PGAT-ABPp: Harnessing Protein Language Models and Graph Attention Networks for Antibacterial Peptide Identification with Remarkable Accuracy.

MOTIVATION: The emergence of drug-resistant pathogens represents a formidable challenge to global health. Using computational methods to identify the antibacterial peptides (ABPs), an alternative antimicrobial agent, has demonstrated advantages in further drug design studies. Most of the current approaches, however, rely on handcrafted features and underutilize structural information, which may affect prediction performance. RESULTS: To present an ultra-accurate model for ABP identification, we propose a novel deep learning approach, PGAT-ABPp. PGAT-ABPp leverages structures predicted by AlphaFold2 and a pretrained protein language model, ProtT5-XL-U50 (ProtT5), to construct graphs. Then the graph attention network (GAT) is adopted to learn global discriminative features from the graphs. PGAT-ABPp outperforms the other fourteen state-of-the-art models in terms of Accuracy, F1-score and Matthews correlation coefficient on the independent test dataset. The results show that ProtT5 has significant advantages in the identification of ABPs and the introduction of spatial information further improves the prediction performance of the model. The interpretability analysis of key residues in known active ABPs further underscores the superiority of PGAT-ABPp. AVAILABILITY: The datasets and source codes for the PGAT-ABPp model are available at https://github.com/moonseter/PGAT-ABPp/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genetic adaptation of skin pigmentation in highland Tibetans.

Strong ultraviolet (UV) radiation at high altitude imposes a serious selective pressure, which may induce skin pigmentation adaptation of indigenous populations. We conducted skin pigmentation phenotyping and genome-wide analysis of Tibetans in order to understand the underlying mechanism of adaptation to UV radiation. We observe that Tibetans have darker baseline skin color compared with lowland Han Chinese, as well as an improved tanning ability, suggesting a two-level adaptation to boost their melanin production. A genome-wide search for the responsible genes identifies GNPAT showing strong signals of positive selection in Tibetans. An enhancer mutation (rs75356281) located in GNPAT intron 2 is enriched in Tibetans (58%) but rare in other world populations (0 to 18%). The adaptive allele of rs75356281 is associated with darker skin in Tibetans and, under UVB treatment, it displays higher enhancer activities compared with the wild-type allele in in vitro luciferase assays. Transcriptome analyses of gene-edited cells clearly show that with UVB treatment, the adaptive variant of GNPAT promotes melanin synthesis, likely through the interactions of CAT and ACAA1 in peroxisomes with other pigmentation genes, and they act synergistically, leading to an improved tanning ability in Tibetans for UV protection.

Unveiling cell subpopulations in T1D mouse islets using single-cell RNA sequencing.

Type 1 diabetes (T1D) is an autoimmune disease characterized by the destruction of beta cells by immune cells. The interactions among cells within the islets may be closely linked to the pathogenesis of T1D. In this study, we used single-cell RNA sequencing (scRNA-Seq) to analyze the cellular heterogeneity within the islets of a T1D mouse model. We established a T1D mouse model induced by streptozotocin and identified cell subpopulations using scRNA-Seq technology. Our results revealed 11 major cell types in the pancreatic islets of T1D mice, with heterogeneity observed in the alpha and beta cell subgroups, which may play a crucial role in the progression of T1D. Flow cytometry further confirmed a mature alpha and beta cell reduction in T1D mice. Overall, our scRNA-Seq analysis provided insights into the cellular heterogeneity of T1D islet tissue and highlighted the potential importance of alpha and beta cells in developing T1D.NEW & NOTEWORTHY In this study, we created a comprehensive single-cell atlas of pancreatic islets in a T1D mouse model using scRNA-Seq and identified 11 major cell types in the islets, highlighting the role of alpha and beta cells in T1D. This study revealed a significant reduction in the maturity alpha and beta cells in T1D mice through flow cytometry. It also demonstrated the heterogeneity of alpha and beta cells, potentially crucial for T1D progression. Overall, our scRNA-Seq analysis provided new insights for understanding and treating T1D by studying cell subtype changes and functions.

