Effectiveness of Covid-19 Vaccines over a 9-Month Period in North Carolina.

BACKGROUND: The duration of protection afforded by coronavirus disease 2019 (Covid-19) vaccines in the United States is unclear. Whether the increase in postvaccination infections during the summer of 2021 was caused by declining immunity over time, the emergence of the B.1.617.2 (delta) variant, or both is unknown. METHODS: We extracted data regarding Covid-19-related vaccination and outcomes during a 9-month period (December 11, 2020, to September 8, 2021) for approximately 10.6 million North Carolina residents by linking data from the North Carolina Covid-19 Surveillance System and the Covid-19 Vaccine Management System. We used a Cox regression model to estimate the effectiveness of the BNT162b2 (Pfizer-BioNTech), mRNA-1273 (Moderna), and Ad26.COV2.S (Johnson & Johnson-Janssen) vaccines in reducing the current risks of Covid-19, hospitalization, and death, as a function of time elapsed since vaccination. RESULTS: For the two-dose regimens of messenger RNA (mRNA) vaccines BNT162b2 (30 µg per dose) and mRNA-1273 (100 µg per dose), vaccine effectiveness against Covid-19 was 94.5% (95% confidence interval [CI], 94.1 to 94.9) and 95.9% (95% CI, 95.5 to 96.2), respectively, at 2 months after the first dose and decreased to 66.6% (95% CI, 65.2 to 67.8) and 80.3% (95% CI, 79.3 to 81.2), respectively, at 7 months. Among early recipients of BNT162b2 and mRNA-1273, effectiveness decreased by approximately 15 and 10 percentage points, respectively, from mid-June to mid-July, when the delta variant became dominant. For the one-dose regimen of Ad26.COV2.S (5 × 1010 viral particles), effectiveness against Covid-19 was 74.8% (95% CI, 72.5 to 76.9) at 1 month and decreased to 59.4% (95% CI, 57.2 to 61.5) at 5 months. All three vaccines maintained better effectiveness in preventing hospitalization and death than in preventing infection over time, although the two mRNA vaccines provided higher levels of protection than Ad26.COV2.S. CONCLUSIONS: All three Covid-19 vaccines had durable effectiveness in reducing the risks of hospitalization and death. Waning protection against infection over time was due to both declining immunity and the emergence of the delta variant. (Funded by a Dennis Gillings Distinguished Professorship and the National Institutes of Health.).

EPIC: Inferring relevant cell types for complex traits by integrating genome-wide association studies and single-cell RNA sequencing.

More than a decade of genome-wide association studies (GWASs) have identified genetic risk variants that are significantly associated with complex traits. Emerging evidence suggests that the function of trait-associated variants likely acts in a tissue- or cell-type-specific fashion. Yet, it remains challenging to prioritize trait-relevant tissues or cell types to elucidate disease etiology. Here, we present EPIC (cEll tyPe enrIChment), a statistical framework that relates large-scale GWAS summary statistics to cell-type-specific gene expression measurements from single-cell RNA sequencing (scRNA-seq). We derive powerful gene-level test statistics for common and rare variants, separately and jointly, and adopt generalized least squares to prioritize trait-relevant cell types while accounting for the correlation structures both within and between genes. Using enrichment of loci associated with four lipid traits in the liver and enrichment of loci associated with three neurological disorders in the brain as ground truths, we show that EPIC outperforms existing methods. We apply our framework to multiple scRNA-seq datasets from different platforms and identify cell types underlying type 2 diabetes and schizophrenia. The enrichment is replicated using independent GWAS and scRNA-seq datasets and further validated using PubMed search and existing bulk case-control testing results.

Mediation analysis of multiple mediators with incomplete omics data.

There is an increasing interest in using multiple types of omics features (e.g., DNA sequences, RNA expressions, methylation, protein expressions, and metabolic profiles) to study how the relationships between phenotypes and genotypes may be mediated by other omics markers. Genotypes and phenotypes are typically available for all subjects in genetic studies, but typically, some omics data will be missing for some subjects, due to limitations such as cost and sample quality. In this article, we propose a powerful approach for mediation analysis that accommodates missing data among multiple mediators and allows for various interaction effects. We formulate the relationships among genetic variants, other omics measurements, and phenotypes through linear regression models. We derive the joint likelihood for models with two mediators, accounting for arbitrary patterns of missing values. Utilizing computationally efficient and stable algorithms, we conduct maximum likelihood estimation. Our methods produce unbiased and statistically efficient estimators. We demonstrate the usefulness of our methods through simulation studies and an application to the Metabolic Syndrome in Men study.

