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Congregate homeless shelters are disproportionately affected by infectious disease outbreaks. We describe enterovirus epidemiology across 23 adult and family shelters in King County, Washington, USA, during October 2019–May 2021, by using repeated cross-sectional respiratory illness and environmental surveillance and viral genome sequencing. Among 3,281 participants >3 months of age, we identified coxsackievirus A21 (CVA21) in 39 adult residents (3.0% [95% CI 1.9%–4.8%] detection) across 7 shelters during October 2019–February 2020. We identified enterovirus D68 (EV-D68) in 5 adult residents in 2 shelters during October–November 2019. Of 812 environmental samples, 1 was EV-D68–positive and 5 were CVA21–positive. Other enteroviruses detected among residents, but not in environmental samples, included coxsackievirus A6/A4 in 3 children. No enteroviruses were detected during April 2020–May 2021. Phylogenetically clustered CVA21 and EV-D68 cases occurred in some shelters. Some shelters also hosted multiple CVA21 lineages.

Abstract CRISPR-based gene activation (CRISPRa) is a strategy for upregulating gene expression by targeting promoters or enhancers in a tissue/cell-type specific manner. Here, we describe an experimental framework that combines highly multiplexed perturbations with single-cell RNA sequencing (sc-RNA-seq) to identify cell-type-specific, CRISPRa-responsive cis-regulatory elements and the gene(s) they regulate. Random combinations of many gRNAs are introduced to each of many cells, which are then profiled and partitioned into test and control groups to test for effect(s) of CRISPRa perturbations of both enhancers and promoters on the expression of neighboring genes. Applying this method to a library of 493 gRNAs targeting candidate cis-regulatory elements in both K562 cells and iPSC-derived excitatory neurons, we identify gRNAs capable of specifically upregulating intended target genes and no other neighboring genes within 1 Mb, including gRNAs yielding upregulation of six autism spectrum disorder (ASD) and neurodevelopmental disorder (NDD) risk genes in neurons. A consistent pattern is that the responsiveness of individual enhancers to CRISPRa is restricted by cell type, implying a dependency on either chromatin landscape and/or additional trans-acting factors for successful gene activation. The approach outlined here may facilitate large-scale screens for gRNAs that activate genes in a cell type-specific manner.

Abstract Sex differences and age-related changes in the human heart at the tissue, cell, and molecular level have been well-documented and many may be relevant for cardiovascular disease. However, how molecular programs within individual cell types vary across individuals by age and sex remains poorly characterized. To better understand this variation, we performed single-nucleus combinatorial indexing (sci) ATAC- and RNA-Seq in human heart samples from nine donors. We identify hundreds of differentially expressed genes by age and sex and find epigenetic signatures of variation in ATAC-Seq data in this discovery cohort. We then scale up our single-cell RNA-Seq analysis by combining our data with five recently published single nucleus RNA-Seq datasets of healthy adult hearts. We find variation such as metabolic alterations by sex and immune changes by age in differential expression tests, as well as alterations in abundance of cardiomyocytes by sex and neurons with age. In addition, we compare our adult-derived ATAC-Seq profiles to analogous fetal cell types to identify putative developmental-stage-specific regulatory factors. Finally, we train predictive models of cell-type-specific RNA expression levels utilizing ATAC-Seq profiles to link distal regulatory sequences to promoters, quantifying the predictive value of a simple TF-to-expression regulatory grammar and identifying cell-type-specific TFs. Our analysis represents the largest single-cell analysis of cardiac variation by age and sex to date and provides a resource for further study of healthy cardiac variation and transcriptional regulation at single-cell resolution.

Abstract Many studies have used mobile device location data to model SARS-CoV-2 dynamics, yet relationships between mobility behavior and endemic respiratory pathogens are less understood. We studied the effects of population mobility on the transmission of 17 endemic viruses and SARS-CoV-2 in Seattle over a 4-year period, 2018-2022. Before 2020, visits to schools and daycares, within-city mixing, and visitor inflow preceded or coincided with seasonal outbreaks of endemic viruses. Pathogen circulation dropped substantially after the initiation of COVID-19 stay-at-home orders in March 2020. During this period, mobility was a positive, leading indicator of transmission of all endemic viruses and lagging and negatively correlated with SARS-CoV-2 activity. Mobility was briefly predictive of SARS-CoV-2 transmission when restrictions relaxed but associations weakened in subsequent waves. The rebound of endemic viruses was heterogeneously timed but exhibited stronger, longer-lasting relationships with mobility than SARS-CoV-2. Overall, mobility is most predictive of respiratory virus transmission during periods of dramatic behavioral change and at the beginning of epidemic waves.

Abstract Single-cell chromatin accessibility has emerged as a powerful means of understanding the epigenetic landscape of diverse tissues and cell types, but profiling cells from many independent specimens is challenging and costly. Here we describe a novel approach, sciPlex-ATAC-seq, which uses unmodified DNA oligos as sample-specific nuclear labels, enabling the concurrent profiling of chromatin accessibility within single nuclei from virtually unlimited specimens or experimental conditions. We first demonstrate our method with a chemical epigenomics screen, in which we identify drug-altered distal regulatory sites predictive of compound- and dose-dependent effects on transcription. We then analyze cell type-specific chromatin changes in PBMCs from multiple donors responding to synthetic and allogeneic immune stimulation. We quantify stimulation-altered immune cell compositions and isolate the unique effects of allogeneic stimulation on chromatin accessibility specific to T-lymphocytes. Finally, we observe that impaired global chromatin decondensation often coincides with chemical inhibition of allogeneic T-cell activation.

SARS-CoV-2 transmission is largely driven by heterogeneous dynamics at a local scale, leaving local health departments to design interventions with limited information. We analyzed SARS-CoV-2 genomes sampled between February 2020 and March 2022 jointly with epidemiological and cell phone mobility data to investigate fine scale spatiotemporal SARS-CoV-2 transmission dynamics in King County, Washington, a diverse, metropolitan US county. We applied an approximate structured coalescent approach to model transmission within and between North King County and South King County alongside the rate of outside introductions into the county. Our phylodynamic analyses reveal that following stay-at-home orders, the epidemic trajectories of North and South King County began to diverge. We find that South King County consistently had more reported and estimated cases, COVID-19 hospitalizations, and longer persistence of local viral transmission when compared to North King County, where viral importations from outside drove a larger proportion of new cases. Using mobility and demographic data, we also find that South King County experienced a more modest and less sustained reduction in mobility following stay-at-home orders than North King County, while also bearing more socioeconomic inequities that might contribute to a disproportionate burden of SARS-CoV-2 transmission. Overall, our findings suggest a role for local-scale phylodynamics in understanding the heterogeneous transmission landscape.