Stop codon variant in EFEMP1 is associated with primary open-angle glaucoma due to impaired regulation of aqueous humor outflow.

It is known that the actin cytoskeleton and its associated cellular interactions in the trabecular meshwork (TM) and juxtacanalicular tissues mainly contribute to the formation of resistance to aqueous outflow of the eye. Fibulin-3, encoded by EFEMP1 gene, has a role in extracellular matrix (ECM) modulation, and interacts with enzymatic ECM regulators, but the effects of fibulin-3 on TM cells has not been explored. Here, we report a stop codon variant (c.T1480C, p.X494Q) of EFEMP1 that co-segregates with primary open angle glaucoma (POAG) in a Chinese pedigree. In the human TM cells, overexpression of wild-type fibulin-3 reduced intracellular actin stress fibers formation and the extracellular fibronectin levels by inhibiting Rho/ROCK signaling. TGFß1 up-regulated fibulin-3 protein levels in human TM cells by activating Rho/ROCK signaling. In rat eyes, overexpression of wild-type fibulin-3 decreased the intraocular pressure and the fibronectin expression of TM, however, overexpression of mutant fibulin-3 (c.T1480C, p.X494Q) showed opposite effects in cells and rat eyes. Taken together, the EFEMP1 variant may impair the regulatory capacity of fibulin-3 which has a role for modulating the cell contractile activity and ECM synthesis in TM cells, and in turn may maintain normal resistance of aqueous humor outflow. This study contributes to the understanding of the important role of fibulin-3 in TM pathophysiology and provides a new possible POAG therapeutic approach.

Explainable Graph Neural Networks with Data Augmentation for Predicting pKa of C-H Acids.

The pKa of C-H acids is an important parameter in the fields of organic synthesis, drug discovery, and materials science. However, the prediction of pKa is still a great challenge due to the limit of experimental data and the lack of chemical insight. Here, a new model for predicting the pKa values of C-H acids is proposed on the basis of graph neural networks (GNNs) and data augmentation. A message passing unit (MPU) was used to extract the topological and target-related information from the molecular graph data, and a readout layer was utilized to retrieve the information on the ionization site C atom. The retrieved information then was adopted to predict pKa by a fully connected network. Furthermore, to increase the diversity of the training data, a knowledge-infused data augmentation technique was established by replacing the H atoms in a molecule with substituents exhibiting different electronic effects. The MPU was pretrained with the augmented data. The efficacy of data augmentation was confirmed by visualizing the distribution of compounds with different substituents and by classifying compounds. The explainability of the model was studied by examining the change of pKa values when a specific atom was masked. This explainability was used to identify the key substituents for pKa. The model was evaluated on two data sets from the iBonD database. Dataset1 includes the experimental pKa values of C-H acids measured in DMSO, while dataset2 comprises the pKa values measured in water. The results show that the knowledge-infused data augmentation technique greatly improves the predictive accuracy of the model, especially when the number of samples is small.

Interpretable Perturbator for Variable Selection in near-Infrared Spectral Analysis.

A perturbator was developed for variable selection in near-infrared (NIR) spectral analysis based on the perturbation strategy in deep learning for developing interpretation methods. A deep learning predictor was first constructed to predict the targets from the spectra in the training set. Then, taking the output of the predictor as a reference, the perturbator was trained to derive the perturbation-positive (P+) and perturbation-negative (P-) features from the spectra. Therefore, the weight (σ) of the perturbator layer can be a criterion to evaluate the importance of the variables in the spectra. Ranking the spectral variables by the criterion, the number of the variables used in the quantitative model can be obtained through cross-validation. Three NIR data sets were used to evaluate the proposed method. The root mean squared error was found to be comparable with or superior to that obtained by the commonly used methods. Moreover, the selected spectral variables are interpretable in identifying the key spectral features related to the prediction target. Therefore, the proposed method provides not only an effective tool for optimizing quantitative model, but also an efficient way for explaining spectra of multicomponent samples.

