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Automatic identification of informative regions with epigenomic changes associated to hematopoiesis
Nucleic Acids Research ( IF 14.9 ) Pub Date : 2017-07-17 , DOI: 10.1093/nar/gkx618
Enrique Carrillo-de-Santa-Pau 1 , David Juan 2 , Vera Pancaldi 3 , Felipe Were 1 , Ignacio Martin-Subero 4 , Daniel Rico 5 , Alfonso Valencia 3, 6 ,
Affiliation  

Hematopoiesis is one of the best characterized biological systems but the connection between chromatin changes and lineage differentiation is not yet well understood. We have developed a bioinformatic workflow to generate a chromatin space that allows to classify 42 human healthy blood epigenomes from the BLUEPRINT, NIH ROADMAP and ENCODE consortia by their cell type. This approach let us to distinguish different cells types based on their epigenomic profiles, thus recapitulating important aspects of human hematopoiesis. The analysis of the orthogonal dimension of the chromatin space identify 32,662 chromatin determinant regions (CDRs), genomic regions with different epigenetic characteristics between the cell types. Functional analysis revealed that these regions are linked with cell identities. The inclusion of leukemia epigenomes in the healthy hematological chromatin sample space gives us insights on the healthy cell types that are more epigenetically similar to the disease samples. Further analysis of tumoral epigenetic alterations in hematopoietic CDRs points to sets of genes that are tightly regulated in leukemic transformations and commonly mutated in other tumors. Our method provides an analytical approach to study the relationship between epigenomic changes and cell lineage differentiation. Method availability: https://github.com/david-juan/ChromDet.

中文翻译:

自动识别与造血相关的表观基因组变化的信息区域

造血是最有特色的生物学系统之一,但染色质变化和谱系分化之间的联系尚未得到很好的理解。我们已经开发了一种生物信息学的工作流程来生成染色质空间,从而可以按细胞类型对BLUEPRINT,NIH ROADMAP和ENCODE财团的42个人类健康血液表观基因组进行分类。这种方法使我们能够根据它们的表观基因组特征来区分不同的细胞类型,从而概括了人类造血的重要方面。染色质空间的正交维度分析确定了32,662个染色质决定簇区域(CDR),这是在细胞类型之间具有不同表观遗传特性的基因组区域。功能分析表明,这些区域与细胞身份有关。健康血液学染色质样本空间中包含白血病表观基因组,使我们对与疾病样本在表观遗传学上更相似的健康细胞类型有了更深入的了解。对造血CDR中肿瘤表观遗传学改变的进一步分析指出,在白血病转化中受到严格调控且通常在其他肿瘤中发生突变的基因集。我们的方法提供了一种分析方法来研究表观基因组变化与细胞谱系分化之间的关系。方法可用性:对造血CDR中肿瘤表观遗传学改变的进一步分析指出,在白血病转化中受到严格调控且通常在其他肿瘤中发生突变的基因集。我们的方法提供了一种分析方法来研究表观基因组变化与细胞谱系分化之间的关系。方法可用性:对造血CDR中肿瘤表观遗传学改变的进一步分析指出,在白血病转化中受到严格调控且通常在其他肿瘤中发生突变的基因集。我们的方法提供了一种分析方法来研究表观基因组变化与细胞谱系分化之间的关系。方法可用性:https://github.com/david-juan/ChromDet。
更新日期:2017-09-21
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