Structural and functional properties of mSWI/SNF chromatin remodeling complexes revealed through single-cell perturbation screens.

The mammalian SWI/SNF (mSWI/SNF or BAF) family of chromatin remodeling complexes play critical roles in regulating DNA accessibility and gene expression. The three final-form subcomplexes-cBAF, PBAF, and ncBAF-are distinct in biochemical componentry, chromatin targeting, and roles in disease; however, the contributions of their constituent subunits to gene expression remain incompletely defined. Here, we performed Perturb-seq-based CRISPR-Cas9 knockout screens targeting mSWI/SNF subunits individually and in select combinations, followed by single-cell RNA-seq and SHARE-seq. We uncovered complex-, module-, and subunit-specific contributions to distinct regulatory networks and defined paralog subunit relationships and shifted subcomplex functions upon perturbations. Synergistic, intra-complex genetic interactions between subunits reveal functional redundancy and modularity. Importantly, single-cell subunit perturbation signatures mapped across bulk primary human tumor expression profiles both mirror and predict cBAF loss-of-function status in cancer. Our findings highlight the utility of Perturb-seq to dissect disease-relevant gene regulatory impacts of heterogeneous, multi-component master regulatory complexes.

Massively parallel phenotyping of coding variants in cancer with Perturb-seq.

Genome sequencing studies have identified millions of somatic variants in cancer, but it remains challenging to predict the phenotypic impact of most. Experimental approaches to distinguish impactful variants often use phenotypic assays that report on predefined gene-specific functional effects in bulk cell populations. Here, we develop an approach to functionally assess variant impact in single cells by pooled Perturb-seq. We measured the impact of 200 TP53 and KRAS variants on RNA profiles in over 300,000 single lung cancer cells, and used the profiles to categorize variants into phenotypic subsets to distinguish gain-of-function, loss-of-function and dominant negative variants, which we validated by comparison with orthogonal assays. We discovered that KRAS variants did not merely fit into discrete functional categories, but spanned a continuum of gain-of-function phenotypes, and that their functional impact could not have been predicted solely by their frequency in patient cohorts. Our work provides a scalable, gene-agnostic method for coding variant impact phenotyping, with potential applications in multiple disease settings.

Mitigation of off-target toxicity in CRISPR-Cas9 screens for essential non-coding elements.

Pooled CRISPR-Cas9 screens are a powerful method for functionally characterizing regulatory elements in the non-coding genome, but off-target effects in these experiments have not been systematically evaluated. Here, we investigate Cas9, dCas9, and CRISPRi/a off-target activity in screens for essential regulatory elements. The sgRNAs with the largest effects in genome-scale screens for essential CTCF loop anchors in K562 cells were not single guide RNAs (sgRNAs) that disrupted gene expression near the on-target CTCF anchor. Rather, these sgRNAs had high off-target activity that, while only weakly correlated with absolute off-target site number, could be predicted by the recently developed GuideScan specificity score. Screens conducted in parallel with CRISPRi/a, which do not induce double-stranded DNA breaks, revealed that a distinct set of off-targets also cause strong confounding fitness effects with these epigenome-editing tools. Promisingly, filtering of CRISPRi libraries using GuideScan specificity scores removed these confounded sgRNAs and enabled identification of essential regulatory elements.

Measuring the reproducibility and quality of Hi-C data.

BACKGROUND: Hi-C is currently the most widely used assay to investigate the 3D organization of the genome and to study its role in gene regulation, DNA replication, and disease. However, Hi-C experiments are costly to perform and involve multiple complex experimental steps; thus, accurate methods for measuring the quality and reproducibility of Hi-C data are essential to determine whether the output should be used further in a study. RESULTS: Using real and simulated data, we profile the performance of several recently proposed methods for assessing reproducibility of population Hi-C data, including HiCRep, GenomeDISCO, HiC-Spector, and QuASAR-Rep. By explicitly controlling noise and sparsity through simulations, we demonstrate the deficiencies of performing simple correlation analysis on pairs of matrices, and we show that methods developed specifically for Hi-C data produce better measures of reproducibility. We also show how to use established measures, such as the ratio of intra- to interchromosomal interactions, and novel ones, such as QuASAR-QC, to identify low-quality experiments. CONCLUSIONS: In this work, we assess reproducibility and quality measures by varying sequencing depth, resolution and noise levels in Hi-C data from 13 cell lines, with two biological replicates each, as well as 176 simulated matrices. Through this extensive validation and benchmarking of Hi-C data, we describe best practices for reproducibility and quality assessment of Hi-C experiments. We make all software publicly available at http://github.com/kundajelab/3DChromatin_ReplicateQC to facilitate adoption in the community.

