SpikChIP: a novel computational methodology to compare multiple ChIP-seq using spike-in chromatin

In order to evaluate cell- and disease-specific changes in the interacting strength of chromatin targets, ChIP-seq signal across multiple conditions must undergo robust normalization. However, this is not possible using the standard ChIP-seq scheme, which lacks a reference for the control of biological and experimental variabilities. While several studies have recently proposed different solutions to circumvent this problem, substantial analytical differences among methodologies could hamper the experimental reproducibility and quantitative accuracy. Here, we propose a computational method to accurately compare ChIP-seq experiments, with exogenous spike-in chromatin, across samples in a genome-wide manner by using a local regression strategy (spikChIP). In contrast to the previous methodologies, spikChIP reduces the influence of sequencing noise of spike-in material during ChIP-seq normalization, while minimizes the overcorrection of non-occupied genomic regions in the experimental ChIP-seq. We demonstrate the utility of spikChIP with both histone and non-histone chromatin protein, allowing us to monitor for experimental reproducibility and the accurate ChIP-seq comparison of distinct experimental schemes. spikChIP software is available on GitHub (https://github.com/eblancoga/spikChIP).

A parallelized, automated platform enabling individual or sequential ChIP of histone marks and transcription factors

Despite its popularity, chromatin immunoprecipitation followed by sequencing (ChIP-seq) remains a tedious (>2 d), manually intensive, low-sensitivity and low-throughput approach. Here, we combine principles of microengineering, surface chemistry, and molecular biology to address the major limitations of standard ChIP-seq. The resulting technology, FloChIP, automates and miniaturizes ChIP in a beadless fashion while facilitating the downstream library preparation process through on-chip chromatin tagmentation. FloChIP is fast (<2 h), has a wide dynamic range (from 106to 500 cells), is scalable and parallelized, and supports antibody- or sample-multiplexed ChIP on both histone marks and transcription factors. In addition, FloChIP’s interconnected design allows for straightforward chromatin reimmunoprecipitation, which allows this technology to also act as a microfluidic sequential ChIP-seq system. Finally, we ran FloChIP for the transcription factor MEF2A in 32 distinct human lymphoblastoid cell lines, providing insights into the main factors driving collaborative DNA binding of MEF2A and into its role in B cell-specific gene regulation. Together, our results validate FloChIP as a flexible and reproducible automated solution for individual or sequential ChIP-seq.

Building a robust chromatin immunoprecipitation (ChIP) method with substantially improved efficiency

ABSTRACTChromatin immunoprecipitation (ChIP) is the gold-standard method to detect the interactions between proteins and chromatin, and is a powerful tool to identify epigenetic modifications. Although ChIP protocols for plant species have been developed, many specific features of plants, especially woody plants, still hinder the efficiency of immunoprecipitation, resulting inefficient ChIP enrichment. There is an active demand for a highly efficient ChIP protocol. In the present study, we employed Betula platyphylla (birch) and Arabidopsis thaliana as the research materials, and five factors closely associated with ChIP efficiency were identified, including crosslinking, chromatin concentration using centrifugal filter, using new immunoprecipitation buffer, rescue DNA with proteinase K, and using sucrose to increase immunoprecipitation efficiency. Optimization of any these factors can significantly improve ChIP efficiency. Considering these factors together, a robust ChIP protocol was developed, for which the average fold enrichments were 16.88 and 6.43 fold of that gained using standard ChIP in birch and Arabidopsis, respectively. As this built ChIP method works well in both birch and Arabidopsis, it should be also suitable for other woody and herbaceous species. In addition, this ChIP method make it is possible to detect low-abundance TF-DNA interactions, and may extend the application of ChIP in plant kingdom.One sentence summaryBuilding a ChIP method that increases fold enrichment of birch by 16 folds in average and is adapted for both woody and herbaceous plants.

Flexible k-mers with variable-length indels for identifying binding sequences of protein dimers

Many DNA-binding proteins interact with partner proteins. Recently, based on the high-throughput consecutive affinity-purification systematic evolution of ligands by exponential enrichment (CAP-SELEX) method, many such protein pairs have been found to bind DNA with flexible spacing between their individual binding motifs. Most existing motif representations were not designed to capture such flexibly spaced regions. In order to computationally discover more co-binding events without prior knowledge about the identities of the co-binding proteins, a new representation is needed. We propose a new class of sequence patterns that flexibly model such variable regions and corresponding algorithms that identify co-bound sequences using these patterns. Based on both simulated and CAP-SELEX data, features derived from our sequence patterns lead to better classification performance than patterns that do not explicitly model the variable regions. We also show that even for standard ChIP-seq data, this new class of sequence patterns can help discover co-bound events in a subset of sequences in an unsupervised manner. The open-source software is available at https://github.com/kevingroup/glk-SVM.

Comparative ChIP-seq (Comp-ChIP-seq): a practical guideline for experimental design and a novel computational methodology

ABSTRACTChromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is a pivotal technique for understanding the functionality of the chromatin-bound factors and for mapping the functional elements of the genome. In order to evaluate cell- and disease-specific changes in the interacting strength of chromatin targets, ChIP-seq signal across multiple conditions must undergo robust normalization. However, this is not possible using the standard ChIP-seq scheme, which lacks a reference for the control of biological and experimental variabilities. While several studies have recently proposed different solutions to circumvent this problem, substantial technical and analytical differences among methodologies could hamper the experimental reproducibility. Here we provide a practical binary decision-making process to experimentally implement a normalizing method for comparative ChIP-seq across different samples. In addition, we evaluate side-by-side the current computational approaches for normalizing using a reference internal genome. Finally, we propose a local regression strategy to accurately normalize ChIP-seq data in a genome-wide manner. Overall, our proposed experimental and computational standard for comparative ChIP-seq (Comp-ChIP-seq) will increase experimental reproducibility, thereby reducing this major confounding factor in interpreting ChIP-seq results.