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From a global viewpoint, a number of challenges need to be met for sustainable rice production: (i) increasingly severe occurrence of insects and diseases and indiscriminate pesticide applications; (ii) high pressure for yield increase and overuse of fertilizers; (iii) water shortage and increasingly frequent occurrence of drought; and (iv) extensive cultivation in marginal lands. A combination of approaches based on the recent advances in genomic research has been formulated to address these challenges, with the long-term goal to develop rice cultivars referred to as Green Super Rice. On the premise of continued yield increase and quality improvement, Green Super Rice should possess resistances to multiple insects and diseases, high nutrient efficiency, and drought resistance, promising to greatly reduce the consumption of pesticides, chemical fertilizers, and water. Large efforts have been focused on identifying germplasms and discovering genes for resistance to diseases and insects, N- and P-use efficiency, drought resistance, grain quality, and yield. The approaches adopted include screening of germplasm collections and mutant libraries, gene discovery and identification, microarray analysis of differentially regulated genes under stressed conditions, and functional test of candidate genes by transgenic analysis. Genes for almost all of the traits have now been isolated in a global perspective and are gradually incorporated into genetic backgrounds of elite cultivars by molecular marker-assisted selection or transformation. It is anticipated that such strategies and efforts would eventually lead to the development of Green Super Rice.

Rice is a staple crop for half the world’s population, which is expected to grow by 3 billion over the next 30 years. It is also a key model for studying the genomics of agroecosystems. This dual role places rice at the centre of an enormous challenge facing agriculture: how to leverage genomics to produce enough food to feed an expanding global population. Scientists worldwide are investigating the genetic variation among domesticated rice species and their wild relatives with the aim of identifying loci that can be exploited to breed a new generation of sustainable crops known as Green Super Rice.

Genomic selection is an upgrading form of marker-assisted selection for quantitative traits, and it differs from the traditional marker-assisted selection in that markers in the entire genome are used to predict genetic values and the QTL detection step is skipped. Genomic selection holds the promise to be more efficient than the traditional marker-assisted selection for traits controlled by polygenes. Genomic selection for pure breed improvement is based on marker information and thus leads to cost-saving due to early selection before phenotypes are measured. When applied to hybrid breeding, genomic selection is anticipated to be even more efficient because genotypes of hybrids are predetermined by their inbred parents. Hybrid breeding has been an important tool to increase crop productivity. Here we proposed and applied an advanced method to predict hybrid performance, in which a subset of all potential hybrids is used as a training sample to predict trait values of all potential hybrids. The method is called genomic best linear unbiased prediction. The technology applied to hybrids is called genomic hybrid breeding. We used 278 randomly selected hybrids derived from 210 recombinant inbred lines of rice as a training sample and predicted all 21,945 potential hybrids. The average yield of top 100 selection shows a 16% increase compared with the average yield of all potential hybrids. The new strategy of marker-guided prediction of hybrid yields serves as a proof of concept for a new technology that may potentially revolutionize hybrid breeding.

Manipulating grain size is an effective strategy for increasing cereal yields. Here we identify a pathway composed of five subunits of the heterotrimeric G proteins that regulate grain length in rice. The Gβ protein is essential for plant survival and growth. Gα provides a foundation for grain size expansion. Three Gγ proteins, DEP1, GGC2 and GS3, antagonistically regulate grain size. DEP1 and GGC2, individually or in combination, increase grain length when in complex with Gβ. GS3, having no effect on grain size by itself, reduces grain length by competitively interacting with Gβ. By combining different G-protein variants, we can decrease grain length by up to 35% or increase it by up to 19%, which leads to over 40% decreasing to 28% increasing of grain weight. The wide existence of such a conserved system among angiosperms suggests a possible general predictable approach to manipulating grain/organ sizes. Grain size is a major determinant of cereal yield. Here the authors characterize five subunits of the rice heterotrimeric G proteins and find that manipulating the three Gγ proteins can achieve designed grain size, which provides a predictable approach to improving grain yield and quality.

Epigenomic modifications are instrumental for transcriptional regulation, but comprehensive reference epigenomes remain unexplored in rice. Here, we develop an enhanced chromatin immunoprecipitation (eChIP) approach for plants, and generate genome-wide profiling of five histone modifications and RNA polymerase II occupancy with it. By integrating chromatin accessibility, DNA methylation, and transcriptome datasets, we construct comprehensive epigenome landscapes across various tissues in 20 representative rice varieties. Approximately 81.8% of rice genomes are annotated with different epigenomic properties. Refinement of promoter regions using open chromatin and H3K4me3-marked regions provides insight into transcriptional regulation. We identify extensive enhancer-like promoters with potential enhancer function on transcriptional regulation through chromatin interactions. Active and repressive histone modifications and the predicted enhancers vary largely across tissues, whereas inactive chromatin states are relatively stable. Together, these datasets constitute a valuable resource for functional element annotation in rice and indicate the central role of epigenomic information in understanding transcriptional regulation. Comprehensive epigenomic maps of various rice varieties are still unavailable. Here, the authors report the development of eChIP as a fast and low-input upgrade of regular plant ChIP-seq protocol for epigenome analysis of 20 rice varieties and annotate over 80% of the genome with different epigenome properties for transcriptional regulation.