AttenGpKa: A Universal Predictor of Solvation Acidity Using Graph Neural Network and Molecular Topology.

Rapid and accurate calculation of acid dissociation constant (pKa) is crucial for designing chemical synthesis routes, optimizing catalysts, and predicting chemical behavior. Despite recent progress in machine learning, predicting solvation acidity, especially in nonaqueous solvents, remains challenging due to limited experimental data. This challenge arises from treating experimental values in different solvents as distinct data domains and modeling them separately. In this work, we treat both the solutes and solvents equally from a perspective of molecular topology and propose a highly universal framework called AttenGpKa for predicting solvation acidity. AttenGpKa is trained using 26,522 experimental pKa values from 60 pure and mixed solvents in the iBonD database. As a result, our model can simultaneously predict the pKa values of a compound in various solvents, including pure water, pure nonaqueous, and mixed solvents. AttenGpKa achieves universality by using graph neural networks and attention mechanisms to learn complex effects within solute and solvent molecules. Furthermore, encodings of both solute and solvent molecules are adaptively fused to simulate the influence of the solvent on acid dissociation. AttenGpKa demonstrates robust generalization in extensive validations. The interpretability studies further indicate that our model has effectively learnt electronic and solvent effects. A free-to-use software is provided to facilitate the use of AttenGpKa for pKa prediction.

A Sensitive Probe of Meso-Cyanophenyl Substituted BODIPY Derivative as Fluorescent Chemosensor for the Detection of Multiple Heavy Metal Ions.

A fluorescent turn-on chemosensor (BA) was constructed by attaching bis(pyridin-2-ylmethyl)-amine (DPA) unit to the BODIPY scaffold. It can give a prominent green/yellow fluorescent response selectivity with each of Zn2+/Hg2+/Cd2+/Ca2+/Mn2+/Pb2+/Al3+. The 1:1 stoichiometry of BA and metal ions was drawn from the analysis of Job's plot. The limit detection of BA in recognition of Zn2+/Hg2+/Cd2+/Ca2+/Mn2+/Pb2+/Al3+ is ranged in 50.8-146.6 nM. There exists a linear relationship between the fluorescence intensity and concentration of metal ions (Zn2+: 4-15 µM). The mechanism of fluorescence signal "turn-on" is based on the photo induced transfer (PET) in the excited state of BA. The coordinated metal ions significantly weakened the electron-donating ability nitrogen atom in DPA, thus recovering the emission character of BODIPY. The substituted group at the phenyl ring in meso-position of BODIPY scaffold determines the recognizable list of metal ions.

Identification and Validation of Basement Membrane Related LncRNA Signatures as a Novel Prognostic Model for Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a significant cancer with limited treatments and a poor prognosis, with the basement membrane (BM) playing a crucial role in its initiation and growth. This study utilized data from The Cancer Genome Atlas and the Gene Expression Omnibus (GEO) databases to identify basement membrane-related genes differentially expressed in HCC. Through gene co-expression analysis, BM-associated long non-coding RNAs (lncRNAs) were discovered. LncRNAs related to HCC survival were selected via univariate analysis, and a prognostic model was constructed using LASSO regression and multivariate analysis. This model effectively classified HCC patients into high and low-risk groups, uncovering significant differences in prognosis, immune response, mutation, and drug sensitivity. Six BM-related lncRNAs (GSEC, MIR4435-2HG, AC092614.1, AC127521.1, LINC02580, and AC008050.1) were validated in normal and HCC cell lines, and the key role of AC092614.1 in regulating proliferation, migration, and invasion of HCC cells in vitro was explored. This research emphasizes the prognostic and therapeutic relevance of BM-related lncRNAs in HCC, highlighting AC092614.1's role in disease progression and as a potential target for targeted therapy.

Detoxification of tetracycline and synthetic dyes by a newly characterized Lentinula edodes laccase, and safety assessment using proteomic analysis.

