Biomedical subjects

Chi Zhang

Publications and source records attributed to Chi Zhang.

5 recordsLinked to original sources

PubMed2026

Transcription factor NtELF3 promotes the polyphenol accumulation by targeting NtFLS-1 and NtCHIL-2 genes in tobacco.

Tobacco (Nicotiana tabacum L.) is an important economic crop, from which polyphenols are crucial for regulating its growth and development as well as shaping its quality. However, few genes associated with polyphenol accumulation have been cloned from tobacco, and the molecular mechanisms underlying this process remain poorly understood. Here, we found that the tobacco transcription factor EARLY FLOWERING 3 (NtELF3), which is highly expressed in tobacco leaves, positively regulates the accumulation of chlorogenic acid, neochlorogenic acid, cryptochlorogenic acid, rutin, scopoletin, and total polyphenols in tobacco middle leaves. The metabolomic and transcriptomic analyses of middle leaves showed that a total of 177 differentially accumulated metabolites and 7409 differentially expressed genes (DEGs) were identified in ntelf3-1 mutant versus wild type, respectively. Further investigation identified that 17 DEGs were involved in phenylpropanoid metabolic and flavonoid metabolic processes. Combined analysis indicated that the phenylpropanoid and flavonoid biosynthesis pathways were also co-enriched in kyoto encyclopedia of genes and genomes enrichment analysis. Molecular biology experiment demonstrated that NtELF3 directly binds to the promoters of NtFLS-1 and NtCHIL-2 that are both associated with phenylpropanoid and flavonoid biosynthesis, and promotes their expression. Taken together, our results not only provide new theoretical support for in-depth understanding of the regulatory mechanisms underlying polyphenol accumulation in tobacco, but also offer excellent genes and germplasm resources for tobacco quality breeding.

NtCHIL↗

PubMed2026

Single-cell transcriptomic atlas of Alzheimer's disease middle temporal gyrus reveals region, cell type, and sex specificity of gene expression with novel genetic risk for MERTK in female.

BackgroundAlzheimer's disease (AD), the most common age-related neurodegenerative disease, is closely associated with both amyloid-β plaque and neuroinflammation. Two thirds of AD patients are female, and they have a higher disease risk; women with AD have more extensive brain histological changes than men along with more severe cognitive symptoms and neurodegeneration.ObjectiveThis study aimed to determine how sex difference induces structural brain changes and molecular cell vulnerabilities in AD, with a focus on identifying sex-specific transcriptional alterations and genetic risk factors.MethodsWe performed single nucleus RNA sequencing on postmortem brains from individuals with AD and age- and sex-matched controls, focusing on the middle temporal gyrus, a cortical brain region strongly affected by the disease, and integrated single nucleus RNA sequencing results with genome-wide association study (GWAS) data using cell type-specific enrichment and generalized gene-set analysis approaches. The analysis pipeline is provided with threshold information.ResultsWe identified a selectively vulnerable subpopulation of layer 2/3 excitatory neurons that were RORB-negative and CDH9-expressing in both males and females. Disease-associated, but sex-independent, reactive astrocyte signatures were also present. In clear contrast, the microglia signatures of AD brains differed between males and females. Integrating single cell transcriptomic data with results from GWAS, we identified MERTK genetic variation as a candidate novel risk factor for AD selectively in females.ConclusionsTaken together, our single cell atlas of middle temporal gyrus revealed a unique cellular-level view of sex-specific transcriptional changes in AD, illuminating GWAS identification of sex-specific AD genes. These data serve as a rich resource for interrogation of the molecular and cellular basis of AD.

Alzheimer's disease↗

PubMed2026

Application efficacy evaluation of the STRSeqTyper122 kit and the FASTASeq 300 second generation sequencer in kinship identification.

