DiabetesOmic: A comprehensive multi-omics diabetes database

被引:0
作者
Cai, Fu-hong [1 ,2 ,3 ,4 ,5 ,6 ]
Qian, Feng-cui [1 ,2 ,5 ,6 ]
Li, Bing-long [5 ]
Li, Li-dong [4 ]
Liao, Bi-hong [7 ]
Yu, Zheng-min [4 ]
Fang, Qiao-li [4 ]
Li, Yan-yu [1 ,2 ,6 ]
Dong, Fu-juan [4 ]
Zhou, Li-wei [6 ]
Li, Chao [8 ]
Wang, Qiu-yu [1 ,2 ,5 ,6 ]
Liu, Jiang-hua [3 ,4 ]
机构
[1] Univ South China, Affiliated Hosp 1, Hengyang 421001, Hunan, Peoples R China
[2] Univ South China, Hengyang Med Sch, Hunan Prov Key Lab Multiom & Artificial Intelligen, Hengyang 421001, Hunan, Peoples R China
[3] Univ South China, Affiliated Hosp 1, Hengyang Med Sch, Dept Endocrinol & Metab, Hengyang 421001, Hunan, Peoples R China
[4] Univ South China, Sch Comp, Hengyang 421001, Hunan, Peoples R China
[5] Univ South China, Sch Basic Med Sci, Hengyang Med Sch, Dept Biochem & Mol Biol, Hengyang 421001, Hunan, Peoples R China
[6] Univ South China, Affiliated Hosp 1, Hengyang Med Sch, Cardiovasc Lab Big Data & Imaging Artificial Intel, Hengyang 421001, Hunan, Peoples R China
[7] Univ South China, Affiliated Hosp 1, Hengyang Med Sch, Dept Radiol, Hengyang 421001, Hunan, Peoples R China
[8] Univ South China, Affiliated Hosp 1, Hengyang Med Sch, Dept Anesthesiol, Hengyang 421001, Hunan, Peoples R China
基金
中国国家自然科学基金;
关键词
Diabetes; Single cell; Multi-omics; DATA SETS; ARCHIVE;
D O I
10.1016/j.csbj.2025.05.008
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Diabetes is a complex disease that involves multiple molecular mechanisms. Recent advances in multi-omics sequencing techniques have significantly enhanced the understanding of the pathogenesis of diabetes. To address the critical need for molecular resources in diabetes research, we present DiabetesOmic (https://bio. liclab.net/diabetesOmicdb/), a comprehensive multi-omics database designed to collect and analyze transcriptional regulatory information across five high-throughput sequencing modalities, including ChIP-seq, RNA-seq, ATAC-seq, scATAC-seq, and scRNA-seq. Currently, DiabetesOmic contains 487 samples, encompassing type 1 and type 2 diabetes spanning multiple tissues. These data underwent stringent quality assessment to ensure highquality molecular profiles. Notably, we manually curated clinical complication annotations including diabetic nephropathy, retinopathy, and atherosclerosis to enhance translational relevance. For each type of sequencing data, we implemented specific analytical pipelines to generate multi-dimensional transcriptional regulatory information, including regulatory network identification, differential gene expression analysis, chromatin accessibility analysis, and transcription factor enrichment analysis. This comprehensive analysis enables the identification of disease-associated regulatory elements, epigenetic modifications, and cell type-specific molecular signatures, providing valuable insights into the molecular mechanisms of diabetes and its complications. This resource represents a significant advancement in diabetes research, facilitating deeper investigations into the disease's pathology and progression.
引用
收藏
页码:2147 / 2154
页数:8
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