Biomedical subjects

Lei Wang

Publications and source records attributed to Lei Wang.

30 records · Page 2Linked to original sources

PubMed2026

Proteomics-Based Identification of the Pyroptosis-Related Biomarker PCSK9 and Its Association With the Pathogenesis of Rheumatoid Arthritis.

Rheumatoid arthritis (RA) is a common autoimmune disease, and early diagnosis is critical for effective treatment. This study aims to identify potential biomarkers related to pyroptosis through serum proteomics analysis, offering new insights for the early diagnosis of RA. We enrolled 100 participants, including 50 patients with RA and 50 healthy controls. Serum samples were collected and analyzed using high-resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS) for proteomics profiling. Differential protein expression analysis and functional annotation revealed significant upregulation of pyroptosis-related proteins in the serum of patients with RA. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, along with protein-protein interaction (PPI) network analysis, showed that these proteins are involved in inflammation and immune pathways, particularly the activation of the NOD-like receptor protein 3 (NLRP3) inflammasome. Enzyme-linked immunosorbent assay (ELISA) validation confirmed a significant increase in PCSK9 levels in patients with RA, suggesting that PCSK9 may play a key role in the pathogenesis of RA. This study provides new directions for biomarker research in RA, particularly regarding the potential involvement of the pyroptosis pathway, with significant clinical application prospects.

Humans↗

PubMed2026

Hi-Enhancer: a two-stage framework for prediction and localization of enhancers based on Blending-KAN and Stacking-Auto models.

MOTIVATION: Gene expression plays a crucial role in cell function, and enhancers can regulate gene expression precisely. Therefore, accurate prediction of enhancers is particularly critical. However, existing prediction methods have low accuracy or rely on fixed multiple epigenetic signals, which may not always be available. RESULTS: We propose a two-stage framework that accurately predicts enhancers by flexibly combining multiple epigenetic signals. In the first stage, we designed a Blending-KAN model, which integrates the results of various base classifiers and employs Kolmogorov-Arnold Networks (KAN) as a meta-classifier to predict enhancers based on flexible combinations of multiple epigenetic signals. In the second stage, we developed a Stacking-Auto model, which extracted sequence features using DNABERT-2 and located the enhancers based on the Stacking strategy and AutoGluon framework. The accuracy of the Blending-KAN model reached 99.69 ± 0.11% when five epigenetic signals were used. In cross-cell line prediction, the accuracy was more significant than or equal to 93.72%. With Gaussian noise, it still maintains an accuracy of 98.74 ± 0.03%. In the second stage, the accuracy of the Stacking-Auto model is 80.50%, which is better than the existing 17 methods. The results show that our models can be flexibly used to predict and locate enhancers utilizing a combination of multiple epigenetic signals. AVAILABILITY AND IMPLEMENTATION: The source code is available at https://github.com/emanlee/Hi-Enhancer and https://doi.org/10.6084/m9.figshare.29262158.v1.

Enhancer Elements, Genetic↗

PubMed2026

Wheat breeding during and after the "green revolution" contributed to the reduced use of elite nitrogen metabolism alleles linked to nitrogen use efficiency.

The wheat "Green Revolution (GR)" that occurred from the 1960s to the 1970s significantly enhanced the harvest index and resistance to lodging, thereby increasing grain production, but at the cost of reduced nitrogen (N) use efficiency (NUE) in wheat. The NUE of wheat is mainly regulated by N metabolism genes (NMGs). However, the evolutionary process of NMGs during GR and post-GR wheat breeding, as well as which of them affect NUE, remains unclear. Here, we collected 265 wheat varieties that were released before, during, and after the GR and investigated grain yield per plant and 24 other traits under different N supply conditions. Next, we identified the genotypes of these wheat varieties using a 100 K targeted sequencing array. Then, we systematically analyzed the signatures in the genomes of GR and post-GR released varieties compared with pre-GR released varieties through population divergence (Fst) and nucleotide diversity (π) ratio analyses, and found that 41 NMGs were located within the selective sweep regions during the GR and post-GR breeding. We further identified 118 quantitative trait loci (QTLs) involved in regulating NUE through genome-wide association studies (GWAS). Four NMGs-NRT1 AND PEPTIDE TRANSPORTER FAMILY 2.7-D (TaNPF2.7-D), TaNPF2.3-D, TaNPF2.7 L-D, and QUASIMODO2-B (TaQUA2-B)-were located within overlapping regions of selective sweeps and NUE-related QTLs. Notably, the elite haplotypes of these genes for NUE are less utilized in GR and post-GR released cultivars. Furthermore, we found that TaNPF2.7-D positively regulates nitrate exudation as well as the wheat development. Collectively, our findings uncover an important reason for the reduction in NUE in modern cultivars and provide a valuable resource for improving wheat NUE.

