An ultra-low-input native ChIP-seq protocol for genome-wide profiling of rare cell populations
Ontology highlight
ABSTRACT: The development of combined chromatin immunoprecipitation and next generation sequencing (ChIP-seq) technologies has enabled genome-wide epigenetic profiling of numerous cell lines and tissue types. A major limitation of ChIP-seq, however, is the large number of cells required to generate high quality datasets, precluding the study of rare cell populations. Here, we present an ultra-low-input micrococcal nuclease-based native ChIP (ULI-NChIP) and sequencing method, to generate genome-wide histone mark profiles with high resolution and reproducibility from as few as one thousand cells. Using ULI-NChIP, we generated high quality maps of several covalent histone marks from 10^3-10^6 embryonic stem cells. To further validate our procedure we demonstrate that genome-wide H3K27me3 profiles generated from 10^3 E13.5 primordial germ cells (PGCs) using ULI-NChIP-seq show high similarity to recently generated datasets using 50-180× more material, illustrating the utility of this method for generating high quality libraries with improved complexity from rare cell populations.
Project description:H3K27 di-methylation and H3K27 trimethylation are marks of facultative heterochromatin which maintains transcriptional repression established during early development in many eukaryotes. However, the mechanism underlying establishment and regulation of epigenetic asymmetry in the zygote remains obscure. Here we report the distribution pattern of H3K27me2 in Ezh2m+/p+ and Ezh2m-/p+ mice zygotes using the approach of ULI-NChIP.
Project description:The transcriptional regulation is often controlled by the epigenetic modifications or by chromatin associated proteins. To understand this regulation, chromatin immunoprecipitation (ChIP) followed by next generation sequencing is an invaluable and powerful technique. However, the major limitation of this approach is often the requirement of large amount of starting material for generating high-quality datasets, and often the workflow is laborious. This limitation also results in application of this approach to study of rare cell populations even more challenging, if not impossible. Here, we present a tagmentation-assisted fragmentation ChIP (TAF-ChIP) and sequencing method to generate high quality dataset from as few as 100 human and 1000 Drosophila cells. The method itself is straightforward and is by far less labor-intensive than conventional library preparation, and other contemporary low amount ChIP-Seq methods. Furthermore, this approach can be applied directly on 100 cells rather than relying on de-multiplexing strategies to generate the profile from limited number of cells. This can be extremely useful when the access to the starting material is very restricted, for example clinically isolated cells from patients. Using this approach we generated the H3K4Me3 and H3K9Me3 profiles from 100 K562 cells and 1000 sorted neural stem cells (NSC) from Drosophila. We benchmarked our TAF-ChIP datasets from K562 cells against the Encode datasets. For validating the TAF-ChIP datasets obtained from Drosophila NSCs we took advantage of Notch induced over proliferation specifically in type II NSCs. The epigenetic profile obtained from conventional ChIP-Seq approach and TAF-ChIP approach shows high degree of agreement, thereby underlining the utility of this approach for generating ChIP-Seq profiles from very low cell numbers.
Project description:The transcriptional regulation is often controlled by the epigenetic modifications or by chromatin associated proteins. To understand this regulation, chromatin immunoprecipitation (ChIP) followed by next generation sequencing is an invaluable and powerful technique. However, the major limitation of this approach is often the requirement of large amount of starting material for generating high-quality datasets, and often the workflow is laborious. This limitation also results in application of this approach to study of rare cell populations even more challenging, if not impossible. Here, we present a tagmentation-assisted fragmentation ChIP (TAF-ChIP) and sequencing method to generate high quality dataset from as few as 100 human and 1000 Drosophila cells. The method itself is straightforward and is by far less labor-intensive than conventional library preparation, and other contemporary low amount ChIP-Seq methods. Furthermore, this approach can be applied directly on 100 cells rather than relying on de-multiplexing strategies to generate the profile from limited number of cells. This can be extremely useful when the access to the starting material is very restricted, for example clinically isolated cells from patients. Using this approach we generated the H3K4Me3 and H3K9Me3 profiles from 100 K562 cells and 1000 sorted neural stem cells (NSC) from Drosophila. We benchmarked our TAF-ChIP datasets from K562 cells against the Encode datasets. For validating the TAF-ChIP datasets obtained from Drosophila NSCs we took advantage of Notch induced over proliferation specifically in type II NSCs. The epigenetic profile obtained from conventional ChIP-Seq approach and TAF-ChIP approach shows high degree of agreement, thereby underlining the utility of this approach for generating ChIP-Seq profiles from very low cell numbers.
Project description:Chromatin immunoprecipitation followed by massively parallel, high throughput sequencing (ChIP-seq) is the method of choice for identifying, on a genome-wide scale, the segments of DNA bound by specific transcription factors (TFs) or in chromatin with particular histone modifications. However, the quality of ChIP-seq datasets vary over a wide range, with a substantial fraction being of intermediate to poor quality. Such experimental variability can lead to many false positives or false negatives, impairing the ability to interpret the data. Thus, it is important to discern and control the factors that contribute to variation in ChIP-seq. In this study we focus on the sonication step to produce sheared chromatin, a variable controllable by the user and applicable to all ChIP-seq protocols. We systematically varied the amount of shearing of fixed chromatin from a mouse erythroid cell line, carefully measured the distribution of resultant fragment lengths using the Agilent Bioanalyzer 2100, and then immunoprecipitated these batches of chromatin using highly specific antibodies against either TAL1 or CTCF. We found that the level of sonication, which was affected by both the number of sonication cycles, as well as the starting cell number, had a pronounced impact on the quality of resulting ChIP-seq signals. Specifically, over-sonication led to degradation of quality (e.g. increased background and reduction in signal), while the impact of under-sonication of chromatin differed between the two transcription factors, leading to the loss of sites occupied by TAL1 but not those bound by CTCF. We leveraged these findings to produce a set of CTCF ChIPs-seq datasets in primary hematopoietic progenitor cells, including several rare cell types. Together, these results suggest that the amount of sonication is a key variable in success of ChIP-seq experiments, and that carefully monitoring the level of chromatin sonication is one way to improve ChIP-seq quality and reproducibility, which in turn facilitates low input ChIP-seq in rare cell types.
