Epigenetic mechanisms have emerged as links between prenatal environmental exposure and disease risk later in life. Here, we studied epigenetic changes associated with maternal smoking at base pair resolution by mapping DNA methylation, histone modifications, and transcription in expectant mothers and their newborn children. We found extensive global differential methylation and carefully evaluated these changes to separate environment associated from genotype-related DNA methylation changes. Differential methylation is enriched in enhancer elements and targets in particular "commuting" enhancers having multiple, regulatory interactions with distal genes. Longitudinal whole-genome bisulfite sequencing revealed that DNA methylation changes associated with maternal smoking persist over years of life. Particularly in children prenatal environmental exposure leads to chromatin transitions into a hyperactive state. Combined DNA methylation, histone modification, and gene expression analyses indicate that differential methylation in enhancer regions is more often functionally translated than methylation changes in promoters or non-regulatory elements. Finally, we show that epigenetic deregulation of a commuting enhancer targeting c-Jun N-terminal kinase 2 (JNK2) is linked to impaired lung function in early childhood.

Embryonic cell division is a mechanical process which is predominantly driven by contraction of the cleavage furrow and response of the remaining cellular matter. While most previous studies focused on contractile ring mechanisms of cytokinesis, effects of environmental factors such as pericellular vitelline membrane and temperature on the mechanics of dividing cells were rarely studied. Here, we apply a model-based analysis to the time-lapse imaging data of two species (Saccoglossus kowalevskii and Xenopus laevis) with relatively large eggs, with the goal of revealing the effects of temperature and vitelline envelope on the mechanics of the first embryonic cell division. We constructed a numerical model of cytokinesis to estimate the effects of vitelline confinement on cellular deformation and to predict deformation of cellular contours. We used the deviations of our computational predictions from experimentally observed cell elongation to adjust variable parameters of the contractile ring model and to quantify the contribution of other factors (constitutive cell properties, spindle polarization) that may influence the mechanics and shape of dividing cells. We find that temperature affects the size and rate of dilatation of the vitelline membrane surrounding fertilized eggs and show that in native (not artificially devitellinized) egg cells the effects of temperature and vitelline envelope on mechanics of cell division are tightly interlinked. In particular, our results support the view that vitelline membrane fulfills an important role of micromechanical environment around the early embryo the absence or improper function of which under moderately elevated temperature impairs normal development. Furthermore, our findings suggest the existence of scale-dependent mechanisms that contribute to cytokinesis in species with different egg size, and challenge the view of mechanics of embryonic cell division as a scale-independent phenomenon.

Circular chromosome conformation capture (4C) has provided important insights into three dimensional (3D) genome organization and its critical impact on the regulation of gene expression. We developed a new quantitative framework based on polymer physics for the analysis of paired-end sequencing 4C (PE-4Cseq) data. We applied this strategy to the study of chromatin interaction changes upon a 4.3 Mb DNA deletion in mouse region 4E2.

Successful RNAi applications depend on strategies allowing robust and persistent expression of minimal gene silencing triggers without perturbing endogenous gene expression. Here, we propose a novel avenue which is integration of a promoterless shmiRNA, i.e. a shRNA embedded in a micro-RNA (miRNA) scaffold, into an engineered genomic miRNA locus. For proof-of-concept, we used TALE or CRISPR/Cas9 nucleases to site-specifically integrate an anti-hepatitis C virus (HCV) shmiRNA into the liver-specific miR-122/hcr locus in hepatoma cells, with the aim to obtain cellular clones that are genetically protected against HCV infection. Using reporter assays, Northern blotting and qRT-PCR, we confirmed anti-HCV shmiRNA expression as well as miR-122 integrity and functionality in selected cellular progeny. Moreover, we employed a comprehensive battery of PCR, cDNA/miRNA profiling and whole genome sequencing analyses to validate targeted integration of a single shmiRNA molecule at the expected position, and to rule out deleterious effects on the genomes or transcriptomes of the engineered cells. Importantly, a subgenomic HCV replicon and a full-length reporter virus, but not a Dengue virus control, were significantly impaired in the modified cells. Our original combination of DNA engineering and RNAi expression technologies benefits numerous applications, from miRNA, genome and transgenesis research, to human gene therapy.