The antioxidant protein glutaredoxin 1 is essential for oxidative stress response and pathogenicity of Toxoplasma gondii.

Glutaredoxins (Grxs) are ubiquitous antioxidant proteins involved in many molecular processes to protect cells against oxidative damage. Here, we study the roles of Grxs in the pathogenicity of Toxoplasma gondii. We show that Grxs are localized in the mitochondria (Grx1), cytoplasm (Grx2), and apicoplast (Grx3, Grx4), while Grx5 had an undetectable level of expression. We generated Δgrx1-5 mutants of T. gondii type I RH and type II Pru strains using CRISPR-Cas9 system. No significant differences in the infectivity were detected between four Δgrx (grx2-grx5) strains and their respective wild-type (WT) strains in vitro or in vivo. Additionally, no differences were detected in the production of reactive oxygen species, total antioxidant capacity, superoxide dismutase activity, and sensitivity to external oxidative stimuli. Interestingly, RHΔgrx1 or PruΔgrx1 exhibited significant differences in all the investigated aspects compared to the other grx2-grx5 mutant and WT strains. Transcriptome analysis suggests that deletion of grx1 altered the expression of genes involved in transport and metabolic pathways, signal transduction, translation, and obsolete oxidation-reduction process. The data support the conclusion that grx1 supports T. gondii resistance to oxidative killing and is essential for the parasite growth in cultured cells and pathogenicity in mice and that the active site CGFS motif was necessary for Grx1 activity.

MB38(M=Be and Zn): A Quasi-Planar Structure Rather Than A Core-Shell Octahedral Borospherene Structure.

In a recent paper (ChemPhysChem, 2023, 24, e202200947), based on the results computed using DFT method, the perfect core-shell octahedral configuration Be@B38 and Zn@B38 was reported to be the global minima of the MB38(M=Be and Zn) clusters. However, this paper presents the lower energy structures of MB38(M=Be and Zn) clusters as a quasi-planar configuration, the Be atom is found to reside on the convex surface of the quasi-planar B38 isomer, while the Zn atom tends to be attached to the top three B atoms of the quasi-planar B38 isomer. Our results show that quasi-planar MB38(M=Be and Zn) at DFT method have lower energy than core-shell octahedral configuration M@B38(M=Be and Zn). Natural atomic charges, valence electron density, electron localization function (ELF) analyses identify the MB38(M=Be and Zn) to be charge transfer complexes (Be2+B382-and Be1+B381-) and suggest primarily the electrostatic interactions between doped atom and B38 fragment. The photoelectron spectra of the corresponding anionic structures were simulated, providing theoretical basis for future structural identification.

Fitting the Cox proportional hazards model to big data.

The semiparametric Cox proportional hazards model, together with the partial likelihood principle, has been widely used to study the effects of potentially time-dependent covariates on a possibly censored event time. We propose a computationally efficient method for fitting the Cox model to big data involving millions of study subjects. Specifically, we perform maximum partial likelihood estimation on a small subset of the whole data and improve the initial estimator by incorporating the remaining data through one-step estimation with estimated efficient score functions. We show that the final estimator has the same asymptotic distribution as the conventional maximum partial likelihood estimator using the whole dataset but requires only a small fraction of computation time. We demonstrate the usefulness of the proposed method through extensive simulation studies and an application to the UK Biobank data.

Proportional rates models for multivariate panel count data.

Multivariate panel count data arise when there are multiple types of recurrent events, and the observation for each study subject consists of the number of recurrent events of each type between two successive examinations. We formulate the effects of potentially time-dependent covariates on multiple types of recurrent events through proportional rates models, while leaving the dependence structures of the related recurrent events completely unspecified. We employ nonparametric maximum pseudo-likelihood estimation under the working assumptions that all types of events are independent and each type of event is a nonhomogeneous Poisson process, and we develop a simple and stable EM-type algorithm. We show that the resulting estimators of the regression parameters are consistent and asymptotically normal, with a covariance matrix that can be estimated consistently by a sandwich estimator. In addition, we develop a class of graphical and numerical methods for checking the adequacy of the fitted model. Finally, we evaluate the performance of the proposed methods through simulation studies and analysis of a skin cancer clinical trial.