Abstract Recent advances in multiplexed single‐cell transcriptomics experiments facilitate the high‐throughput study of drug and genetic perturbations. However, an exhaustive exploration of the combinatorial perturbation space is experimentally unfeasible. Therefore, computational methods are needed to predict, interpret, and prioritize perturbations. Here, we present the compositional perturbation autoencoder (CPA), which combines the interpretability of linear models with the flexibility of deep‐learning approaches for single‐cell response modeling. CPA learns to in silico predict transcriptional perturbation response at the single‐cell level for unseen dosages, cell types, time points, and species. Using newly generated single‐cell drug combination data, we validate that CPA can predict unseen drug combinations while outperforming baseline models. Additionally, the architecture's modularity enables incorporating the chemical representation of the drugs, allowing the prediction of cellular response to completely unseen drugs. Furthermore, CPA is also applicable to genetic combinatorial screens. We demonstrate this by imputing in silico 5,329 missing combinations (97.6% of all possibilities) in a single‐cell Perturb‐seq experiment with diverse genetic interactions. We envision CPA will facilitate efficient experimental design and hypothesis generation by enabling in silico response prediction at the single‐cell level and thus accelerate therapeutic applications using single‐cell technologies.

This study presents results from a SARS-CoV-2 genomic surveillance study at a university campus in which ~2,000 samples were sequenced over five months. The authors document the replacement of Delta with Omicron as the dominant variant, and describe clinical characteristics and transmission dynamics.

BackgroundRespiratory viruses might influence Streptococcus pneumoniae nasal carriage and subsequent disease risk. We estimated the association between common respiratory viruses and semiquantitative S. pneumoniae nasal carriage density in a household setting before and during the COVID-19 pandemic.MethodsFrom November 2019–June 2021, we enrolled participants in a remote household surveillance study of respiratory pathogens. Participants submitted weekly reports of acute respiratory illness (ARI) symptoms. Mid-turbinate or anterior nasal swabs were self-collected at enrollment, when ARI occurred, and, in the second year of the study only, from household contacts after SARS-CoV-2 was detected in a household member. Specimens were tested using multiplex reverse-transcription PCR for respiratory pathogens, including S. pneumoniae, rhinovirus, adenovirus, common human coronavirus, influenza A/B virus, respiratory syncytial virus (RSV) A/B, human metapneumovirus, enterovirus, and human parainfluenza virus. We estimated differences in semiquantitative S. pneumoniae nasal carriage density, estimated by the inverse of S. pneumoniae relative cycle threshold (Crt) values, with and without viral detection for any virus and for specific respiratory viruses using linear generalized estimating equations of S. pneumoniae Crt values on virus detection adjusted for age and swab type and accounting for clustering of swabs within households.ResultsWe collected 346 swabs from 239 individuals in 151 households that tested positive for S. pneumoniae (n = 157 with and 189 without ≥1 viruses co-detected). Difficulty breathing, cough, and runny nose were more commonly reported among individuals with specimens with viral co-detection compared to without (15%, 80% and 93% vs. 8%, 57%, and 51%, respectively) and ear pain and headache were less commonly reported (3% and 26% vs. 16% and 41%, respectively). For specific viruses among all ages, semiquantitative S. pneumoniae nasal carriage density was greater with viral co-detection for enterovirus, RSV A/B, adenovirus, rhinovirus, and common human coronavirus (P

Abstract Background Mammalian development is associated with extensive changes in gene expression, chromatin accessibility, and nuclear structure. Here, we follow such changes associated with mouse embryonic stem cell differentiation and X inactivation by integrating, for the first time, allele-specific data from these three modalities obtained by high-throughput single-cell RNA-seq, ATAC-seq, and Hi-C. Results Allele-specific contact decay profiles obtained by single-cell Hi-C clearly show that the inactive X chromosome has a unique profile in differentiated cells that have undergone X inactivation. Loss of this inactive X-specific structure at mitosis is followed by its reappearance during the cell cycle, suggesting a “bookmark” mechanism. Differentiation of embryonic stem cells to follow the onset of X inactivation is associated with changes in contact decay profiles that occur in parallel on both the X chromosomes and autosomes. Single-cell RNA-seq and ATAC-seq show evidence of a delay in female versus male cells, due to the presence of two active X chromosomes at early stages of differentiation. The onset of the inactive X-specific structure in single cells occurs later than gene silencing, consistent with the idea that chromatin compaction is a late event of X inactivation. Single-cell Hi-C highlights evidence of discrete changes in nuclear structure characterized by the acquisition of very long-range contacts throughout the nucleus. Novel computational approaches allow for the effective alignment of single-cell gene expression, chromatin accessibility, and 3D chromosome structure. Conclusions Based on trajectory analyses, three distinct nuclear structure states are detected reflecting discrete and profound simultaneous changes not only to the structure of the X chromosomes, but also to that of autosomes during differentiation. Our study reveals that long-range structural changes to chromosomes appear as discrete events, unlike progressive changes in gene expression and chromatin accessibility.

Alternative polyadenylation regulates localization, half-life and translation of mRNA isoforms. Here the authors investigate alternative polyadenylation using single cell RNA sequencing data from mouse embryos and identify 3’-UTR isoforms that are regulated across cell types and developmental time.

Abstract Background Splicing of genomic exons into mRNAs is a critical prerequisite for the accurate synthesis of human proteins. Genetic variants impacting splicing underlie a substantial proportion of genetic disease, but are challenging to identify beyond those occurring at donor and acceptor dinucleotides. To address this, various methods aim to predict variant effects on splicing. Recently, deep neural networks (DNNs) have been shown to achieve better results in predicting splice variants than other strategies. Methods It has been unclear how best to integrate such process-specific scores into genome-wide variant effect predictors. Here, we use a recently published experimental data set to compare several machine learning methods that score variant effects on splicing. We integrate the best of those approaches into general variant effect prediction models and observe the effect on classification of known pathogenic variants. Results We integrate two specialized splicing scores into CADD (Combined Annotation Dependent Depletion; cadd.gs.washington.edu ), a widely used tool for genome-wide variant effect prediction that we previously developed to weight and integrate diverse collections of genomic annotations. With this new model, CADD-Splice, we show that inclusion of splicing DNN effect scores substantially improves predictions across multiple variant categories, without compromising overall performance. Conclusions While splice effect scores show superior performance on splice variants, specialized predictors cannot compete with other variant scores in general variant interpretation, as the latter account for nonsense and missense effects that do not alter splicing. Although only shown here for splice scores, we believe that the applied approach will generalize to other specific molecular processes, providing a path for the further improvement of genome-wide variant effect prediction.