A remarkable observation emerging from recent cancer genome analyses is the identification of chromothripsis as a one-off genomic catastrophe, resulting in massive somatic DNA structural rearrangements (SRs). Largely due to lack of suitable model systems, the mechanistic basis of chromothripsis has remained elusive. We developed an integrative method termed "complex alterations after selection and transformation (CAST)," enabling efficient in vitro generation of complex DNA rearrangements including chromothripsis, using cell perturbations coupled with a strong selection barrier followed by massively parallel sequencing. We employed this methodology to characterize catastrophic SR formation processes, their temporal sequence, and their impact on gene expression and cell division. Our in vitro system uncovered a propensity of chromothripsis to occur in cells with damaged telomeres, and in particular in hyperploid cells. Analysis of primary medulloblastoma cancer genomes verified the link between hyperploidy and chromothripsis in vivo. CAST provides the foundation for mechanistic dissection of complex DNA rearrangement processes.

Integrative analysis of multi-omics layers at single cell level is critical for accurate dissection of cell-to-cell variation within certain cell populations. Here we report scCAT-seq, a technique for simultaneously assaying chromatin accessibility and the transcriptome within the same single cell. We show that the combined single cell signatures enable accurate construction of regulatory relationships between cis-regulatory elements and the target genes at single-cell resolution, providing a new dimension of features that helps direct discovery of regulatory patterns specific to distinct cell identities. Moreover, we generate the first single cell integrated map of chromatin accessibility and transcriptome in early embryos and demonstrate the robustness of scCAT-seq in the precise dissection of master transcription factors in cells of distinct states. The ability to obtain these two layers of omics data will help provide more accurate definitions of "single cell state" and enable the deconvolution of regulatory heterogeneity from complex cell populations.

As a result of its simplicity and high efficiency, the CRISPR-Cas system has been widely used as a genome editing tool. Recently, CRISPR base editors, which consist of deactivated Cas9 (dCas9) or Cas9 nickase (nCas9) linked with a cytidine or a guanine deaminase, have been developed. Base editing tools will be very useful for gene correction because they can produce highly specific DNA substitutions without the introduction of any donor DNA, but dedicated web-based tools to facilitate the use of such tools have not yet been developed.

Exposure to endocrine-disrupting chemicals can alter normal physiology and increase susceptibility to non-communicable diseases like obesity. Especially the prenatal and early postnatal period is highly vulnerable to adverse effects by environmental exposure, promoting developmental reprogramming by epigenetic alterations. To obtain a deeper insight into the role of prenatal bisphenol A (BPA) exposure in children's overweight development, we combine epidemiological data with experimental models and BPA-dependent DNA methylation changes.

Natural killer (NK) cells eliminate infected and tumorigenic cells through delivery of granzymes via perforin pores or by activation of caspases via death receptors. In order to understand how NK cells combine different cell death mechanisms, it is important to quantify target cell responses on a single cell level. However, currently existing reporters do not allow the measurement of several protease activities inside the same cell. Here, we present a strategy for the comparison of two different proteases at a time inside individual target cells upon engagement by NK cells. We developed single-fluorescent protein reporters containing the RIEAD or the VGPD cleavage site for the measurement of granzyme B activity. We show that these two granzyme B reporters can be applied in combination with caspase-8 or caspase-3 reporters. While we did not find that caspase-8 was activated by granzyme B, our method revealed that caspase-3 activity follows granzyme B activity with a delay of about 6 min. Finally, we illustrate the comparison of several different reporters for granzyme A, M, K, and H. The approach presented here is a valuable means for the investigation of the temporal evolution of cell death mediated by cytotoxic lymphocytes.

