Identification of Genetic Loci for Rice Seedling Mesocotyl Elongation in Both Natural and Artificial Segregating Populations.

Mesocotyl elongation of rice seedlings is a key trait for deep sowing tolerance and well seedling establishment in dry direct sowing rice (DDSR) production. Subsets of the Rice Diversity Panel 1 (RDP1, 294 accessions) and Hanyou 73 (HY73) recombinant inbred line (RIL) population (312 lines) were screened for mesocotyl length (ML) via dark germination. Six RDP1 accessions (Phudugey, Kasalath, CA902B21, Surjamkuhi, Djimoron, and Goria) had an ML longer than 10 cm, with the other 19 accessions being over 4 cm. A GWAS in RDP1 detected 118 associated SNPs on all 12 chromosomes using a threshold of FDR-adjusted p < 0.05, including 11 SNPs on chromosomes 1, 4, 5, 7, 10, and 12 declared by -log10(P) > 5.868 as the Bonferroni-corrected threshold. Using phenotypic data of three successive trials and a high-density bin map from resequencing genotypic data, four to six QTLs were detected on chromosomes 1, 2, 5, 6, and 10, including three loci repeatedly mapped for ML from two or three replicated trials. Candidate genes were predicted from the chromosomal regions covered by the associated LD blocks and the confidence intervals (CIs) of QTLs and partially validated by the dynamic RNA-seq data in the mesocotyl along different periods of light exposure. Potential strategies of donor parent selection for seedling establishment in DDSR breeding were discussed.

Overexpression of a novel small auxin-up RNA gene, OsSAUR11, enhances rice deep rootedness.

BACKGROUND: Deep rooting is an important factor affecting rice drought resistance. However, few genes have been identified to control this trait in rice. Previously, we identified several candidate genes by QTL mapping of the ratio of deep rooting and gene expression analysis in rice. RESULTS: In the present work, we cloned one of these candidate genes, OsSAUR11, which encodes a small auxin-up RNA (SAUR) protein. Overexpression of OsSAUR11 significantly enhanced the ratio of deep rooting of transgenic rice, but knockout of this gene did not significantly affect deep rooting. The expression of OsSAUR11 in rice root was induced by auxin and drought, and OsSAUR11-GFP was localized both in the plasma membrane and cell nucleus. Through an electrophoretic mobility shift assay and gene expression analysis in transgenic rice, we found that the transcription factor OsbZIP62 can bind to the promoter of OsSAUR11 and promote its expression. A luciferase complementary test showed that OsSAUR11 interacts with the protein phosphatase OsPP36. Additionally, expression of several auxin synthesis and transport genes (e.g., OsYUC5 and OsPIN2) were down-regulated in OsSAUR11-overexpressing rice plants. CONCLUSIONS: This study revealed a novel gene OsSAUR11 positively regulates deep rooting in rice, which provides an empirical basis for future improvement of rice root architecture and drought resistance.

Genome-wide association study identifies a gene conferring high physiological phosphorus use efficiency in rice.

Phosphate (Pi) is indispensable for the growth and development of plant, and low-Pi stress is a major limitation for crop growth and yield worldwide. The tolerance to low-Pi stress varied among rice germplasm resources. However, the mechanisms underlying the tolerance of rice to low-Pi stress, as a complex quantitative trait, are not clear. We performed a genome-wide association study (GWAS) through a diverse worldwide collection of 191 rice accessions in the field under normal-Pi and low-Pi supply in two years. Twenty and three significant association loci were identified for biomass and grain yield per plant under low-Pi supply respectively. The expression level of OsAAD as a candidate gene from a associated locus was significantly up-regulated after low-Pi stress treatment for five days and tended to return to normal levels after Pi re-supply in shoots. Suppression of OsAAD expression could improve the physiological phosphorus use efficiency (PPUE) and grain yields through affecting the expression of several genes associated with GA biosynthesis and metabolism. OsAAD would be a promising gene for increasing PPUE and grain yield in rice under normal- and low-Pi supply via genome editing.

GpemDB: A Scalable Database Architecture with the Multi-omics Entity-relationship Model to Integrate Heterogeneous Big-data for Precise Crop Breeding.

