重要的 Hi-C 相关文献

第一篇 Hi-C 文章： Comprehensive Mapping of Long-Range Interactions Reveals Folding Principles of the Human Genome； DOI: 10.1126/science.1181369

TAD 提出： Topological Domains in Mammalian Genomes Identified by Analysis of Chromatin Interactions ；doi: 10.1038/nature11082

高分辨率 Hi-C： A 3D Map of the Human Genome at Kilobase Resolution Reveals Principles of Chromatin Looping https://doi.org/10.1016/j.cell.2014.11.021

单细胞 Single cell： Hi-C reveals cell-to-cell variability in chromosome structure doi: 10.1038/nature12593；3D structures of individual mammalian genomes studied by single-cell Hi-C doi:10.1038/nature21429

综述：老师所讲 Hi-C 相关基础知识主要来自于综述 Organization and function of the 3D genome，doi:10.1038/nrg.2016.112

Chromatin interaction in different resolutions

不同分辨率 Hi-C 可以看到的内容不同

5KB 可以看到各种 loop

10KB 可以看到 TAD

50kb 可以看到 TAD 之间的关联

在整个染色体的水平可以看到染色质的位置分布

什么造成了所谓的 TAD

cohesin complex

Cohesin is a protein complex that regulates the separation of sister chromatids during cell division, either mitosis or meiosis.

Cohesins hold sister chromatids together after DNA replication until anaphase when removal of cohesin leads to separation of sister chromatids.

CTCF proteins

转录阻抑物 CTCF

CTCF 与靶顺序因子的结合可阻断增强子和启动子的相互作用，从而将增强子的活性限制在一定的功能区域

除了阻断增强子外，CTCF 还可作为染色质屏障阻止异染色质的传播

Predicting enhancer-promoter loops 如何预测 EPL

两种类似的算法

TargetFinder(Whalen et al. Nat Gen 2016)— an algorithm that uses many functional genomic datasets, including DNase-seq, histone marks, transcription factor (TF) ChIP-seq, gene expression, and DNA methylation data etc.

• Enhancer–promoter interactions are encoded by complex genomic signatures on looping chromatin ,doi:10.1038/ng.3539

• pipeline

RIPPLE (Roy et al. NAR 2016) — Also uses functional genomic datasets for feature extraction.

• A predictive modeling approach for cell line-specific long-range regulatory interactions , https://doi.org/10.1093/nar/gkv865

二者共同的发现

• signals from these functional genomic data are informative to computationally distinguish enhancer-promoter interactions from noninteracting enhancer-promoter pairs.

PEP 只用序列信息来进行分析（马坚实验室）

Hi-C 分析流程

Analysis methods for studying the 3D architecture of the genome ，https://doi.org/10.1186/s13059-015-0745-7

流程

contact map

定义：A contact map is a matrix with rows and columns representing non-overlapping ‘bins’ across the genome.

Each entry in the matrix contains a count of read pairs that connect the corresponding bin pair in a Hi-C experiment.

How to determine bin size

• No standard rule. Rao et al. 2014 suggests using a bin size that results in at least 80% of all possible bins with >1000 contacts.

Two types of approaches to correct bias in the contact map

• Explicit approach — assuming some known bias

  - Restriction enzyme fragment lengths, GC content, and sequence mappability are three major sources of biases in Hi-C data (Yaffe and Tanay, Nat Genet 2011)
  - HiCNorm — simpler and faster (Hu et al. Bioinformatics 2012)
  

• Implicit approach — assume no known source of bias and that each locus receives equal sequence coverage after biases are removed

  - In other words, if there is no bias, the total genome-wide contact summation for each locus will be a constant, i.e., each locus has 'equal visibility'
  

Contact matrix normalization

如何进行标准化

鉴别 TAD 的算法

HMM（任兵）

Arrowhead

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