funRiceGenes dataset for comprehensive understanding and application of rice functional genes

Comparative population genomic analysis provides insights into breeding of modern indica rice in China

Comparative genomic analysis within Asian cultivated rice (Oryza sativa L.) populations has greatly enriched our knowledge regarding rice domestication and the divergence of the indica and japonica subspecies, while study on genomic regions associated with improvement within the indica subspecies is still limited. Here, through combined investigation of 2,429 indica cultivar genomes from public sequencing projects, we depict the improvement of modern indica rice in China. We identify three subgroups within indica populations: two geographically distinct, historical subgroups indica I (Ind_I) and indica III (Ind_III) and a modern subgroup indica II (Ind_II). The modern indica subgroup Ind_II shows admixture of the other two subgroups and enrichment of alleles that had been low-frequency in the other two subgroups. The Chinese indica cultivars exhibit a strong subgroup component change from Ind_I to Ind_II in the 1980s. Through haplotype-based comparative analysis, we detect 187 regions associated with separation of Ind_II compared to Ind_I or Ind_III. Within those regions we find strong representation of beneficial agricultural production-related alleles in Ind_II and a positive correlation between grain yield and number of differentiated haplotypes. Phenotypic features of long and slender grain, small tiller angle and decreased flowering time were detected for Ind_II. Through haplotype-based comparative analysis between rice subpopulations and subspecies, we find differentiated haplotypes not only from indica itself but also from japonica and aus, suggesting that introgression from other rice sub-populations has substantially contributed to modern indica rice breeds. These results help clarify the evolutionary landscape of modern indica rice in China and provide useful targets for future improvement.

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.

Global Analysis of Cereal microProteins Suggests Diverse Roles in Crop Development and Environmental Adaptation

MicroProteins are a class of small single-domain proteins that post-translationally regulate larger multidomain proteins from which they evolved or which they relate to. They disrupt the normal function of their targets by forming microProtein-target heterodimers through compatible protein-protein interaction (PPI) domains. Recent studies confirm the significance of microProteins in the fine-tuning of plant developmental processes such as shoot apical meristem maintenance and flowering time regulation. While there are a number of well-characterized microProteins in Arabidopsis thaliana, studies from more complex plant genomes are still missing. We have previously developed miPFinder, a software for identifying microProteins from annotated genomes. Here we present an improved version where we have updated the algorithm to increase its accuracy and speed, and used it to analyze five cereal crop genomes – wheat, rice, barley, maize and sorghum. We found 20,064 potential microProteins from a total of 258,029 proteins in these five organisms, of which approximately 2000 are high-confidence, i.e., likely to function as actual microProteins. Gene ontology analysis of these 2000 microProtein candidates revealed their roles in stress, light and growth responses, hormone signaling and transcriptional regulation. Using a recently developed rice gene co-expression database, we analyzed 347 potential rice microProteins that are also conserved in other cereal crops and found over 50 of these rice microProteins to be co-regulated with their identified interaction partners. Overall, our study reveals a rich source of biotechnologically interesting small proteins that regulate fundamental plant processes such a growth and stress response that could be utilized in crop bioengineering.

Analysis of rice nuclear-localized seed-expressed proteins and their database (RSNP-DB)

Nuclear proteins are primarily regulatory factors governing gene expression. Multiple factors determine the localization of a protein in the nucleus. An upright identification of nuclear proteins is way far from accuracy. We have attempted to combine information from subcellular prediction tools, experimental evidence, and nuclear proteome data to identify a reliable list of seed-expressed nuclear proteins in rice. Depending upon the number of prediction tools calling a protein nuclear, we could sort 19,441 seed expressed proteins into five categories. Of which, half of the seed-expressed proteins were called nuclear by at least one out of four prediction tools. Further, gene ontology (GO) enrichment and transcription factor composition analysis showed that 6116 seed-expressed proteins could be called nuclear with a greater assertion. Localization evidence from experimental data was available for 1360 proteins. Their analysis showed that a 92.04% accuracy of a nuclear call is valid for proteins predicted nuclear by at least three tools. Distribution of nuclear localization signals and nuclear export signals showed that the majority of category four members were nuclear resident proteins, whereas other categories have a low fraction of nuclear resident proteins and significantly higher constitution of shuttling proteins. We compiled all the above information for the seed-expressed genes in the form of a searchable database named Rice Seed Nuclear Protein DataBase (RSNP-DB) https://pmb.du.ac.in/rsnpdb. This information will be useful for comprehending the role of seed nuclear proteome in rice.