BACKGROUND: With the development of high-throughput genome sequencing and phenotype screening techniques, there is a possibility of leveraging multi-omics to speed up the breeding process. However, the heterogeneity of big data handicaps the progress and the lack of a comprehensive database supporting end-to-end association analysis impedes the efficient use of these data. METHODS: In response to this problem, a scalable entity-relationship model and a database architecture are firstly proposed in this paper to manage the cross-platform data sets and explore the relationship among multi-omics, and finally accelerate our breeding efficiency. First, the targeted omics data of crops should be normalized before being stored in the database. A typical breeding data content and structure is demonstrated with the case study of rice (Oryza sativa L). Second, the structure, patterns and hierarchy of multi-omics data are described with the entity-relationship modeling technique. Third, some statistical tools used frequently in the agricultural analysis have been embedded into the database to help breeding. RESULTS: As a result, a general-purpose scalable database, called GpemDB integrating genomics, phenomics, enviromics and management, is developed. It is the first database designed to manage all these four omics data together. The GpemDB involving Gpem metadata-level layer and informative-level layer provides a visualized scheme to display the content of the database and facilitates users to manage, analyze and share breeding data. CONCLUSIONS: GpemDB has been successfully applied to a rice population, which demonstrates this database architecture and model are promising to serve as a powerful tool to utilize the big data for high precise and efficient research and breeding of crops.

Panicle-3D: Efficient Phenotyping Tool for Precise Semantic Segmentation of Rice Panicle Point Cloud.

The automated measurement of crop phenotypic parameters is of great significance to the quantitative study of crop growth. The segmentation and classification of crop point cloud help to realize the automation of crop phenotypic parameter measurement. At present, crop spike-shaped point cloud segmentation has problems such as fewer samples, uneven distribution of point clouds, occlusion of stem and spike, disorderly arrangement of point clouds, and lack of targeted network models. The traditional clustering method can realize the segmentation of the plant organ point cloud with relatively independent spatial location, but the accuracy is not acceptable. This paper first builds a desktop-level point cloud scanning apparatus based on a structured-light projection module to facilitate the point cloud acquisition process. Then, the rice ear point cloud was collected, and the rice ear point cloud data set was made. In addition, data argumentation is used to improve sample utilization efficiency and training accuracy. Finally, a 3D point cloud convolutional neural network model called Panicle-3D was designed to achieve better segmentation accuracy. Specifically, the design of Panicle-3D is aimed at the multiscale characteristics of plant organs, combined with the structure of PointConv and long and short jumps, which accelerates the convergence speed of the network and reduces the loss of features in the process of point cloud downsampling. After comparison experiments, the segmentation accuracy of Panicle-3D reaches 93.4%, which is higher than PointNet. Panicle-3D is suitable for other similar crop point cloud segmentation tasks.

SeedGerm: a cost-effective phenotyping platform for automated seed imaging and machine-learning based phenotypic analysis of crop seed germination.

Efficient seed germination and establishment are important traits for field and glasshouse crops. Large-scale germination experiments are laborious and prone to observer errors, leading to the necessity for automated methods. We experimented with five crop species, including tomato, pepper, Brassica, barley, and maize, and concluded an approach for large-scale germination scoring. Here, we present the SeedGerm system, which combines cost-effective hardware and open-source software for seed germination experiments, automated seed imaging, and machine-learning based phenotypic analysis. The software can process multiple image series simultaneously and produce reliable analysis of germination- and establishment-related traits, in both comma-separated values (CSV) and processed images (PNG) formats. In this article, we describe the hardware and software design in detail. We also demonstrate that SeedGerm could match specialists' scoring of radicle emergence. Germination curves were produced based on seed-level germination timing and rates rather than a fitted curve. In particular, by scoring germination across a diverse panel of Brassica napus varieties, SeedGerm implicates a gene important in abscisic acid (ABA) signalling in seeds. We compared SeedGerm with existing methods and concluded that it could have wide utilities in large-scale seed phenotyping and testing, for both research and routine seed technology applications.

Bi-directional Selection in Upland Rice Leads to Its Adaptive Differentiation from Lowland Rice in Drought Resistance and Productivity.

