CASCADE: high-throughput characterization of regulatory complex binding altered by non-coding variants

Bray, David A.; Hook, Heather; R, Zhao; Keenan, Jessica L.; Penvose, Ashley; Osayame, Yemi; Mohaghegh, Nima; Xiaoting, Chen; Parameswaran, Sreeja; Kottyan, Leah; Weirauch, Matthew T.; Siggers, Trevor

doi:10.1016/j.xgen.2022.100098

Cited by 7 publications

(21 citation statements)

References 66 publications

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“…To do this, we assayed COF recruitment to all single-nucleotide variants spanning each NCV loci and determined recruitment motifs that can be used to infer the underlying TFs by matching against TF motif databases ( Supplementary Fig. 6) 42 . We profiled recruitment of our six COFs, using Jurkat nuclear extracts, and determined COF recruitment motifs for 273 loci ( Methods ).…”

Section: Resultsmentioning

confidence: 99%

“…Nuclear extracts were obtained as previously described 42,79 , with modifications detailed below. To harvest nuclear extracts from Jurkat cells, the cells were collected in a falcon tube and placed on ice.…”

Section: Methodsmentioning

confidence: 99%

“…This microarray was designed to determine COF recruitment motifs for each NCV loci. The design is based on the exhaustive mutagenesis approach outlined in Bray & Hook et al 42 where all possible single-nucleotide variant (SV) probes of a defined genomic locus are included as probes in the microarray. By profiling the differential binding of a COF to all SV probes we can directly determine a motif/logo for that COF and genomic loci as described in Bray & Hook et al (details below).…”

Section: Methodsmentioning

confidence: 99%

“…To do this, we assayed COF recruitment to all singlenucleotide variants spanning each NCV loci and determined recruitment motifs that can be used to infer the underlying TFs by matching against TF motif databases (Supplementary Fig. 6) 42 .…”

Section: Tf-abt Ncvs Primarily Affect the Binding Of Ets Factorsmentioning

confidence: 99%

“…We used ICGC probabilities for each NCV-donor combination to assign them a given mutational process if its probability is greater than 0.5, as described 9 . Then, we compared the MPRA and CASCADE Nuclear extracts were obtained as previously described 42,79 , with modifications detailed below. To harvest nuclear extracts from Jurkat cells, the cells were collected in a falcon tube and placed on ice.…”

Section: Mutational Signatures For Mpra Validated Driversmentioning

confidence: 99%

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Widespread perturbation of ETS factor binding sites in cancer

Pro

Hook

Bray

et al. 2022

Preprint

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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 novel transcription factor (TF)-aware burden test (TFA-BT) based on a model of coherent TF function in promoters. We applied our TFA-BT to NCVs from the Pan-Cancer Analysis of Whole Genomes cohort and predicted 2,555 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 found 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.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Tf-abt Ncvs Primarily Affect the Binding Of Ets Factorsmentioning

confidence: 99%

Section: Mutational Signatures For Mpra Validated Driversmentioning

confidence: 99%

See 3 more Smart Citations

Widespread perturbation of ETS factor binding sites in cancer

Pro

Hook

Bray

et al. 2022

Preprint

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Widespread perturbation of ETS factor binding sites in cancer

et al. 2023

Self Cite

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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.

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Optimized high-throughput screening of non-coding variants identified from genome-wide association studies

Morova¹,

Ding

Huang³

et al. 2022

Nucleic Acids Research

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The vast majority of disease-associated single nucleotide polymorphisms (SNP) identified from genome-wide association studies (GWAS) are localized in non-coding regions. A significant fraction of these variants impact transcription factors binding to enhancer elements and alter gene expression. To functionally interrogate the activity of such variants we developed snpSTARRseq, a high-throughput experimental method that can interrogate the functional impact of hundreds to thousands of non-coding variants on enhancer activity. snpSTARRseq dramatically improves signal-to-noise by utilizing a novel sequencing and bioinformatic approach that increases both insert size and the number of variants tested per loci. Using this strategy, we interrogated known prostate cancer (PCa) risk-associated loci and demonstrated that 35% of them harbor SNPs that significantly altered enhancer activity. Combining these results with chromosomal looping data we could identify interacting genes and provide a mechanism of action for 20 PCa GWAS risk regions. When benchmarked to orthogonal methods, snpSTARRseq showed a strong correlation with in vivo experimental allelic-imbalance studies whereas there was no correlation with predictive in silico approaches. Overall, snpSTARRseq provides an integrated experimental and computational framework to functionally test non-coding genetic variants.

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CASCADE: high-throughput characterization of regulatory complex binding altered by non-coding variants

Cited by 7 publications

References 66 publications

Widespread perturbation of ETS factor binding sites in cancer

Widespread perturbation of ETS factor binding sites in cancer

Widespread perturbation of ETS factor binding sites in cancer

Optimized high-throughput screening of non-coding variants identified from genome-wide association studies

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