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Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a method used to profile protein-DNA interactions genome-wide. RELACS (Restriction Enzyme-based Labeling of Chromatin in Situ) is a recently developed ChIP-seq protocol that deploys a chromatin barcoding strategy to enable standardized and high-throughput generation of ChIP-seq data. The manual implementation of RELACS is constrained by human processivity in both data generation and data analysis. To overcome these limitations, we have developed AutoRELACS, an automated implementation of the RELACS protocol using the liquid handler Biomek i7 workstation. We match the unprecedented processivity in data generation allowed by AutoRELACS with the automated computation pipelines offered by snakePipes. In doing so, we build a continuous workflow that streamlines epigenetic profiling, from sample collection to biological interpretation. Here, we show that AutoRELACS successfully automates chromatin barcode integration, and is able to generate high-quality ChIP-seq data comparable with the standards of the manual protocol, also for limited amounts of biological samples.

Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) is an invaluable tool for mapping chromatin-associated proteins. However, sample preparation is still a largely individual and labor-intensive process that hinders assay throughput and comparability. Here, we present a novel method for ultra-parallelized high-throughput ChIP-seq that addresses the aforementioned problems. The method, called RELACS (Restriction Enzyme-based Labeling of Chromatin in Situ), employs barcoding of chromatin within intact nuclei extracted from different sources (e.g. tissues, treatments, time points). Barcoded nuclei are pooled and processed within the same ChIP, for maximal comparability and significant workload reduction. The choice of user-friendly, straightforward, enzymatic steps for chromatin fragmentation and barcoding makes RELACS particularly suitable for implementation large-scale clinical studies and scarce samples. RELACS can generate ChIP-seq libraries from hundreds of samples within three days and with less than 1000 cells per sample.

Summary To date, it remains largely unclear to what extent chromatin machinery contributes to the susceptibility and progression of complex diseases. Here, we combine deep epigenome mapping with single-cell transcriptomics to mine for evidence of chromatin dysregulation in type 2 diabetes. We find two chromatin-state signatures that track β cell dysfunction in mice and humans: ectopic activation of bivalent Polycomb-silenced domains and loss of expression at an epigenomically unique class of lineage-defining genes. β cell-specific Polycomb (Eed/PRC2) loss of function in mice triggers diabetes-mimicking transcriptional signatures and highly penetrant, hyperglycemia-independent dedifferentiation, indicating that PRC2 dysregulation contributes to disease. The work provides novel resources for exploring β cell transcriptional regulation and identifies PRC2 as necessary for long-term maintenance of β cell identity. Importantly, the data suggest a two-hit (chromatin and hyperglycemia) model for loss of β cell identity in diabetes., Graphical Abstract, Highlights • Deep epigenome mapping and single-cell transcriptomics of β cells in T2D • Human and mouse diabetes mimic PRC2 loss of function • Eed/PRC2 safeguards transcription integrity in terminally differentiated β cells • Eed/PRC2-sensitive dedifferentiation is pharmacologically targetable, Lu et al. provide evidence of chromatin dysregulation in type 2 diabetes in mice and humans. Loss of Polycomb silencing in mouse pancreas triggers hyperglycemia-independent dedifferentiation of β cells and diabetes, suggesting a two-hit (chromatin and hyperglycemia) model for loss of β cell identity in diabetes.

SummaryThe global rise in obesity has revitalized a search for genetic and epigenetic factors underlying the disease. We present a Drosophila model of paternal-diet-induced intergenerational metabolic reprogramming (IGMR) and identify genes required for its encoding in offspring. Intriguingly, we find that as little as 2 days of dietary intervention in fathers elicits obesity in offspring. Paternal sugar acts as a physiological suppressor of variegation, desilencing chromatin-state-defined domains in both mature sperm and in offspring embryos. We identify requirements for H3K9/K27me3-dependent reprogramming of metabolic genes in two distinct germline and zygotic windows. Critically, we find evidence that a similar system may regulate obesity susceptibility and phenotype variation in mice and humans. The findings provide insight into the mechanisms underlying intergenerational metabolic reprogramming and carry profound implications for our understanding of phenotypic variation and evolution.