Drought resistance is required in rice breeding to address the challenge of frequent droughts. However, the evolutionary mechanism of rice drought resistance is not fully understood. We investigated the genetic differentiation between upland and lowland rice domesticated in agro-ecosystems with contrasting water-soil conditions using genome-wide SNPs. We estimated morphological differences among upland and lowland rice in drought resistance and productivity through common garden experiments. Upland rice had better drought resistance but poorer productivity. The negative correlations between traits of drought resistance and productivity are attributed to the underlying genetic trade-offs through tight linkages (e.g., DCA1 and OsCesA7) or pleiotropic effects (e.g., LAX1). The genetic trade-offs are common and greatly shape the evolution of drought resistance in upland rice. In genomic regions associated with both productivity and drought resistance, signs of balancing selection were detected in upland rice, while signs of directional selection were detected in lowland rice, potentially contributing to their adaptive differentiation. Signs of balancing selection in upland rice resulted from bi-directional selection during its domestication in drought-prone upland agro-ecosystems. Using genome-wide association analysis, we identified several valuable quantitative trait loci associated with drought resistance, for which highly differentiated genes should be considered candidates. Bi-directional selection breaking tight linkages by accumulating recombination events would be applicable in breeding water-saving and drought-resistance rice.

Alternative splicing complexity contributes to genetic improvement of drought resistance in the rice maintainer HuHan2B.

Water-saving and drought-resistantce rice (WDR) breeding practices have greatly increased grain yield and drought resistance. To study the genetic basis of adaptation to drought, transcriptome sequences from the WDR maintainer line HuHan2B and the recurrent parent HanFengB were analyzed for alternative splicing (AS) complexity. Intron retention, the dominant AS type, accounted for 42% of the observed AS events. Differential expression analysis revealed transcripts were preferentially expressed in different varieties and conditions. Based on gene ontology predictions, the biological functions of drought-induced transcripts were significantly enriched in genes involved in transcription regulation, chloroplast components and response to abiotic stimulus in HuHan2B, whereas developmental processes for reproduction were primarily enriched in HanFengB. The regulatory network of transcription factors was driven by cohorts of transcript splicing targets, resulting in more diversified regulatory relationships due to AS complexity than in our previous findings. Moreover, several genes were validated to accumulate novel splicing transcripts in a drought-induced manner. Together, these results suggest that HuHan2B and HanFengB share similar AS features but that a subset of genes with increased levels of AS involved in transcription regulatory networks may contribute an additional level of control for genetic improvement of drought resistance in rice maintainer HuHan2B through breeding.

Root Transcriptomic Analysis Revealing the Importance of Energy Metabolism to the Development of Deep Roots in Rice (Oryza sativa L.).

Drought is the most serious abiotic stress limiting rice production, and deep root is the key contributor to drought avoidance. However, the genetic mechanism regulating the development of deep roots is largely unknown. In this study, the transcriptomes of 74 root samples from 37 rice varieties, representing the extreme genotypes of shallow or deep rooting, were surveyed by RNA-seq. The 13,242 differentially expressed genes (DEGs) between deep rooting and shallow rooting varieties (H vs. L) were enriched in the pathway of genetic information processing and metabolism, while the 1,052 DEGs between the deep roots and shallow roots from each of the plants (D vs. S) were significantly enriched in metabolic pathways especially energy metabolism. Ten quantitative trait transcripts (QTTs) were identified and some were involved in energy metabolism. Forty-nine candidate DEGs were confirmed by qRT-PCR and microarray. Through weighted gene co-expression network analysis (WGCNA), we found 18 hub genes. Surprisingly, all these hub genes expressed higher in deep roots than in shallow roots, furthermore half of them functioned in energy metabolism. We also estimated that the ATP production in the deep roots was faster than shallow roots. Our results provided a lot of reliable candidate genes to improve deep rooting, and firstly highlight the importance of energy metabolism to the development of deep roots.

Transgenerational epimutations induced by multi-generation drought imposition mediate rice plant's adaptation to drought condition.

Epigenetic mechanisms are crucial mediators of appropriate plant reactions to adverse environments, but their involvement in long-term adaptation is less clear. Here, we established two rice epimutation accumulation lines by applying drought conditions to 11 successive generations of two rice varieties. We took advantage of recent technical advances to examine the role of DNA methylation variations on rice adaptation to drought stress. We found that multi-generational drought improved the drought adaptability of offspring in upland fields. At single-base resolution, we discovered non-random appearance of drought-induced epimutations. Moreover, we found that a high proportion of drought-induced epimutations maintained their altered DNA methylation status in advanced generations. In addition, genes related to transgenerational epimutations directly participated in stress-responsive pathways. Analysis based on a cluster of drought-responsive genes revealed that their DNA methylation patterns were affected by multi-generational drought. These results suggested that epigenetic mechanisms play important roles in rice adaptations to upland growth conditions. Epigenetic variations have morphological, physiological and ecological consequences and are heritable across generations, suggesting that epigenetics can be considered an important regulatory mechanism in plant long-term adaptation and evolution under adverse environments.