Triticum↗

PubMed2025

DeepWheat: predicting the effects of genomic variants on gene expression and regulatory activities across tissues and varieties in wheat using deep learning.

Spatiotemporal gene expression shapes key agronomic traits, yet tissue-specific prediction remains challenging in complex crops. We present DeepWheat, a broadly applicable deep learning framework comprising DeepEXP and DeepEPI, for accurate, tissue-specific gene expression prediction. DeepEXP integrates sequence and epigenomic features to predict gene expression (PCC 0.82-0.88), while DeepEPI predicts epigenomic maps from DNA sequence to support model transfer across varieties. Validations in five wheat cultivars confirm robustness and accuracy. DeepWheat also identifies regulatory variants with strong expression effects, enabling targeted cis-regulatory elements editing and offering a powerful tool for crop functional genomics and breeding.

Triticum↗

PubMed2025

Chromosome-level genome assembly and annotation of Petunia hybrida.

Petunia hybrida is the world's most popular garden plant and is regarded as a supermodel for studying the biology associated with the Asterid clade, the largest of the two major groups of flowering plants. Unlike other Solanaceae, petunia has a base chromosome number of seven, not 12. This along with recombination suppression has previously hindered efforts to assemble its genome to chromosome level. Here we achieve a chromosome-level assembly for P. hybrida using a combination of short-read and long-read sequencing, optical mapping (Bionano) and Hi-C technologies. The resulting assembly spans 1253.6 Mb with a BUSCO score of 99.8%. A total of 35,089 genes were predicted and of those 29,655 were functionally annotated. Syntenic regions between petunia, tomato and pepper were identified, highlighting rearrangements that have occurred since their divergence indicating that the 12 chromosomes of Solanaceae did not originate from whole genome duplication of an ancestral species with seven chromosomes like petunia. This assembly will enhance trait mapping efficiency and serve as a valuable resource for functional genomic studies.

Petunia↗

PubMed2025

Chromosome-level genome assembly of Elaeocarpus petiolatus (Elaeocarpaceae).

Elaeocarpus petiolatus is an ecologically and economically important species in tropical and subtropical forests. Despite its significance, the lack of genomic resources has hindered research on the genetic diversity and adaptive traits of E. petiolatus. To address this gap, we present a comprehensive chromosome-level genome assembly of E. petiolatus generated using advanced PacBio high-fidelity (HiFi) long-read sequencing and Hi-C technology. The assembly spans 322.45 Mb, with a scaffold N50 of 20.58 Mb, indicating that 37.11% of the genome is composed of repetitive elements. We identified 25,295 protein-coding genes, of which 96.74% were functionally annotated. This high-quality genome provides a critical resource for understanding the genetic mechanisms underlying environmental adaptability and biosynthesis of bioactive compounds in E. petiolatus, thereby supporting conservation efforts and sustainable forest management. The assembled genome and associated sequencing data are publicly available, facilitating further evolutionary and functional studies on the Elaeocarpaceae family.

Chromosomes, Plant↗

PubMed2025

Development and Validation an Integrated Deep Learning Model to Assist Eosinophilic Chronic Rhinosinusitis Diagnosis: A Multicenter Study.