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.

Pleiotropic changes revealed by in situ recovery of the semi-dwarf gene sd1 in rice

The "Green Revolution" that dramatically reduced cultivar heights and sharply boosted rice production mid-century was achieved in large part through introgression of defective alleles of Semi-Dwarf 1 (SD1), which encodes a GA20ox oxidase involved in the final steps of the synthesis of bioactive gibberellin in rice. Here, we ask whether converting the defective sd1 version in a modern semi-dwarf cultivar back to wild-type SD1 in situ recovers ancestral plant traits, and more broadly, what it reveals about pleiotropic effects of this gene. We assess these effects of SD1 restoration in three independent recombinant lines recovered from F₂ progeny of a cross between 93-11 and PA64s. We then used RNA-seq to dissect gene network changes that accompanied SD1 restoration. We report that this in situ restoration of wild-type SD1 nearly doubles plant height, increases total grain yield per panicle, and elongates the second-leaf length. Comparison of expression profiles reveals changes in key nodes of the gibberellin pathway, such as OsKO1 and OsGA2ox3, and more broadly in genes related to metabolic networks, defense response, and catabolic processes. Two JA-induced genes, RIR1b and OsPR1b, are extremely down-regulated after SD1 restoration, suggesting that SD1 restoration alters the balance between GA and JA to plant growth, at the cost of degrading the defense response. This in situ approach at the SD1 locus also provides a model example that is applicable to other systems and will further understanding of gene networks underlying high-yield traits in crops.

Genome wide screening and comparative genome analysis for Meta-QTLs, ortho-MQTLs and candidate genes controlling yield and yield-related traits in rice

Background

Improving yield and yield-related traits is the crucial goal in breeding programmes of cereals. Meta-QTL (MQTL) analysis discovers the most stable QTLs regardless of populations genetic background and field trial conditions and effectively narrows down the confidence interval (CI) for identification of candidate genes (CG) and markers development.

Results

A comprehensive MQTL analysis was implemented on 1052 QTLs reported for yield (YLD), grain weight (GW), heading date (HD), plant height (PH) and tiller number (TN) in 122 rice populations evaluated under normal condition from 1996 to 2019. Consequently, these QTLs were confined into 114 MQTLs and the average CI was reduced up to 3.5 folds in compare to the mean CI of the original QTLs with an average of 4.85 cM CI in the resulted MQTLs. Among them, 27 MQTLs with at least five initial QTLs from independent studies were considered as the most stable QTLs over different field trials and genetic backgrounds. Furthermore, several known and novel CGs were detected in the high confident MQTLs intervals. The genomic distribution of MQTLs indicated the highest density at subtelomeric chromosomal regions. Using the advantage of synteny and comparative genomics analysis, 11 and 15 ortho-MQTLs were identified at co-linear regions between rice with barley and maize, respectively. In addition, comparing resulted MQTLs with GWAS studies led to identification of eighteen common significant chromosomal regions controlling the evaluated traits.

Conclusion

This comprehensive analysis defines a genome wide landscape on the most stable loci associated with reliable genetic markers and CGs for yield and yield-related traits in rice. Our findings showed that some of these information are transferable to other cereals that lead to improvement of their breeding programs.

Crop Phenomics and High-Throughput Phenotyping: Past Decades, Current Challenges, and Future Perspectives

Since whole-genome sequencing of many crops has been achieved, crop functional genomics studies have stepped into the big-data and high-throughput era. However, acquisition of large-scale phenotypic data has become one of the major bottlenecks hindering crop breeding and functional genomics studies. Nevertheless, recent technological advances provide us potential solutions to relieve this bottleneck and to explore advanced methods for large-scale phenotyping data acquisition and processing in the coming years. In this article, we review the major progress on high-throughput phenotyping in controlled environments and field conditions as well as its use for post-harvest yield and quality assessment in the past decades. We then discuss the latest multi-omics research combining high-throughput phenotyping with genetic studies. Finally, we propose some conceptual challenges and provide our perspectives on how to bridge the phenotype-genotype gap. It is no doubt that accurate high-throughput phenotyping will accelerate plant genetic improvements and promote the next green revolution in crop breeding.

