Genome-wide functional screen of 3'UTR variants uncovers causal variants for human disease and evolution.

3' untranslated region (3'UTR) variants are strongly associated with human traits and diseases, yet few have been causally identified. We developed the massively parallel reporter assay for 3'UTRs (MPRAu) to sensitively assay 12,173 3'UTR variants. We applied MPRAu to six human cell lines, focusing on genetic variants associated with genome-wide association studies (GWAS) and human evolutionary adaptation. MPRAu expands our understanding of 3'UTR function, suggesting that simple sequences predominately explain 3'UTR regulatory activity. We adapt MPRAu to uncover diverse molecular mechanisms at base pair resolution, including an adenylate-uridylate (AU)-rich element of LEPR linked to potential metabolic evolutionary adaptations in East Asians. We nominate hundreds of 3'UTR causal variants with genetically fine-mapped phenotype associations. Using endogenous allelic replacements, we characterize one variant that disrupts a miRNA site regulating the viral defense gene TRIM14 and one that alters PILRB abundance, nominating a causal variant underlying transcriptional changes in age-related macular degeneration.

A MicroRNA Linking Human Positive Selection and Metabolic Disorders.

Positive selection in Europeans at the 2q21.3 locus harboring the lactase gene has been attributed to selection for the ability of adults to digest milk to survive famine in ancient times. However, the 2q21.3 locus is also associated with obesity and type 2 diabetes in humans, raising the possibility that additional genetic elements in the locus may have contributed to evolutionary adaptation to famine by promoting energy storage, but which now confer susceptibility to metabolic diseases. We show here that the miR-128-1 microRNA, located at the center of the positively selected locus, represents a crucial metabolic regulator in mammals. Antisense targeting and genetic ablation of miR-128-1 in mouse metabolic disease models result in increased energy expenditure and amelioration of high-fat-diet-induced obesity and markedly improved glucose tolerance. A thrifty phenotype connected to miR-128-1-dependent energy storage may link ancient adaptation to famine and modern metabolic maladaptation associated with nutritional overabundance.

Direct Identification of Hundreds of Expression-Modulating Variants using a Multiplexed Reporter Assay.

Although studies have identified hundreds of loci associated with human traits and diseases, pinpointing causal alleles remains difficult, particularly for non-coding variants. To address this challenge, we adapted the massively parallel reporter assay (MPRA) to identify variants that directly modulate gene expression. We applied it to 32,373 variants from 3,642 cis-expression quantitative trait loci and control regions. Detection by MPRA was strongly correlated with measures of regulatory function. We demonstrate MPRA's capabilities for pinpointing causal alleles, using it to identify 842 variants showing differential expression between alleles, including 53 well-annotated variants associated with diseases and traits. We investigated one in detail, a risk allele for ankylosing spondylitis, and provide direct evidence of a non-coding variant that alters expression of the prostaglandin EP4 receptor. These results create a resource of concrete leads and illustrate the promise of this approach for comprehensively interrogating how non-coding polymorphism shapes human biology.

Clinical Sequencing Uncovers Origins and Evolution of Lassa Virus.

The 2013-2015 West African epidemic of Ebola virus disease (EVD) reminds us of how little is known about biosafety level 4 viruses. Like Ebola virus, Lassa virus (LASV) can cause hemorrhagic fever with high case fatality rates. We generated a genomic catalog of almost 200 LASV sequences from clinical and rodent reservoir samples. We show that whereas the 2013-2015 EVD epidemic is fueled by human-to-human transmissions, LASV infections mainly result from reservoir-to-human infections. We elucidated the spread of LASV across West Africa and show that this migration was accompanied by changes in LASV genome abundance, fatality rates, codon adaptation, and translational efficiency. By investigating intrahost evolution, we found that mutations accumulate in epitopes of viral surface proteins, suggesting selection for immune escape. This catalog will serve as a foundation for the development of vaccines and diagnostics. VIDEO ABSTRACT.

Multicenter integrated analysis of noncoding CRISPRi screens.

