicle Nitrogen Allocation for Grain Yield and Quality

Proper allocation of nitrogen (N) from source leaves to grains is essential step for high crop grain yield and N use efficiency. In rice (Oryza sativa) grown in flooding paddy field, amino acids are the major N compounds for N distribution and re-allocation. We have recently identified that Lysine-Histidine-type Transporter 1 (OsLHT1) is the major transporter for root uptake and root-to-shoot allocation of amino acids in rice. In this study, we planted knockout mutant lines of OsLHT1 together wild-type (WT) in paddy field for evaluating OsLHT1 function in N redistribution and grain production. OsLHT1 is expressed in vascular bundles of leaves, rachis, and flowering organs. Oslht1 plants showed lower panicle length and seed setting rate, especially lower grain number per panicle and total grain weight. The concentrations of both total N and free amino acids in the flag leaf were similar at anthesis between Oslht1 lines and WT while significantly higher in the mutants than WT at maturation. The Oslht1 seeds contained higher proteins and most of the essential free amino acids, similar total starch but less amylose with lower paste viscosity than WT seeds. The mutant seeds showed lower germination rate than WT. Knockout of OsLHT1 decreased N uptake efficiency and physiological utilization efficiency (kg-grains/kg-N) by about 55% and 72%, respectively. Taken together, we conclude that OsLHT1 plays critical role in the translocation of amino acids from vegetative to reproductive organs for grain yield and quality of nutrition and functionality.

CRISPR-Cas9 mediated genome editing of drought and salt tolerance (OsDST) gene in indica mega rice cultivar MTU1010

Development of abiotic stress tolerant rice cultivars is necessary for sustainable rice production under the scenario of global climate change, dwindling fresh water resources and increase in salt affected areas. Several genes from rice have been functionally validated by using EMS mutants and transgenics. Often, many of these desirable alleles are not available indica rice which is mainly cultivated, and where available, introgression of these alleles into elite cultivars is a time and labour intensive process, in addition to the potential introgression of non-desirable genes due to linkage. CRISPR-Cas technology helps development of elite cultivars with desirable alleles by precision gene editing. Hence, this study was carried out to create mutant alleles of drought and salt tolerance (DST) gene by using CRISPR-Cas9 gene editing in indica rice cv. MTU1010. We used two different gRNAs to target regions of DST protein that might be involved in protein-protein interaction and successfully generated different mutant alleles of DST gene. We selected homozygous dst mutant with 366 bp deletion between the two gRNAs for phenotypic analysis. This 366 bp deletion led to the deletion of amino acid residues from 184 to 305 in frame, and hence the mutant was named as dst ∆184-305 . The dst ∆184-305 mutation induced by CRISPR-Cas9 method in DST gene in indica rice cv. MTU1010 phenocopied EMS-induced dst (N69D) mutation reported earlier in japonica cultivar. The dst ∆184-305 mutant produced leaves with broader width and reduced stomatal density, and thus enhanced leaf water retention under dehydration stress. Our study showed that the reduction in stomatal density in loss of function mutants of dst is, at least, in part due to downregulation of stomatal developmental genes SPCH1, MUTE and ICE1. The Cas9-free dst ∆184-305 mutant exhibited moderate level tolerance to osmotic stress and high level of salt stress in seedling stage. Thus, dst mutant alleles generated in this study will be useful for improving drought and salt tolerance and grain yield in indica rice cultivars.

Genetic architecture underpinning yield component traits in wheat

Genetic atlas, reliable QTL and candidate genes of yield component traits in wheat were figured out, laying concrete foundations for map-based gene cloning and dissection of regulatory mechanisms underlying yield. Mining genetic loci for yield is challenging due to the polygenic nature, large influence of environment and complex relationship among yield component traits (YCT). Many genetic loci related to wheat yield have been identified, but its genetic architecture and key genetic loci for selection are largely unknown. Wheat yield potential can be determined by three YCT, thousand kernel weight, kernel number per spike and spike number. Here, we summarized the genetic loci underpinning YCT from QTL mapping, association analysis and homology-based gene cloning. The major loci determining yield-associated agronomic traits, such as flowering time and plant height, were also included in comparative analyses with those for YCT. We integrated yield-related genetic loci onto chromosomes based on their physical locations. To identify the major stable loci for YCT, 58 QTL-rich clusters (QRC) were defined based on their distribution on chromosomes. Candidate genes in each QRC were predicted according to gene annotation of the wheat reference genome and previous information on validation of those genes in other species. Finally, a technological route was proposed to take full advantage of the resultant resources for gene cloning, molecular marker-assisted breeding and dissection of molecular regulatory mechanisms underlying wheat yield.

A Bridge to the World

Zhi-Hong Xu is a plant physiologist who studied botany at Peking University (1959–1965). He joined the Shanghai Institute of Plant Physiology (SIPP), Chinese Academy of Sciences (CAS), as a graduate student in 1965. He recalls what has happened for the institute, during the Cultural Revolution, and he witnessed the spring of science eventually coming to China. Xu was a visiting scholar at the John Innes Institute and in the Department of Botany at Nottingham University in the United Kingdom (1979–1981). He became deputy director of SIPP in 1983 and director in 1991; he also chaired the State Key Laboratory of Plant Molecular Genetics SIPP (1988–1996). He worked as a visiting scientist in the Institute of Molecular and Cell Biology, National University of Singapore, for three months each year (1989–1992). He served as vice president of CAS (1992–2002) and as president of Peking University (1999–2008). Over these periods he was heavily involved in the design and implementation of major scientific projects in life sciences and agriculture in China. He is an academician of CAS and member of the Academy of Sciences for the Developing World. His scientific contributions mainly cover plant tissue culture, hormone mechanism in development, as well as plant developmental response to environment. Xu, as a scientist and leader who has made an impact in the community, called up a lot of excellent young scientists returning to China. His efforts have promoted the fast development of China's plant and agricultural sciences.