Forensic DNA technology is the method of choice for kinship identification. However, existing standard methods still have certain limitations in accurately determining the range of kinship relationships. China's independently developed second generation sequencing technology and equipment are expected to enhance the capability of forensic DNA kinship identification. In this study, we utilized the STRSeqTyper122 second generation sequencing STR typing kit and the FASTASeq 300 second generation sequencer to analyze 107 real kinship samples. The analysis included 63 autosomal STR loci, 42 Y-STR loci, 16 X-STR loci, and one gender-determining locus, Amel. The samples covered various kinship relationships, including 113 parent-child pairs, 48 full-sibling pairs, 76 uncle-nephew pairs, 66 grandparent-grandchild pairs, and 4 half-sibling pairs. Combined with simulated data, the ITO method was applied to calculate the cumulative likelihood ratio (CLR) for different levels of kinship based on the length polymorphism and sequence polymorphism of autosomal STR loci, systematically evaluating the practical application performance of this system in kinship identification. The results showed that, using log10CLR values of 4 and -4 as thresholds, the system achieved 100% efficiency in identifying real parent-child and full-sibling relationships. For second degree kinship identification, the system efficiency based on simulated length polymorphism data was 55.2%, while sequence polymorphism improved it to 75.11%. For real sample data, length polymorphism based efficiency was 54.45%, and sequence polymorphism based efficiency reached 76.71%. The findings indicate that the STRSeqTyper122 kit holds significant value in first degree kinship identification. Sequence polymorphism can improve second degree kinship identification efficiency to over 75%.

Humans↗

PubMed2025

Robust pleiotropy-decomposed polygenic scores identify distinct contributions to elevated coronary artery disease polygenic risk.

BACKGROUND: Polygenic risk score (PRS) have proved to offer robust risk prediction for coronary artery disease (CAD). However, the global CAD PRS summarizes the joint effects of all the markers in the genome, masking potential genetic heterogeneity that may be important for disease interpretation and targeted interventions. METHODS: Using summary-level data, we identified 43 significant CAD-related traits based on genetic correlations, and further classified them into eight pleiotropy clusters based on their biological functions. We then partitioned the genome into 2,353 near-independent regions. Variants in each region were assigned to the trait most genetically similar to CAD, and then were labeled with the corresponding pleiotropy cluster. We grouped variants without labels into a ninth, non-specific cluster. The Pleiotropy Decomposed (PD) PRSs for each of the nine clusters were calculated using variants assigned to each cluster for 407,903 samples of European ancestry from the UK Biobank (UKBB). RESULTS: We decomposed the CAD PRS into nine PD-PRSs and further stratified individuals with high CAD-PRS into nine subgroups. Each PD-PRS accounted for a higher proportion of the global CAD-PRS within its corresponding subgroup than in the remaining subjects with high CAD-PRS (e.g., 25.2% (0.07) vs. 10.06% (0.07) for lipids-PD-PRS). Additionally, these subgroups showed distinct clinical features. For example, in the lipids-related subgroup, lipoprotein(a) and LDL-cholesterol levels were 67.5% and 18.3% higher, respectively, compared to the remaining high-risk individuals. Furthermore, significant interactions were observed between blood pressure and BP PD-PRS, and between current smoking and respiratory system PD-PRS. CONCLUSION: Our findings suggest that PD-PRSs may reveal substantial genetic and phenotypic heterogeneity among individuals with high CAD-PRS. The unique PD-PRS compositions of each individual can highlight the relative importance of different pleiotropic regions.

Humans↗

PubMed2023

Single-cell transcriptomic atlas of Alzheimer's disease middle temporal gyrus reveals region, cell type and sex specificity of gene expression with novel genetic risk for MERTK in female.

Alzheimer's disease, the most common age-related neurodegenerative disease, is closely associated with both amyloid-ß plaque and neuroinflammation. Two thirds of Alzheimer's disease patients are females and they have a higher disease risk. Moreover, women with Alzheimer's disease have more extensive brain histological changes than men along with more severe cognitive symptoms and neurodegeneration. To identify how sex difference induces structural brain changes, we performed unbiased massively parallel single nucleus RNA sequencing on Alzheimer's disease and control brains focusing on the middle temporal gyrus, a brain region strongly affected by the disease but not previously studied with these methods. We identified a subpopulation of selectively vulnerable layer 2/3 excitatory neurons that that were RORB-negative and CDH9-expressing. This vulnerability differs from that reported for other brain regions, but there was no detectable difference between male and female patterns in middle temporal gyrus samples. Disease-associated, but sex-independent, reactive astrocyte signatures were also present. In clear contrast, the microglia signatures of diseased brains differed between males and females. Combining single cell transcriptomic data with results from genome-wide association studies (GWAS), we identified MERTK genetic variation as a risk factor for Alzheimer's disease selectively in females. Taken together, our single cell dataset revealed a unique cellular-level view of sex-specific transcriptional changes in Alzheimer's disease, illuminating GWAS identification of sex-specific Alzheimer's risk genes. These data serve as a rich resource for interrogation of the molecular and cellular basis of Alzheimer's disease.

Journal Article↗