The ENCODE Consortium's efforts to annotate noncoding cis-regulatory elements (CREs) have advanced our understanding of gene regulatory landscapes. Pooled, noncoding CRISPR screens offer a systematic approach to investigate cis-regulatory mechanisms. The ENCODE4 Functional Characterization Centers conducted 108 screens in human cell lines, comprising >540,000 perturbations across 24.85 megabases of the genome. Using 332 functionally confirmed CRE-gene links in K562 cells, we established guidelines for screening endogenous noncoding elements with CRISPR interference (CRISPRi), including accurate detection of CREs that exhibit variable, often low, transcriptional effects. Benchmarking five screen analysis tools, we find that CASA produces the most conservative CRE calls and is robust to artifacts of low-specificity single guide RNAs. We uncover a subtle DNA strand bias for CRISPRi in transcribed regions with implications for screen design and analysis. Together, we provide an accessible data resource, predesigned single guide RNAs for targeting 3,275,697 ENCODE SCREEN candidate CREs with CRISPRi and screening guidelines to accelerate functional characterization of the noncoding genome.

Three linked variants have opposing regulatory effects on isovaleryl-CoA dehydrogenase gene expression.

While genome-wide association studies (GWAS) and positive selection scans identify genomic loci driving human phenotypic diversity, functional validation is required to discover the variant(s) responsible. We dissected the IVD gene locus-which encodes the isovaleryl-CoA dehydrogenase enzyme-implicated by selection statistics, multiple GWAS, and clinical genetics as important to function and fitness. We combined luciferase assays, CRISPR/Cas9 genome-editing, massively parallel reporter assays (MPRA), and a deletion tiling MPRA strategy across regulatory loci. We identified three regulatory variants, including an indel, that may underpin GWAS signals for pulmonary fibrosis and testosterone, and that are linked on a positively selected haplotype in the Japanese population. These regulatory variants exhibit synergistic and opposing effects on IVD expression experimentally. Alleles at these variants lie on a haplotype tagged by the variant most strongly associated with IVD expression and metabolites, but with no functional evidence itself. This work demonstrates how comprehensive functional investigation and multiple technologies are needed to discover the true genetic drivers of phenotypic diversity.

CoRE-ATAC: A deep learning model for the functional classification of regulatory elements from single cell and bulk ATAC-seq data.

Cis-Regulatory elements (cis-REs) include promoters, enhancers, and insulators that regulate gene expression programs via binding of transcription factors. ATAC-seq technology effectively identifies active cis-REs in a given cell type (including from single cells) by mapping accessible chromatin at base-pair resolution. However, these maps are not immediately useful for inferring specific functions of cis-REs. For this purpose, we developed a deep learning framework (CoRE-ATAC) with novel data encoders that integrate DNA sequence (reference or personal genotypes) with ATAC-seq cut sites and read pileups. CoRE-ATAC was trained on 4 cell types (n = 6 samples/replicates) and accurately predicted known cis-RE functions from 7 cell types (n = 40 samples) that were not used in model training (mean average precision = 0.80, mean F1 score = 0.70). CoRE-ATAC enhancer predictions from 19 human islet samples coincided with genetically modulated gain/loss of enhancer activity, which was confirmed by massively parallel reporter assays (MPRAs). Finally, CoRE-ATAC effectively inferred cis-RE function from aggregate single nucleus ATAC-seq (snATAC) data from human blood-derived immune cells that overlapped with known functional annotations in sorted immune cells, which established the efficacy of these models to study cis-RE functions of rare cells without the need for cell sorting. ATAC-seq maps from primary human cells reveal individual- and cell-specific variation in cis-RE activity. CoRE-ATAC increases the functional resolution of these maps, a critical step for studying regulatory disruptions behind diseases.

Systematic dissection of genomic features determining transcription factor binding and enhancer function.