Three-dimensional protein localization intricately determines the functional coordination of cellular processes. The complex spatial context of protein landscape has been assessed by multiplexed immunofluorescent staining or mass spectrometry, applied to 2D cell culture with limited physiological relevance or tissue sections. Here, we present 3D SPECS, an automated technology for 3D Spatial characterization of Protein Expression Changes by microscopic Screening. This workflow comprises iterative antibody staining, high-content 3D imaging, and machine learning for detection of mitoses. This is followed by mapping of spatial protein localization into a spherical, cellular coordinate system, a basis for model-based prediction of spatially resolved affinities of proteins. As a proof-of-concept, we mapped twelve epitopes in 3D-cultured spheroids and investigated the network effects of twelve mitotic cancer drugs. Our approach reveals novel insights into spindle fragility and chromatin stress, and predicts unknown interactions between proteins in specific mitotic pathways. 3D SPECS's ability to map potential drug targets by multiplexed immunofluorescence in 3D cell culture combined with our automated high-content assay will inspire future functional protein expression and drug assays.

Mutation is a fundamental process in tumorigenesis. However, the degree to which the rate of somatic mutation varies across the human genome and the mechanistic basis underlying this variation remain to be fully elucidated. Here, we performed a cross-cancer comparison of 402 whole genomes comprising a diverse set of childhood and adult tumors, including both solid and hematopoietic malignancies. Surprisingly, we found that the inactive X chromosome of many female cancer genomes accumulates on average twice and up to four times as many somatic mutations per megabase, as compared to the individual autosomes. Whole-genome sequencing of clonally expanded hematopoietic stem/progenitor cells (HSPCs) from healthy individuals and a premalignant myelodysplastic syndrome (MDS) sample revealed no X chromosome hypermutation. Our data suggest that hypermutation of the inactive X chromosome is an early and frequent feature of tumorigenesis resulting from DNA replication stress in aberrantly proliferating cells.

The function of many eukaryotic proteins is regulated by highly dynamic changes in their nucleocytoplasmic distribution. The ability to precisely and reversibly control nuclear translocation would, therefore, allow dissecting and engineering cellular networks. Here we develop a genetically encoded, light-inducible nuclear localization signal (LINuS) based on the LOV2 domain of Avena sativa phototropin 1. LINuS is a small, versatile tag, customizable for different proteins and cell types. LINuS-mediated nuclear import is fast and reversible, and can be tuned at different levels, for instance, by introducing mutations that alter AsLOV2 domain photo-caging properties or by selecting nuclear localization signals (NLSs) of various strengths. We demonstrate the utility of LINuS in mammalian cells by controlling gene expression and entry into mitosis with blue light.

Common approaches to pathway analysis treat pathways merely as lists of genes disregarding their topological structures, that is, ignoring the genes' interactions on which a pathway's cellular function depends. In contrast, PathWave has been developed for the analysis of high-throughput gene expression data that explicitly takes the topology of networks into account to identify both global dysregulation of and localized (switch-like) regulatory shifts within metabolic and signaling pathways. For this purpose, it applies adjusted wavelet transforms on optimized 2D grid representations of curated pathway maps.

A hierarchically organized cell compartment drives colorectal cancer (CRC) progression. Genetic barcoding allows monitoring of the clonal output of tumorigenic cells without prospective isolation. In this study, we asked whether tumor clone-initiating cells (TcICs) were genetically heterogeneous and whether differences in self-renewal and activation reflected differential kinetics among individual subclones or functional hierarchies within subclones. Monitoring genomic subclone kinetics in three patient tumors and corresponding serial xenografts and spheroids by high-coverage whole-genome sequencing, clustering of genetic aberrations, subclone combinatorics, and mutational signature analysis revealed at least two to four genetic subclones per sample. Long-term growth in serial xenografts and spheroids was driven by multiple genomic subclones with profoundly differing growth dynamics and hence different quantitative contributions over time. Strikingly, genetic barcoding demonstrated stable functional heterogeneity of CRC TcICs during serial xenografting despite near-complete changes in genomic subclone contribution. This demonstrates that functional heterogeneity is, at least frequently, present within genomic subclones and independent of mutational subclone differences.

Timely and accurate assembly of the mitotic spindle is critical for the faithful segregation of chromosomes, and centrosome separation is a key step in this process. The timing of centrosome separation varies dramatically between cell types; however, the mechanisms responsible for these differences and its significance are unclear. Here, we show that activation of epidermal growth factor receptor (EGFR) signaling determines the timing of centrosome separation. Premature separation of centrosomes decreases the requirement for the major mitotic kinesin Eg5 for spindle assembly, accelerates mitosis, and decreases the rate of chromosome missegregation. Importantly, EGF stimulation impacts upon centrosome separation and mitotic progression to different degrees in different cell lines. Cells with high EGFR levels fail to arrest in mitosis upon Eg5 inhibition. This has important implications for cancer therapy because cells with high centrosomal response to EGF are more susceptible to combinatorial inhibition of EGFR and Eg5.