Firre encodes a lncRNA involved in nuclear organization in mammals. Here, the authors find that allelic deletion of Firre on the active X chromosome (Xa) results in dose-dependent loss of histone H3K27me3 on the inactive X chromosome (Xi), along with other trans-acting effects, including disruption of the perinuclear location and minor dysregulation of gene expression.

Objective: Type 2 diabetes (T2D) is a complex disease characterized by pancreatic islet dysfunction, insulin resistance, and disruption of blood glucose levels. Genome-wide association studies (GWAS) have identified > 400 independent signals that encode genetic predisposition. More than 90% of associated single-nucleotide polymorphisms (SNPs) localize to non-coding regions and are enriched in chromatin-defined islet enhancer elements, indicating a strong transcriptional regulatory component to disease susceptibility. Pancreatic islets are a mixture of cell types that express distinct hormonal programs, so each cell type may contribute differentially to the underlying regulatory processes that modulate T2D-associated transcriptional circuits. Existing chromatin profiling methods such as ATAC-seq and DNase-seq, applied to islets in bulk, produce aggregate profiles that mask important cellular and regulatory heterogeneity. Methods: We present genome-wide single-cell chromatin accessibility profiles in >1,600 cells derived from a human pancreatic islet sample using single-cell combinatorial indexing ATAC-seq (sci-ATAC-seq). We also developed a deep learning model based on U-Net architecture to accurately predict open chromatin peak calls in rare cell populations. Results: We show that sci-ATAC-seq profiles allow us to deconvolve alpha, beta, and delta cell populations and identify cell-type-specific regulatory signatures underlying T2D. Particularly, T2D GWAS SNPs are significantly enriched in beta cell-specific and across cell-type shared islet open chromatin, but not in alpha or delta cell-specific open chromatin. We also demonstrate, using less abundant delta cells, that deep learning models can improve signal recovery and feature reconstruction of rarer cell populations. Finally, we use co-accessibility measures to nominate the cell-specific target genes at 104 non-coding T2D GWAS signals. Conclusions: Collectively, we identify the islet cell type of action across genetic signals of T2D predisposition and provide higher-resolution mechanistic insights into genetically encoded risk pathways. Keywords: Islet, Epigenomics, Deep learning, Single cell, Chromatin, Type 2 diabetes

Abstract Variants of uncertain significance represent a massive challenge to medical genetics. Multiplexed functional assays, in which the functional effects of thousands of genomic variants are assessed simultaneously, are increasingly generating data that can be used as additional evidence for or against variant pathogenicity. Such assays have the potential to resolve variants of uncertain significance, thereby increasing the clinical utility of genomic testing. Existing standards from the American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) and new guidelines from the Clinical Genome Resource (ClinGen) establish the role of functional data in variant interpretation, but do not address the specific challenges or advantages of using functional data derived from multiplexed assays. Here, we build on these existing guidelines to provide recommendations to experimentalists for the production and reporting of multiplexed functional data and to clinicians for the evaluation and use of such data. By following these recommendations, experimentalists can produce transparent, complete, and well-validated datasets that are primed for clinical uptake. Our recommendations to clinicians and diagnostic labs on how to evaluate the quality of multiplexed functional datasets, and how different datasets could be incorporated into the ACMG/AMP variant-interpretation framework, will hopefully clarify whether and how such data should be used. The recommendations that we provide are designed to enhance the quality and utility of multiplexed functional data, and to promote their judicious use.

Male germ cell (GC) production is a metabolically driven and apoptosis-prone process. Here, we show that the glucose-sensing transcription factor (TF) MAX-Like protein X (MLX) and its binding partner MondoA are both required for male fertility in the mouse, as well as survival of human tumor cells derived from the male germ line. Loss of Mlx results in altered metabolism as well as activation of multiple stress pathways and GC apoptosis in the testes. This is concomitant with dysregulation of the expression of male-specific GC transcripts and proteins. Our genomic and functional analyses identify loci directly bound by MLX involved in these processes, including metabolic targets, obligate components of male-specific GC development, and apoptotic effectors. These in vivo and in vitro studies implicate MLX and other members of the proximal MYC network, such as MNT, in regulation of metabolism and differentiation, as well as in suppression of intrinsic and extrinsic death signaling pathways in both spermatogenesis and male germ cell tumors (MGCTs).

Abstract Background Recent advances in genome editing have facilitated the direct manipulation of not only the genome, but also the epigenome. Genome editing is typically performed by introducing a single CRISPR/Cas9-mediated double-strand break (DSB), followed by non-homologous end joining (NHEJ)- or homology-directed repair-mediated repair. Epigenome editing, and in particular methylation of CpG dinucleotides, can be performed using catalytically inactive Cas9 (dCas9) fused to a methyltransferase domain. However, for investigations of the role of methylation in gene silencing, studies based on dCas9-methyltransferase have limited resolution and are potentially confounded by the effects of binding of the fusion protein. As an alternative strategy for epigenome editing, we tested CRISPR/Cas9 dual cutting of the genome in the presence of in vitro methylated exogenous DNA, with the aim of driving replacement of the DNA sequence intervening the dual cuts via NHEJ. Results In a proof of concept at the HPRT1 promoter, successful replacement events with heavily methylated alleles of a CpG island resulted in functional silencing of the HPRT1 gene. Although still limited in efficiency, our study demonstrates concurrent epigenome and genome editing in a single event. Conclusions This study opens the door to investigations of the functional consequences of methylation patterns at single CpG dinucleotide resolution. Our results furthermore support the conclusion that promoter methylation is sufficient to functionally silence gene expression.

