Super interactive promoters provide insight into cell type-specific regulatory networks in blood lineage cell types.
Super interactive promoters provide insight into cell type-specific regulatory networks in blood lineage cell types.
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超级交互式启动子提供了对血统细胞类型中细胞类型特异性调节网络的见解。
DOI：
10.1371/journal.pgen.1009984
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发表时间：
2022-01
期刊：
影响因子：
4.5
通讯作者：
Li Y
中科院分区：
文献类型：
--
作者：
Wen J;Lagler TM;Sun Q;Yang Y;Chen J;Harigaya Y;Sankaran VG;Hu M;Reiner AP;Raffield LM;Li Y
现有的染色质构象的研究主要集中在与基因启动子相互作用的潜在增强子。相比之下，启动子本身的相互作用，而同样重要的理解转录控制，已在很大程度上未被探索，特别是在细胞类型特异性的方式为血液谱系细胞类型。在这项研究中，我们利用启动子捕获Hi-C数据在血液谱系细胞类型的纲要，以确定和表征细胞类型特异性的超级相互作用的启动子（SIP）。值得注意的是，SIP的启动子相互作用区域（PIR）比非SIP的PIR更可能与相关血细胞性状的细胞类型特异性ATAC-seq峰和GWAS变体重叠。此外，与非SIP的PIR相比，细胞类型特异性SIP的PIR显示相关血细胞性状的富集遗传性，并且更富集与血细胞性状相关的GWAS变体。此外，SIP基因倾向于在相应的细胞类型中以更高的水平表达。重要的是，包含细胞类型特异性SIP和ATAC-seq峰的SIP子网有助于解释GWAS变体。实例包括与巨核细胞SIP基因EPHB 3附近的血小板计数相关的GWAS变体和与天然CD 4 T细胞SIP基因ETS 1附近的淋巴细胞计数相关的变体。有趣的是，约25.7% ~ 39.6%的血细胞性状GWAS变异体位于SIP PIR区域，破坏转录因子结合基序。重要的是，我们的分析显示了使用启动子为中心的染色质空间组织数据的分析，以确定生物学上重要的基因和它们的调控区域的潜力。通过分析pcHi-C数据，我们在五种血细胞类型中对超级相互作用启动子（SIPs）进行了分类。血细胞中的这些SIP和SIP基因不仅对于研究血液学性状而且对于许多复杂的表型都是有价值的。我们提供了关于SIP形成的机制假说。为了被鉴定为SIP，启动子可以由少数超强相互作用或许多显著（不一定都是强）相互作用驱动。重要的是，我们发现后者似乎是常态。这一发现揭示了SIP的形成：为了确保某些关键基因（这里是SIP基因）的表达水平，多个调控区域可能是协调精细转录控制的关键。这些多个调控区提供了一定水平的“冗余”，确保即使在存在破坏一些增强子的遗传变体的情况下，在给定的造血细胞类型中仍然可以维持适当的转录调控。这一发现也对数十万GWAS发现的解释和功能随访具有重要意义。一个SIP基因的多个调控区有助于解释一个基因座上多个独立的GWAS信号。总之，我们相信我们的工作提供了重要的发现，这些发现控制了血液谱系细胞类型中的协调转录控制，并为许多复杂性状的GWAS发现的解释和后续工作提供了有价值的见解和资源。
Existing studies of chromatin conformation have primarily focused on potential enhancers interacting with gene promoters. By contrast, the interactivity of promoters per se, while equally critical to understanding transcriptional control, has been largely unexplored, particularly in a cell type-specific manner for blood lineage cell types. In this study, we leverage promoter capture Hi-C data across a compendium of blood lineage cell types to identify and characterize cell type-specific super-interactive promoters (SIPs). Notably, promoter-interacting regions (PIRs) of SIPs are more likely to overlap with cell type-specific ATAC-seq peaks and GWAS variants for relevant blood cell traits than PIRs of non-SIPs. Moreover, PIRs of cell-type-specific SIPs show enriched heritability of relevant blood cell trait (s), and are more enriched with GWAS variants associated with blood cell traits compared to PIRs of non-SIPs. Further, SIP genes tend to express at a higher level in the corresponding cell type. Importantly, SIP subnetworks incorporating cell-type-specific SIPs and ATAC-seq peaks help interpret GWAS variants. Examples include GWAS variants associated with platelet count near the megakaryocyte SIP gene EPHB3 and variants associated lymphocyte count near the native CD4 T-Cell SIP gene ETS1. Interestingly, around 25.7% ~ 39.6% blood cell