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The very first days of mammalian embryonic development are accompanied by epigenetic reprogramming and extensive changes in nuclear organization. In particular, genomic regions located at the periphery of the nucleus, termed lamina-associated domains (LADs), undergo major rearrangements after fertilization. However, the role of LADs in regulating gene expression as well as the interplay with various chromatin marks during preimplantation development remains elusive. In this study, we obtained single-cell LAD profiles coupled with the corresponding gene expression readout throughout the first days of mouse development. We detect extensive cell-cell LAD variability at the 2-cell stage, which surprisingly does not seem to functionally affect gene expression. This suggests an unusual uncoupling between 3D-nuclear genome organization and gene expression during totipotent developmental stages. By analyzing LAD dynamics and chromatin states across early developmental stages in an allelic-specific manner, we identify genomic regions that transiently detach from the nuclear lamina and are enriched by non-canonical H3K27me3. Upon maternal knock-out of a component of the Polycomb repressive complex 2 and concomitant loss of H3K27me3 during early embryogenesis, these regions relocate to the lamina at the 2-cell stage. Our results suggest that H3K27me3 is the prime determinant in establishing the atypical distribution of the genome at the nuclear periphery during the first days of embryonic development. This study provides insight into the molecular mechanisms regulating nuclear organization of parental genomes during very early mammalian development.

Recent advances in single-cell sequencing technologies have enabled simultaneous measurement of multiple cellular modalities, including various combinations of transcriptome, genome and epigenome. However, comprehensive profiling of the histone post-translational modifications that influence gene expression at single-cell resolution has remained limited. Here, we introduce EpiDamID, an experimental approach to target a diverse set of chromatin types by leveraging the binding specificities of genetically engineered proteins. By fusing Dam to single-chain variable fragment antibodies, engineered chromatin reader domains, or endogenous chromatin-binding proteins, we render the DamID technology and all its implementations compatible with the genome-wide identification of histone post-translational modifications. Importantly, this enables the joint analysis of chromatin marks and transcriptome in a variety of biological systems at the single-cell level. In this study, we use EpiDamID to profile single-cell Polycomb occupancy in mouse embryoid bodies and provide evidence for hierarchical gene regulatory networks. We further demonstrate the applicability of this method to in vivo systems by mapping H3K9me3 in early zebrafish embryogenesis, and detect striking heterochromatic regions specifically in the notochord. Overall, EpiDamID is a new addition to a vast existing toolbox for obtaining systematic insights into the role of chromatin states during dynamic cellular processes.

Protein-DNA interactions are essential for establishing cell type-specific chromatin architecture and gene expression. We recently developed scDam&T-seq, a multi-omics method that can simultaneously quantify protein-DNA interactions and the transcriptome in single cells. The method effectively combines two existing methods: DNA adenine methyltransferase identification (DamID) and CEL-Seq2. DamID works through the tethering of a protein of interest (POI) to the Escherichia coli DNA adenine methyltransferase (Dam). Upon expression of this fusion protein, DNA in proximity to the POI is methylated by Dam and can be selectively digested and amplified. CEL-Seq2, in contrast, makes use of poly-dT primers to reverse transcribe mRNA, followed by linear amplification through in vitro transcription. scDam&T-seq is the first technique capable of providing a combined readout of protein-DNA contact and transcription from single-cell samples. Once suitable cell lines have been established, the protocol can be completed in 5 d, with a throughput of hundreds to thousands of cells. The processing of raw sequencing data takes an additional 1-2 d. Our method can be used to understand the transcriptional changes a cell undergoes upon the DNA binding of a POI. It can be performed in any laboratory with access to FACS, robotic and high-throughput-sequencing facilities.

The epigenome plays a critical role in regulating gene expression in mammalian cells. However, understanding how cell-to-cell heterogeneity in the epigenome influences gene expression variability remains a major challenge. Here we report a novel method for simultaneous single-cell quantification of protein-DNA contacts with DamID and transcriptomics (scDamID&T). This method enables quantifying the impact of protein-DNA contacts on gene expression from the same cell. By profiling lamina-associated domains (LADs) in human cells, we reveal different dependencies between genome-nuclear lamina (NL) association and gene expression in single cells. In addition, we introduce the E. coli methyltransferase, Dam, as an in vivo marker of chromatin accessibility in single cells and show that scDamID&T can be utilized as a general technology to identify cell types in silico while simultaneously determining the underlying gene-regulatory landscape. With this strategy the effect of chromatin states, transcription factor binding, and genome organization on the acquisition of cell-type specific transcriptional programs can be quantified.

Nanopore sequencing is a rapidly maturing technology delivering long reads in real time on a portable instrument at low cost. Not surprisingly, the community has rapidly taken up this new way of sequencing and has used it successfully for a variety of research applications. A major limitation of nanopore sequencing is its high error rate, which despite recent improvements to the nanopore chemistry and computational tools still ranges between 5% and 15%. Here, we review computational approaches determining the nanopore sequencing error rate. Furthermore, we outline strategies for translation of raw sequencing data into base calls for detection of base modifications and for obtaining consensus sequences. Electronic supplementary material The online version of this article (10.1186/s13059-018-1462-9) contains supplementary material, which is available to authorized users.