SuPreMo: a computational tool for streamlining in silico perturbation using sequence-based predictive models.

SUMMARY: The increasing development of sequence-based machine learning models has raised the demand for manipulating sequences for this application. However, existing approaches to edit and evaluate genome sequences using models have limitations, such as incompatibility with structural variants, challenges in identifying responsible sequence perturbations, and the need for vcf file inputs and phased data. To address these bottlenecks, we present Sequence Mutator for Predictive Models (SuPreMo), a scalable and comprehensive tool for performing and supporting in silico mutagenesis experiments. We then demonstrate how pairs of reference and perturbed sequences can be used with machine learning models to prioritize pathogenic variants or discover new functional sequences. AVAILABILITY AND IMPLEMENTATION: SuPreMo was written in Python, and can be run using only one line of code to generate both sequences and 3D genome disruption scores. The codebase, instructions for installation and use, and tutorials are on the GitHub page: https://github.com/ketringjoni/SuPreMo.

Systematic decoding of cis gene regulation defines context-dependent control of the multi-gene costimulatory receptor locus in human T cells.

Cis-regulatory elements (CREs) interact with trans regulators to orchestrate gene expression, but how transcriptional regulation is coordinated in multi-gene loci has not been experimentally defined. We sought to characterize the CREs controlling dynamic expression of the adjacent costimulatory genes CD28, CTLA4 and ICOS, encoding regulators of T cell-mediated immunity. Tiling CRISPR interference (CRISPRi) screens in primary human T cells, both conventional and regulatory subsets, uncovered gene-, cell subset- and stimulation-specific CREs. Integration with CRISPR knockout screens and assay for transposase-accessible chromatin with sequencing (ATAC-seq) profiling identified trans regulators influencing chromatin states at specific CRISPRi-responsive elements to control costimulatory gene expression. We then discovered a critical CCCTC-binding factor (CTCF) boundary that reinforces CRE interaction with CTLA4 while also preventing promiscuous activation of CD28. By systematically mapping CREs and associated trans regulators directly in primary human T cell subsets, this work overcomes longstanding experimental limitations to decode context-dependent gene regulatory programs in a complex, multi-gene locus critical to immune homeostasis.

SuPreMo: a computational tool for streamlining in silico perturbation using sequence-based predictive models.

Computationally editing genome sequences is a common bioinformatics task, but current approaches have limitations, such as incompatibility with structural variants, challenges in identifying responsible sequence perturbations, and the need for vcf file inputs and phased data. To address these bottlenecks, we present Sequence Mutator for Predictive Models (SuPreMo), a scalable and comprehensive tool for performing in silico mutagenesis. We then demonstrate how pairs of reference and perturbed sequences can be used with machine learning models to prioritize pathogenic variants or discover new functional sequences.

Comparing chromatin contact maps at scale: methods and insights.

Comparing chromatin contact maps is an essential step in quantifying how three-dimensional (3D) genome organization shapes development, evolution, and disease. However, no gold standard exists for comparing contact maps, and even simple methods often disagree. In this study, we propose novel comparison methods and evaluate them alongside existing approaches using genome-wide Hi-C data and 22,500 in silico predicted contact maps. We also quantify the robustness of methods to common sources of biological and technical variation, such as boundary size and noise. We find that simple difference-based methods such as mean squared error are suitable for initial screening, but biologically informed methods are necessary to identify why maps diverge and propose specific functional hypotheses. We provide a reference guide, codebase, and benchmark for rapidly comparing chromatin contact maps at scale to enable biological insights into the 3D organization of the genome.

Comparing chromatin contact maps at scale: methods and insights.

Comparing chromatin contact maps is an essential step in quantifying how three-dimensional (3D) genome organization shapes development, evolution, and disease. However, no gold standard exists for comparing contact maps, and even simple methods often disagree. In this study, we propose novel comparison methods and evaluate them alongside existing approaches using genome-wide Hi-C data and 22,500 in silico predicted contact maps. We also quantify the robustness of methods to common sources of biological and technical variation, such as boundary size and noise. We find that simple difference-based methods such as mean squared error are suitable for initial screening, but biologically informed methods are necessary to identify why maps diverge and propose specific functional hypotheses. We provide a reference guide, codebase, and benchmark for rapidly comparing chromatin contact maps at scale to enable biological insights into the 3D organization of the genome.

Oligogenic Architecture of Rare Noncoding Variants Distinguishes 4 Congenital Heart Disease Phenotypes.

BACKGROUND: Congenital heart disease (CHD) is highly heritable, but the power to identify inherited risk has been limited to analyses of common variants in small cohorts. METHODS: We performed reimputation of 4 CHD cohorts (n=55 342) to the TOPMed reference panel (freeze 5), permitting meta-analysis of 14 784 017 variants including 6 035 962 rare variants of high imputation quality as validated by whole genome sequencing. RESULTS: Meta-analysis identified 16 novel loci, including 12 rare variants, which displayed moderate or large effect sizes (median odds ratio, 3.02) for 4 separate CHD categories. Analyses of chromatin structure link 13 of the genome-wide significant loci to key genes in cardiac development; rs373447426 (minor allele frequency, 0.003 [odds ratio, 3.37 for Conotruncal heart disease]; P=1.49×10-8) is predicted to disrupt chromatin structure for 2 nearby genes BDH1 and DLG1 involved in Conotruncal development. A lead variant rs189203952 (minor allele frequency, 0.01 [odds ratio, 2.4 for left ventricular outflow tract obstruction]; P=1.46×10-8) is predicted to disrupt the binding sites of 4 transcription factors known to participate in cardiac development in the promoter of SPAG9. A tissue-specific model of chromatin conformation suggests that common variant rs78256848 (minor allele frequency, 0.11 [odds ratio, 1.4 for Conotruncal heart disease]; P=2.6×10-8) physically interacts with NCAM1 (PFDR=1.86×10-27), a neural adhesion molecule acting in cardiac development. Importantly, while each individual malformation displayed substantial heritability (observed h2 ranging from 0.26 for complex malformations to 0.37 for left ventricular outflow tract obstructive disease) the risk for different CHD malformations appeared to be separate, without genetic correlation measured by linkage disequilibrium score regression or regional colocalization. CONCLUSIONS: We describe a set of rare noncoding variants conferring significant risk for individual heart malformations which are linked to genes governing cardiac development. These results illustrate that the oligogenic basis of CHD and significant heritability may be linked to rare variants outside protein-coding regions conferring substantial risk for individual categories of cardiac malformation.