TRAF6: A player in CVB3-induced myocarditis?

Coxsackievirus B3 (CVB3) is an important inducer of myocarditis, which, in susceptible individuals, can chronify and eventually lead to the development of dilated cardiomyopathy and heart failure. The respective mechanisms are not completely understood. Here, we analyzed expression of the TRAF6 gene, encoding TNF receptor-associated factor 6 (TRAF6), a signal transduction scaffold protein that acts downstream of cytokine receptors, in heart tissue of susceptible and non-susceptible mouse strains. We found that after infection, TRAF6 expression was upregulated in both non-susceptible C57BL/6 wildtype and susceptible A.BY/SnJ and C57BL/6-TLR3 (-/-) mice, however, to different degrees. In infected HeLa cells, we also found moderately elevated TRAF6 levels after infection, in addition, activity of the transcription factor nuclear factor kappa B (NFκB), which can be activated downstream of TRAF6, was strongly enhanced in infected cells. To functionally analyze the role of TRAF6 with regard to infection progression, TRAF6 expression was knocked down in cultured HeLa cells using specific siRNAs. We found that reduction of TRAF6 expression had no effect on NFκB activation in response to infection. Taken together, our data suggest that CVB3 infection enhances TRAF6 levels, however, this induction might not be necessary for infection-induced NFκB activation.

NETWORK MODELLING OF TOPOLOGICAL DOMAINS USING HI-C DATA.

Chromosome conformation capture experiments such as Hi-C are used to map the three-dimensional spatial organization of genomes. One specific feature of the 3D organization is known as topologically associating domains (TADs), which are densely interacting, contiguous chromatin regions playing important roles in regulating gene expression. A few algorithms have been proposed to detect TADs. In particular, the structure of Hi-C data naturally inspires application of community detection methods. However, one of the drawbacks of community detection is that most methods take exchangeability of the nodes in the network for granted; whereas the nodes in this case, that is, the positions on the chromosomes, are not exchangeable. We propose a network model for detecting TADs using Hi-C data that takes into account this nonexchangeability. in addition, our model explicitly makes use of cell-type specific CTCF binding sites as biological covariates and can be used to identify conserved TADs across multiple cell types. The model leads to a likelihood objective that can be efficiently optimized via relaxation. We also prove that when suitably initialized, this model finds the underlying TAD structure with high probability. using simulated data, we show the advantages of our method and the caveats of popular community detection methods, such as spectral clustering, in this application. Applying our method to real Hi-C data, we demonstrate the domains identified have desirable epigenetic features and compare them across different cell types.

GenomeDISCO: a concordance score for chromosome conformation capture experiments using random walks on contact map graphs.

Motivation: The three-dimensional organization of chromatin plays a critical role in gene regulation and disease. High-throughput chromosome conformation capture experiments such as Hi-C are used to obtain genome-wide maps of three-dimensional chromatin contacts. However, robust estimation of data quality and systematic comparison of these contact maps is challenging due to the multi-scale, hierarchical structure of chromatin contacts and the resulting properties of experimental noise in the data. Measuring concordance of contact maps is important for assessing reproducibility of replicate experiments and for modeling variation between different cellular contexts. Results: We introduce a concordance measure called DIfferences between Smoothed COntact maps (GenomeDISCO) for assessing the similarity of a pair of contact maps obtained from chromosome conformation capture experiments. The key idea is to smooth contact maps using random walks on the contact map graph, before estimating concordance. We use simulated datasets to benchmark GenomeDISCO's sensitivity to different types of noise that affect chromatin contact maps. When applied to a large collection of Hi-C datasets, GenomeDISCO accurately distinguishes biological replicates from samples obtained from different cell types. GenomeDISCO also generalizes to other chromosome conformation capture assays, such as HiChIP. Availability and implementation: Software implementing GenomeDISCO is available at https://github.com/kundajelab/genomedisco. Supplementary information: Supplementary data are available at Bioinformatics online.

Network modeling of kinase inhibitor polypharmacology reveals pathways targeted in chemical screens.