Fungal laccase has strong ability in detoxification of many environmental contaminants. A putative laccase gene, LeLac12, from Lentinula edodes was screened by secretome approach. LeLac12 was heterogeneously expressed and purified to characterize its enzymatic properties to evaluate its potential use in bioremediation. This study showed that the extracellular fungal laccase from L. edodes could effectively degrade tetracycline (TET) and the synthetic dye Acid Green 25 (AG). The growth inhibition of Escherichia coli and Bacillus subtilis by TET revealed that the antimicrobial activity was significantly reduced after treatment with the laccase-HBT system. 16 transformation products of TET were identified by UPLC-MS-TOF during the laccase-HBT oxidation process. Gas chromatography-mass spectrometry (GC-MS) analysis revealed that LeLac12 could completely mineralize ring-cleavage products. LeLac12 completely catalyzed 50 mg/L TET within 4 h by adding AG (200 mg/L), while the degradation of AG was above 96% even in the co-contamination system. Proteomic analysis revealed that central carbon metabolism, energy metabolism, and DNA replication/repair were affected by TET treatment and the latter system could contribute to the formation of multidrug-resistant strains. The results demonstrate that LeLac12 is an efficient and environmentally method for the removal of antibiotics and dyes in the complex polluted wastewater.

cis-Regulatory variation affecting gene expression contributes to the improvement of maize kernel size.

cis-Regulatory variations contribute to trait evolution and adaptation during crop domestication and improvement. As the most important harvested organ in maize (Zea mays L.), kernel size has undergone intensive selection for size. However, the associations between maize kernel size and cis-regulatory variations remain unclear. We chose two independent association populations to dissect the genetic architecture of maize kernel size together with transcriptomic and genotypic data. The resulting phenotypes reflected a strong influence of population structure on kernel size. Compared with genome-wide association studies (GWASs), which accounted for population structure and relatedness, GWAS based on a naïve or simple linear model revealed additional associated single-nucleotide polymorphisms significantly involved in the conserved pathways controlling seed size in plants. Regulation analyses through expression quantitative trait locus mapping revealed that cis-regulatory variations likely control kernel size by fine-tuning the expression of proximal genes, among which ZmKL1 (GRMZM2G098305) was transgenically validated. We also proved that the pyramiding of the favorable cis-regulatory variations has contributed to the improvement of maize kernel size. Collectively, our results demonstrate that cis-regulatory variations, together with their regulatory genes, provide excellent targets for future maize improvement.

Genomic insight into changes of root architecture under drought stress in maize.

Drought stress is a central environmental factor that severely limits maize production worldwide. Root architecture plays an important role in drought tolerance and can be targeted in breeding programmes. Here, we conducted phenotyping of root architecture under different water treatments for 373 maize inbred lines, representative germplasm from both China and the United States in different breeding eras. We found that seminal root length in response to drought stress experienced convergent increase during breeding in both countries. Using a genome-wide association study, we identified a total of 221 associated loci underlying 13 root traits under well-watered and water-stressed conditions. These loci harboured many reported root- and abiotic stress-related genes. Furthermore, a total of 75 strong candidate genes were prioritised by integrating candidate genes associated with seminal root length and differentially expressed genes in seminal root. One of high-confidence candidate genes, ZmCIPK3 was functionally characterised and probably plays a role in enhancing drought tolerance through regulating seminal root growth. This study provides valuable information for genetic improvement of root architecture and drought tolerance in maize.

Overexpression of ZmEXPA5 reduces anthesis-silking interval and increases grain yield under drought and well-watered conditions in maize.

Drought is one of the major abiotic stresses affecting the maize production worldwide. As a cross-pollination crop, maize is sensitive to water stress at flowering stage. Drought at this stage leads to asynchronous development of male and female flower organ and increased interval between anthesis and silking, which finally causes failure of pollination and grain yield loss. In the present study, the expansin gene ZmEXPA5 was cloned and its function in drought tolerance was characterized. An indel variant in promoter of ZmEXPA5 is significantly associated with natural variation in drought-induced anthesis-silking interval. The drought susceptible haplotypes showed lower expression level of ZmEXPA5 than tolerant haplotypes and lost the cis-regulatory activity of ZmDOF29. Increasing ZmEXPA5 expression in transgenic maize decreases anthesis-silking interval and improves grain yield under both drought and well-watered environments. In addition, the expression pattern of ZmEXPA5 was analyzed. These findings provide insights into the genetic basis of drought tolerance and a promising gene for drought improvement in maize breeding. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-023-01432-x.

