Zilong Guo

Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice

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.

A Novel Integrated Method for Large-Scale Detection, Identification, and Quantification of Widely Targeted Metabolites: Application in the Study of Rice Metabolomics

Liquid chromatography-mass spectrometry (LC-MS)-based metabolomics has been facilitated by the construction of MS(2) spectral tag (MS2T) library from the total scan ESI MS/MS data, and the development of widely targeted metabolomics method using MS/MS data gathered from authentic standards. In this report, a novel strategy called stepwise multiple ion monitoring-enhanced product ions (stepwise MIM-EPI) was developed to construct the MS2T library, in which stepwise MIM was used as survey scans to trigger the acquisition of EPI. A total number of 698 (almost) non-redundant metabolites with MS(2) spectra were obtained, of which 135 metabolites were identified/annotated. Integrating the data gathered from our MS2T library and other available multiple reaction monitoring (MRM) information, a widely targeted metabolomics method was developed to quantify 277 metabolites, including some phytohormones. Evaluation of the dehydration responses and natural variations of these metabolites in rice leaf not only suggested the coordinated regulation of abscisic acid (ABA) with metabolites such as serotonin derivative(s), polyamine conjugates under drought stress, but also revealed some C-glycosylated flavones as the potential markers for the discrimination of indica and japonica rice subspecies. The new MS2T library construction and widely targeted metabolomics strategy could be used as a tool for rice functional genomics.

Genome-wide association study of rice (Oryza sativa L.) leaf traits with a high-throughput leaf scorer

Highlight A combination of high-throughput leaf phenotyping and genome-wide association analysis provides valuable insights into the genetic basis of rice leaf traits.

New insights into the genetic basis of natural chilling and cold shock tolerance in rice by genome‐wide association analysis

In order to understand cold adaptability and explore additional genetic resources for the cold tolerance improvement of rice, we investigated the genetic variation of 529 rice accessions under natural chilling and cold shock stress conditions at the seedling stage using genome-wide association studies; a total of 132 loci were identified. Among them, 12 loci were common for both chilling and cold shock tolerance, suggesting that rice has a distinct and overlapping genetic response and adaptation to the two stresses. Haplotype analysis of a known gene OsMYB2, which is involved in cold tolerance, revealed indica-japonica differentiation and latitude tendency for the haplotypes of this gene. By checking the subpopulation and geographical distribution of accessions with tolerance or sensitivity under these two stress conditions, we found that the chilling tolerance group, which mainly consisted of japonica accessions, has a wider latitudinal distribution than the chilling sensitivity group. We conclude that the genetic basis of natural chilling stress tolerance in rice is distinct from that of cold shock stress frequently used for low-temperature treatment in the laboratory and the cold adaptability of rice is associated with the subpopulation and latitudinal distribution.

MODD mediates deactivation and degradation of OsbZIP46 to negatively regulate ABA signaling and drought resistance in rice

MODD negatively regulates OsbZIP46 activity and stability through HDAC-related chromatin remodeling and PUB70-mediated ubiquitination, respectively, to fine-tune ABA signaling and drought resistance. Plants have evolved complicated protective mechanisms to survive adverse conditions. Previously, we reported that the transcription factor OsbZIP46 regulates abscisic acid (ABA) signaling-mediated drought tolerance in rice (Oryza sativa) by modulating stress-related genes. An intrinsic D domain represses OsbZIP46 activity, but the detailed mechanism for the repression of OsbZIP46 activation remains unknown. Here, we report an OsbZIP46-interacting protein, MODD (Mediator of OsbZIP46 deactivation and degradation), which is homologous to the Arabidopsis thaliana ABSCISIC ACID-INSENSITIVE5 binding protein AFP. MODD was induced by ABA and drought stress, but the induction was much slower than that of OsbZIP46. In contrast to OsbZIP46, MODD negatively regulates ABA signaling and drought tolerance, and inhibits the expression of OsbZIP46 target genes. We found that MODD negatively regulates OsbZIP46 activity and stability. MODD represses OsbZIP46 activity via interaction with the OsTPR3-HDA702 corepressor complex and downregulation of the histone acetylation level at OsbZIP46 target genes. MODD promotes OsbZIP46 degradation via interaction with the U-box type ubiquitin E3 ligase OsPUB70. Interestingly, the D domain is required for both deactivation and degradation of OsbZIP46 via its interaction with MODD. These findings show that plants fine-tune their drought responses by elaborate regulatory mechanisms, including the coordination of activity and stability of key transcription factors.

