Capturing cell type-specific chromatin compartment patterns by applying topic modeling to single-cell Hi-C data.
Capturing cell type-specific chromatin compartment patterns by applying topic modeling to single-cell Hi-C data.
复制标题
DOI：
10.1371/journal.pcbi.1008173
复制
发表时间：
2020-09
影响因子：
4.3
通讯作者：
Noble WS
中科院分区：
文献类型：
--
作者：
Kim HJ;Yardımcı GG;Bonora G;Ramani V;Liu J;Qiu R;Lee C;Hesson J;Ware CB;Shendure J;Duan Z;Noble WS
单细胞Hi-C(Schi-C)询问单个细胞中全基因组染色质的相互作用，使我们能够深入了解3D基因组组织。然而，Schi-C数据的极端稀疏性对分析构成了重大障碍，限制了我们梳理出隐藏的生物信息的能力。在这项工作中，我们通过将主题建模应用于Schi-C数据来解决这个问题。主题建模非常适合于在离散数据集合中发现潜在主题。在我们的分析中，我们从五个人类细胞系(GM12878、H1Esc、HFF、IMR90和HAP1)中生成了九个不同的单细胞组合索引Hi-C(SCI-Hi-C)文库，包含超过19,000个细胞。我们证明，主题建模能够以“染色质主题”的形式成功地从SCI-Hi-C数据中捕获细胞类型的差异。在这些主题中，我们进一步展示了与基因座对相关的特定隔室结构的丰富。高等生物的基因组以一种动态的方式错综复杂地折叠和组织，这对许多生物过程具有重要的意义。每条染色体在细胞周期中都经历了其三维构象的剧烈变化，而染色体在细胞核内的定位在控制特定基因的激活方面起着重要作用。最近，使用一种称为单细胞Hi-C(Schi-C)的高通量测序技术来研究单个细胞基因组的3D构象已经成为可能。然而，这些检测的数据稀少且有噪声，这使得对Schi-C数据的分析和解释具有挑战性。在这项工作中，我们从五个人类细胞系中生成了一个包含19,000多个细胞的Schi-C数据集，并应用了一种称为主题建模的自然语言处理方法来发现细胞类型特定的“染色质”主题。我们表明，尽管数据稀少，但这些主题可以用于区分处于细胞周期不同阶段的细胞和来自不同组织的细胞，这是基于它们基因组的3D构象。我们进一步表明，单细胞的3D构象与细胞类型特异性基因的表达和细胞周期相关的构象模式有关。
Single-cell Hi-C (scHi-C) interrogates genome-wide chromatin interaction in individual cells, allowing us to gain insights into 3D genome organization. However, the extremely sparse nature of scHi-C data poses a significant barrier to analysis, limiting our ability to tease out hidden biological information. In this work, we approach this problem by applying topic modeling to scHi-C data. Topic modeling is well-suited for discovering latent topics in a collection of discrete data. For our analysis, we generate nine different single-cell combinatorial indexed Hi-C (sci-Hi-C) libraries from five human cell lines (GM12878, H1Esc, HFF, IMR90, and HAP1), consisting over 19,000 cells. We demonstrate that topic modeling is able to successfully capture cell type differences from sci-Hi-C data in the form of “chromatin topics.” We further show enrichment of particular compartment structures associated with locus pairs in these topics. The genomes of higher organisms are intricately folded and organized in a dynamic manner that has strong implications for many biological processes. Each chromosome undergoes dramatic changes to their three dimensional conformation during the cell cycle, whereas the positioning of chromosomes within the nucleus plays an important role in controlling the activation of specific genes. Recently, it has become possible to investigate the 3D conformations of the genomes of individual cells using a high throughput sequencing assay called single cell Hi-C (scHi-C). However, data from these assays are sparse and noisy, making analysis and interpretation of scHi-C data challenging. In this work, we generated a scHi-C dataset of over 19,000 cells from five human cell lines and applied a natural language processing method called topic modeling to discover cell type-specific “chromatin” topics. We show that these topics can be used to distinguish between cells at different stages of the cell cycle and cells from different tissues based on the 3D conformation of their genomes, despite the sparsity of the data. We further show that the 3D conformations of single cells are linked to the expression of cell type-specific genes and to cell cycle-associated conformational patterns.
登录
查看更多内容
DOI：
10.1093/bioinformatics/btq033
发表时间：
2010-03-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Quinlan AR;Hall IM
通讯作者：
Hall IM
影响因子：
12.3
作者：
Fortin JP;Hansen KD
通讯作者：
Hansen KD
影响因子：
48
作者：
Langmead, Ben;Salzberg, Steven L.
通讯作者：
Salzberg, Steven L.
影响因子：
48
作者：
Ramani V;Deng X;Qiu R;Gunderson KL;Steemers FJ;Disteche CM;Noble WS;Duan Z;Shendure J
通讯作者：
Shendure J
DOI：
10.1073/pnas.0307752101
发表时间：
2004-04-06
影响因子：
11.1
作者：
Griffiths, TL;Steyvers, M
通讯作者：
Steyvers, M