Small molecule screens are widely used to prioritize pharmaceutical development. However, determining the pathways targeted by these molecules is challenging, since the compounds are often promiscuous. We present a network strategy that takes into account the polypharmacology of small molecules in order to generate hypotheses for their broader mode of action. We report a screen for kinase inhibitors that increase the efficacy of gemcitabine, the first-line chemotherapy for pancreatic cancer. Eight kinase inhibitors emerge that are known to affect 201 kinases, of which only three kinases have been previously identified as modifiers of gemcitabine toxicity. In this work, we use the SAMNet algorithm to identify pathways linking these kinases and genetic modifiers of gemcitabine toxicity with transcriptional and epigenetic changes induced by gemcitabine that we measure using DNaseI-seq and RNA-seq. SAMNet uses a constrained optimization algorithm to connect genes from these complementary datasets through a small set of protein-protein and protein-DNA interactions. The resulting network recapitulates known pathways including DNA repair, cell proliferation and the epithelial-to-mesenchymal transition. We use the network to predict genes with important roles in the gemcitabine response, including six that have already been shown to modify gemcitabine efficacy in pancreatic cancer and ten novel candidates. Our work reveals the important role of polypharmacology in the activity of these chemosensitizing agents.

Genome-scale measurement of off-target activity using Cas9 toxicity in high-throughput screens.

CRISPR-Cas9 screens are powerful tools for high-throughput interrogation of genome function, but can be confounded by nuclease-induced toxicity at both on- and off-target sites, likely due to DNA damage. Here, to test potential solutions to this issue, we design and analyse a CRISPR-Cas9 library with 10 variable-length guides per gene and thousands of negative controls targeting non-functional, non-genic regions (termed safe-targeting guides), in addition to non-targeting controls. We find this library has excellent performance in identifying genes affecting growth and sensitivity to the ricin toxin. The safe-targeting guides allow for proper control of toxicity from on-target DNA damage. Using this toxicity as a proxy to measure off-target cutting, we demonstrate with tens of thousands of guides both the nucleotide position-dependent sensitivity to single mismatches and the reduction of off-target cutting using truncated guides. Our results demonstrate a simple strategy for high-throughput evaluation of target specificity and nuclease toxicity in Cas9 screens.

Genetic Control of Chromatin States in Humans Involves Local and Distal Chromosomal Interactions.

Deciphering the impact of genetic variants on gene regulation is fundamental to understanding human disease. Although gene regulation often involves long-range interactions, it is unknown to what extent non-coding genetic variants influence distal molecular phenotypes. Here, we integrate chromatin profiling for three histone marks in lymphoblastoid cell lines (LCLs) from 75 sequenced individuals with LCL-specific Hi-C and ChIA-PET-based chromatin contact maps to uncover one of the largest collections of local and distal histone quantitative trait loci (hQTLs). Distal QTLs are enriched within topologically associated domains and exhibit largely concordant variation of chromatin state coordinated by proximal and distal non-coding genetic variants. Histone QTLs are enriched for common variants associated with autoimmune diseases and enable identification of putative target genes of disease-associated variants from genome-wide association studies. These analyses provide insights into how genetic variation can affect human disease phenotypes by coordinated changes in chromatin at interacting regulatory elements.

Heme oxygenase-1 mediates oxidative stress and apoptosis in coxsackievirus B3-induced myocarditis.

BACKGROUND: Heme oxygenase-1 (HO-1), which is suggested to play a role in defending the organism against oxidative stress-mediated injuries, can be induced by diverse factors including viruses and iron. As coxsackievirus B3 (CVB3)-infected SWR/J mice susceptible for chronic myocarditis were found to have a significant iron incorporation and HO-1 upregulation in the myocardium, we aimed to investigate the molecular interplay between HO-1 expression and iron homeostasis in the outcome of viral myocarditis. METHODS AND RESULTS: In susceptible SWR/J mice, but not in resistant C57BL/6 mice, we observed at later stages of CVB3 myocarditis significant iron deposits in macrophages and also in cardiomyocytes, which were spatially associated with oxidative stress, upregulation of HO-1 and caspase-3 activation. HO-1, which is also expressed in cultivated RAW 264.7 macrophages upon incubation with iron and/or CVB3, could be downregulated by inhibition of NO/iNOS using L-NAME. Moreover, specific inhibition of HO-1 by tin mesoporphyrin revealed a suppression of superoxide production in iron and/or CVB3-treated macrophages. The molecular relationship of HO-1 and caspase-3 activation was proven by downregulation with HO-1 siRNA in iron- and/or CVB3-treated cultivated cells. Importantly, iron was found to increase viral replication in vitro. CONCLUSION: These results indicate that HO-1 induces a paracrine signalling in macrophages via reactive oxygen species production, mediating apoptosis of heart muscle cells at later stages of myocarditis. Notably, in genetically susceptible mice iron potentiates the detrimental effects of CVB3 by the NO/HO-1 pathway, thus increasing cardiac pathogenicity.

