Xinchen Wang, Liang He, Sarah M. Goggin, Alham Saadat, Li Wang et al.
Genome-wide epigenomic maps have revealed millions of putative enhancers and promoters, but experimental validation of their function and high-resolution dissection of their driver nucleotides remain limited. Here, we present HiDRA (High-resolution Dissection of Regulatory Activity), a combined experimental and computational method for high-resolution genome-wide testing and dissection of putative regulatory regions. We test ~7 million accessible DNA fragments in a single experiment, by coupling accessible chromatin extraction with self-transcribing episomal reporters (ATAC-STARR-seq). By design, fragments are highly overlapping in densely-sampled accessible regions, enabling us to pinpoint driver regulatory nucleotides by exploiting differences in activity between partially-overlapping fragments using a machine learning model (SHARPR-RE). In GM12878 lymphoblastoid cells, we find ~65,000 regions showing enhancer function, and pinpoint ~13,000 high-resolution driver elements. These are enriched for regulatory motifs, evolutionarily-conserved nucleotides, and disease-associated genetic variants from genome-wide association studies. Overall, HiDRA provides a high-throughput, high-resolution approach for dissecting regulatory regions and driver nucleotides.
Xinchen Wang, Liang He, Sarah M. Goggin, Alham Saadat, Li Wang, Nasa Sinnott-Armstrong, Melina Claussnitzer, Manolis Kellis. High-resolution genome-wide functional dissection of transcriptional regulatory regions and nucleotides in human. 2018-12-19. https://doi.org/10.1038/s41467-018-07746-1
HiDRA captured accessible human genomic fragments from GM12878 cells, cloned them into an episomal STARR-seq reporter, and transfected the same lymphoblastoid cell line in five biological replicates. Matched plasmid-input and RNA-output sequencing quantified regulatory activity across overlapping fragment groups, with SHARPR-RE used by the authors to infer high-resolution driver elements.
Original supplemental and deposited inputs retained for this study. Download files individually or together as a ZIP; nested folders are preserved. Source reuse terms apply, and sequencing reads may be omitted.
Download all 11 files (ZIP)GSE104001_family.soft.gzGSE104001_HiDRA_counts_per_fragmentgroup.txt.gzGSE104001_MiSeq_Counts_per_SNP_group_by_90percent_overlap.txt.gzGSE104001_MiSeq_Fragment_to_SNP_group_by_90percent_overlap.txt.gzsource_notes.txtsupplementary_data_1_active_regions_hg19.bedsupplementary_data_2_tiled_regions_hg19.bedsupplementary_data_3_driver_elements_hg19.bedsupplementary_data_4_allele_specific_snps.txtsupplementary_file_description.pdfsupplementary_information.pdf