BACKGROUND: The assessment of eosinophilic chronic rhinosinusitis (eCRS) lacks accurate non-invasive preoperative prediction methods, relying primarily on invasive histopathological sections. This study aims to use computed tomography (CT) images and clinical parameters to develop an integrated deep learning model for the preoperative identification of eCRS and further explore the biological basis of its predictions. METHODS: A total of 1098 patients with sinus CT images were included from two hospitals and were divided into training, internal, and external test sets. The region of interest of sinus lesions was manually outlined by an experienced radiologist. We utilized three deep learning models (3D-ResNet, 3D-Xception, and HR-Net) to extract features from CT images and calculate deep learning scores. The clinical signature and deep learning score were inputted into a support vector machine for classification. The receiver operating characteristic curve, sensitivity, specificity, and accuracy were used to evaluate the integrated deep learning model. Additionally, proteomic analysis was performed on 34 patients to explore the biological basis of the model's predictions. RESULTS: The area under the curve of the integrated deep learning model to predict eCRS was 0.851 (95% confidence interval [CI]: 0.77-0.93) and 0.821 (95% CI: 0.78-0.86) in the internal and external test sets. Proteomic analysis revealed that in patients predicted to be eCRS, 594 genes were dysregulated, and some of them were associated with pathways and biological processes such as chemokine signaling pathway. CONCLUSIONS: The proposed integrated deep learning model could effectively predict eCRS patients. This study provided a non-invasive way of identifying eCRS to facilitate personalized therapy, which will pave the way toward precision medicine for CRS.

Humans↗

PubMed2025

The Tartary Buckwheat FtMYB46-FtNRAMP3 Module Enhances Plant Lead and Cadmium Tolerance.

The presence of toxic heavy metals lead (Pb) and cadmium (Cd) in polluted soil damage crop production and consequently harms human and livestock health. Tartary buckwheat (Fagopyrum tataricum) is a potential model plant for heavy metal phytoremediation because of its valuable characteristics of high heavy metal tolerance and abundant biomass production. Here, we report that the Tartary buckwheat FtMYB46-FtNRAMP3 module enhances plant Pb and Cd tolerance. RNA sequencing analysis showed that Pb treatment specifically induced expression of FtNRAMP3, a member of the NRAMP (Natural Resistance-Associated Macrophage Protein) transporter gene family. Further cytological and biochemical analysis revealed that FtNRAMP3 was localised to the plasma membrane and significantly contributed to increased tolerance to Pb and Cd in yeast cells. Consistently, transgenic overexpression of FtNRAMP3 in Arabidopsis significantly increased plant tolerance to Pb and Cd applications, reducing Pb concentration but increasing Cd concentration in the overexpression transgenic plants. Subsequent yeast one-hybrid and electrophoretic mobility shift assays showed that the transcription factor FtMYB46 directly binds to the FtNRAMP3 promoter. Further, FtMYB46 promoted FtNRAMP3 expression and increased plant Pb and Cd tolerance. Overall, this study demonstrates the important role of the FtMYB46-FtNRAMP3 module and its potential value in the phytoremediation of Pb and Cd stress.

Cadmium↗

PubMed2025

Nitric oxide delays floral transition in Arabidopsis by inhibiting histone deacetylases HDA5 and HDA6.

Nitric oxide (NO), a reactive small molecule, plays a critical role in various developmental and physiological processes in living organisms. Previous studies by our group revealed that NO delays flowering in Arabidopsis by increasing transcript levels of the flowering repressor FLOWERING LOCUS C (FLC). In this study, we further investigated the molecular mechanism by which NO regulates FLC expression. Genetic experiments demonstrated that NO-induced delayed flowering specifically depends on elevated FLC transcript levels. Chromatin Immunoprecipitation assays revealed that NO significantly enhances histone H3 acetylation at the FLC locus. Biochemical analyses further showed that NO reduces total histone deacetylase activity through S-nitrosylation of histone deacetylases HDA5 and HDA6. Additionally, we identified and evaluated potential S-nitrosylation sites on HDA5 and HDA6, revealing their effects on deacetylase activity and floral regulation. Collectively, our findings uncover a novel mechanism by which NO mediates epigenetic modification to modulate flowering in Arabidopsis. This study sheds light on the functional network linking NO signaling, epigenetic modification, and flowering.

Arabidopsis↗

PubMed2023

Photoaffinity labeling coupled with proteomics identify PDI-ADAM17 module is targeted by (-)-vinigrol to induce TNFR1 shedding and ameliorate rheumatoid arthritis in mice.