Abstract Multiplex assays of variant effect (MAVEs), such as deep mutational scans and massively parallel reporter assays, test thousands of sequence variants in a single experiment. Despite the importance of MAVE data for basic and clinical research, there is no standard resource for their discovery and distribution. Here, we present MaveDB (https://www.mavedb.org), a public repository for large-scale measurements of sequence variant impact, designed for interoperability with applications to interpret these datasets. We also describe the first such application, MaveVis, which retrieves, visualizes, and contextualizes variant effect maps. Together, the database and applications will empower the community to mine these powerful datasets.

Interpreting genetic variation in the noncoding genome remains challenging, with functional effects difficult to predict. Here, the authors perform saturation mutagenesis combined with massively parallel reporter assays for 20 disease-associated regulatory elements, quantifying the effects of over 30,000 variants.

GWAS have identified risk loci for osteoarthritis (OA), but the causal variants still have to be determined. Here, the authors apply a massively-parallel reporter assay to screen 1,605 candidate SNPs in 35 OA loci, which prioritizes six SNPs in four loci, one of which, rs4730222, is characterized in more detail.

Resistance to antibiotics hampers the treatment of infectious diseases such as tuberculosis (TB). Here, Farhat et al. perform genome-wide association testing for minimum inhibitory concentration (MIC) of 12 anti-TB drugs in whole-genome sequenced clinical M. tuberculosis isolates and identify 13 genomic loci.

The spatial organization of the genome plays an important but unclearly defined role in gene regulation. Here, the authors integrate Hi-C, RNA-seq and ATAC-seq data to map cardiogenesis from pluripotent stem cells and describe an RBM20-dependent splicing factory assembling the TTN locus with other RBM20 targets.

Introduction Influenza epidemics and pandemics cause significant morbidity and mortality. An effective response to a potential pandemic requires the infrastructure to rapidly detect, characterise, and potentially contain new and emerging influenza strains at both an individual and population level. The objective of this study is to use data gathered simultaneously from community and hospital sites to develop a model of how influenza enters and spreads in a population.Methods and analysis Starting in the 2018–2019 season, we have been enrolling individuals with acute respiratory illness from community sites throughout the Seattle metropolitan area, including clinics, childcare facilities, Seattle-Tacoma International Airport, workplaces, college campuses and homeless shelters. At these sites, we collect clinical data and mid-nasal swabs from individuals with at least two acute respiratory symptoms. Additionally, we collect residual nasal swabs and data from individuals who seek care for respiratory symptoms at four regional hospitals. Samples are tested using a multiplex molecular assay, and influenza whole genome sequencing is performed for samples with influenza detected. Geospatial mapping and computational modelling platforms are in development to characterise the regional spread of influenza and other respiratory pathogens.Ethics and dissemination The study was approved by the University of Washington’s Institutional Review Board (STUDY00006181). Results will be disseminated through talks at conferences, peer-reviewed publications and on the study website (www.seattleflu.org).

Single-cell Hi-C (scHi-C) interrogates genome-wide chromatin interaction in individual cells, allowing us to gain insights into 3D genome organization. However, the extremely sparse nature of scHi-C data poses a significant barrier to analysis, limiting our ability to tease out hidden biological information. In this work, we approach this problem by applying topic modeling to scHi-C data. Topic modeling is well-suited for discovering latent topics in a collection of discrete data. For our analysis, we generate nine different single-cell combinatorial indexed Hi-C (sci-Hi-C) libraries from five human cell lines (GM12878, H1Esc, HFF, IMR90, and HAP1), consisting over 19,000 cells. We demonstrate that topic modeling is able to successfully capture cell type differences from sci-Hi-C data in the form of "chromatin topics." We further show enrichment of particular compartment structures associated with locus pairs in these topics.

Pseudomonas aeruginosa colonizes the airways of cystic fibrosis (CF) patients, causing infections that can last for decades. During the course of these infections, P. aeruginosa undergoes a number of genetic adaptations. One such adaptation is the loss of swimming motility functions. Another involves the formation of the rugose small colony variant (RSCV) phenotype, which is characterized by overproduction of the exopolysaccharides Pel and Psl. Here, we provide evidence that the two adaptations are linked. Using random transposon mutagenesis, we discovered that flagellar mutations are linked to the RSCV phenotype. We found that flagellar mutants overexpressed Pel and Psl in a surface-contact dependent manner. Genetic analyses revealed that flagellar mutants were selected for at high frequencies in biofilms, and that Pel and Psl expression provided the primary fitness benefit in this environment. Suppressor mutagenesis of flagellar RSCVs indicated that Psl overexpression required the mot genes, suggesting that the flagellum stator proteins function in a surface-dependent regulatory pathway for exopolysaccharide biosynthesis. Finally, we identified flagellar mutant RSCVs among CF isolates. The CF environment has long been known to select for flagellar mutants, with the classic interpretation being that the fitness benefit gained relates to an impairment of the host immune system to target a bacterium lacking a flagellum. Our new findings lead us to propose that exopolysaccharide production is a key gain-of-function phenotype that offers a new way to interpret the fitness benefits of these mutations.

Summary: Algorithms that accurately predict gene structure from primary sequence alone were transformative for annotating the human genome. Can we also predict the expression levels of genes based solely on genome sequence? Here, we sought to apply deep convolutional neural networks toward that goal. Surprisingly, a model that includes only promoter sequences and features associated with mRNA stability explains 59% and 71% of variation in steady-state mRNA levels in human and mouse, respectively. This model, termed Xpresso, more than doubles the accuracy of alternative sequence-based models and isolates rules as predictive as models relying on chromatic immunoprecipitation sequencing (ChIP-seq) data. Xpresso recapitulates genome-wide patterns of transcriptional activity, and its residuals can be used to quantify the influence of enhancers, heterochromatic domains, and microRNAs. Model interpretation reveals that promoter-proximal CpG dinucleotides strongly predict transcriptional activity. Looking forward, we propose cell-type-specific gene-expression predictions based solely on primary sequences as a grand challenge for the field.