Enhancers regulate gene expression through the binding of sequence-specific transcription factors (TFs) to cognate motifs. Various features influence TF binding and enhancer function-including the chromatin state of the genomic locus, the affinities of the binding site, the activity of the bound TFs, and interactions among TFs. However, the precise nature and relative contributions of these features remain unclear. Here, we used massively parallel reporter assays (MPRAs) involving 32,115 natural and synthetic enhancers, together with high-throughput in vivo binding assays, to systematically dissect the contribution of each of these features to the binding and activity of genomic regulatory elements that contain motifs for PPARγ, a TF that serves as a key regulator of adipogenesis. We show that distinct sets of features govern PPARγ binding vs. enhancer activity. PPARγ binding is largely governed by the affinity of the specific motif site and higher-order features of the larger genomic locus, such as chromatin accessibility. In contrast, the enhancer activity of PPARγ binding sites depends on varying contributions from dozens of TFs in the immediate vicinity, including interactions between combinations of these TFs. Different pairs of motifs follow different interaction rules, including subadditive, additive, and superadditive interactions among specific classes of TFs, with both spatially constrained and flexible grammars. Our results provide a paradigm for the systematic characterization of the genomic features underlying regulatory elements, applicable to the design of synthetic regulatory elements or the interpretation of human genetic variation.

Predicting gene expression in massively parallel reporter assays: A comparative study.

In many human diseases, associated genetic changes tend to occur within noncoding regions, whose effect might be related to transcriptional control. A central goal in human genetics is to understand the function of such noncoding regions: given a region that is statistically associated with changes in gene expression (expression quantitative trait locus [eQTL]), does it in fact play a regulatory role? And if so, how is this role "coded" in its sequence? These questions were the subject of the Critical Assessment of Genome Interpretation eQTL challenge. Participants were given a set of sequences that flank eQTLs in humans and were asked to predict whether these are capable of regulating transcription (as evaluated by massively parallel reporter assays), and whether this capability changes between alternative alleles. Here, we report lessons learned from this community effort. By inspecting predictive properties in isolation, and conducting meta-analysis over the competing methods, we find that using chromatin accessibility and transcription factor binding as features in an ensemble of classifiers or regression models leads to the most accurate results. We then characterize the loci that are harder to predict, putting the spotlight on areas of weakness, which we expect to be the subject of future studies.

The importance of phase information for human genomics.

Contemporary sequencing studies often ignore the diploid nature of the human genome because they do not routinely separate or 'phase' maternally and paternally derived sequence information. However, many findings - both from recent studies and in the more established medical genetics literature - indicate that relationships between human DNA sequence and phenotype, including disease, can be more fully understood with phase information. Thus, the existing technological impediments to obtaining phase information must be overcome if human genomics is to reach its full potential.

De novo finished 2.8 Mbp Staphylococcus aureus genome assembly from 100 bp short and long range paired-end reads.

MOTIVATION: Paired-end sequencing allows circumventing the shortness of the reads produced by second generation sequencers and is essential for de novo assembly of genomes. However, obtaining a finished genome from short reads is still an open challenge. We present an algorithm that exploits the pairing information issued from inserts of potentially any length. The method determines paths through an overlaps graph by using a constrained search tree. We also present a method that automatically determines suited overlaps cutoffs according to the contextual coverage, reducing thus the need for manual parameterization. Finally, we introduce an interactive mode that allows querying an assembly at targeted regions. RESULTS: We assess our methods by assembling two Staphylococcus aureus strains that were sequenced on the Illumina platform. Using 100 bp paired-end reads and minimal manual curation, we produce a finished genome sequence for the previously undescribed isolate SGH-10-168. AVAILABILITY AND IMPLEMENTATION: The presented algorithms are implemented in the standalone Edena software, freely available under the General Public License (GPLv3) at www.genomic.ch/edena.php.

Alternative mutational pathways to intermediate resistance to vancomycin in methicillin-resistant Staphylococcus aureus.