Fast Track to Discover Novel Promoters in Rice

Promoters are key components for the application of biotechnological techniques in crop plants. Reporter genes such as GUS or GFP have been used to test the activity of promoters for diverse applications. A huge number of T-DNAs carrying promoterless GUS near their right borders have been inserted into the rice genome, and 105,739 flanking sequence tags from rice lines with this T-DNA insertion have been identified, establishing potential promoter trap lines for 20,899 out of 55,986 genes in the rice genome. Anatomical meta-expression data and information on abiotic stress related to these promoter trap lines enable us to quickly identify new promoters associated with various expression patterns. In the present report, we introduce a strategy to identify new promoters in a very short period of time using a combination of meta-expression analysis and promoter trap lines.

Insertional Mutagenesis Approaches and Their Use in Rice for Functional Genomics

Insertional mutagenesis is an indispensable tool for engendering a mutant population using exogenous DNA as the mutagen. The advancement in the next-generation sequencing platform has allowed for faster screening and analysis of generated mutated populations. Rice is a major staple crop for more than half of the world's population; however, the functions of most of the genes in its genome are yet to be analyzed. Various mutant populations represent extremely valuable resources in order to achieve this goal. Here, we have reviewed different insertional mutagenesis approaches that have been used in rice, and have discussed their principles, strengths, and limitations. Comparisons between transfer DNA (T-DNA), transposons, and entrapment tagging approaches have highlighted their utilization in functional genomics studies in rice. We have also summarised different forward and reverse genetics approaches used for screening of insertional mutant populations. Furthermore, we have compiled information from several efforts made using insertional mutagenesis approaches in rice. The information presented here would serve as a database for rice insertional mutagenesis populations. We have also included various examples which illustrate how these populations have been useful for rice functional genomics studies. The information provided here will be very helpful for future functional genomics studies in rice aimed at its genetic improvement.

A Systematic View Exploring the Role of Chloroplasts in Plant Abiotic Stress Responses

Chloroplasts are intracellular semiautonomous organelles central to photosynthesis and are essential for plant growth and yield. The significance of the function of chloroplast-related genes in response to climate change has not been well studied in crops. In the present study, the initial focus was on genes that were predicted to be located in the chloroplast genome in rice, a model crop plant, with genes either preferentially expressed in the leaf or ubiquitously expressed in all organs. The characteristics were analyzed by Gene Ontology (GO) enrichment and MapMan functional classification tools. It was then identified that 110 GO terms (45 for leaf expression and 65 for ubiquitous expression) and 1,695 genes mapped to MapMan overviews were strongly associated with chloroplasts. In particular, the MapMan cellular response overview revealed a close association between heat stress response and chloroplast-related genes in rice. Moreover, features of these genes in response to abiotic stress were analyzed using a large-scale publicly available transcript dataset. Consequently, the expression of 215 genes was found to be upregulated in response to high temperature stress. Conversely, genes that responded to other stresses were extremely limited. In other words, chloroplast-related genes were found to affect abiotic stress response mainly through high temperature response, with little effect on response to drought and salinity stress. These results suggest that genes involved in diurnal rhythm in the leaves participate in the reaction to recognize temperature changes in the environment. Furthermore, the predicted protein–protein interaction network analysis associated with high temperature stress is expected to provide a very important basis for the study of molecular mechanisms by which chloroplasts will respond to future climate changes.

The rice genome revolution: from an ancient grain to 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.

Identification of Transcription Factors Regulating Senescence in Wheat through Gene Regulatory Network Modelling

Senescence is a tightly regulated developmental program coordinated by transcription factors. Identifying these transcription factors in crops will provide opportunities to tailor the senescence process to different environmental conditions and regulate the balance between yield and grain nutrient content. Here, we use ten time points of gene expression data along with gene network modeling to identify transcription factors regulating senescence in polyploid wheat (Triticum aestivum). We observe two main phases of transcriptional changes during senescence: early down-regulation of housekeeping functions and metabolic processes followed by up-regulation of transport and hormone-related genes. These two phases are largely conserved with Arabidopsis (Arabidopsis thaliana), although the individual genes underlying these changes are often not orthologous. We have identified transcription factor families associated with these early and later waves of differential expression. Using gene regulatory network modeling, we identified candidate transcription factors that may control senescence. Using independent, publicly available datasets, we found that the most highly ranked candidate genes in the network were enriched for senescence-related functions compared with all genes in the network. We validated the function of one of these candidate transcription factors in senescence using wheat chemically induced mutants. This study lays the groundwork to understand the transcription factors that regulate senescence in polyploid wheat and exemplifies the integration of time-series data with publicly available expression atlases and networks to identify candidate regulatory genes.