The emergence of high-throughput, next-generation sequencing technologies has dramatically altered the way we assess genomes in population genetics and in cancer genomics. Currently, there are four commonly used whole-genome sequencing platforms on the market: Illumina's HiSeq2000, Life Technologies' SOLiD 4 and its completely redesigned 5500xl SOLiD, and Complete Genomics' technology. A number of earlier studies have compared a subset of those sequencing platforms or compared those platforms with Sanger sequencing, which is prohibitively expensive for whole genome studies. Here we present a detailed comparison of the performance of all currently available whole genome sequencing platforms, especially regarding their ability to call SNVs and to evenly cover the genome and specific genomic regions. Unlike earlier studies, we base our comparison on four different samples, allowing us to assess the between-sample variation of the platforms. We find a pronounced GC bias in GC-rich regions for Life Technologies' platforms, with Complete Genomics performing best here, while we see the least bias in GC-poor regions for HiSeq2000 and 5500xl. HiSeq2000 gives the most uniform coverage and displays the least sample-to-sample variation. In contrast, Complete Genomics exhibits by far the smallest fraction of bases not covered, while the SOLiD platforms reveal remarkable shortcomings, especially in covering CpG islands. When comparing the performance of the four platforms for calling SNPs, HiSeq2000 and Complete Genomics achieve the highest sensitivity, while the SOLiD platforms show the lowest false positive rate. Finally, we find that integrating sequencing data from different platforms offers the potential to combine the strengths of different technologies. In summary, our results detail the strengths and weaknesses of all four whole-genome sequencing platforms. It indicates application areas that call for a specific sequencing platform and disallow other platforms. This helps to identify the proper sequencing platform for whole genome studies with different application scopes.

During development and differentiation of an organism, accurate gene regulation is central for cells to maintain and balance their differentiation processes. Transcriptional interactions between cis-acting DNA elements such as promoters and enhancers are the basis for precise and balanced transcriptional regulation. We identified modules of combinations of binding sites in proximal and distal regulatory regions upstream of all transcription start sites (TSSs) in silico and applied these modules to gene expression time-series of mouse embryonic development and differentiation of human stem cells. In addition to tissue-specific regulation controlled by combinations of transcription factors (TFs) binding at promoters, we observed that in particular the combination of TFs binding at promoters together with TFs binding at the respective enhancers regulate highly specifically temporal progression during development: whereas 40% of TFs were specific for time intervals, 79% of TF pairs and even 97% of promoter-enhancer modules showed specificity for single time intervals of the human stem cells. Predominantly SP1 and E2F contributed to temporal specificity at promoters and the forkhead (FOX) family of TFs at enhancer regions. Altogether, we characterized three classes of TFs: with binding sites being enriched at the TSS (like SP1), depleted at the TSS (like FOX), and rather uniformly distributed.

The current progress in sequencing projects calls for rapid, reliable and accurate function assignments of gene products. A variety of methods has been designed to annotate sequences on a large scale. However, these methods can either only be applied for specific subsets, or their results are not formalised, or they do not provide precise confidence estimates for their predictions.

The dynamics of nuclear organization, nuclear bodies and RNPs in particular has been the focus of many studies. To understand their function, knowledge of their spatial nuclear position and temporal translocation is essential. Typically, such studies generate a wealth of data that require novel methods in image analysis and computational tools to quantitatively track particle movement on the background of moving cells and shape changing nuclei.

Normalization of microarrays is a standard practice to account for and minimize effects which are not due to the controlled factors in an experiment. There is an overwhelming number of different methods that can be applied, none of which is ideally suited for all experimental designs. Thus, it is important to identify a normalization method appropriate for the experimental setup under consideration that is neither too negligent nor too stringent. Major aim is to derive optimal results from the underlying experiment. Comparisons of different normalization methods have already been conducted, none of which, to our knowledge, comparing more than a handful of methods.