Evaluating treatment efficacy in hospitalized COVID-19 patients, with applications to Adaptive COVID-19 Treatment Trials.

BACKGROUND: The current endpoints for therapeutic trials of hospitalized COVID-19 patients capture only part of the clinical course of a patient and have limited statistical power and robustness. METHODS: We specify proportional odds models for repeated measures of clinical status, with a common odds ratio of lower severity over time. We also specify the proportional hazards model for time to each level of improvement or deterioration of clinical status, with a common hazard ratio for overall treatment benefit. We apply these methods to Adaptive COVID-19 Treatment Trials. RESULTS: For remdesivir versus placebo, the common odds ratio was 1.48 (95% confidence interval (CI) = 1.23-1.79; p < 0.001), and the common hazard ratio was 1.27 (95% CI = 1.09-1.47; p = 0.002). For baricitinib plus remdesivir versus remdesivir alone, the common odds ratio was 1.32 (95% CI = 1.10-1.57; p = 0.002), and the common hazard ratio was 1.30 (95% CI = 1.13-1.49; p < 0.001). For interferon beta-1a plus remdesivir versus remdesivir alone, the common odds ratio was 0.95 (95% CI = 0.79-1.14; p = 0.56), and the common hazard ratio was 0.98 (95% CI = 0.85-1.12; p = 0.74). CONCLUSIONS: The proposed methods comprehensively characterize the treatment effects on the entire clinical course of a hospitalized COVID-19 patient.

Impact of Vaccination, Prior Infection, and Therapy on Omicron Infection and Mortality.

BACKGROUND: Understanding immunity against Omicron infection and severe outcomes conferred by coronavirus disease 2019 (Covid-19) vaccination, prior severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, and monoclonal antibody therapy will inform intervention strategies. METHODS: We considered 295 691 patients tested for SARS-CoV-2 at Cleveland Clinic between 1 October 2021 and 31 January 2022. We used logistic regression to investigate the association of vaccination and prior infection with the risk of SARS-CoV-2 infection and used Cox regression to investigate the association of vaccination, prior infection, and monoclonal antibody therapy with the risks of intensive care unit (ICU) stay and death. RESULTS: Vaccination and prior infection were less effective against Omicron than Delta infection but provided strong protection against ICU admission and death. Boosting greatly increased vaccine effectiveness against Omicron infection and severe outcomes, although effectiveness waned rapidly over time. Monoclonal antibody therapy considerably reduced risks of ICU admission and death. The relatively low mortality of the Omicron variant was due to both reduced lethality of this variant and increased population immunity acquired from booster vaccination and previous infection. CONCLUSIONS: Booster vaccination and prior SARS-CoV-2 infection provide strong protection against ICU admission and death from Omicron infection. Monoclonal antibody therapy is also beneficial.

Effect of deleting four Toxoplasma gondii calcium-binding EGF domain-containing proteins on parasite replication and virulence.

Several calcium-binding proteins including calcium-dependent protein kinases play important roles in several facets of the intracellular infection cycle of the apicomplexan protozoan parasite Toxoplasma gondii. However, the role of the calcium-binding epidermal growth factor (EGF) domain-containing proteins (CBDPs) remains poorly understood. In this study, we examined the functions of four CBDP genes in T. gondii RH strain of type I by generating knock-out strains using CRISPR-Cas9 system. We investigated the ability of mutant strains deficient in CBDP1, CBDP2, CBDP3, or CBDP4 to form plaques, replicate intracellularly, and egress from the host cells. The results showed that no definite differences between any of these four CBDP mutant strains and the wild-type strain in terms of their ability to form plaques, intracellular replication, and egress. Additionally, CBDP mutants did not exhibit any significant attenuated virulence compared to the wild-type strain in mice. The expression profiles of CBDP2-4 genes were conserved among T. gondii strains of different genotypes, life cycle stages, and developmental forms. Whether other CBDP genes play any roles in the pathogenicity of T. gondii strains of different genotypes remains to be elucidated.

Associations between phthalate metabolites and cytokines in the follicular fluid of women undergoing in vitro fertilization.