Tetanus toxin and botulinum neurotoxin-derived fusion molecules are effective bivalent vaccines.

Tetanus toxin (TeNT) and botulinum neurotoxins (BoNTs) are neuroprotein toxins, with the latter being the most toxic known protein. They are structurally similar and contain three functional domains: an N-terminal catalytic domain (light chain), an internal heavy-chain translocation domain (HN domain), and a C-terminal heavy chain receptor binding domain (Hc domain or RBD). In this study, fusion functional domain molecules consisting of the TeNT RBD (THc) and the BoNT/A RBD (AHc) (i.e., THc-Linker-AHc and AHc-Linker-THc) were designed, prepared, and identified. The interaction of each Hc domain and the ganglioside receptor (GT1b) or the receptor synaptic vesicle glycoprotein 2 (SV2) was explored in vitro. Their immune response characteristics and protective efficacy were investigated in animal models. The recombinant THc-linker-AHc and AHc-linker-THc proteins with the binding activity had the correct size and structure, thus representing novel subunit vaccines. THc-linker-AHc and AHc-linker-THc induced high levels of specific neutralizing antibodies, and showed strong immune protective efficacy against both toxins. The high antibody titers against the two novel fusion domain molecules and against individual THc and AHc suggested that the THc and AHc domains, as antigens in the fusion functional domain molecules, do not interact with each other and retain their full key epitopes responsible for inducing neutralizing antibodies. Thus, the recombinant THc-linker-AHc and AHc-linker-THc molecules are strong and effective bivalent biotoxin vaccines, protecting against two biotoxins simultaneously. Our experimental design will be valuable to develop recombinant double-RBD fusion molecules as potent bivalent subunit vaccines against bio-toxins. KEY POINTS: • Double-RBD fusion molecules from two toxins had the correct structure and activity. • THc-linker-AHc and AHc-linker-THc efficiently protected against both biotoxins. • Such bivalent biotoxin vaccines based on the RBD are a valuable experimental design.

Biology activity and characterization of the functional L-HN fragment derivative of botulinum neurotoxin serotype E.

OBJECTIVES: The mature botulinum neurotoxin (BoNT) is a long peptide chain consisting of a light chain (L) and a heavy chain (H) linked by a disulfide bond, where the heavy chain is divided into a translocation domain and an acceptor binding domain (Hc). In this study, we further explored the biology activity and characteristics of recombinant L-HN fragment (EL-HN) composed of the L and HN domains of BoNT/E in vivo and in vitro. METHODS: Neurotoxicity of L-HN fragments from botulinum neurotoxins was assessed in mice. Cleavage of dichain EL-HN in vitro and in neuro-2a cells was assessed and compared with that of single chain EL-HN. Interaction of HN domain and the receptor synaptic vesicle glycoprotein 2C (SV2C) was explored in vitro and in neuro-2a cells only expressing SV2C. RESULTS: We found that the 50% mouse lethal dose of the nicked dichain EL-HN fragment (EL-HN-DC) was 0.5 µg and its neurotoxicity was the highest among the L-HN's of the four serotypes of BoNT (A/B/E/F). The cleavage efficiency of EL-HN-DC toward synaptosome associated protein 25 (SNAP25) in vitro was 3-fold higher than that of the single chain at the cellular level, and showed 200-fold higher animal toxicity. The EL-HN-DC fragment might enter neuro-2a cells via binding to SV2C to efficiently cleave SNAP25. CONCLUSIONS: The EL-HN fragment showed good biological activities in vivo and in vitro, and could be used as a drug screening model and to further explore the molecular mechanism of its transmembrane transport.