Abstract Background Enhancers play an important role in morphological evolution and speciation by controlling the spatiotemporal expression of genes. Previous efforts to understand the evolution of enhancers in primates have typically studied many enhancers at low resolution, or single enhancers at high resolution. Although comparative genomic studies reveal large-scale turnover of enhancers, a specific understanding of the molecular steps by which mammalian or primate enhancers evolve remains elusive. Results We identified candidate hominoid-specific liver enhancers from H3K27ac ChIP-seq data. After locating orthologs in 11 primates spanning around 40 million years, we synthesized all orthologs as well as computational reconstructions of 9 ancestral sequences for 348 active tiles of 233 putative enhancers. We concurrently tested all sequences for regulatory activity with STARR-seq in HepG2 cells. We observe groups of enhancer tiles with coherent trajectories, most of which can be potentially explained by a single gain or loss-of-activity event per tile. We quantify the correlation between the number of mutations along a branch and the magnitude of change in functional activity. Finally, we identify 84 mutations that correlate with functional changes; these are enriched for cytosine deamination events within CpGs. Conclusions We characterized the evolutionary-functional trajectories of hundreds of liver enhancers throughout the primate phylogeny. We observe subsets of regulatory sequences that appear to have gained or lost activity. We use these data to quantify the relationship between sequence and functional divergence, and to identify CpG deamination as a potentially important force in driving changes in enhancer activity during primate evolution.

Abstract Background Genome-wide knockout studies, noncoding deletion scans, and other large-scale studies require a simple and lightweight framework that can quickly discover and score thousands of candidate CRISPR guides targeting an arbitrary DNA sequence. While several CRISPR web applications exist, there is a need for a high-throughput tool to rapidly discover and process hundreds of thousands of CRISPR targets. Results Here, we introduce FlashFry, a fast and flexible command-line tool for characterizing large numbers of CRISPR target sequences. With FlashFry, users can specify an unconstrained number of mismatches to putative off-targets, richly annotate discovered sites, and tag potential guides with commonly used on-target and off-target scoring metrics. FlashFry runs at speeds comparable to commonly used genome-wide sequence aligners, and output is provided as an easy-to-manipulate text file. Conclusions FlashFry is a fast and convenient command-line tool to discover and score CRISPR targets within large DNA sequences.

Abstract A comprehensive characterization of tumor genetic heterogeneity is critical for understanding how cancers evolve and escape treatment. Although many algorithms have been developed for capturing tumor heterogeneity, they are designed for analyzing either a single type of genomic aberration or individual biopsies. Here we present THEMIS (Tumor Heterogeneity Extensible Modeling via an Integrative System), which allows for the joint analysis of different types of genomic aberrations from multiple biopsies taken from the same patient, using a dynamic graphical model. Simulation experiments demonstrate higher accuracy of THEMIS over its ancestor, TITAN. The heterogeneity analysis results from THEMIS are validated with single cell DNA sequencing from a clinical tumor biopsy. When THEMIS is used to analyze tumor heterogeneity among multiple biopsies from the same patient, it helps to reveal the mutation accumulation history, track cancer progression, and identify the mutations related to treatment resistance. We implement our model via an extensible modeling platform, which makes our approach open, reproducible, and easy for others to extend.

Abstract: Hemophilia A and B are rare, X-linked bleeding disorders. My Life, Our Future (MLOF) is a collaborative project established to genotype and study hemophilia. Patients were enrolled at US hemophilia treatment centers (HTCs). Genotyping was performed centrally using next-generation sequencing (NGS) with an approach that detected common F8 gene inversions simultaneously with F8 and F9 gene sequencing followed by confirmation using standard genotyping methods. Sixty-nine HTCs enrolled the first 3000 patients in under 3 years. Clinically reportable DNA variants were detected in 98.1% (2357/2401) of hemophilia A and 99.3% (595/599) of hemophilia B patients. Of the 924 unique variants found, 285 were novel. Predicted gene-disrupting variants were common in severe disease; missense variants predominated in mild–moderate disease. Novel DNA variants accounted for ∼30% of variants found and were detected continuously throughout the project, indicating that additional variation likely remains undiscovered. The NGS approach detected >1 reportable variants in 36 patients (10 females), a finding with potential clinical implications. NGS also detected incidental variants unlikely to cause disease, including 11 variants previously reported in hemophilia. Although these genes are thought to be conserved, our findings support caution in interpretation of new variants. In summary, MLOF has contributed significantly toward variant annotation in the F8 and F9 genes. In the near future, investigators will be able to access MLOF data and repository samples for research to advance our understanding of hemophilia.

Transcriptome sequencing is a powerful tool for functional analysis of different types of RNA molecules in a wide range of applications. Here the authors use targeted resequencing of cDNA with single-molecule molecular inversion probes as a cost-effective, high-throughput tool for mRNA quantification.

The genome forms specific three-dimensional contacts in response to cellular or environmental conditions. However, it remains largely unknown which proteins specify and mediate such contacts. Here we describe an assay, MAP-C (Mutation Analysis in Pools by Chromosome conformation capture), that simultaneously characterizes the effects of hundreds of cis or trans-acting mutations on a chromosomal contact. Using MAP-C, we show that inducible interchromosomal pairing between HAS1pr-TDA1pr alleles in saturated cultures of Saccharomyces yeast is mediated by three transcription factors, Leu3, Sdd4 (Ypr022c), and Rgt1. The coincident, combined binding of all three factors is strongest at the HAS1pr-TDA1pr locus and is also specific to saturated conditions. We applied MAP-C to further explore the biochemical mechanism of these contacts, and find they require the structured regulatory domain of Rgt1, but no known interaction partners of Rgt1. Altogether, our results demonstrate MAP-C as a powerful method for dissecting the mechanistic basis of chromosome conformation.

The manner by which eukaryotic genomes are packaged into nuclei while maintaining crucial nuclear functions remains one of the fundamental mysteries in biology. Over the last ten years, we have witnessed rapid advances in both microscopic and nucleic acid-based approaches to map genome architecture, and the application of these approaches to the dissection of higher-order chromosomal structures has yielded much new information. It is becoming increasingly clear, for example, that interphase chromosomes form stable, multilevel hierarchical structures. Among them, self-associating domains like so-called topologically associating domains (TADs) appear to be building blocks for large-scale genomic organization. This review describes features of these broadly-defined hierarchical structures, insights into the mechanisms underlying their formation, our current understanding of how interactions in the nuclear space are linked to gene regulation, and important future directions for the field.

