Nature：两篇文章介绍生物新方法

1. Broad Institute of Harvard and MIT,
2. Division of Health Sciences and Technology, MIT, and
3. Whitehead Institute for Biomedical Research, Cambridge, Massachusetts 02142, USA
4. Molecular Pathology Unit and Center for Cancer Research, Massachusetts General Hospital, Charlestown, Massachusetts 02129, USA
5. Department of Neurology, Children's Hospital, and
6. Department of Pathology, Harvard Medical School, Boston, Massachusetts 02115, USA
7. These authors contributed equally to this work.

Abstract

We report the application of single-molecule-based sequencing technology for high-throughput profiling of histone modifications in mammalian cells. By obtaining over four billion bases of sequence from chromatin immunoprecipitated DNA, we generated genome-wide chromatin-state maps of mouse embryonic stem cells, neural progenitor cells and embryonic fibroblasts. We find that lysine 4 and lysine 27 trimethylation effectively discriminates genes that are expressed, poised for expression, or stably repressed, and therefore reflect cell state and lineage potential. Lysine 36 trimethylation marks primary coding and non-coding transcripts, facilitating gene annotation. Trimethylation of lysine 9 and lysine 20 is detected at satellite, telomeric and active long-terminal repeats, and can spread into proximal unique sequences. Lysine 4 and lysine 9 trimethylation marks imprinting control regions. Finally, we show that chromatin state can be read in an allele-specific manner by using single nucleotide polymorphisms. This study provides a framework for the application of comprehensive chromatin profiling towards characterization of diverse mammalian cell populations.

1. Center for Cell Decision Processes, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
2. Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
3. Department of Cell Biology, Harvard Medical School, Boston, Massachusetts 02115, USA
4. Departments of Biology and Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
5. These authors contributed equally to this work.

The fundamental components of many signalling pathways are common to all cells1, 2, 3. However, stimulating or perturbing the intracellular network often causes distinct phenotypes that are specific to a given cell type4, 5. This 'cell specificity' presents a challenge in understanding how intracellular networks regulate cell behaviour and an obstacle to developing drugs that treat signalling dysfunctions6, 7. Here we apply a systems-modelling approach8 to investigate how cell-specific signalling events are integrated through effector proteins to cause cell-specific outcomes. We focus on the synergy between tumour necrosis factor and an adenoviral vector as a therapeutically relevant stimulus that induces cell-specific responses9, 10, 11. By constructing models that estimate how kinase-signalling events are processed into phenotypes through effector substrates, we find that accurate predictions of cell specificity are possible when different cell types share a common 'effector-processing' mechanism. Partial-least-squares regression models based on common effector processing accurately predict cell-specific apoptosis, chemokine release, gene induction, and drug sensitivity across divergent epithelial cell lines. We conclude that cell specificity originates from the differential activation of kinases and other upstream transducers, which together enable different cell types to use common effectors to generate diverse outcomes. The common processing of network signals by downstream effectors points towards an important cell biological principle, which can be applied to the understanding of cell-specific responses to targeted drug therapies6