Peter Rogov

Systematic dissection and optimization of inducible enhancers in human cells using a massively parallel reporter assay

Learning to read and write the transcriptional regulatory code is of central importance to progress in genetic analysis and engineering. Here we describe a massively parallel reporter assay (MPRA) that facilitates the systematic dissection of transcriptional regulatory elements. In MPRA, microarray-synthesized DNA regulatory elements and unique sequence tags are cloned into plasmids to generate a library of reporter constructs. These constructs are transfected into cells and tag expression is assayed by high-throughput sequencing. We apply MPRA to compare >27,000 variants of two inducible enhancers in human cells: a synthetic cAMP-regulated enhancer and the virus-inducible interferon-β enhancer. We first show that the resulting data define accurate maps of functional transcription factor binding sites in both enhancers at single-nucleotide resolution. We then use the data to train quantitative sequence-activity models (QSAMs) of the two enhancers. We show that QSAMs from two cellular states can be combined to design enhancer variants that optimize potentially conflicting objectives, such as maximizing induced activity while minimizing basal activity.

Systematic dissection of regulatory motifs in 2000 predicted human enhancers using a massively parallel reporter assay

Genome-wide chromatin annotations have permitted the mapping of putative regulatory elements across multiple human cell types. However, their experimental dissection by directed regulatory motif disruption has remained unfeasible at the genome scale. Here, we use a massively parallel reporter assay (MPRA) to measure the transcriptional levels induced by 145-bp DNA segments centered on evolutionarily conserved regulatory motif instances within enhancer chromatin states. We select five predicted activators (HNF1, HNF4, FOXA, GATA, NFE2L2) and two predicted repressors (GFI1, ZFP161) and measure reporter expression in erythroleukemia (K562) and liver carcinoma (HepG2) cell lines. We test 2104 wild-type sequences and 3314 engineered enhancer variants containing targeted motif disruptions, each using 10 barcode tags and two replicates. The resulting data strongly confirm the enhancer activity and cell-type specificity of enhancer chromatin states, the ability of 145-bp segments to recapitulate both, the necessary role of regulatory motifs in enhancer function, and the complementary roles of activator and repressor motifs. We find statistically robust evidence that (1) disrupting the predicted activator motifs abolishes enhancer function, while silent or motif-improving changes maintain enhancer activity; (2) evolutionary conservation, nucleosome exclusion, binding of other factors, and strength of the motif match are predictive of enhancer activity; (3) scrambling repressor motifs leads to aberrant reporter expression in cell lines where the enhancers are usually inactive. Our results suggest a general strategy for deciphering cis-regulatory elements by systematic large-scale manipulation and provide quantitative enhancer activity measurements across thousands of constructs that can be mined to develop predictive models of gene expression.

Systematic Functional Dissection of Common Genetic Variation Affecting Red Blood Cell Traits

Genome-wide association studies (GWAS) have successfully identified thousands of associations between common genetic variants and human disease phenotypes, but the majority of these variants are non-coding, often requiring genetic fine-mapping, epigenomic profiling, and individual reporter assays to delineate potential causal variants. We employ a massively parallel reporter assay (MPRA) to simultaneously screen 2,756 variants in strong linkage disequilibrium with 75 sentinel variants associated with red blood cell traits. We show that this assay identifies elements with endogenous erythroid regulatory activity. Across 23 sentinel variants, we conservatively identified 32 MPRA functional variants (MFVs). We used targeted genome editing to demonstrate endogenous enhancer activity across 3 MFVs that predominantly affect the transcription of SMIM1, RBM38, and CD164. Functional follow-up of RBM38 delineates a key role for this gene in the alternative splicing program occurring during terminal erythropoiesis. Finally, we provide evidence for how common GWAS-nominated variants can disrupt cell-type-specific transcriptional regulatory pathways.

Hybrid selection for sequencing pathogen genomes from clinical samples

We have adapted a solution hybrid selection protocol to enrich pathogen DNA in clinical samples dominated by human genetic material. Using mock mixtures of human and Plasmodium falciparum malaria parasite DNA as well as clinical samples from infected patients, we demonstrate an average of approximately 40-fold enrichment of parasite DNA after hybrid selection. This approach will enable efficient genome sequencing of pathogens from clinical samples, as well as sequencing of endosymbiotic organisms such as Wolbachia that live inside diverse metazoan phyla.

Comprehensive mutational scanning of a kinase in vivo reveals substrate-dependent fitness landscapes

Deep mutational scanning has emerged as a promising tool for mapping sequence–activity relationships in proteins, ribonucleic acid and deoxyribonucleic acid. In this approach, diverse variants of a sequence of interest are first ranked according to their activities in a relevant assay, and this ranking is then used to infer the shape of the fitness landscape around the wild-type sequence. Little is currently known, however, about the degree to which such fitness landscapes are dependent on the specific assay conditions from which they are inferred. To explore this issue, we performed comprehensive single-substitution mutational scanning of APH(3′)II, a Tn5 transposon-derived kinase that confers resistance to aminoglycoside antibiotics, in Escherichia coli under selection with each of six structurally diverse antibiotics at a range of inhibitory concentrations. We found that the resulting local fitness landscapes showed significant dependence on both antibiotic structure and concentration, and that this dependence can be exploited to guide protein engineering. Specifically, we found that differential analysis of fitness landscapes allowed us to generate synthetic APH(3′)II variants with orthogonal substrate specificities.