X chromosome inactivation (XCI) is a female-specific mechanism that serves to balance gene dosage between the sexes whereby one X chromosome in females is inactivated during early development. Despite this silencing, a small portion of genes escape inactivation and remain expressed from the inactive X (Xi). Little is known about the distribution of escape from XCI in different tissues in vivo and about the mechanisms that control tissue-specific differences. Using a new binomial model in conjunction with a mouse model with identifiable alleles and skewed X inactivation we are able to survey genes that escape XCI in vivo. We show that escape from X inactivation can be a common feature of some genes, whereas others escape in a tissue specific manner. Furthermore, we characterize the chromatin environment of escape genes and show that expression from the Xi correlates with factors associated with open chromatin and that CTCF co-localizes with escape genes. Here, we provide a detailed description of the experimental design and data analysis pipeline we used to assay allele-specific expression and epigenetic characteristics of genes escaping X inactivation. The data is publicly available through the GEO database under ascension numbers GSM1014171, GSE44255, and GSE59779. Interpretation and discussion of these data are included in a previously published study (Berletch et al., 2015) [1].

The budding yeast Saccharomyces cerevisiae is a long-standing model for the three-dimensional organization of eukaryotic genomes. However, even in this well-studied model, it is unclear how homolog pairing in diploids or environmental conditions influence overall genome organization. Here, we performed high-throughput chromosome conformation capture on diverged Saccharomyces hybrid diploids to obtain the first global view of chromosome conformation in diploid yeasts. After controlling for the Rabl-like orientation using a polymer model, we observe significant homolog proximity that increases in saturated culture conditions. Surprisingly, we observe a localized increase in homologous interactions between the HAS1-TDA1 alleles specifically under galactose induction and saturated growth. This pairing is accompanied by relocalization to the nuclear periphery and requires Nup2, suggesting a role for nuclear pore complexes. Together, these results reveal that the diploid yeast genome has a dynamic and complex 3D organization.

[This corrects the article DOI: 10.1371/journal.pgen.1005413.].

Malignant tumors shed DNA into the circulation. The transient half-life of circulating tumor DNA (ctDNA) may afford the opportunity to diagnose, monitor recurrence, and evaluate response to therapy solely through a non-invasive blood draw. However, detecting ctDNA against the normally occurring background of cell-free DNA derived from healthy cells has proven challenging, particularly in non-metastatic solid tumors. In this study, distinct differences in fragment length size between ctDNAs and normal cell-free DNA are defined. Human ctDNA in rat plasma derived from human glioblastoma multiforme stem-like cells in the rat brain and human hepatocellular carcinoma in the rat flank were found to have a shorter principal fragment length than the background rat cell-free DNA (134-144 bp vs. 167 bp, respectively). Subsequently, a similar shift in the fragment length of ctDNA in humans with melanoma and lung cancer was identified compared to healthy controls. Comparison of fragment lengths from cell-free DNA between a melanoma patient and healthy controls found that the BRAF V600E mutant allele occurred more commonly at a shorter fragment length than the fragment length of the wild-type allele (132-145 bp vs. 165 bp, respectively). Moreover, size-selecting for shorter cell-free DNA fragment lengths substantially increased the EGFR T790M mutant allele frequency in human lung cancer. These findings provide compelling evidence that experimental or bioinformatic isolation of a specific subset of fragment lengths from cell-free DNA may improve detection of ctDNA.

Development of a subunit vaccine targeting liver-stage Plasmodium parasites requires the identification of antigens capable of inducing protective T cell responses. However, traditional methods of antigen identification are incapable of evaluating T cell responses against large numbers of proteins expressed by these parasites. This bottleneck has limited development of subunit vaccines against Plasmodium and other complex intracellular pathogens. To address this bottleneck, we are developing a synthetic minigene technology for multi-antigen DNA vaccines. In an initial test of this approach, pools of long (150 bp) antigen-encoding oligonucleotides were synthesized and recombined into vectors by ligation-independent cloning to produce two DNA minigene library vaccines. Each vaccine encoded peptides derived from 36 (vaccine 1) and 53 (vaccine 2) secreted or transmembrane pre-erythrocytic P. yoelii proteins. BALB/cj mice were vaccinated three times with a single vaccine by biolistic particle delivery (gene gun) and screened for interferon-γ-producing T cell responses by ELISPOT. Library vaccination induced responses against four novel antigens. Naïve mice exposed to radiation-attenuated sporozoites mounted a response against only one of the four novel targets (PyMDH, malate dehydrogenase). The response to PyMDH could not be recalled by additional homologous sporozoite immunizations but could be partially recalled by heterologous cross-species sporozoite exposure. Vaccination against the dominant PyMDH epitope by DNA priming and recombinant Listeria boosting did not protect against sporozoite challenge. Improvements in library design and delivery, combined with methods promoting an increase in screening sensitivity, may enable complex minigene screening to serve as a high-throughput system for discovery of novel T cell antigens.

Bacterial whole genome sequencing holds promise as a disruptive technology in clinical microbiology, but it has not yet been applied systematically or comprehensively within a clinical context. Here, over the course of one year, we performed prospective collection and whole genome sequencing of nearly all bacterial isolates obtained from a tertiary care hospital's intensive care units (ICUs). This unbiased collection of 1,229 bacterial genomes from 391 patients enables detailed exploration of several features of clinical pathogens. A sizable fraction of isolates identified as clinically relevant corresponded to previously undescribed species: 12% of isolates assigned a species-level classification by conventional methods actually qualified as distinct, novel genomospecies on the basis of genomic similarity. Pan-genome analysis of the most frequently encountered pathogens in the collection revealed substantial variation in pan-genome size (1,420 to 20,432 genes) and the rate of gene discovery (1 to 152 genes per isolate sequenced). Surprisingly, although potential nosocomial transmission of actively surveilled pathogens was rare, 8.7% of isolates belonged to genomically related clonal lineages that were present among multiple patients, usually with overlapping hospital admissions, and were associated with clinically significant infection in 62% of patients from which they were recovered. Multi-patient clonal lineages were particularly evident in the neonatal care unit, where seven separate Staphylococcus epidermidis clonal lineages were identified, including one lineage associated with bacteremia in 5/9 neonates. Our study highlights key differences in the information made available by conventional microbiological practices versus whole genome sequencing, and motivates the further integration of microbial genome sequencing into routine clinical care.