Various biological agents have been developed to target tumor necrosis factor alpha (TNF-α) and its receptor TNFR1 for the rheumatoid arthritis (RA) treatment, whereas small molecules modulating such cytokine receptors are rarely reported in comparison to the biologicals. Here, by revealing the mechanism of action of vinigrol, a diterpenoid natural product, we show that inhibition of the protein disulfide isomerase (PDI, PDIA1) by small molecules activates A disintegrin and metalloprotease 17 (ADAM17) and then leads to the TNFR1 shedding on mouse and human cell membranes. This small-molecule-induced receptor shedding not only effectively blocks the inflammatory response caused by TNF-α in cells, but also reduces the arthritic score and joint damage in the collagen-induced arthritis mouse model. Our study indicates that targeting the PDI-ADAM17 signaling module to regulate the shedding of cytokine receptors by the chemical approach constitutes a promising strategy for alleviating RA.

Mice↗

PubMed2010

Human dopamine β-hydroxylase promoter variant alters transcription in chromaffin cells, enzyme secretion, and blood pressure.

BACKGROUND: Dopamine β-hydroxylase (DBH) plays an indispensable role in catecholamine synthesis by converting dopamine into norepinephrine. Here, we characterized a DBH promoter polymorphism (C-2073T; rs1989787; minor allele frequency ~16%) that influences not only gene transcription but also enzyme secretion and blood pressure (BP) in vivo. METHODS: Plasma DBH activity was measured spectrophotometrically. DBH genetic effects on BP were tested in subjects with the most extreme BP values in a large primary care population. Functional effects of promoter variants were studied by site-directed mutagenesis in DBH promoter haplotype/luciferase reporter plasmids transfected into chromaffin cells. Sequence motifs were predicted from position weight matrices, and endogenous transcription factor binding was probed by Chromatin ImmunoPrecipitation (ChIP). RESULTS: The T-allele of common promoter variant C-2073T was contained in a promoter haplotype that associated with plasma DBH activity, a trait also predicted by that variant itself. Promoter haplotypes including C-2073T predicted BP in the population, and the effect was also referable to C-2073T itself. Computationally, C-2073 disrupted a predicted match for transcription factor c-FOS. Site-directed mutagenesis at C-2073T altered not only basal promoter activity, but also transactivation by c-FOS, as well as the chromaffin cell secretory stimuli nicotine or pituitary adenylate cyclase-activating polypeptide (PACAP). Endogenous c-FOS bound to the motif in chromatin. CONCLUSIONS: These results suggest that DBH promoter variant C-2073T is functional in vivo: this promoter variant seems to initiate a cascade of transcriptional and biochemical changes including augmented DBH secretion, eventuating in elevation of basal BP, and hence cardiovascular risk. The observations suggest new strategies for probing the pathophysiology, risk, and treatment of hypertension.

Animals↗

PubMed2009

Peptide YY (PYY) gene polymorphisms in the 3'-untranslated and proximal promoter regions regulate cellular gene expression and PYY secretion and metabolic syndrome traits in vivo.

RATIONALE: Obesity is a heritable trait that contributes to hypertension and subsequent cardiorenal disease risk; thus, the investigation of genetic variation that predisposes individuals to obesity is an important goal. Circulating peptide YY (PYY) is known for its appetite and energy expenditure-regulating properties; linkage and association studies have suggested that PYY genetic variation contributes to susceptibility for obesity, rendering PYY an attractive candidate for study of disease risk. DESIGN: To explore whether common genetic variation at the human PYY locus influences plasma PYY or metabolic traits, we systematically resequenced the gene for polymorphism discovery and then genotyped common single-nucleotide polymorphisms across the locus in an extensively phenotyped twin sample to determine associations. Finally, we experimentally validated the marker-on-trait associations using PYY 3'-untranslated region (UTR)/reporter and promoter/reporter analyses in neuroendocrine cells. RESULTS: Four common genetic variants were discovered across the locus, and three were typed in phenotyped twins. Plasma PYY was highly heritable (P < 0.0001), and genetic pleiotropy was noted between plasma PYY and body mass index (BMI) (P = 0.03). A PYY haplotype extending from the proximal promoter (A-23G, rs2070592) to the 3'-UTR (C+1134A, rs162431) predicted not only plasma PYY (P = 0.009) but also other metabolic syndrome traits. Functional studies with transfected luciferase reporters confirmed regulatory roles in altering gene expression for both 3'-UTR C+1134A (P < 0.001) and promoter A-23G (P = 0.0016). CONCLUSIONS: Functional genetic variation at the PYY locus influences multiple heritable metabolic syndrome traits, likely conferring susceptibility to obesity and subsequent cardiorenal disease.

3' Untranslated Regions↗