Population genomics studies identify signatures of global dispersal and drug resistance in Plasmodium vivax

Plasmodium vivax is a major public health burden, responsible for the majority of malaria infections outside Africa. We explored the impact of demographic history and selective pressures on the P. vivax genome by sequencing 182 clinical isolates sampled from 11 countries across the globe, using hybrid selection to overcome human DNA contamination. We confirmed previous reports of high genomic diversity in P. vivax relative to the more virulent Plasmodium falciparum species; regional populations of P. vivax exhibited greater diversity than the global P. falciparum population, indicating a large and/or stable population. Signals of natural selection suggest that P. vivax is evolving in response to antimalarial drugs and is adapting to regional differences in the human host and the mosquito vector. These findings underline the variable epidemiology of this parasite species and highlight the breadth of approaches that may be required to eliminate P. vivax globally.

Targeted Exon Sequencing by In‐Solution Hybrid Selection

This unit describes a protocol for the targeted enrichment of exons from randomly sheared genomic DNA libraries using an in‐solution hybrid selection approach for sequencing on an Illumina Genome Analyzer II. The steps for designing and ordering a hybrid selection oligo pool are reviewed, as are critical steps for performing the preparation and hybrid selection of an Illumina paired‐end library. Critical parameters, performance metrics, and analysis workflow are discussed. Curr. Protoc. Hum. Genet. 66:18.4.1‐18.4.24

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

Significance A central question in biology is how transcription factors (TFs) recognize specific binding sites in enhancers and regulate gene expression. In general, only a fraction of potential binding sites for TFs are occupied in a particular cell type. TF affinity for a motif site, local interactions among TFs, and larger-scale chromatin accessibility can influence binding, although the relative contributions of these factors is unclear. Moreover, little is known about how specific combinations of TFs control quantitative gene expression once bound. Here, we use large-scale synthetic biology approaches to explore the features that govern TF binding vs. enhancer activity. This approach provides a paradigm for systematic study of key regulatory sequences within enhancers and how they interact to influence gene expression. 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.

Longitudinal genomic surveillance of Plasmodium falciparum malaria parasites reveals complex genomic architecture of emerging artemisinin resistance

BackgroundArtemisinin-based combination therapies are the first line of treatment for Plasmodium falciparum infections worldwide, but artemisinin resistance has risen rapidly in Southeast Asia over the past decade. Mutations in the kelch13 gene have been implicated in this resistance. We used longitudinal genomic surveillance to detect signals in kelch13 and other loci that contribute to artemisinin or partner drug resistance. We retrospectively sequenced the genomes of 194 P. falciparum isolates from five sites in Northwest Thailand, over the period of a rapid increase in the emergence of artemisinin resistance (2001–2014).ResultsWe evaluate statistical metrics for temporal change in the frequency of individual SNPs, assuming that SNPs associated with resistance increase in frequency over this period. After Kelch13-C580Y, the strongest temporal change is seen at a SNP in phosphatidylinositol 4-kinase, which is involved in a pathway recently implicated in artemisinin resistance. Furthermore, other loci exhibit strong temporal signatures which warrant further investigation for involvement in artemisinin resistance evolution. Through genome-wide association analysis we identify a variant in a kelch domain-containing gene on chromosome 10 that may epistatically modulate artemisinin resistance.ConclusionsThis analysis demonstrates the potential of a longitudinal genomic surveillance approach to detect resistance-associated gene loci to improve our mechanistic understanding of how resistance develops. Evidence for additional genomic regions outside of the kelch13 locus associated with artemisinin-resistant parasites may yield new molecular markers for resistance surveillance, which may be useful in efforts to reduce the emergence or spread of artemisinin resistance in African parasite populations.

High-throughput Screening and CRISPR-Cas9 Modeling of Causal Lipid-associated Expression Quantitative Trait Locus Variants

Genome-wide association studies have identified a number of novel genetic loci linked to serum cholesterol and triglyceride levels. The causal DNA variants at these loci and the mechanisms by which they influence phenotype and disease risk remain largely unexplored. Expression quantitative trait locus analyses of patient liver and fat biopsies indicate that many lipid-associated variants influence gene expression in a cis-regulatory manner. However, linkage disequilibrium among neighboring SNPs at a genome-wide association study-implicated locus makes it challenging to pinpoint the actual variant underlying an association signal. We used a methodological framework for causal variant discovery that involves high-throughput identification of putative disease-causal loci through a functional reporter-based screen, the massively parallel reporter assay, followed by validation of prioritized variants in genome-edited human pluripotent stem cell models generated with CRISPR-Cas9. We complemented the stem cell models with CRISPR interference experiments in vitro and in knock-in mice in vivo. We provide validation for two high-priority SNPs, rs2277862 and rs10889356, being causal for lipid-associated expression quantitative trait loci. We also highlight the challenges inherent in modeling common genetic variation with these experimental approaches. Author Summary Genome-wide association studies have identified numerous loci linked to a variety of clinical phenotypes. It remains a challenge to identify and validate the causal DNA variants in these loci. We describe the use of a high-throughput technique called the massively parallel reporter assay to analyze thousands of candidate causal DNA variants for their potential effects on gene expression. We use a combination of genome editing in human pluripotent stem cells, “CRISPR interference” experiments in other cultured human cell lines, and genetically modified mice to analyze the two highest-priority candidate DNA variants to emerge from the massively parallel reporter assay, and we confirm the relevance of the variants to nearby gene expression. These findings highlight a methodological framework with which to identify and functionally validate causal DNA variants.