Genetic determination of the enhanced drought resistance of rice maintainer HuHan2B by pedigree breeding.

The ongoing deficit of fresh water resource in rice growing regions has made the selection of water-saving and drought-resistance rice (WDR) a crucial factor in developing sustainable cultivation. HuHan2B, a new japonica maintainer for WDR breeding, had the same yield potential as recurrent parent HanFengB but showed improved drought resistance in fields. We investigated the genomic content accumulation and candidate genes passed from parent to offspring using the genomic and transcriptomic approaches. The genomic constitution indicated that the genetic similarity was 84% between HuHan2B and HanFengB; additionally, 7,256 genes with specific alleles were inherited by HuHan2B from parents other than HanFengB. The differentially expressed genes (DEGs) under drought stress showed that biological function was significantly enriched for transcript regulation in HuHan2B, while the oxidation-reduction process was primarily enriched in HanFengB. Furthermore, 36 DEGs with specific inherited alleles in HuHan2B were almost involved in the regulatory network of TFs and target genes. These findings suggested that major-effect genes were congregated and transformed into offspring in manner of interacting network by breeding. Thus, exploiting the potential biological function of allelic-influencing DEGs would be of great importance for improving selection efficiency and the overall genetic gain of multiple complex traits.

Quantitative trait locus mapping of deep rooting by linkage and association analysis in rice.

Deep rooting is a very important trait for plants' drought avoidance, and it is usually represented by the ratio of deep rooting (RDR). Three sets of rice populations were used to determine the genetic base for RDR. A linkage mapping population with 180 recombinant inbred lines and an association mapping population containing 237 rice varieties were used to identify genes linked to RDR. Six quantitative trait loci (QTLs) of RDR were identified as being located on chromosomes 1, 2, 4, 7, and 10. Using 1 019 883 single-nucleotide polymorphisms (SNPs), a genome-wide association study of the RDR was performed. Forty-eight significant SNPs of the RDR were identified and formed a clear peak on the short arm of chromosome 1 in a Manhattan plot. Compared with the shallow-rooting group and the whole collection, the deep-rooting group had selective sweep regions on chromosomes 1 and 2, especially in the major QTL region on chromosome 2. Seven of the nine candidate SNPs identified by association mapping were verified in two RDR extreme groups. The findings from this study will be beneficial to rice drought-resistance research and breeding.

Dissection of additive, epistatic effect and QTL × environment interaction of quantitative trait loci for sheath blight resistance in rice.

A recombinant inbred line (RIL) population from a cross between 'HH1B' and 'RSB02' (a deep-water rice variety with resistance to sheath blight) was planted in two locations for four different growing seasons. Seven traits were used to evaluate the disease severity, namely disease rating (DR), lesion length (LL), lesion height (LH), relative lesion length (RLL), relative lesion height (RLH), plant height (PH) and heading date (HD). Based on a linkage map of 163 simple sequence repeat (SSR) markers, a total of 37 QTLs were mapped on nine chromosomes. Additionally, 32 epistatic QTLs were identified, distributed on all the 12 chromosomes. The contribution of a single QTL's additive and epistatic effect was of low magnitude for most cases (from 0.39% to 24.62%). Among QTL × environment interaction test, 28 additive QTLs and six pairs of epistatic interactions were involved. Correlation analysis showed that DR had significant positive correlations with LL, RLL and RLH, but had a negative correlation with PH, two of six QTLs controlling DR were mapped in the same chromosome regions as the QTLs controlling PH. The alleles which can enhance disease resistance and increase PH are from the resistant parent 'RSB02', indicating that PH has certain effect on sheath blight resistance in the present study.

Transgenerational variations in DNA methylation induced by drought stress in two rice varieties with distinguished difference to drought resistance.

