Study / S1169F3AF2026-04-07

Using a modular massively parallel reporter assay to discover context-dependent regulatory activity in type 2 diabetes-linked noncoding regions

Adelaide Tovar, Yasuhiro Kyono, Kirsten Nishino, Maya Bose, Arushi Varshney et al.

About this study

Most complex trait association signals reside in the noncoding genome, where defining function is challenging. MPRAs (massively parallel reporter assays) offer a scalable means to test variants’ regulatory impacts but are typically cell-type agnostic, pairing cloned fragments with generic ‘housekeeping’ promoters. To explore MPRAs’ context sensitivity, we screened a panel of nearly 12,000 fragments across >300 diabetes- and metabolic-trait-associated regions in a pancreatic β cell line model. We compared activity when fragments were placed up- versus downstream of a reporter gene and combined with the synthetic housekeeping promoter super core promoter 1 (SCP1) versus the physiologically relevant human insulin (INS) gene promoter. We identified clear effects of MPRA construct design on regulatory activity. A subset of fragments (n = 702/11,656) displayed positional bias, evenly distributed across up- and downstream preferences. Promoter choice also influenced MPRA activity (n = 698/11,656), mostly biased toward the cell-specific INS promoter (73.4%). A screen for sequence annotations associated with INS promoter preference revealed enrichment for HNF1 binding motifs. HNF1 family transcription factors are key regulators of glucose metabolism disrupted in maturity-onset diabetes of the young (MODY), suggesting genetic convergence between rare coding variants that cause MODY and common type 2 diabetes (T2D)-associated regulatory regions. A follow-up HNF1-focused MPRA highlighted several instances where motif deletion or mutation disrupted regulatory activity specifically in the context of the INS1 promoter and in the β cell model but not in another diabetes-relevant cell type, skeletal muscle. These results identify technical factors that may require careful consideration while designing MPRA experiments.

Full author list & citation

Adelaide Tovar, Yasuhiro Kyono, Kirsten Nishino, Maya Bose, Arushi Varshney, Stephen C.J. Parker, Jacob O. Kitzman. Using a modular massively parallel reporter assay to discover context-dependent regulatory activity in type 2 diabetes-linked noncoding regions. 2026-04-07. https://doi.org/10.1016/j.xhgg.2026.100606

Experiments 3

E0940FA5C

MYBPC2-promoter integrated MPRA in differentiated LHCN-M2 myotubes

This table summarizes the processed LHCN-M2 barcode/count data deposited under GSE247455 for the muscle-context arm of the study. Because the deposited barcode dictionary exposes only the MYBPC2 promoter and six element-group names rather than variant-level oligo identities, the table honestly reports six group-level activity summaries across four RNA and four gDNA replicates.

Integrated lentiMPRAHuman
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E58347FE1

HNF1 motif-perturbation MPRA in INS-1 832/13 beta cells

The follow-up episomal MPRA tested original, HNF1-motif-deleted, and dinucleotide-shuffled fragments selected from the first library, with reference and alternate alleles where applicable. The table contains the 379 finite fragment/promoter records in publisher Table S15 for INS and SCP1 contexts in INS-1 832/13 cells, including five replicate log2 RNA/DNA values.

Episomal Plasmid MPRANCBITaxon:10116hg38
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Raw source data 42 files

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 42 files (ZIP)1-s2.0-S2666247726000461-mmc1.pdf1-s2.0-S2666247726000461-mmc10.xlsx1-s2.0-S2666247726000461-mmc11.xlsx1-s2.0-S2666247726000461-mmc12.xlsx1-s2.0-S2666247726000461-mmc13.xlsx1-s2.0-S2666247726000461-mmc14.xlsx1-s2.0-S2666247726000461-mmc15.xlsx1-s2.0-S2666247726000461-mmc16.xlsx1-s2.0-S2666247726000461-mmc17.pdf1-s2.0-S2666247726000461-mmc2.xlsx1-s2.0-S2666247726000461-mmc3.xlsx1-s2.0-S2666247726000461-mmc4.xlsx1-s2.0-S2666247726000461-mmc5.xlsx1-s2.0-S2666247726000461-mmc6.xlsx1-s2.0-S2666247726000461-mmc7.xlsx1-s2.0-S2666247726000461-mmc8.xlsx1-s2.0-S2666247726000461-mmc9.xlsxbuild_processed_tables.pyfirst_library.RGSE247455_bc_dictionary.txt.gzGSE247455_family.soft.gzGSE247455_family.xml.tgzGSE247455_lhcnm2-mpra-counts.txt.gzGSE247455_series_matrix.txt.gzGSE279057-GPL21616_series_matrix.txt.gzGSE279057-GPL22396_series_matrix.txt.gzGSE279057_family.soft.gzGSE279057_family.xml.tgzGSE279057_kyono_library_annotations.txt.gzGSE279057_kyono_library_barcode_pairing.txt.gzGSE279057_kyono_library_counts.txt.gzGSE279071-GPL25947_series_matrix.txt.gzGSE279071-GPL26526_series_matrix.txt.gzGSE279071_family.soft.gzGSE279071_family.xml.tgzGSE279071_tovar_library_annotations.txt.gzGSE279071_tovar_library_barcode_pairing.txt.gzGSE279071_tovar_library_counts.txt.gzLICENSEREADME.mdREADME.txtsecond_library.R

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