X chromosome inactivation (XCI) silences most genes on one X chromosome in female mammals, but some genes escape XCI. To identify escape genes in vivo and to explore molecular mechanisms that regulate this process we analyzed the allele-specific expression and chromatin structure of X-linked genes in mouse tissues and cells with skewed XCI and distinguishable alleles based on single nucleotide polymorphisms. Using a binomial model to assess allelic expression, we demonstrate a continuum between complete silencing and expression from the inactive X (Xi). The validity of the RNA-seq approach was verified using RT-PCR with species-specific primers or Sanger sequencing. Both common escape genes and genes with significant differences in XCI status between tissues were identified. Such genes may be candidates for tissue-specific sex differences. Overall, few genes (3-7%) escape XCI in any of the mouse tissues examined, suggesting stringent silencing and escape controls. In contrast, an in vitro system represented by the embryonic-kidney-derived Patski cell line showed a higher density of escape genes (21%), representing both kidney-specific escape genes and cell-line specific escape genes. Allele-specific RNA polymerase II occupancy and DNase I hypersensitivity at the promoter of genes on the Xi correlated well with levels of escape, consistent with an open chromatin structure at escape genes. Allele-specific CTCF binding on the Xi clustered at escape genes and was denser in brain compared to the Patski cell line, possibly contributing to a more compartmentalized structure of the Xi and fewer escape genes in brain compared to the cell line where larger domains of escape were observed.

In addition to their protein coding function, exons can also serve as transcriptional enhancers. Mutations in these exonic-enhancers (eExons) could alter both protein function and transcription. However, the functional consequence of eExon mutations is not well known. Here, using massively parallel reporter assays, we dissect the enhancer activity of three liver eExons (SORL1 exon 17, TRAF3IP2 exon 2, PPARG exon 6) at single nucleotide resolution in the mouse liver. We find that both synonymous and non-synonymous mutations have similar effects on enhancer activity and many of the deleterious mutation clusters overlap known liver-associated transcription factor binding sites. Carrying a similar massively parallel reporter assay in HeLa cells with these three eExons found differences in their mutation profiles compared to the liver, suggesting that enhancers could have distinct operating profiles in different tissues. Our results demonstrate that eExon mutations could lead to multiple phenotypes by disrupting both the protein sequence and enhancer activity and that enhancers can have distinct mutation profiles in different cell types.

The majority of recently emerging infectious diseases in humans is due to cross-species pathogen transmissions from animals. To establish a productive infection in new host species, viruses must overcome barriers to replication mediated by diverse and rapidly evolving host restriction factors such as protein kinase R (PKR). Many viral antagonists of these restriction factors are species specific. For example, the rhesus cytomegalovirus PKR antagonist, RhTRS1, inhibits PKR in some African green monkey (AGM) cells, but does not inhibit human or rhesus macaque PKR. To model the evolutionary changes necessary for cross-species transmission, we generated a recombinant vaccinia virus that expresses RhTRS1 in a strain that lacks PKR inhibitors E3L and K3L (VVΔEΔK+RhTRS1). Serially passaging VVΔEΔK+RhTRS1 in minimally-permissive AGM cells increased viral replication 10- to 100-fold. Notably, adaptation in these AGM cells also improved virus replication 1000- to 10,000-fold in human and rhesus cells. Genetic analyses including deep sequencing revealed amplification of the rhtrs1 locus in the adapted viruses. Supplying additional rhtrs1 in trans confirmed that amplification alone was sufficient to improve VVΔEΔK+RhTRS1 replication. Viruses with amplified rhtrs1 completely blocked AGM PKR, but only partially blocked human PKR, consistent with the replication properties of these viruses in AGM and human cells. Finally, in contrast to AGM-adapted viruses, which could be serially propagated in human cells, VVΔEΔK+RhTRS1 yielded no progeny virus after only three passages in human cells. Thus, rhtrs1 amplification in a minimally permissive intermediate host was a necessary step, enabling expansion of the virus range to previously nonpermissive hosts. These data support the hypothesis that amplification of a weak viral antagonist may be a general evolutionary mechanism to permit replication in otherwise resistant host species, providing a molecular foothold that could enable further adaptations necessary for efficient replication in the new host.

Asthma is a complex genetic disease caused by a combination of genetic and environmental risk factors. We sought to test classes of genetic variants largely missed by genome-wide association studies (GWAS), including copy number variants (CNVs) and low-frequency variants, by performing whole-genome sequencing (WGS) on 16 individuals from asthma-enriched and asthma-depleted families. The samples were obtained from an extended 13-generation Hutterite pedigree with reduced genetic heterogeneity due to a small founding gene pool and reduced environmental heterogeneity as a result of a communal lifestyle. We sequenced each individual to an average depth of 13-fold, generated a comprehensive catalog of genetic variants, and tested the most severe mutations for association with asthma. We identified and validated 1960 CNVs, 19 nonsense or splice-site single nucleotide variants (SNVs), and 18 insertions or deletions that were out of frame. As follow-up, we performed targeted sequencing of 16 genes in 837 cases and 540 controls of Puerto Rican ancestry and found that controls carry a significantly higher burden of mutations in IL27RA (2.0% of controls; 0.23% of cases; nominal p = 0.004; Bonferroni p = 0.21). We also genotyped 593 CNVs in 1199 Hutterite individuals. We identified a nominally significant association (p = 0.03; Odds ratio (OR) = 3.13) between a 6 kbp deletion in an intron of NEDD4L and increased risk of asthma. We genotyped this deletion in an additional 4787 non-Hutterite individuals (nominal p = 0.056; OR = 1.69). NEDD4L is expressed in bronchial epithelial cells, and conditional knockout of this gene in the lung in mice leads to severe inflammation and mucus accumulation. Our study represents one of the early instances of applying WGS to complex disease with a large environmental component and demonstrates how WGS can identify risk variants, including CNVs and low-frequency variants, largely untested in GWAS.