Adverse environmental conditions have large impacts on plant growth and crop production. One of the crucial mechanisms that plants use in variable and stressful natural environments is gene expression modulation through epigenetic modification. In this study, two rice varieties with different drought resistance levels were cultivated under drought stress from tilling stage to seed filling stage for six successive generations. The variations in DNA methylation of the original generation (G0) and the sixth generation (G6) of these two varieties in normal condition (CK) and under drought stress (DT) at seedling stage were assessed by using Methylation Sensitive Amplification Polymorphism (MSAP) method. The results revealed that drought stress had a cumulative effect on the DNA methylation pattern of both varieties, but these two varieties had different responses to drought stress in DNA methylation. The DNA methylation levels of II-32B (sensitive) and Huhan-3 (resistant) were around 39% and 32%, respectively. Genome-wide DNA methylation variations among generations or treatments accounted for around 13.1% of total MSAP loci in II-32B, but was only approximately 1.3% in Huhan-3. In II-32B, 27.6% of total differentially methylated loci (DML) were directly induced by drought stress and 3.2% of total DML stably transmitted their changed DNA methylation status to the next generation. In Huhan-3, the numbers were 48.8% and 29.8%, respectively. Therefore, entrainment had greater effect on Huhan-3 than on II-32B. Sequence analysis revealed that the DML were widely distributed on all 12 rice chromosomes and that it mainly occurred on the gene's promoter and exon region. Some genes with DML respond to environmental stresses. The inheritance of epigenetic variations induced by drought stress may provide a new way to develop drought resistant rice varieties.

Drought-responsive mechanisms in rice genotypes with contrasting drought tolerance during reproductive stage.

Water status is the main factor affecting rice production. In order to understand rice strategies in response to drought condition in the field, the drought-responsive mechanisms at the physiological and molecular levels were studied in two rice genotypes with contrasting susceptibility to drought stress at reproductive stage. After 20 d of drought treatment, the osmotic potential of leaves reduced 78% and 8% in drought susceptible rice cultivar Zhenshan97B and tolerant rice cultivar IRAT109, respectively. The panicle lengths had no obvious changes in drought stressed Zhenshan97B and IRAT109, suggesting that drought stress impose less effect on assimilate translocation from leaf to vegetative growth of panicles. IRAT109 showed more extensive deeper root growth that could be considered a second line of defense against drought stress. The C(i)/C(a) ratio exhibited enhancement over reduction of g(s) in both cultivars, reflecting the non-stomatal limitation to photosynthesis occurred during drought stress. Orthophosphate dikinase, glycine dehydrogenase, ribulose bisphosphate carboxylase (Rubisco), glycine hydroxymethyltransferase and ATP synthase were down-regulated for Zhenshan97B in response to drought stress, suggesting the reduction of capacity of carbon assimilation in this rice cultivar. In drought-stressed IRAT109, transketolase, Rubisco were down-regulated, however, Rubisco activase and peptidyl-prolyl cis-trans isomerase, which might alleviate the damage on Rubisco by drought stress, were up-regulated. The increased abundances of chloroplastic superoxide dismutase [Cu-Zn] and dehydroascorbate reductase might provide antioxidant protection for IRAT109 against damage by dehydration.

Genetic, proteomic and metabolic analysis of the regulation of energy storage in rice seedlings in response to drought.

We used proteomic analysis to determine the response of rice plant seedlings to drought-induced stress. The expression of 71 protein spots was significantly altered, and 60 spots were successfully identified. The greatest down-regulated protein functional category was translation. Up-regulated proteins were mainly related to protein folding and assembly. Additionally, many proteins involved in metabolism (e.g. carbohydrate metabolism) also showed differences in expression. cDNA microarray and GC-MS analysis showed 4756 differentially expressed mRNAs and 37 differentially expressed metabolites. Once these data were integrated with the proteomic analysis, we were able to elucidate the metabolic pathways affected by drought-induced stress. These results suggest that increased energy consumption from storage substances occurred during drought. In addition, increased expression of the enzymes involved in anabolic pathways corresponded with an increase in the content of six amino acids. We speculated that energy conversion from carbohydrates and/or fatty acids to amino acids was increased. Analysis of basic metabolism networks allowed us to understand how rice plants adjust to drought conditions.

Profiling and association mapping of grain metabolites in a subset of the core collection of Chinese rice germplasm (Oryza sativa L.).

In this study, metabolic profiles of a set of 48 rice germplasms from the Chinese core collection were obtained by gas chromatography and time-of-flight mass spectrometry (GC-TOF-MS). Forty-one metabolites were identified and relatively quantified according to the internal standard (IS). Wide ranges of variations for all metabolites were observed among rice accessions. The maximum/minimum ratios varied from 4.73 to 211.36. The metabolites were categorized into seven groups based on their chemical characteristics. Clustering analysis and a correlation network showed that most of the metabolites had variations among rice accessions in the same direction. Using 218 molecular markers, association mapping was conducted to identify the chromosomal loci influencing the concentrations of identified metabolites. Twenty markers were identified associating with the concentrations of 29 metabolites [-lg(P) > 3]. Allelic effects were investigated in detail in two markers (RM315 and RM541) as examples.