An atlas of lamina-associated chromatin across twelve human cell types reveals an intermediate chromatin subtype.

BACKGROUND: Association of chromatin with lamin proteins at the nuclear periphery has emerged as a potential mechanism to coordinate cell type-specific gene expression and maintain cellular identity via gene silencing. Unlike many histone modifications and chromatin-associated proteins, lamina-associated domains (LADs) are mapped genome-wide in relatively few genetically normal human cell types, which limits our understanding of the role peripheral chromatin plays in development and disease. RESULTS: To address this gap, we map LAMIN B1 occupancy across twelve human cell types encompassing pluripotent stem cells, intermediate progenitors, and differentiated cells from all three germ layers. Integrative analyses of this atlas with gene expression and repressive histone modification maps reveal that lamina-associated chromatin in all twelve cell types is organized into at least two subtypes defined by differences in LAMIN B1 occupancy, gene expression, chromatin accessibility, transposable elements, replication timing, and radial positioning. Imaging of fluorescently labeled DNA in single cells validates these subtypes and shows radial positioning of LADs with higher LAMIN B1 occupancy and heterochromatic histone modifications primarily embedded within the lamina. In contrast, the second subtype of lamina-associated chromatin is relatively gene dense, accessible, dynamic across development, and positioned adjacent to the lamina. Most genes gain or lose LAMIN B1 occupancy consistent with cell types along developmental trajectories; however, we also identify examples where the enhancer, but not the gene body and promoter, changes LAD state. CONCLUSIONS: Altogether, this atlas represents the largest resource to date for peripheral chromatin organization studies and reveals an intermediate chromatin subtype.

Transcription factor overexpression drives reliable differentiation of retinal pigment epithelium from human induced pluripotent stem cells.

Age-related macular degeneration and genetic forms of blindness such as Best Disease and Retinitis Pigmentosa can be caused by degeneration of the Retinal Pigment Epithelium (RPE). RPE generated from patient-derived induced pluripotent stem cells (iPSCs) is valuable for both the study of disease mechanisms and development of therapeutic strategies. However, protocols to produce iPSC-derived RPE in vitro are often inefficient, labor-intensive, low-throughput, and highly variable between cell lines and within batches. Here, we report a robust, scalable method to generate iPSC-RPE using doxycycline-inducible expression of eye field transcription factors OTX2, PAX6 and MITF paired with RPE-permissive culture media. Doxycycline addition induces exogenous expression of these transcription factors in Best Disease patient- and wildtype iPSCs to efficiently produce monolayers of RPE with characteristic morphology and gene expression. Further, these RPE monolayers display functionality features including light absorption via pigmentation, polarity-driven fluid transport, and phagocytosis. With this method, we achieve a highly efficient and easily scalable differentiation without the need for mechanical isolation or enrichment methods, generating RPE cultures applicable for in vitro studies.

Rapid, precise quantification of large DNA excisions and inversions by ddPCR.

The excision of genomic sequences using paired CRISPR-Cas nucleases is a powerful tool to study gene function, create disease models and holds promise for therapeutic gene editing. However, our understanding of the factors that favor efficient excision is limited by the lack of a rapid, accurate measurement of DNA excision outcomes that is free of amplification bias. Here, we introduce ddXR (droplet digital PCR eXcision Reporter), a method that enables the accurate and sensitive detection of excisions and inversions independent of length. The method can be completed in a few hours without the need for next-generation sequencing. The ddXR method uncovered unexpectedly high rates of large (> 20 kb) excisions and inversions, while also revealing a surprisingly low dependence on linear distance, up to 170 kb. We further modified the method to measure precise repair of excision junctions and allele-specific excision, with important implications for disease modeling and therapeutic gene editing.

Cellular response to small molecules that selectively stall protein synthesis by the ribosome.

Identifying small molecules that inhibit protein synthesis by selectively stalling the ribosome constitutes a new strategy for therapeutic development. Compounds that inhibit the translation of PCSK9, a major regulator of low-density lipoprotein cholesterol, have been identified that reduce LDL cholesterol in preclinical models and that affect the translation of only a few off-target proteins. Although some of these compounds hold potential for future therapeutic development, it is not known how they impact the physiology of cells or ribosome quality control pathways. Here we used a genome-wide CRISPRi screen to identify proteins and pathways that modulate cell growth in the presence of high doses of a selective PCSK9 translational inhibitor, PF-06378503 (PF8503). The two most potent genetic modifiers of cell fitness in the presence of PF8503, the ubiquitin binding protein ASCC2 and helicase ASCC3, bind to the ribosome and protect cells from toxic effects of high concentrations of the compound. Surprisingly, translation quality control proteins Pelota (PELO) and HBS1L sensitize cells to PF8503 treatment. In genetic interaction experiments, ASCC3 acts together with ASCC2, and functions downstream of HBS1L. Taken together, these results identify new connections between ribosome quality control pathways, and provide new insights into the selectivity of compounds that stall human translation that will aid the development of next-generation selective translation stalling compounds to treat disease.