Functional dissection of metabolic trait-associated variants in steady state and stimulated human skeletal muscle cells [II]

Type 2 diabetes (T2D) is a common metabolic disorder characterized by dysregulation of glucose metabolism. Genome-wide association studies have defined hundreds of signals associated with T2D and related metabolic traits, most of which are found in noncoding regions. Given their central role in insulin production and glucose homeostasis, much focus has been devoted to investigating T2D-associated genetic variation in pancreatic islets; however, metabolic disease pathogenesis and risk is distributed across other important metabolic tissues, including the liver, adipose, and skeletal muscle. Here, we used a massively parallel reporter assay (MPRA) to characterize the regulatory activity of T2D-associated variants in human skeletal muscle cells at basal and multiple stimulatory states. We constructed a library of 1,255 oligos spanning 333 metabolic trait-associated variants, half of which were previously characterized using luciferase reporters or in MPRA libraries in any metabolic tissue, and therefore serve as positive controls. We delivered this library to LHCN-M2 human skeletal muscle myocytes in one of four conditions: (1) undifferentiated or differentiated with (2) basal media, (3) media supplemented with the AMP analog 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR) to mimic physiological effects of exercise or (4) media containing sodium palmitate which is known to induce insulin resistance. We gathered signal variants relevant to T2D and metabolic traits and designed 198-bp fragment sequences.We cloned these sequences into a modified form of the pMPRA1 vector with 20-bp barcodes. We shuttled this assembled library to the pLentiMPRA vector and generated infectious lentivirus. We infected 15 million LHCN-M2 at an MOI of ~10. We later isolated total RNA and gDNA and generated custom barcode sequencing libraries. We performed paired-end sequencing on an Illumina NovaSeq 6000 instrument.