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

Tewhey, R; Kotliar, Dylan; Park, Daniel; Liu, Brandon; Winnicki, S; Reilly, Steven K.; Andersen, Kristian G.; Mikkelsen, Tarjei S.; Lander, Eric S.; Schaffner, Stephen F.; Sabeti, Pardis C.

doi:10.1016/j.cell.2018.02.021

Cited by 81 publications

(122 citation statements)

References 19 publications

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“…Predicting functional effects of genetic variants is an active area of research with continuous improvements for both computational (CADD and Eigen) and experimental approaches, such as massively parallel reporter assays. 4,5,36 For noncoding variants, prediction of functional effects in a tissue-and cell-type-specific manner is essential given that many disease-causing variants in noncoding regions are assumed to be involved in gene regulation in a tissue-and cell-type specific manner. Although the best tissue or cell type is generally unknown for a disease of interest, our proposed tests can readily incorporate multiple correlated functional scores for related tissues and cell types.…”

Section: Discussionmentioning

confidence: 99%

Unified Sequence-Based Association Tests Allowing for Multiple Functional Annotations and Meta-analysis of Noncoding Variation in Metabochip Data

Lee

et al. 2017

The American Journal of Human Genetics

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Substantial progress has been made in the functional annotation of genetic variation in the human genome. Integrative analysis that incorporates such functional annotations into sequencing studies can aid the discovery of disease-associated genetic variants, especially those with unknown function and located outside protein-coding regions. Direct incorporation of one functional annotation as weight in existing dispersion and burden tests can suffer substantial loss of power when the functional annotation is not predictive of the risk status of a variant. Here, we have developed unified tests that can utilize multiple functional annotations simultaneously for integrative association analysis with efficient computational techniques. We show that the proposed tests significantly improve power when variant risk status can be predicted by functional annotations. Importantly, when functional annotations are not predictive of risk status, the proposed tests incur only minimal loss of power in relation to existing dispersion and burden tests, and under certain circumstances they can even have improved power by learning a weight that better approximates the underlying disease model in a data-adaptive manner.The tests can be constructed with summary statistics of existing dispersion and burden tests for sequencing data, therefore allowing meta-analysis of multiple studies without sharing individual-level data. We applied the proposed tests to a meta-analysis of noncoding rare variants in Metabochip data on 12,281 individuals from eight studies for lipid traits. By incorporating the Eigen functional score, we detected significant associations between noncoding rare variants in SLC22A3 and low-density lipoprotein and total cholesterol, associations that are missed by standard dispersion and burden tests.

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Section: Discussionmentioning

confidence: 99%

Unified Sequence-Based Association Tests Allowing for Multiple Functional Annotations and Meta-analysis of Noncoding Variation in Metabochip Data

Lee

et al. 2017

The American Journal of Human Genetics

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“…Several putative DAP-disruptive eQTL SNPs were associated with relevant phenotypes in liver tissue, including glucose homeostasis, drug metabolism, and circulating lipid levels, and therefore represent a promising resource for future mechanistic follow-up. Despite a limited sample size, our application of this method for prioritizing variants represents an improvement over large agnostic assays that have reported a success rate <5% (Tewhey et al 2016).…”

Section: Discussionmentioning

confidence: 99%

A genome-wide interactome of DNA-associated proteins in the human liver

et al. 2017

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Large-scale efforts like the ENCODE Project have made tremendous progress in cataloging the genomic binding patterns of DNA-associated proteins (DAPs), such as transcription factors (TFs). However, most chromatin immunoprecipitation-sequencing (ChIP-seq) analyses have focused on a few immortalized cell lines whose activities and physiology differ in important ways from endogenous cells and tissues. Consequently, binding data from primary human tissue are essential to improving our understanding of in vivo gene regulation. Here, we identify and analyze more than 440,000 binding sites using ChIP-seq data for 20 DAPs in two human liver tissue samples. We integrated binding data with transcriptome and phased WGS data to investigate allelic DAP interactions and the impact of heterozygous sequence variation on the expression of neighboring genes. Our tissue-based data set exhibits binding patterns more consistent with liver biology than cell lines, and we describe uses of these data to better prioritize impactful noncoding variation. Collectively, our rich data set offers novel insights into genome function in human liver tissue and provides a valuable resource for assessing disease-related disruptions.

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“…Oligonucleotide libraries containing the 145-or 150-bp candidate enhancers were synthesized (Agilent Technologies) and unique barcodes were added by PCR. The oligonucleotide libraries were cloned into a plasmid backbone with a minP-luc2 insert, as previously described (48,95).…”

Section: Methodsmentioning

confidence: 99%

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

Grossman

Zhang

Wang

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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164

142

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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.gene regulation | transcription factor binding | systems biology

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

Cited by 81 publications

References 19 publications

Unified Sequence-Based Association Tests Allowing for Multiple Functional Annotations and Meta-analysis of Noncoding Variation in Metabochip Data

Unified Sequence-Based Association Tests Allowing for Multiple Functional Annotations and Meta-analysis of Noncoding Variation in Metabochip Data

A genome-wide interactome of DNA-associated proteins in the human liver

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

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