Biomedical subjects

Zheng Zhang

Publications and source records attributed to Zheng Zhang.

6 recordsLinked to original sources

PubMed2026

Pan-genome-based resequencing of 2,320 accessions reveals structural variations and accelerates breeding advances in cultivated peanut.

The cultivated peanut is a crucial global legume crop that is essential for food security and nutrition, particularly in developing regions. However, its limited genetic variation hampers breeding progress and yield improvement. Here we constructed a graph-based pan-genome for peanut, incorporating 14 genomes that represent all 6 peanut varieties. Using this pan-genome, we genotyped 2,320 accessions, covering 88.03% of ICRISAT and 59.21% of USDA core germplasm, enriching valuable resources for genomic studies and breeding. We cataloged genomic structural variations and investigated the role of homoeologous exchanges in population divergence. Through our pan-genome approach, we overcame the challenges of genotyping posed by homoeologous exchanges and identified key genes associated with flowering and dwarfism in peanut. By integrating superior haplotypes and germplasm resources guided by the pan-genome, we further developed high-yield dwarf lines. This work provides essential genomic resources to accelerate functional gene discovery and modern peanut breeding.

Journal Article↗

PubMed2026

Association between the interleukin 17F rs763780 polymorphism and immune thrombocytopenia risk: A systematic review and meta-analysis.

The literature on the Interleukin 17F (IL-17F) rs763780 polymorphism and its association with immune thrombocytopenia (ITP) risk remains inconsistent and controversial. These uncertainties underscore the urgent need for a meta-analysis to objectively synthesize the heterogeneous findings, mitigate bias, and improve statistical power. This study strictly adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement and guidelines. A systematic literature search for original studies was conducted across the CNKI, Wanfang Data, Cochrane Library, Web of Science, and PubMed databases, covering publications up to April 5, 2026. Odds ratios and corresponding 95% confidence intervals were calculated to assess the association. STATA 14.2 software was used to synthesize the pooled estimates. A total of eight case-control studies consisting of 805 ITP cases and 841 controls were included. The summarized statistics suggested the detrimental effect of the A allele in the homozygote and recessive models. In the sensitivity analysis, the results that were initially non-significant in the allele, heterozygote, and dominant models became significant after excluding a single dataset, which was also identified as the source of heterogeneity. Region-stratified analyses revealed statistical significance in the Chinese/Japanese and Egyptian subgroups under specific analytic contrasts. When stratified according to age, the children subgroup showed significant associations in a subset of genetic models, while the adult counterpart demonstrated significance across all models. In conclusion, the pooled estimates of the homozygote and recessive models suggested that the rs763780 polymorphism is associated with ITP risk, but this finding requires further validation through large-scale studies.

Humans↗

PubMed2026

Online Social Anxiety in the Digital Age: Transitions, Predictors, and Mental Health Associations in Emerging Adulthood.

BACKGROUND: Online social anxiety (OSA), a multidimensional form of social evaluative anxiety in online social contexts, disproportionately affects emerging adults who constitute the largest active group of media users and face heightened psychological sensitivity due to growing pressures and immature sociocognitive regulation during the transition to adulthood. However, its heterogeneity, transitions, and longitudinal associations with mental health outcomes remain underexplored. METHODS: This study utilized data from two waves of a three-wave longitudinal survey, with 849 Chinese participants (Meanage = 21.6 years; 50.4 percent female) assessed at 4-month intervals. Individuals were classified using latent profile analysis and the stability and changes of profiles were assessed via latent transition analysis (LTA). Multinomial logistic regressions were conducted separately at baseline and follow-up to identify correlates of profile membership. Predictors of profile transitions were examined using manual three-step LTA models, and associations between latent transition patterns and follow-up mental health outcomes were examined using BCH-LTA distal outcome analyses controlling for the corresponding baseline symptom level. RESULTS: Four profiles of OSA were identified: low, privacy-sensitive, moderate-high, and high OSA. Extreme profiles (low/high OSA) showed high stability (80.4 percent and 79.1 percent), while privacy-sensitive OSA exhibited the lowest stability (55.1 percent). Profile memberships were influenced by social-cognitive biases and digital interaction, particularly fear of negative evaluation and online interpersonal trust, whereas profile transitions were mainly associated with anxiety. Transitions toward less severe OSA profiles were generally associated with better subsequent mental health, whereas transitions toward more severe profiles corresponded to poorer outcomes, particularly for offline social anxiety. CONCLUSION: OSA was heterogeneous in its manifestation, severity and transitions. Personalized and early interventions targeting profile-specific vulnerabilities are critical to prevent the worsening of OSA and mitigate its psychological burden.