A Novel Tiller Angle Gene, TAC3 , together with TAC1 and D2 Largely Determine the Natural Variation of Tiller Angle in Rice Cultivars

Tiller angle is one of the most important components of the ideal plant architecture that can greatly enhance rice grain yield. Understanding the genetic basis of tiller angle and mining favorable alleles will be helpful for breeding new plant-type varieties. Here, we performed genome-wide association studies (GWAS) to identify genes controlling tiller angle using 529 diverse accessions of Oryza sativa including 295 indica and 156 japonica accessions in two environments. We identified 7 common quantitative trait loci (QTLs), including the previously reported major gene Tiller Angle Control 1 (TAC1), in the two environments, 10 and 13 unique QTLs in Hainan and Wuhan, respectively. More QTLs were identified in indica than in japonica, and three major QTLs (qTA3, qTA1b/DWARF2 (D2) and qTA9c/TAC1) were fixed in japonica but segregating in indica, which explained the wider variation observed in indica compared with that in japonica. No common QTLs were identified between the indica and japonica subpopulations. Mutant analysis for the candidate gene of qTA3 on chromosome 3 indicated a novel gene, Tiller Angle Control 3 (TAC3), encoding a conserved hypothetical protein controlling tiller angle. TAC3 is preferentially expressed in the tiller base. The ebisu dwarf (d2) mutant exhibited a decreased tiller angle, in addition to its previously described abnormal phenotype. A nucleotide diversity analysis revealed that TAC3, D2 and TAC1 have been subjected to selection during japonica domestication. A haplotype analysis identified favorable alleles of TAC3, D2 and TAC1, which may be used for breeding plants with an ideal architecture. In conclusion, there is a diverse genetic basis for tiller angle between the two subpopulations, and it is the novel gene TAC3 together with TAC1, D2, and other newly identified genes in this study that controls tiller angle in rice cultivars.

Genome-Wide Association Analysis Reveals Different Genetic Control in Panicle Architecture Between and Rice.

Thirty loci for panicle size were identified by genome‐wide association analysis. Ghd7 and DST were specifically associated with panicle length in indica and japonica rice. Different gene networks regulate panicle architecture in indica and japonica rice.

Genetic control of the root system in rice under normal and drought stress conditions by genome-wide association study

A variety of adverse conditions including drought stress severely affect rice production. Root system plays a critical role in drought avoidance, which is one of the major mechanisms of drought resistance. In this study, we adopted genome-wide association study (GWAS) to dissect the genetic basis controlling various root traits by using a natural population consisting of 529 representative rice accessions. A total of 413 suggestive associations, containing 143 significant associations, were identified for 21 root traits, such as maximum root length, root volume, and root dry weight under normal and drought stress conditions at the maturation stage. More than 80 percent of the suggestive loci were located in the region of reported QTLs for root traits, while about 20 percent of suggestive loci were novel loci detected in this study. Besides, 11 reported root-related genes, including DRO1, WOX11, and OsPID, were found to co-locate with the association loci. We further proved that the association results can facilitate the efficient identification of causal genes for root traits by the two case studies of Nal1 and OsJAZ1. These loci and their candidate causal genes provide an important basis for the genetic improvement of root traits and drought resistance.

Natural variation in the sequence of SNAC1 and its expression level polymorphism in rice Germplasms under drought stress.

Water is a major limiting factor for food production and many countries fail to produce sufficient food for their population due to severe water scarcity(Jury and Vaux,2005).Rice is the main staple food worldwide.More than 50%of rice in the world is rain-fed and drought causes severe reduction in rice grain yield in rain-fed environments(Venuprasad et al.,2007;Zhang.2007;Sandhu et al.,2014).Therefore,enhancing drought resistance(DR)of rice is important for food security.However,DR is a complex trait,which is controlled by a large number of loci with small effect and is also affected by different genetic background,genotype-by-environment interaction and other stresses such as heat(Hu and Xiong,

Novel Digital Features Discriminate Between Drought Resistant and Drought Sensitive Rice Under Controlled and Field Conditions

Dynamic quantification of drought response is a key issue both for variety selection and for functional genetic study of rice drought resistance. Traditional assessment of drought resistance traits, such as stay-green and leaf-rolling, has utilized manual measurements, that are often subjective, error-prone, poorly quantified and time consuming. To relieve this phenotyping bottleneck, we demonstrate a feasible, robust and non-destructive method that dynamically quantifies response to drought, under both controlled and field conditions. Firstly, RGB images of individual rice plants at different growth points were analyzed to derive 4 features that were influenced by imposition of drought. These include a feature related to the ability to stay green, which we termed greenness plant area ratio (GPAR) and 3 shape descriptors [total plant area/bounding rectangle area ratio (TBR), perimeter area ratio (PAR) and total plant area/convex hull area ratio (TCR)]. Experiments showed that these 4 features were capable of discriminating reliably between drought resistant and drought sensitive accessions, and dynamically quantifying the drought response under controlled conditions across time (at either daily or half hourly time intervals). We compared the 3 shape descriptors and concluded that PAR was more robust and sensitive to leaf-rolling than the other shape descriptors. In addition, PAR and GPAR proved to be effective in quantification of drought response in the field. Moreover, the values obtained in field experiments using the collection of rice varieties were correlated with those derived from pot-based experiments. The general applicability of the algorithms is demonstrated by their ability to probe archival Miscanthus data previously collected on an independent platform. In conclusion, this image-based technology is robust providing a platform-independent tool for quantifying drought response that should be of general utility for breeding and functional genomics in future.