Many studies have showed that phthalates have reproductive and embryonic toxicity, while the potential mechanisms are mostly unknown. Inflammation may play a mediating part in phthalate exposure and adverse reproductive endpoints. A cross-sectional survey was conducted to investigate the associations of phthalate metabolites with inflammatory cytokines in the follicular fluid (FF) of women undergoing in vitro fertilization (IVF). We determined the levels of eight phthalate metabolites and five cytokines in the FF of 76 women, including interleukin (IL)- 6, IL-8, IL-10, monocyte chemoattractant protein-1 (MCP-1) and tumor necrosis factor-α (TNF-α). The associations of individual phthalate exposure with cytokines in FF samples were explored by multiple linear regression. We further evaluated the combined effects of multiple phthalate exposures on FF levels of cytokines by using Bayesian kernel machine regression (BKMR) models. We found that there was a positive relationship between mono-ethyl phthalate (MEP) and IL-6 in the FF (percent change:12.4%; 95% CI: 1.3%, 24.9%). In contrast, elevated mono-benzyl phthalate (MBzP), mono(2-ethylhexyl) phthalate (MEHP) and %MEHP levels were associated with decreased MCP-1. In the BKMR models, phthalate metabolite mixtures were positively associated with TNF-α when the mixtures were lower than 65th percentile compared with their medians. In the stratified analyses, MEHP was inversely associated with MCP-1 among women with BMI ≥ 23 kg/m2 (test for interaction <0.05). Our results suggest that certain phthalate metabolites or their mixtures may alter levels of inflammatory cytokines in the FF, and further research is necessary to elucidate the mechanisms underlying the relationship between phthalates exposure, ovarian dysfunction and adverse pregnancy outcomes.

Reliably Assessing Duration of Protection for Coronavirus Disease 2019 Vaccines.

Decision making about vaccination and boosting schedules for coronavirus disease 2019 (COVID-19) hinges on reliable methods for evaluating the longevity of vaccine protection. We show that modeling of protection as a piecewise linear function of time since vaccination for the log hazard ratio of the vaccine effect provides more reliable estimates of vaccine effectiveness at the end of an observation period and also detects plateaus in protective effectiveness more reliably than the standard method of estimating a constant vaccine effect over each time period. This approach will be useful for analyzing data pertaining to COVID-19 vaccines and other vaccines for which rapid and reliable understanding of vaccine effectiveness over time is desired.

[Latest Findings on the Interaction Mechanism Between Depressive Disorder and Intestinal Permeability].

The intestinal barrier, a complex structure consisting of multiple layers of defense barriers, blocks the transfer of intestinal and foreign bacteria and their metabolites into the internal environment of the human body. Intestinal permeability can be used to evaluate the integrity of the intestinal barrier. Increased intestinal permeability has been observed in patients with depressive disorder. Some studies have reported an interaction between depressive disorder and intestinal barrier. Herein, we reviewed reported findings on the mechanisms of how systematic low-grade inflammation, vagal nerve dysfunction, and hypothalamic-pituitary-adrenal axis dysfunction cause changes in intestinal permeability in patients with depressive disorder and the pathogenic mechanism of how bacterial translocation caused by damaged intestinal barrier leads to depressive disorder. In addition, the potential mechanisms of how antidepressants improve intestinal permeability and how probiotics improve depressive disorder have been discussed.

Evaluating Vaccine Efficacy Against Severe Acute Respiratory Syndrome Coronavirus 2 Infection.

Although interim results from several large, placebo-controlled, phase 3 trials demonstrated high vaccine efficacy (VE) against symptomatic coronavirus disease 2019 (COVID-19), it is unknown how effective the vaccines are in preventing people from becoming asymptomatically infected and potentially spreading the virus unwittingly. It is more difficult to evaluate VE against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection than against symptomatic COVID-19 because infection is not observed directly but rather is known to occur between 2 antibody or reverse-transcription polymerase chain reaction (RT-PCR) tests. Additional challenges arise as community transmission changes over time and as participants are vaccinated on different dates because of staggered enrollment of participants or crossover of placebo recipients to the vaccine arm before the end of the study. Here, we provide valid and efficient statistical methods for estimating potentially waning VE against SARS-CoV-2 infection with blood or nasal samples under time-varying community transmission, staggered enrollment, and blinded or unblinded crossover. We demonstrate the usefulness of the proposed methods through numerical studies that mimic the BNT162b2 phase 3 trial and the Prevent COVID U study. In addition, we assess how crossover and the frequency of diagnostic tests affect the precision of VE estimates.