Vitamin D supplementation induces CatG-mediated CD4+ T cell inactivation and restores pancreatic ß-cell function in mice with type 1 diabetes.

Type 1 diabetes (T1D) is a chronic autoimmune disease accompanied by the immune-mediated destruction of pancreatic ß-cells. In this study, we aimed to explore the regulatory effects of vitamin D (VD) supplementation on pancreatic ß-cell function by altering the expression of bioinformatically identified cathepsin G (CatG) in T1D mice. A T1D mouse model was established in nonobese diabetic (NOD) mice, and their islets were isolated and purified. Pancreatic mononuclear cells (MNCs) were collected, from which CD4+ T cells were isolated. The levels of interleukin (IL)-2, IL-10, tumor necrosis factor-α (TNF-α), and interferon-γ (IFN-γ) in the supernatant of mouse pancreatic tissue homogenate were assessed using ELISA. Immunohistochemistry and terminal deoxynucleotidyl transferase-mediated dUTP-biotin nick-end labelin (TUNEL) staining were conducted to evaluate the effects of VD supplementation on pancreatic tissues of T1D mice. The pancreatic ß-cell line MIN6 was used for in vitro substantiation of findings in vivo. VD supplementation reduced glucose levels and improved glucose tolerance in T1D mice. Furthermore, VD supplementation improved pancreatic ß-cell function and suppressed immunological and inflammatory reactions in the T1D mice. We documented overexpression of CatG in diabetes tissue samples, and then showed that VD supplementation normalized the islet immune microenvironment through downregulating CatG expression in T1D mice. Experiments in vitro subsequently demonstrated that VD supplementation impeded CD4+ T activation by downregulating CatG expression and thereby enhanced pancreatic ß-cell function. Results of the present study elucidated that VD supplementation can downregulate the expression of CatG and inhibit CD4+ T cell activation, thereby improving ß-cell function in T1D.NEW & NOTEWORTHY We report that vitamin D (VD) supplementation downregulates CatG expression and inhibits CD4+ T cell activation, thereby improving ß-cell function in type 1 diabetes (T1D). This study deepens our understanding of the pathogenesis of T1D and clarifies molecular events underlying the alleviatory effect of VD for immunotherapy against T1D.

Deletion of the Impg2 gene causes the degeneration of rod and cone cells in mice.

Variants in interphotoreceptor matrix proteoglycans (IMPG2) have been reported in retinitis pigmentosa (RP) and vitelliform macular dystrophy (VMD) patients. However, the underlying molecular mechanisms remain elusive due to a lack of suitable disease models. We developed two independent Impg2 knockout (KO) mouse models using the CRISPR/Cas9 technique to assess the in vivo functions of Impg2 in the retina. Impg2 ablation in mice recapitulated the RP phenotypes of patients, including an attenuated electroretinogram (ERG) response and the progressive degeneration of photoreceptors. The histopathological examination of Impg2-KO mice revealed irregularly arranged rod cells and mislocalized rhodopsin protein in the inner segment at 6 months of age. In addition to the pathological changes in rod cells, cone cells were also affected in KO retinas. KO retinas exhibited progressive cone cell death and impaired cone cell elongation. Further immunoblotting analysis revealed increased levels of endoplasmic reticulum (ER) stress-related proteins, including C/EBP homologous protein (CHOP), immunoglobulin heavy-chain-binding protein (BIP) and protein disulfide isomerase (PDI), in Impg2-KO mouse retinas. Increased gliosis and apoptotic cell death were also observed in the KO retinas. As autophagy is closely associated with ER stress, we then checked whether autophagy was disturbed in Impg2-KO mouse retinas. The results showed that autophagy was impaired in KO retinas, as revealed by the increased accumulation of SQSTM1 and other proteins involved in autophagy. Our results demonstrate the essential roles of Impg2 in the retina, and this study provides novel models for mechanistic investigations and development of therapies for RP caused by IMPG2 mutations.

Spectral Encoder to Extract the Features of Near-Infrared Spectra for Multivariate Calibration.