Project description:Difficulties to accurately map epigenomes in a few cells sorted or dissected from tissues have hampered our understanding of how chromatin modification regulates development and diseases. Despite recent progress, all reported chromatin-immunoprecipitation-based deep sequencing (ChIP-seq) methods have not achieved high quality mapping of rare cell populations. We report Recovery via Protection (RP)-ChIP-seq and favored amplification RP-ChIP-seq (FARP-ChIP-seq) for as few as 500 cells with superior quality compared to all reported techniques to date. FARP-ChIP-seq accurately mapped histone H3 lysine 4 trimethylation (H3K4me3) and H3K27me3 in long-term hematopoietic stem cells (LT-HSCs), short-term HSCs (ST-HSCs), and multi-potent progenitors (MPPs) sorted from one mouse. These high quality datasets not only implicate genes involved in HSC differentiation but also demonstrate a general lack of H3K4me3/H3K27me3 bivalency on hematopoietic genes in HSCs. Thus the method offers accurate mapping for fewest cells.
Project description:Next-generation sequencing has been widely used for the genome-wide profiling of histone modifications, transcription factor binding and gene expression through chromatin immunoprecipitated DNA sequencing (ChIP-seq) and cDNA sequencing (RNA-seq). Here, we describe a versatile library construction method that can be applied to both ChIP-seq and RNA-seq on the widely used Illumina platforms. Standard methods for ChIP-seq library construction require nanograms of starting DNA, substantially limiting its application to rare cell types or limited clinical samples. By minimizing the DNA purification steps that cause major sample loss, our method achieved a high sensitivity in ChIP-seq library preparation. Using this method, we achieved the following: (1) generated high-quality epigenomic and transcription factor-binding maps using ChIP-seq for murine adipocytes; (2) successfully prepared a ChIP-seq library from as little as 25 pg of starting DNA; (3) achieved paired-end sequencing of the ChIP-seq libraries; (4) systematically profiled gene expression dynamics during murine adipogenesis using RNA-seq; and (5) preserved the strand specificity of the transcripts in RNA-seq. Given its sensitivity and versatility in both double-stranded and single-stranded DNA library construction, this method has wide applications in genomic, epigenomic, transcriptomic and interactomic studies. Pre-adipocytes and mature adipocytes were collected. Their chromatin and RNA were subjected to ChIP and mRNA extraction. Sequencing libraries from ChIP DNA or mRNA were generated following either standard protocols or TELP method. The quality and features of TELP libraries were proved and demonstrated in comparison with standard libraries or other published data.
Project description:Next-generation sequencing has been widely used for the genome-wide profiling of histone modifications, transcription factor binding and gene expression through chromatin immunoprecipitated DNA sequencing (ChIP-seq) and cDNA sequencing (RNA-seq). Here, we describe a versatile library construction method that can be applied to both ChIP-seq and RNA-seq on the widely used Illumina platforms. Standard methods for ChIP-seq library construction require nanograms of starting DNA, substantially limiting its application to rare cell types or limited clinical samples. By minimizing the DNA purification steps that cause major sample loss, our method achieved a high sensitivity in ChIP-seq library preparation. Using this method, we achieved the following: (1) generated high-quality epigenomic and transcription factor-binding maps using ChIP-seq for murine adipocytes; (2) successfully prepared a ChIP-seq library from as little as 25 pg of starting DNA; (3) achieved paired-end sequencing of the ChIP-seq libraries; (4) systematically profiled gene expression dynamics during murine adipogenesis using RNA-seq; and (5) preserved the strand specificity of the transcripts in RNA-seq. Given its sensitivity and versatility in both double-stranded and single-stranded DNA library construction, this method has wide applications in genomic, epigenomic, transcriptomic and interactomic studies.
Project description:ChIP-exo/nexus experiments present modifications on the commonly used ChIP-seq protocol for high resolution mapping of transcription factor binding sites. Although many aspects of the ChIP-exo data analysis are similar to those of ChIP-seq, these high throughput experiments pose a number of unique quality control and analysis challenges. We develop a statistical quality control pipeline and accompanying R package, ChIPexoQual, to enable exploration and analysis of ChIP-exo and related experiments. ChIPexoQual evaluates a number of key issues including strand imbalance, library complexity, and signal enrichment of data. Assessment of these features are facilitated through diagnostic plots and summary statistics calculated over regions of the genome with varying levels of coverage. We evaluated our QC pipeline with both large collections of public ChIP-exo/nexus data and multiple, new ChIP-exo datasets from E. coli. ChIPexoQual analysis of these datasets resulted in guidelines for using these QC metrics across a wide range of sequencing depths and provided further insights for modelling ChIP-exo data. Finally, although ChIP-exo experiments have been compared to ChIP-seq experiments with single-end (SE) sequencing, we provide, for the first time, comparisons with paired-end (PE) ChIP-seq experiments. We illustrate that, at fixed sequencing depths, ChIP-exo provides higher sensitivity, specificity, and spatial resolution than PE ChIP-seq and both significantly outperform their SE ChIP-seq counterpart.