Adipose Tissue Gene Expression Associations Reveal Hundreds of Candidate Genes for Cardiometabolic Traits.

Genome-wide association studies (GWASs) have identified thousands of genetic loci associated with cardiometabolic traits including type 2 diabetes (T2D), lipid levels, body fat distribution, and adiposity, although most causal genes remain unknown. We used subcutaneous adipose tissue RNA-seq data from 434 Finnish men from the METSIM study to identify 9,687 primary and 2,785 secondary cis-expression quantitative trait loci (eQTL; <1 Mb from TSS, FDR < 1%). Compared to primary eQTL signals, secondary eQTL signals were located further from transcription start sites, had smaller effect sizes, and were less enriched in adipose tissue regulatory elements compared to primary signals. Among 2,843 cardiometabolic GWAS signals, 262 colocalized by LD and conditional analysis with 318 transcripts as primary and conditionally distinct secondary cis-eQTLs, including some across ancestries. Of cardiometabolic traits examined for adipose tissue eQTL colocalizations, waist-hip ratio (WHR) and circulating lipid traits had the highest percentage of colocalized eQTLs (15% and 14%, respectively). Among alleles associated with increased cardiometabolic GWAS risk, approximately half (53%) were associated with decreased gene expression level. Mediation analyses of colocalized genes and cardiometabolic traits within the 434 individuals provided further evidence that gene expression influences variant-trait associations. These results identify hundreds of candidate genes that may act in adipose tissue to influence cardiometabolic traits.

Consistency and overfitting of multi-omics methods on experimental data.

Knowledge on the relationship between different biological modalities (RNA, chromatin, etc.) can help further our understanding of the processes through which biological components interact. The ready availability of multi-omics datasets has led to the development of numerous methods for identifying sources of common variation across biological modalities. However, evaluation of the performance of these methods, in terms of consistency, has been difficult because most methods are unsupervised. We present a comparison of sparse multiple canonical correlation analysis (Sparse mCCA), angle-based joint and individual variation explained (AJIVE) and multi-omics factor analysis (MOFA) using a cross-validation approach to assess overfitting and consistency. Both large and small-sample datasets were used to evaluate performance, and a permuted null dataset was used to identify overfitting through the application of our framework and approach. In the large-sample setting, we found that all methods demonstrated consistency and lack of overfitting; however, in the small-sample size setting, AJIVE provided the most stable results. We provide an R package so that our framework and approach can be applied to evaluate other methods and datasets.

A new phenotype of syndromic retinitis pigmentosa with myopathy is caused by mutations in retinol dehydrogenase 11.

Retinol dehydrogenase 11 (RDH11) is an 11-cis-retinol dehydrogenase that has a well-characterized, albeit auxiliary role in the retinoid cycle. Diseases caused by mutations in the RDH11 gene are very rare, and only one affected family with eye and intelligence involvement has been reported. In the present study, we describe the clinical and genetic findings in a Chinese patient with retinitis pigmentosa (RP), juvenile cataracts, intellectual disability, and myopathy. Trio-based whole-exome sequencing and whole genomic copy number variation detection were performed in this family, and compound heterozygous mutations were identified in RDH11 of the patient: c.938T>C (p.Leu313Pro) derived from the father and c.75-3C>A derived from the mother. Variant c.75-3C>A was confirmed to be a splice-site mutation by cDNA sequencing. It caused exon 2 skipping, resulting in a frameshift mutation and premature translation termination (p.Lys26Serfs*38). Moreover, we found mislocalization of RDH11 protein in muscle cells of the patient by using immunofluorescence staining. This is the first case reported in the Chinese population harboring mutations in RDH11 and revealing a new phenotype of syndromic RP with myopathy.

Association of Primary and Booster Vaccination and Prior Infection With SARS-CoV-2 Infection and Severe COVID-19 Outcomes.