Even in cases where there is no obvious family history of disease, genome sequencing may contribute to clinical diagnosis and management. Clinical application of the genome has not yet become routine, however, in part because physicians are still learning how best to utilize such information. As an educational research exercise performed in conjunction with our medical school human anatomy course, we explored the potential utility of determining the whole genome sequence of a patient who had died following a clinical diagnosis of idiopathic pulmonary fibrosis (IPF). Medical students performed dissection and whole genome sequencing of the cadaver. Gross and microscopic findings were more consistent with the fibrosing variant of nonspecific interstitial pneumonia (NSIP), as opposed to IPF per se. Variants in genes causing Mendelian disorders predisposing to IPF were not detected. However, whole genome sequencing identified several common variants associated with IPF, including a single nucleotide polymorphism (SNP), rs35705950, located in the promoter region of the gene encoding mucin glycoprotein MUC5B. The MUC5B promoter polymorphism was recently found to markedly elevate risk for IPF, though a particular association with NSIP has not been previously reported, nor has its contribution to disease risk previously been evaluated in the genome-wide context of all genetic variants. We did not identify additional predicted functional variants in a region of linkage disequilibrium (LD) adjacent to MUC5B, nor did we discover other likely risk-contributing variants elsewhere in the genome. Whole genome sequencing thus corroborates the association of rs35705950 with MUC5B dysregulation and interstitial lung disease. This novel exercise additionally served a unique mission in bridging clinical and basic science education.

Classifying individual bacterial species comprising complex, polymicrobial patient specimens remains a challenge for culture-based and molecular microbiology techniques in common clinical use. We therefore adapted practices from metagenomics research to rapidly catalog the bacterial composition of clinical specimens directly from patients, without need for prior culture. We have combined a semiconductor deep sequencing protocol that produces reads spanning 16S ribosomal RNA gene variable regions 1 and 2 (∼360 bp) with a de-noising pipeline that significantly improves the fraction of error-free sequences. The resulting sequences can be used to perform accurate genus- or species-level taxonomic assignment. We explore the microbial composition of challenging, heterogeneous clinical specimens by deep sequencing, culture-based strain typing, and Sanger sequencing of bulk PCR product. We report that deep sequencing can catalog bacterial species in mixed specimens from which usable data cannot be obtained by conventional clinical methods. Deep sequencing a collection of sputum samples from cystic fibrosis (CF) patients reveals well-described CF pathogens in specimens where they were not detected by standard clinical culture methods, especially for low-prevalence or fastidious bacteria. We also found that sputa submitted for CF diagnostic workup can be divided into a limited number of groups based on the phylogenetic composition of the airway microbiota, suggesting that metagenomic profiling may prove useful as a clinical diagnostic strategy in the future. The described method is sufficiently rapid (theoretically compatible with same-day turnaround times) and inexpensive for routine clinical use.

The identification of novel T cell antigens is central to basic and translational research in autoimmunity, tumor immunology, transplant immunology, and vaccine design for infectious disease. However, current methods for T cell antigen discovery are low throughput, and fail to explore a wide range of potential antigen-receptor interactions. To overcome these limitations, we developed a method in which programmable microarrays are used to cost-effectively synthesize complex libraries of thousands of minigenes that collectively encode the content of hundreds of candidate protein targets. Minigene-derived mRNA are transfected into autologous antigen presenting cells and used to challenge complex populations of purified peripheral blood CD8+ T cells in multiplex, parallel ELISPOT assays. In this proof-of-concept study, we apply synthetic minigene screening to identify two novel pancreatic islet autoantigens targeted in a patient with Type I Diabetes. To our knowledge, this is the first successful screen of a highly complex, synthetic minigene library for identification of a T cell antigen. In principle, responses against the full protein complement of any tissue or pathogen can be assayed by this approach, suggesting that further optimization of synthetic libraries holds promise for high throughput antigen discovery.

ABSTRACT We describe a deep-sequencing procedure for tracking large numbers of transposon mutants of Pseudomonas aeruginosa. The procedure employs a new Tn-seq methodology based on the generation and amplification of single-strand circles carrying transposon junction sequences (the Tn-seq circle method), a method which can be used with virtually any transposon. The procedure reliably identified more than 100,000 transposon insertions in a single experiment, providing near-saturation coverage of the genome. To test the effectiveness of the procedure for mutant identification, we screened for mutations reducing intrinsic resistance to the aminoglycoside antibiotic tobramycin. Intrinsic tobramycin resistance had been previously analyzed at genome scale using mutant-by-mutant screening and thus provided a benchmark for evaluating the new method. The new Tn-seq procedure identified 117 tobramycin resistance genes, the majority of which were then verified with individual mutants. The group of genes with the strongest mutant phenotypes included nearly all (13 of 14) of those with strong mutant phenotypes identified in the previous screening, as well as a nearly equal number of new genes. The results thus show the effectiveness of the Tn-seq method in defining the genetic basis of a complex resistance trait of P. aeruginosa and indicate that it can be used to analyze a variety of growth-related processes. IMPORTANCE Research progress in microbiology is technology limited in the sense that the analytical methods available dictate how questions are experimentally addressed and, to some extent, what questions are asked. This report describes a new transposon tracking procedure for defining the genetic basis of growth-related processes in Pseudomonas aeruginosa, an important bacterial pathogen. The method employs next-generation sequencing to monitor the makeup of mutant populations (Tn-seq) and has several potential advantages over other Tn-seq methodologies. The new method was validated through the analysis of a clinically relevant antibiotic resistance trait.

Recent work indicates that allelic incompatibility in the mouse PRDM9 (Meisetz) gene can cause hybrid male sterility, contributing to genetic isolation and potentially speciation. The only phenotype of mouse PRDM9 knockouts is a meiosis I block that causes sterility in both sexes. The PRDM9 gene encodes a protein with histone H3(K4) trimethyltransferase activity, a KRAB domain, and a DNA-binding domain consisting of multiple tandem C2H2 zinc finger (ZF) domains. We have analyzed human coding polymorphism and interspecies evolutionary changes in the PRDM9 gene. The ZF domains of PRDM9 are evolving very rapidly, with compelling evidence of positive selection in primates. Positively selected amino acids are predominantly those known to make nucleotide specific contacts in C2H2 zinc fingers. These results suggest that PRDM9 is subject to recurrent selection to change DNA-binding specificity. The human PRDM9 protein is highly polymorphic in its ZF domains and nearly all polymorphisms affect the same nucleotide contact residues that are subject to positive selection. ZF domain nucleotide sequences are strongly homogenized within species, indicating that interfinger recombination contributes to their evolution. PRDM9 has previously been assumed to be a transcription factor required to induce meiosis specific genes, a role that is inconsistent with its molecular evolution. We suggest instead that PRDM9 is involved in some aspect of centromere segregation conflict and that rapidly evolving centromeric DNA drives changes in PRDM9 DNA-binding domains.