BACKGROUND: We used 2 in vitro experimental systems to compare phenotypic and genotypic changes that accompany selection of mutants of methicillin-resistant Staphylococcus aureus (MRSA) strain JH1 with low-level vancomycin resistance similar to the type found in vancomycin-intermediate S. aureus (VISA). METHODS: The previously described MRSA strain JH1 and its vancomycin-intermediate mutant derivative JH2, both of which were recovered from a patient undergoing vancomycin chemotherapy, were used in this study. Mutants of JH1 were selected in vitro by means of a pharmacokinetic/pharmacodynamic (PK/PD) model of simulated endocardial vegetations (SEVs) and by exposure to vancomycin in laboratory growth medium. Phenotypic abnormalities of JH1 mutants generated by each in vitro experimental system were compared to those of JH2, and whole genomes of 2 in vitro JH1 mutants were sequenced to identify mutations that may be associated with an increased vancomycin minimum inhibitory concentration. RESULTS: JH1R1 was selected from the PK/PD model, and JH1R2 was selected in laboratory growth medium. Both mutants displayed reduced vancomycin and daptomycin susceptibility and phenotypic alterations (eg, thicker cell walls and abnormal autolysis) that are typical of in vivo VISA mutants. Genome sequencing of JH1R1 identified point mutations in 4 genes, all of which were different from the mutations described in JH2, including 1 mutation in yycG, a component of the WalKR sensory regulatory system. Sequencing of the JH1R2 genome identified mutations in 7 genes, including 2 in rpoB. CONCLUSION: Our findings indicate that JH1 is able to develop VISA-type resistance through several alternative genetic pathways.

A systematic strategy for identifying causal single nucleotide polymorphisms and their target genes on Juvenile arthritis risk haplotypes.

BACKGROUND: Although genome-wide association studies (GWAS) have identified multiple regions conferring genetic risk for juvenile idiopathic arthritis (JIA), we are still faced with the task of identifying the single nucleotide polymorphisms (SNPs) on the disease haplotypes that exert the biological effects that confer risk. Until we identify the risk-driving variants, identifying the genes influenced by these variants, and therefore translating genetic information to improved clinical care, will remain an insurmountable task. We used a function-based approach for identifying causal variant candidates and the target genes on JIA risk haplotypes. METHODS: We used a massively parallel reporter assay (MPRA) in myeloid K562 cells to query the effects of 5,226 SNPs in non-coding regions on JIA risk haplotypes for their ability to alter gene expression when compared to the common allele. The assay relies on 180 bp oligonucleotide reporters ("oligos") in which the allele of interest is flanked by its cognate genomic sequence. Barcodes were added randomly by PCR to each oligo to achieve > 20 barcodes per oligo to provide a quantitative read-out of gene expression for each allele. Assays were performed in both unstimulated K562 cells and cells stimulated overnight with interferon gamma (IFNg). As proof of concept, we then used CRISPRi to demonstrate the feasibility of identifying the genes regulated by enhancers harboring expression-altering SNPs. RESULTS: We identified 553 expression-altering SNPs in unstimulated K562 cells and an additional 490 in cells stimulated with IFNg. We further filtered the SNPs to identify those plausibly situated within functional chromatin, using open chromatin and H3K27ac ChIPseq peaks in unstimulated cells and open chromatin plus H3K4me1 in stimulated cells. These procedures yielded 42 unique SNPs (total = 84) for each set. Using CRISPRi, we demonstrated that enhancers harboring MPRA-screened variants in the TRAF1 and LNPEP/ERAP2 loci regulated multiple genes, suggesting complex influences of disease-driving variants. CONCLUSION: Using MPRA and CRISPRi, JIA risk haplotypes can be queried to identify plausible candidates for disease-driving variants. Once these candidate variants are identified, target genes can be identified using CRISPRi informed by the 3D chromatin structures that encompass the risk haplotypes.

Functional dissection of complex and molecular trait variants at single nucleotide resolution.