Importance: Data about the association of COVID-19 vaccination and prior SARS-CoV-2 infection with risk of SARS-CoV-2 infection and severe COVID-19 outcomes may guide prevention strategies. Objective: To estimate the time-varying association of primary and booster COVID-19 vaccination and prior SARS-CoV-2 infection with subsequent SARS-CoV-2 infection, hospitalization, and death. Design, Setting, and Participants: Cohort study of 10.6 million residents in North Carolina from March 2, 2020, through June 3, 2022. Exposures: COVID-19 primary vaccine series and boosters and prior SARS-CoV-2 infection. Main Outcomes and Measures: Rate ratio (RR) of SARS-CoV-2 infection and hazard ratio (HR) of COVID-19-related hospitalization and death. Results: The median age among the 10.6 million participants was 39 years; 51.3% were female, 71.5% were White, and 9.9% were Hispanic. As of June 3, 2022, 67% of participants had been vaccinated. There were 2 771 364 SARS-CoV-2 infections, with a hospitalization rate of 6.3% and mortality rate of 1.4%. The adjusted RR of the primary vaccine series compared with being unvaccinated against infection became 0.53 (95% CI, 0.52-0.53) for BNT162b2, 0.52 (95% CI, 0.51-0.53) for mRNA-1273, and 0.51 (95% CI, 0.50-0.53) for Ad26.COV2.S 10 months after the first dose, but the adjusted HR for hospitalization remained at 0.29 (95% CI, 0.24-0.35) for BNT162b2, 0.27 (95% CI, 0.23-0.32) for mRNA-1273, and 0.35 (95% CI, 0.29-0.42) for Ad26.COV2.S and the adjusted HR of death remained at 0.23 (95% CI, 0.17-0.29) for BNT162b2, 0.15 (95% CI, 0.11-0.20) for mRNA-1273, and 0.24 (95% CI, 0.19-0.31) for Ad26.COV2.S. For the BNT162b2 primary series, boosting in December 2021 with BNT162b2 had the adjusted RR relative to primary series of 0.39 (95% CI, 0.38-0.40) and boosting with mRNA-1273 had the adjusted RR of 0.32 (95% CI, 0.30-0.34) against infection after 1 month and boosting with BNT162b2 had the adjusted RR of 0.84 (95% CI, 0.82-0.86) and boosting with mRNA-1273 had the adjusted RR of 0.60 (95% CI, 0.57-0.62) after 3 months. Among all participants, the adjusted RR of Omicron infection compared with no prior infection was estimated at 0.23 (95% CI, 0.22-0.24) against infection, and the adjusted HRs were 0.10 (95% CI, 0.07-0.14) against hospitalization and 0.11 (95% CI, 0.08-0.15) against death after 4 months. Conclusions and Relevance: Receipt of primary COVID-19 vaccine series compared with being unvaccinated, receipt of boosters compared with primary vaccination, and prior infection compared with no prior infection were all significantly associated with lower risk of SARS-CoV-2 infection (including Omicron) and resulting hospitalization and death. The associated protection waned over time, especially against infection.

AtCPS V326M significantly affect the biosynthesis of gibberellins.

Gibberellins are a class of typical phytohormones, which regulate plant growth and development. The contents of gibberellins dramatically affect the morphology and biomass of plant. The encoding protein of copalyl diphosphate synthase gene (CPS) catalyzes the first-step in the biosynthetic pathway of gibberellins. The mutation in this gene may significantly affect the contents of gibberellins in plants. In this study, we found an EMS-triggered mutant, ga1-168, showing short roots, short hypocotyls, late flowering and dwarf. Map-based cloning revealed that the causal gene of ga1-168 was AtCPS-168, an allele of AtCPS gene. The encoding protein of AtCPS-168 was AtCPS V326M which was resulted from a single-point mutation (guanine to adenine at nucleotide 2768) of AtCPS gene. Protein domain analysis showed that V326 was located in the Terpene_synth domain. The allelism test demonstrated that AtCPS-168 was an allele of AtCPS gene. The transgenic complementation of ga1-168 indicated that AtCPS V326M led to the dwarf and bushy phenotype of ga1-168. The endogenous gibberellins contents analysis suggested that the gibberellins contents of ga1-168 were much lower than that of wild-type. The exogenous GA3 application assay uncovered that application of GA3 can complement the dwarf and bushy phenotype of ga1-168 caused by low endogenous gibberellins contents. Therefore, this study suggested that it is an elegant way to create the ideal plant architecture and height by site-directed mutating the gibberellin biosynthetic genes.