Hybrid rice has greatly contributed to the global increase of rice productivity. A major component that facilitated the development of hybrids was a mutant showing photoperiod-sensitive male sterility (PSMS) with its fertility regulated by day length. Transcriptome studies have shown that large portions of the eukaryotic genomic sequences are transcribed to long noncoding RNAs (lncRNAs). However, the potential roles for only a few lncRNAs have been brought to light at present. Thus, great efforts have to be invested to understand the biological functions of lncRNAs. Here we show that a lncRNA of 1,236 bases in length, referred to as long-day–specific male-fertility–associated RNA (LDMAR), regulates PSMS in rice. We found that sufficient amount of the LDMAR transcript is required for normal pollen development of plants grown under long-day conditions. A spontaneous mutation causing a single nucleotide polymorphism (SNP) between the wild-type and mutant altered the secondary structure of LDMAR. This change brought about increased methylation in the putative promoter region of LDMAR, which reduced the transcription of LDMAR specifically under long-day conditions, resulting in premature programmed cell death (PCD) in developing anthers, thus causing PSMS. Thus, a lncRNA could directly exert a major effect on a trait like a structure gene, and a SNP could alter the function of a lncRNA similar to amino acid substitution in structural genes. Molecular elucidating of PSMS has important implications for understanding molecular mechanisms of photoperiod regulation of many biological processes and also for developing male sterile germplasms for hybrid crop breeding.

Even as the study of plant genomics rapidly develops through the use of high-throughput sequencing techniques, traditional plant phenotyping lags far behind. Here we develop a high-throughput rice phenotyping facility (HRPF) to monitor 13 traditional agronomic traits and 2 newly defined traits during the rice growth period. Using genome-wide association studies (GWAS) of the 15 traits, we identify 141 associated loci, 25 of which contain known genes such as the Green Revolution semi-dwarf gene, SD1 . Based on a performance evaluation of the HRPF and GWAS results, we demonstrate that high-throughput phenotyping has the potential to replace traditional phenotyping techniques and can provide valuable gene identification information. The combination of the multifunctional phenotyping tools HRPF and GWAS provides deep insights into the genetic architecture of important traits. Next-generation sequencing technology has made the generation of huge amounts of genetic data possible, but phenotype characterization remains slow and difficult. Here the authors develop a high-throughput phenotyping facility for rice that is able to accurately identify and characterize traits related to morphology, biomass and yield.

Plants deploy receptor-like kinases and nucleotide-binding leucine-rich repeat receptors to confer host plant resistance (HPR) to herbivores 1 . These gene-for-gene interactions between insects and their hosts have been proposed for more than 50 years 2 . However, the molecular and cellular mechanisms that underlie HPR have been elusive, as the identity and sensing mechanisms of insect avirulence effectors have remained unknown. Here we identify an insect salivary protein perceived by a plant immune receptor. The BPH14-interacting salivary protein (BISP) from the brown planthopper ( Nilaparvata lugens Stål) is secreted into rice ( Oryza sativa ) during feeding. In susceptible plants, BISP targets O.   satvia RLCK185 ( Os RLCK185; hereafter Os is used to denote O.   satvia -related proteins or genes) to suppress basal defences. In resistant plants, the nucleotide-binding leucine-rich repeat receptor BPH14 directly binds BISP to activate HPR. Constitutive activation of Bph14 -mediated immunity is detrimental to plant growth and productivity. The fine-tuning of Bph14 -mediated HPR is achieved through direct binding of BISP and BPH14 to the selective autophagy cargo receptor Os NBR1, which delivers BISP to Os ATG8 for degradation. Autophagy therefore controls BISP levels. In Bph14 plants, autophagy restores cellular homeostasis by downregulating HPR when feeding by brown planthoppers ceases. We identify an insect saliva protein sensed by a plant immune receptor and discover a three-way interaction system that offers opportunities for developing high-yield, insect-resistant crops. Insect salivary protein (BISP) targets Os RLCK185 to suppress defence in susceptible plants, whereas in resistant plants BISP binds BPH14 to activate host plant resistance. To restore cellular homeostasis, the resistance mechanism is fine-tuned by selective autophagy.

Insight into high-resolution three-dimensional genome organization and its effect on transcription remains largely elusive in plants. Here, using a long-read ChIA-PET approach, we map H3K4me3- and RNA polymerase II (RNAPII)-associated promoter–promoter interactions and H3K9me2-marked heterochromatin interactions at nucleotide/gene resolution in rice. The chromatin architecture is separated into different independent spatial interacting modules with distinct transcriptional potential and covers approximately 82% of the genome. Compared to inactive modules, active modules possess the majority of active loop genes with higher density and contribute to most of the transcriptional activity in rice. In addition, promoter–promoter interacting genes tend to be transcribed cooperatively. In contrast, the heterochromatin-mediated loops form relative stable structure domains in chromatin configuration. Furthermore, we examine the impact of genetic variation on chromatin interactions and transcription and identify a spatial correlation between the genetic regulation of eQTLs and e-traits. Thus, our results reveal hierarchical and modular 3D genome architecture for transcriptional regulation in rice. Three-dimensional genome organization and its effect on transcription remain elusive in rice. Here, the authors map promoter–promoter interactions and heterochromatin interactions using ChIA-PET and reveal spatial correlation between the genetic regulation of eQTLs and e-traits.

Grain yield in many cereal crops is largely determined by grain size. Here we report the genetic and molecular characterization of GS3, a major quantitative trait locus for grain size. It functions as a negative regulator of grain size and organ size. The wild-type isoform is composed of four putative domains: a plant-specific organ size regulation (OSR) domain in the N terminus, a transmembrane domain, a tumor necrosis factor receptor/nerve growth factor receptor (TNFR/NGFR) family cysteine-rich domain, and a von Willebrand factor type C (VWFC) in the C terminus. These domains function differentially in grain size regulation. The OSR domain is both necessary and sufficient for functioning as a negative regulator. The wild-type allele corresponds to medium grain. Loss of function of OSR results in long grain. The C-terminal TNFR/NGFR and VWFC domains show an inhibitory effect on the OSR function; loss-of-function mutations of these domains produced very short grain. This study linked the functional domains of the GS3 protein to natural variation of grain size in rice.