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RNA variant assessment using transactivation and transdifferentiation.

ABSTRACT: Understanding the impact of splicing and nonsense variants on RNA is crucial for the resolution of variant classification as well as their suitability for precision medicine interventions. This is primarily enabled through RNA studies involving transcriptomics followed by targeted assays using RNA isolated from clinically accessible tissues (CATs) such as blood or skin of affected individuals. Insufficient disease gene expression in CATs does however pose a major barrier to RNA based investigations, which we show is relevant to 1,436 Mendelian disease genes. We term these "silent" Mendelian genes (SMGs), the largest portion (36%) of which are associated with neurological disorders. We developed two approaches to induce SMG expression in human dermal fibroblasts (HDFs) to overcome this limitation, including CRISPR-activation-based gene transactivation and fibroblast-to-neuron transdifferentiation. Initial transactivation screens involving 40 SMGs stimulated our development of a highly multiplexed transactivation system culminating in the 6- to 90,000-fold induction of expression of 20/20 (100%) SMGs tested in HDFs. Transdifferentiation of HDFs directly to neurons led to expression of 193/516 (37.4%) of SMGs implicated in neurological disease. The magnitude and isoform diversity of SMG expression following either transactivation or transdifferentiation was comparable to clinically relevant tissues. We apply transdifferentiation and/or gene transactivation combined with short- and long-read RNA sequencing to investigate the impact that variants in USH2A, SCN1A, DMD, and PAK3 have on RNA using HDFs derived from affected individuals. Transactivation and transdifferentiation represent rapid, scalable functional genomic solutions to investigate variants impacting SMGs in the patient cell and genomic context.

SUBMITTER: Nicolas-Martinez EC

PROVIDER: S-EPMC11339655 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature

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RNA variant assessment using transactivation and transdifferentiation.

Nicolas-Martinez Emmylou C EC Robinson Olivia O Pflueger Christian C Gardner Alison A Corbett Mark A MA Ritchie Tarin T Kroes Thessa T van Eyk Clare L CL Scheffer Ingrid E IE Hildebrand Michael S MS Barnier Jean-Vianney JV Rousseau Véronique V Genevieve David D Haushalter Virginie V Piton Amélie A Denommé-Pichon Anne-Sophie AS Bruel Ange-Line AL Nambot Sophie S Isidor Bertrand B Grigg John J Gonzalez Tina T Ghedia Sondhya S Marchant Rhett G RG Bournazos Adam A Wong Wui-Kwan WK Webster Richard I RI Evesson Frances J FJ Jones Kristi J KJ Cooper Sandra T ST Lister Ryan R Gecz Jozef J Jolly Lachlan A LA

American journal of human genetics 20240730 8

Understanding the impact of splicing and nonsense variants on RNA is crucial for the resolution of variant classification as well as their suitability for precision medicine interventions. This is primarily enabled through RNA studies involving transcriptomics followed by targeted assays using RNA isolated from clinically accessible tissues (CATs) such as blood or skin of affected individuals. Insufficient disease gene expression in CATs does however pose a major barrier to RNA based investigati ...[more]

PMID: 39084224

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Project description:Synthetic transcription factors can be applied to many areas of biotechnology, medicine, and basic research.Â Currently, the most common method for engineering synthetic transcription factors has been based on programmable DNA-binding domains of zinc finger proteins, Transcription Activator-Like Effectors (TALEs), and most recently the CRISPR/Cas9 system. These transcription factor platforms consist of the DNA-binding domain fused to potent transcriptional activation domains, most commonly the tetramer of the minimal transactivation domain of the VP16 protein from herpes simplex virus, referred to as VP64. Although many applications are well-suited for the targeted activation of a single gene, genetic reprogramming requires the coordinated regulation of many nodes of natural gene networks as is typically performed by naturally occurring reprogramming factors. Thus we sought to combine principles from each of these approaches by attaching potent transcriptional activation domains to a natural reprogramming factor to increase the efficiency and/or rate of cell fate conversion. In this study, we evaluated the effects of fusing potent activation domains to the transcription factor MyoD, the master regulator of the skeletal myoblast lineage. In certain non-myogenic lineages, MyoD overexpression causes upregulation of the myogenic gene network and conversion to a myoblast phenotype including cell fusion into multinucleated myotubes. Compared to wild-type MyoD, the VP64-MyoD fusion protein induced greater overall reprogramming of global gene expression. This simple approach for increasing the potency of natural reprogramming factors circumvents the need for screening engineered proteins and leads to a more robust cellular reprogramming compared to treatment with the wild type transcription factor. Human dermal fibroblasts were transduced with a single tet inducible lentivirus that expresses either WT-MyoD or VP64-MyoD in response to treatment with doxycycline. Untreated human dermal fibroblast served as the negative control. Gene expression was measured using mRNA-seq, and differential expression was calculated using DESeq. All experiments were performed in biological duplicates.

Dataset Information

RNA variant assessment using transactivation and transdifferentiation.

Publications

RNA variant assessment using transactivation and transdifferentiation.

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