Structural basis of PI(4,5)P2-dependent regulation of GluA1 by phosphatidylinositol-5-phosphate 4-kinase, type II, alpha (PIP5K2A).

Ionotropic glutamate receptors are the most important excitatory receptors in the central nervous system, and their impairment can lead to multiple neuronal diseases. Here, we show that glutamate-induced currents in oocytes expressing GluA1 are increased by coexpression of the schizophrenia-associated phosphoinositide kinase PIP5K2A. This effect was due to enhanced membrane abundance and was blunted by a point mutation (N251S) in PIP5K2A. An increase in GluA1 currents was also observed upon acute injection of PI(4,5)P2, the main product of PIP5K2A. By expression of wild-type and mutant PIP5K2A in human embryonic kidney cells, we were able to provide evidence of impaired kinase activity of the mutant PIP5K2A. We defined the region K813-K823 of GluA1 as critical for the PI(4,5)P2 effect by performing an alanine scan that suggested PI(4,5)P2 binding to this area. A PIP strip assay revealed PI(4,5)P2 binding to the C-terminal GluA1 peptide. The present observations disclose a novel mechanism in the regulation of GluA1.

SAMNet: a network-based approach to integrate multi-dimensional high throughput datasets.

The rapid development of high throughput biotechnologies has led to an onslaught of data describing genetic perturbations and changes in mRNA and protein levels in the cell. Because each assay provides a one-dimensional snapshot of active signaling pathways, it has become desirable to perform multiple assays (e.g. mRNA expression and phospho-proteomics) to measure a single condition. However, as experiments expand to accommodate various cellular conditions, proper analysis and interpretation of these data have become more challenging. Here we introduce a novel approach called SAMNet, for Simultaneous Analysis of Multiple Networks, that is able to interpret diverse assays over multiple perturbations. The algorithm uses a constrained optimization approach to integrate mRNA expression data with upstream genes, selecting edges in the protein-protein interaction network that best explain the changes across all perturbations. The result is a putative set of protein interactions that succinctly summarizes the results from all experiments, highlighting the network elements unique to each perturbation. We evaluated SAMNet in both yeast and human datasets. The yeast dataset measured the cellular response to seven different transition metals, and the human dataset measured cellular changes in four different lung cancer models of Epithelial-Mesenchymal Transition (EMT), a crucial process in tumor metastasis. SAMNet was able to identify canonical yeast metal-processing genes unique to each commodity in the yeast dataset, as well as human genes such as ß-catenin and TCF7L2/TCF4 that are required for EMT signaling but escaped detection in the mRNA and phospho-proteomic data. Moreover, SAMNet also highlighted drugs likely to modulate EMT, identifying a series of less canonical genes known to be affected by the BCR-ABL inhibitor imatinib (Gleevec), suggesting a possible influence of this drug on EMT.

Altered stress stimulation of inward rectifier potassium channels in Andersen-Tawil syndrome.

Inward rectifier potassium channels of the Kir2 subfamily are important determinants of the electrical activity of brain and muscle cells. Genetic mutations in Kir2.1 associate with Andersen-Tawil syndrome (ATS), a familial disorder leading to stress-triggered periodic paralysis and ventricular arrhythmia. To identify the molecular mechanisms of this stress trigger, we analyze Kir channel function and localization electrophysiologically and by time-resolved confocal microscopy. Furthermore, we employ a mathematical model of muscular membrane potential. We identify a novel corticoid signaling pathway that, when activated by glucocorticoids, leads to enrichment of Kir2 channels in the plasma membranes of mammalian cell lines and isolated cardiac and skeletal muscle cells. We further demonstrate that activation of this pathway can either partly restore (40% of cases) or further impair (20% of cases) the function of mutant ATS channels, depending on the particular Kir2.1 mutation. This means that glucocorticoid treatment might either alleviate or deteriorate symptoms of ATS depending on the patient's individual Kir2.1 genotype. Thus, our findings provide a possible explanation for the contradictory effects of glucocorticoid treatment on symptoms in patients with ATS and may open new pathways for the design of personalized medicines in ATS therapy.