Infrastructures of systems biology that facilitate functional genomic study in rice

Rice (Oryza sativa L.) is both a major staple food for the worldwide population and a model crop plant for studying the mode of action of agronomically valuable traits, providing information that can be applied to other crop plants. Due to the development of high-throughput technologies such as next generation sequencing and mass spectrometry, a huge mass of multi-omics data in rice has been accumulated. Through the integration of those data, systems biology in rice is becoming more advanced.To facilitate such systemic approaches, we have summarized current resources, such as databases and tools, for systems biology in rice. In this review, we categorize the resources using six omics levels: genomics, transcriptomics, proteomics, metabolomics, integrated omics, and functional genomics. We provide the names, websites, references, working states, and number of citations for each individual database or tool and discuss future prospects for the integrated understanding of rice gene functions.

A web-based tool for the prediction of rice transcription factor function

Transcription factors (TFs) are an important class of regulatory molecules. Despite their importance, only a small number of genes encoding TFs have been characterized in Oryza sativa (rice), often because gene duplication and functional redundancy complicate their analysis. To address this challenge, we developed a web-based tool called the Rice Transcription Factor Phylogenomics Database (RTFDB) and demonstrate its application for predicting TF function. The RTFDB hosts transcriptome and co-expression analyses. Sources include high-throughput data from oligonucleotide microarray (Affymetrix and Agilent) as well as RNA-Seq-based expression profiles. We used the RTFDB to identify tissue-specific and stress-related gene expression. Subsequently, 273 genes preferentially expressed in specific tissues or organs, 455 genes showing a differential expression pattern in response to 4 abiotic stresses, 179 genes responsive to infection of various pathogens and 512 genes showing differential accumulation in response to various hormone treatments were identified through the meta-expression analysis. Pairwise Pearson correlation coefficient analysis between paralogous genes in a phylogenetic tree was used to assess their expression collinearity and thereby provides a hint on their genetic redundancy. Integrating transcriptome with the gene evolutionary information reveals the possible functional redundancy or dominance played by paralog genes in a highly duplicated genome such as rice. With this method, we estimated a predominant role for 83.3% (65/78) of the TF or transcriptional regulator genes that had been characterized via loss-of-function studies. In this regard, the proposed method is applicable for functional studies of other plant species with annotated genome.

funRiceGenes dataset for comprehensive understanding and application of rice functional genes

Background

As a main staple food, rice is also a model plant for functional genomic studies of monocots. Decoding of every DNA element of the rice genome is essential for genetic improvement to address increasing food demands. The past 15 years have witnessed extraordinary advances in rice functional genomics. Systematic characterization and proper deposition of every rice gene are vital for both functional studies and crop genetic improvement.

Findings

We built a comprehensive and accurate dataset of ∼2800 functionally characterized rice genes and ∼5000 members of different gene families by integrating data from available databases and reviewing every publication on rice functional genomic studies. The dataset accounts for 19.2% of the 39 045 annotated protein-coding rice genes, which provides the most exhaustive archive for investigating the functions of rice genes. We also constructed 214 gene interaction networks based on 1841 connections between 1310 genes. The largest network with 762 genes indicated that pleiotropic genes linked different biological pathways. Increasing degree of conservation of the flowering pathway was observed among more closely related plants, implying substantial value of rice genes for future dissection of flowering regulation in other crops. All data are deposited in the funRiceGenes database (https://funricegenes.github.io/). Functionality for advanced search and continuous updating of the database are provided by a Shiny application (http://funricegenes.ncpgr.cn/).

Conclusions

The funRiceGenes dataset would enable further exploring of the crosslink between gene functions and natural variations in rice, which can also facilitate breeding design to improve target agronomic traits of rice.

A comprehensive review of web-based resources of non-coding RNAs for plant science research

Non-coding RNAs (ncRNAs) are transcribed from genome but not translated into proteins. Many ncRNAs are key regulators of plants growth and development, metabolism and stress tolerance. In order to make the web-based ncRNA resources for plant science research be more easily accessible and understandable, we made a comprehensive review for 83 web-based resources of three types, including genome databases containing ncRNA data, microRNA (miRNA) databases and long non-coding RNA (lncRNA) databases. To facilitate effective usage of these resources, we also suggested some preferred resources of miRNAs and lncRNAs for performing meaningful analysis.