Identifying the causal variants and mechanisms that drive complex traits and diseases remains a core problem in human genetics. The majority of these variants have individually weak effects and lie in non-coding gene-regulatory elements where we lack a complete understanding of how single nucleotide alterations modulate transcriptional processes to affect human phenotypes. To address this, we measured the activity of 221,412 trait-associated variants that had been statistically fine-mapped using a Massively Parallel Reporter Assay (MPRA) in 5 diverse cell-types. We show that MPRA is able to discriminate between likely causal variants and controls, identifying 12,025 regulatory variants with high precision. Although the effects of these variants largely agree with orthogonal measures of function, only 69% can plausibly be explained by the disruption of a known transcription factor (TF) binding motif. We dissect the mechanisms of 136 variants using saturation mutagenesis and assign impacted TFs for 91% of variants without a clear canonical mechanism. Finally, we provide evidence that epistasis is prevalent for variants in close proximity and identify multiple functional variants on the same haplotype at a small, but important, subset of trait-associated loci. Overall, our study provides a systematic functional characterization of likely causal common variants underlying complex and molecular human traits, enabling new insights into the regulatory grammar underlying disease risk.

ß-Lactam antibiotics targeting PBP1 selectively enhance daptomycin activity against methicillin-resistant Staphylococcus aureus.

The activity of daptomycin (DAP) against methicillin-resistant Staphylococcus aureus (MRSA) is enhanced in the presence of subinhibitory concentrations of antistaphylococcal ß-lactam antibiotics by an undefined mechanism. Given the variability in the penicillin-binding protein (PBP)-binding profiles of different ß-lactam antibiotics, the purpose of this study was to examine the relative enhancement of DAP activity against MRSA by different ß-lactam antibiotics to determine if a specific PBP-binding profile is associated with the ability to enhance the anti-MRSA activity of DAP. We determined that both broad- and narrow-spectrum ß-lactam antibiotics known to exhibit PBP1 binding demonstrated potent enhancement of DAP anti-MRSA activity, whereas ß-lactam antibiotics with minimal PBP1 binding (cefoxitin, ceftriaxone, cefaclor, and cefotaxime) were less effective. We suspect that PBP1 disruption by ß-lactam antibiotics affects pathways of cell division in S. aureus that may be a compensatory response to DAP membrane insertion, resulting in DAP hypersusceptibility.

Ceftaroline increases membrane binding and enhances the activity of daptomycin against daptomycin-nonsusceptible vancomycin-intermediate Staphylococcus aureus in a pharmacokinetic/pharmacodynamic model.

New antimicrobial agents and novel combination therapies are needed to treat serious infections caused by methicillin-resistant Staphylococcus aureus (MRSA) with reduced susceptibility to daptomycin and vancomycin. The purpose of this study was to evaluate the combination of ceftaroline plus daptomycin or vancomycin in an in vitro pharmacokinetic/pharmacodynamic model. Simulations of ceftaroline-fosamil at 600 mg per kg of body weight every 8 h (q8h) (maximum free-drug concentration in serum [fC(max)], 15.2 mg/liter; half-life [t(1/2)], 2.3 h), daptomycin at 10 mg/kg/day (fC(max), 11.3 mg/liter; t(1/2), 8 h), vancomycin at 2 g q12h (fC(max), 30 mg/liter; t(1/2), 6 h), ceftaroline plus daptomycin, and ceftaroline plus vancomycin were evaluated against a clinical, isogenic MRSA strain pair: D592 (daptomycin susceptible and heterogeneous vancomycin intermediate) and D712 (daptomycin nonsusceptible and vancomycin intermediate) in a one-compartment in vitro pharmacokinetic/pharmacodynamic model over 96 h. Therapeutic enhancement of combinations was defined as ≥2 log(10) CFU/ml reduction over the most active single agent. The effect of ceftaroline on the membrane charge, cell wall thickness, susceptibility to killing by the human cathelicidin LL37, and daptomycin binding were evaluated. Therapeutic enhancement was observed with daptomycin plus ceftaroline in both strains and vancomycin plus ceftaroline against D592. Ceftaroline exposure enhanced daptomycin-induced depolarization (81.7% versus 72.3%; P = 0.03) and killing by cathelicidin LL37 (P < 0.01) and reduced cell wall thickness (P < 0.001). Fluorescence-labeled daptomycin was bound over 7-fold more in ceftaroline-exposed cells. Whole-genome sequencing and mutation analysis of these strains indicated that change in daptomycin susceptibility is related to an fmtC (mprF) mutation. The combination of daptomycin plus ceftaroline appears to be potent, with rapid and sustained bactericidal activity against both daptomycin-susceptible and -nonsusceptible strains of MRSA.