An autoencoder architecture was adopted for near-infrared (NIR) spectral analysis by extracting the common features in the spectra. Three autoencoder-based networks with different purposes were constructed. First, a spectral encoder was established by training the network with a set of spectra as the input. The features of the spectra can be encoded by the nodes in the bottleneck layer, which in turn can be used to build a sparse and robust model. Second, taking the spectra of one instrument as the input and that of another instrument as the reference output, the common features in both spectra can be obtained in the bottleneck layer. Therefore, in the prediction step, the spectral features of the second can be predicted by taking the reverse of the decoder as the encoder. Furthermore, transfer learning was used to build the model for the spectra of more instruments by fine-tuning the trained network. NIR datasets of plant, wheat, and pharmaceutical tablets measured on multiple instruments were used to test the method. The multi-linear regression (MLR) model with the encoded features was found to have a similar or slightly better performance in prediction compared with the partial least-squares (PLS) model.

Genetic Variation in ZmPAT7 Contributes to Tassel Branch Number in Maize.

Tassel branch number (TBN) is one of the important agronomic traits that contribute to the efficiency of seed production and has been selected strongly during the modern maize breeding process. However, the genetic mechanisms of TBN in maize are not entirely clear. In this study, we used a B73 × CML247 recombination inbred lines (RILs) population to detect quantitative trait loci (QTLs) for TBN. A total of four QTLs (qTBN2a, qTBN2b, qTBN4, and qTBN6) and six candidate genes were identified through expression analysis. Further, one of the candidates (GRMZM2G010011, ZmPAT7) encoding an S-acyltransferase was selected to validate its function by CRISPR-Cas9 technology, and its loss-of-function lines showed a significant increase in TBN. A key SNP(-101) variation in the promoter of ZmPAT7 was significantly associated with TBN. A total of 17 distant eQTLs associated with the expression of ZmPAT7 were identified in expression quantitative trait loci (eQTL) analysis, and ZmNAC3 may be a major factor involved in regulating ZmPAT7. These findings of the present study promote our understanding of the genetic basis of tassel architecture and provide new gene resources for maize breeding improvement.

Forkhead domain inhibitory-6 attenuates subconjunctival fibrosis in rabbit model with trabeculectomy.

Antiproliferative therapies are crucially important for improving the success rate of the glaucoma filtration surgeries. In this study, we investigated the potential efficacy of Forkhead Domain Inhibitory-6 (FDI-6) in inhibiting post-trabeculectomy subconjunctival fibrosis. In vitro, the effect of FDI-6 (10 µM) on fibrotic response and its underlying mechanism were investigated in rabbit tenon's fibroblasts (RTFs) treated with or without transforming growth factor-ß1 (TGF-ß1, 20 ng/mL). In vivo, FDI-6 (40 µM) was injected subconjunctivally to a rabbit trabeculectomy model. Intraocular pressure (IOP) changes were monitored within the 14-day period post-surgery. Bleb morphology and subepithelial fibrosis at the operating area were evaluated with slit lamp and confocal microscopic examinations and with histologic examinations. The results showed that, in cell culture studies, FDI-6 suppressed the proliferation, migration, collagen gel contraction and the expression levels of fibronectin (FN) and α-smooth muscle actin (α-SMA) in RTFs with TGF-ß treatment by down-regulating the TGF-ß1/Smad2/3 signaling pathway. In animal studies, the IOPs of the FDI-6-treated group were significantly lower than those of the saline-treated group after trabeculectomy. The FDI-6-treated eyes showed a better bleb appearance with fewer blood vessels compared to the saline-treated eyes. The analysis of confocal microscopy in vivo and histopathology revealed that subconjunctival fibrosis after trabeculectomy was significantly attenuated in the FDI-6-treated group compared to the controls. In conclusion, our studies indicate that FDI-6 exerts an inhibitory effect on subconjunctival fibrosis caused by trabeculectomy, holding potentials as a new antiproliferative agent used in anti-glaucoma filtration surgeries in the future.