traits GWAS variants residing in SIP PIR regions disrupt transcription factor binding motifs. Importantly, our analysis shows the potential of using promoter-centric analyses of chromatin spatial organization data to identify biologically important genes and their regulatory regions. By analyzing pcHi-C data, we catalogue super-interactive promoters (SIPs) in five blood cell types. These SIPs and SIP genes in blood cells will be valuable not only for studying hematological traits but for many complex phenotypes. We provide mechanistic hypotheses regarding the formation of SIPs. To be identified as a SIP, a promoter can be driven by few super strong interactions or many significant (not necessarily all strong) interactions. Importantly, we find that the latter seems to be the norm. This finding sheds light regarding the formation of SIPs: to ensure the expression level of some critical gene (here a SIP gene), multiple regulatory regions are likely key for orchestrating fine transcriptional control. These multiple regulatory regions provide a level of “redundancy”, ensuring that even in the presence of genetic variant (s) that disrupt some enhancer(s), appropriate transcriptional regulation can still be maintained in a given hematopoietic cell type. This finding also has important implications for the interpretation and functional follow-up of hundreds of thousands of GWAS findings. These multiple regulatory regions for one SIP gene help explain multiple independent GWAS signals at one locus. In summary, we believe our work presents important findings governing the orchestrated transcriptional control in blood lineage cell types, and provides valuable insights and resources for the interpretation and follow-up of GWAS findings of many complex traits.
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DOI：
10.1093/bioinformatics/btr064
发表时间：
2011-04-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Grant CE;Bailey TL;Noble WS
通讯作者：
Noble WS
影响因子：
16.6
作者：
Kuwahara, Makoto;Suzuki, Junpei;Tofukuji, Soichi;Yamada, Takeshi;Kanoh, Makoto;Matsumoto, Akira;Maruyama, Saho;Kometani, Kohei;Kurosaki, Tomohiro;Ohara, Osamu;Nakayama, Toshinori;Yamashita, Masakatsu
通讯作者：
Yamashita, Masakatsu
影响因子：
30.8
作者：
Finucane HK;Bulik-Sullivan B;Gusev A;Trynka G;Reshef Y;Loh PR;Anttila V;Xu H;Zang C;Farh K;Ripke S;Day FR;ReproGen Consortium;Schizophrenia Working Group of the Psychiatric Genomics Consortium;RACI Consortium;Purcell S;Stahl E;Lindstrom S;Perry JR;Okada Y;Raychaudhuri S;Daly MJ;Patterson N;Neale BM;Price AL
通讯作者：
Price AL
影响因子：
30.8
作者：
Finucane HK;Reshef YA;Anttila V;Slowikowski K;Gusev A;Byrnes A;Gazal S;Loh PR;Lareau C;Shoresh N;Genovese G;Saunders A;Macosko E;Pollack S;Brainstorm Consortium;Perry JRB;Buenrostro JD;Bernstein BE;Raychaudhuri S;McCarroll S;Neale BM;Price AL
通讯作者：
Price AL
影响因子：
64.5
作者：
Hnisz D;Abraham BJ;Lee TI;Lau A;Saint-André V;Sigova AA;Hoke HA;Young RA
通讯作者：
Young RA