Accurate detection and genotyping of SNPs utilizing population sequencing data.

Next-generation sequencing technologies have made it possible to sequence targeted regions of the human genome in hundreds of individuals. Deep sequencing represents a powerful approach for the discovery of the complete spectrum of DNA sequence variants in functionally important genomic intervals. Current methods for single nucleotide polymorphism (SNP) detection are designed to detect SNPs from single individual sequence data sets. Here, we describe a novel method SNIP-Seq (single nucleotide polymorphism identification from population sequence data) that leverages sequence data from a population of individuals to detect SNPs and assign genotypes to individuals. To evaluate our method, we utilized sequence data from a 200-kilobase (kb) region on chromosome 9p21 of the human genome. This region was sequenced in 48 individuals (five sequenced in duplicate) using the Illumina GA platform. Using this data set, we demonstrate that our method is highly accurate for detecting variants and can filter out false SNPs that are attributable to sequencing errors. The concordance of sequencing-based genotype assignments between duplicate samples was 98.8%. The 200-kb region was independently sequenced to a high depth of coverage using two sequence pools containing the 48 individuals. Many of the novel SNPs identified by SNIP-Seq from the individual sequencing were validated by the pooled sequencing data and were subsequently confirmed by Sanger sequencing. We estimate that SNIP-Seq achieves a low false-positive rate of approximately 2%, improving upon the higher false-positive rate for existing methods that do not utilize population sequence data. Collectively, these results suggest that analysis of population sequencing data is a powerful approach for the accurate detection of SNPs and the assignment of genotypes to individual samples.

Whole-genome functional characterization of RE1 silencers using a modified massively parallel reporter assay.

Both upregulation and downregulation by cis-regulatory elements help modulate precise gene expression. However, our understanding of repressive elements is far more limited than activating elements. To address this gap, we characterized RE1, a group of transcriptional silencers bound by REST, at genome-wide scale using a modified massively parallel reporter assay (MPRAduo). MPRAduo empirically defined a minimal binding strength of REST (REST motif-intrinsic value [m-value]), above which cofactors colocalize and silence transcription. We identified 1,500 human variants that alter RE1 silencing and found that their effect sizes are predictable when they overlap with REST-binding sites above the m-value. Additionally, we demonstrate that non-canonical REST-binding motifs exhibit silencer function only if they precisely align half sites with specific spacer lengths. Our results show mechanistic insights into RE1, which allow us to predict its activity and effect of variants on RE1, providing a paradigm for performing genome-wide functional characterization of transcription-factor-binding sites.

Widespread perturbation of ETS factor binding sites in cancer.

Although >90% of somatic mutations reside in non-coding regions, few have been reported as cancer drivers. To predict driver non-coding variants (NCVs), we present a transcription factor (TF)-aware burden test based on a model of coherent TF function in promoters. We apply this test to NCVs from the Pan-Cancer Analysis of Whole Genomes cohort and predict 2555 driver NCVs in the promoters of 813 genes across 20 cancer types. These genes are enriched in cancer-related gene ontologies, essential genes, and genes associated with cancer prognosis. We find that 765 candidate driver NCVs alter transcriptional activity, 510 lead to differential binding of TF-cofactor regulatory complexes, and that they primarily impact the binding of ETS factors. Finally, we show that different NCVs within a promoter often affect transcriptional activity through shared mechanisms. Our integrated computational and experimental approach shows that cancer NCVs are widespread and that ETS factors are commonly disrupted.