Humans↗

PubMed2026

Deficiency of Setd2 in mesenchymal stem cells facilitates the progression of myelodysplastic syndrome to leukemia.

While previous studies have indicated that H3K36me3, which is mediated by Setd2, may regulate the cell fate of mesenchymal stem cells (MSCs) both in vitro and in vivo, the specific role of MSCs in the onset and progression of MDS remains unclear. Thus, the histone methyltransferase Setd2 is implicated in MDS-associated leukemia. This study utilized NUP98-HOXD13 (NHD13) mice with targeted deletion of Setd2 in MSCs. Here, we found that Setd2-deficient mice undergo faster leukemia transformation than control mice do, as evidenced by the abnormal differentiation of hematopoietic stem progenitor cells in the bone marrow, abnormal hematopoiesis, and increased number of blast cells. Compared with that of control mice, the morphology of NHD13 mouse MSCs with Setd2 deficiency was irregular, and the support function of hematopoietic cells was compromised. This study demonstrated that targeted deletion of Setd2 in MSCs facilitates the advancement of MDS. Furthermore, we identified increased expression of coagulation factor XII as a key leukemic transformation mediator in Setd2-deficient MSCs. Moreover, we found that SETD2 expression is significantly lower in high-risk MDS patients than in low-risk MDS patients, further suggesting that the targeted deletion of Setd2 in MSCs is associated with MDS progression. Collectively, our results suggest that Setd2 in MSCs suppresses MDS progression to leukemia through coagulation factor XII-mediated suppression of the stem cell support capacity of MSCs. Overall, this study sheds light on the pathogenesis of MDS and provides a therapeutic strategy for regulating the microenvironment in patients with MDS who cannot be cured by haematopoietic stem cell transplantation.

Animals↗

PubMed2025

Integration of single cell multiomics data by deep transfer hypergraph neural network.

Multi-omics characterization of individual cells offers remarkable potential for analyzing the dynamics and relationships of gene regulatory states across millions of cells. How to integrate multimodal data is an open problem, existing integration methods struggle with accuracy and modality-specific biological variation retention. In this paper, we present scHyper (scalable, interpretable machine learning for single cell integration), a low-code and data-efficient deep transfer model designed for integrating paired and unpaired single-cell multimodal data. We benchmark scHyper against datasets from different multimodal data. ScHyper learns a low-dimensional representation and aligns the covariance matrices of the measured modalities, achieving high accuracy even with large scale atlas-level datasets with low memory and computational time across different cell lines, shedding light on regulatory relationships between different types of omics. Altogether, we show that scHyper is a versatile and robust tool for cell-type label transfer and integration from multimodal single-cell datasets.

Single-Cell Analysis↗

PubMed2024

Mapping Start Codons of Small Open Reading Frames by N-Terminomics Approach.

sORF-encoded peptides (SEPs) refer to proteins encoded by small open reading frames (sORFs) with a length of less than 100 amino acids, which play an important role in various life activities. Analysis of known SEPs showed that using non-canonical initiation codons of SEPs was more common. However, the current analysis of SEP sequences mainly relies on bioinformatics prediction, and most of them use AUG as the start site, which may not be completely correct for SEPs. Chemical labeling was used to systematically analyze the N-terminal sequences of SEPs to accurately define the start sites of SEPs. By comparison, we found that dimethylation and guanidinylation are more efficient than acetylation. The ACN precipitation and heating precipitation performed better in SEP enrichment. As an N-terminal peptide enrichment material, Hexadhexaldehyde was superior to CNBr-activated agarose and NHS-activated agarose. Combining these methods, we identified 128 SEPs with 131 N-terminal sequences. Among them, two-thirds are novel N-terminal sequences, and most of them start from the 11-31st amino acids of the original sequence. Partial novel N-termini were produced by proteolysis or signal peptide removal. Some SEPs' transcription start sites were corrected to be non-AUG start codons. One novel start codon was validated using GFP-tag vectors. These results demonstrated that the chemical labeling approaches would be beneficial for identifying the start codons of sORFs and the real N-terminal of their encoded peptides, which helps better understand the characterization of SEPs.

Open Reading Frames↗