Massively parallel characterization of transcriptional regulatory elements

• 成果类型: Article
• 署名作者: Agarwal, Vikram; Inoue, Fumitaka; Schubach, Max; Penzar, Dmitry; Martin, Beth K.; Dash, Pyaree Mohan; Keukeleire, Pia; Zhang, Zicong; Sohota, Ajuni; Zhao, Jingjing; Georgakopoulos-Soares, Ilias; Noble, William S.; Yardimci, Galip Gurkan; Kulakovskiy, Ivan V.; Kircher, Martin; Shendure, Jay; Ahituv, Nadav
• 署名单位: University of Washington; University of Washington Seattle; Sanofi-Aventis; Sanofi USA; University of California System; University of California San Francisco; University of California System; University of California San Francisco; Kyoto University; Humboldt University of Berlin; Free University of Berlin; Charite Universitatsmedizin Berlin; Berlin Institute of Health; Russian Academy of Sciences; Vavilov Institute of General Genetics; Russian Academy of Sciences; Pirogov Russian National Research Medical University; University of Lubeck; University of Kiel; Schleswig Holstein University Hospital; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Penn State Health; University of Washington; University of Washington Seattle; Oregon Health & Science University; Oregon Health & Science University; Howard Hughes Medical Institute; University of Washington; University of Washington Seattle
• 刊物名称: Nature
• ISSN/ISSBN: 0028-3551
• DOI: 10.1038/s41586-024-08430-9
• 发表日期: 2025-03-13
• 关键词: beta-globin gene; factor-binding; expression; chromatin; tissue

摘要

The human genome contains millions of candidate cis-regulatory elements (cCREs) with cell-type-specific activities that shape both health and many disease states1. However, we lack a functional understanding of the sequence features that control the activity and cell-type-specific features of these cCREs. Here we used lentivirus-based massively parallel reporter assays (lentiMPRAs) to test the regulatory activity of more than 680,000 sequences, representing an extensive set of annotated cCREs among three cell types (HepG2, K562 and WTC11), and found that 41.7% of these sequences were active. By testing sequences in both orientations, we find promoters to have strand-orientation biases and their 200-nucleotide cores to function as non-cell-type-specific 'on switches' that provide similar expression levels to their associated gene. By contrast, enhancers have weaker orientation biases, but increased tissue-specific characteristics. Utilizing our lentiMPRA data, we develop sequence-based models to predict cCRE function and variant effects with high accuracy, delineate regulatory motifs and model their combinatorial effects. Testing a lentiMPRA library encompassing 60,000 cCREs in all three cell types further identified factors that determine cell-type specificity. Collectively, our work provides an extensive catalogue of functional CREs in three widely used cell lines and showcases how large-scale functional measurements can be used to dissect regulatory grammar.