Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
Diabetologia. 2024 Dec;67(12):2740-2753. doi: 10.1007/s00125-024-06261-x. Epub 2024 Sep 6.
AIMS/HYPOTHESIS: Genome-wide association studies (GWAS) have identified hundreds of type 2 diabetes loci, with the vast majority of signals located in non-coding regions; as a consequence, it remains largely unclear which 'effector' genes these variants influence. Determining these effector genes has been hampered by the relatively challenging cellular settings in which they are hypothesised to confer their effects.
To implicate such effector genes, we elected to generate and integrate high-resolution promoter-focused Capture-C, assay for transposase-accessible chromatin with sequencing (ATAC-seq) and RNA-seq datasets to characterise chromatin and expression profiles in multiple cell lines relevant to type 2 diabetes for subsequent functional follow-up analyses: EndoC-BH1 (pancreatic beta cell), HepG2 (hepatocyte) and Simpson-Golabi-Behmel syndrome (SGBS; adipocyte).
The subsequent variant-to-gene analysis implicated 810 candidate effector genes at 370 type 2 diabetes risk loci. Using partitioned linkage disequilibrium score regression, we observed enrichment for type 2 diabetes and fasting glucose GWAS loci in promoter-connected putative cis-regulatory elements in EndoC-BH1 cells as well as fasting insulin GWAS loci in SGBS cells. Moreover, as a proof of principle, when we knocked down expression of the SMCO4 gene in EndoC-BH1 cells, we observed a statistically significant increase in insulin secretion.
CONCLUSIONS/INTERPRETATION: These results provide a resource for comparing tissue-specific data in tractable cellular models as opposed to relatively challenging primary cell settings.
Raw and processed next-generation sequencing data for EndoC-BH1, HepG2, SGBS_undiff and SGBS_diff cells are deposited in GEO under the Superseries accession GSE262484. Promoter-focused Capture-C data are deposited under accession GSE262496. Hi-C data are deposited under accession GSE262481. Bulk ATAC-seq data are deposited under accession GSE262479. Bulk RNA-seq data are deposited under accession GSE262480.
目的/假设：全基因组关联研究（GWAS）已经确定了数百个 2 型糖尿病的位点，其中绝大多数信号位于非编码区域；因此，这些变异体影响哪些“效应”基因仍然很大程度上不清楚。由于假设这些效应基因在相对具有挑战性的细胞环境中发挥作用，因此确定这些效应基因一直受到阻碍。
为了暗示这些效应基因，我们选择生成和整合高分辨率启动子聚焦的捕获-C、转座酶可及染色质的测定（ATAC-seq）和 RNA-seq 数据集，以描述与 2 型糖尿病相关的多种细胞系中的染色质和表达谱，随后进行功能后续分析：EndoC-BH1（胰腺β细胞）、HepG2（肝细胞）和 Simpson-Golabi-Behmel 综合征（SGBS；脂肪细胞）。
随后的变异体到基因分析在 370 个 2 型糖尿病风险位点中暗示了 810 个候选效应基因。使用分区连锁不平衡评分回归，我们观察到在 EndoC-BH1 细胞中与启动子相连的假定顺式调节元件中富集了 2 型糖尿病和空腹血糖 GWAS 位点，以及在 SGBS 细胞中富集了空腹胰岛素 GWAS 位点。此外，作为一个原理证明，当我们在 EndoC-BH1 细胞中敲低 SMCO4 基因的表达时，我们观察到胰岛素分泌有统计学意义的增加。
结论/解释：这些结果为在可处理的细胞模型中比较组织特异性数据提供了资源，而不是相对具有挑战性的原代细胞环境。
EndoC-BH1、HepG2、SGBS_undiff 和 SGBS_diff 细胞的下一代测序原始和处理数据已在 GEO 中以超级系列访问号 GSE262484 进行存储。启动子聚焦的捕获-C 数据以访问号 GSE262496 进行存储。Hi-C 数据以访问号 GSE262481 进行存储。批量 ATAC-seq 数据以访问号 GSE262479 进行存储。批量 RNA-seq 数据以访问号 GSE262480 进行存储。
