A study of gene expression, structure, and contractility of iPSC-Derived Cardiac Myocytes from a family with heart disease due to LMNA mutation
Creators: name: Mehrabi, Mehrsa
name: Morris, Tessa A.
name: Cang, Zixuan
name: Nguyen, Cecilia H. H.
name: Sha, Yutong
name: Asad, Mira N.
name: Khachikyan, Nyree
name: Greene, Taylor L.
name: Becker, Danielle M.
name: Nie, Qing
name: Zaragoza, Michael V.
name: Grosberg, Anna
Publisher: name: Zenodo
Year: 2021

description: Genetic mutations to the Lamin A/C gene (LMNA) can cause heart disease, but the mechanisms making cardiac tissues uniquely vulnerable to the mutations remain largely unknown. Further, patients with LMNA mutations have highly variable presentation of heart disease progression and type. In vitro patient-specific experiments could provide a powerful platform for studying this phenomenon, but the use of induced pluripotent stem cell-derived cardiomyocytes (iPSC-CM) introduces heterogeneity in maturity and function thus complicating the interpretation of the results of any single experiment. We hypothesized that integrating single cell RNA sequencing (scRNA-seq) with analysis of the tissue architecture and contractile function would elucidate some of the probable mechanisms. To test this, we investigated five iPSC-CM lines, three controls and two patients with a (c.357-2A&gt;G) mutation. The patient iPSC-CM tissues had significantly weaker stress generation potential than control iPSC-CM tissues demonstrating the viability of our in vitro approach. Through scRNA-seq, differentially expressed genes between control and patient lines were identified. Some of these genes, linked to quantitative structural and functional changes, were cardiac specific, explaining the targeted nature of the disease progression seen in patients. The results of this work demonstrate the utility of combining in vitro tools in exploring heart disease mechanics.
description: The readme file contains an explanation of each if the supplement files in the DRYAD. More information the other methods and statistics can be found in the associated manuscript referenced above. Funding provided by: National Heart, Lung, and Blood Institute<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000050<br>Award Number: R01 HL129008Funding provided by: National Heart, Lung, and Blood Institute<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000050<br>Award Number: T32 HL116270Funding provided by: NSF D*<br>Crossref Funder Registry ID: <br>Award Number: Funding provided by: NSF DMS*<br>Crossref Funder Registry ID: <br>Award Number: DMS1763272Funding provided by: Simons Foundation<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000893<br>Award Number: 594598Funding provided by: National Heart, Lung, and Blood Institute<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000050<br>Award Number: R03 EB028605
description: The data set for single cell RNA analyzed by SCTransform utility in Seurat with default parameters to preprocess the two datasets separately. The two datasets then were integrated using Seurat with the top 3000 variable genes. A UMAP coordination shared by the two datasets were generated using the top 20 principal components. All the graphical plots were generated based on the single cell RNA dataset. Other data was collected using tissue engineering experimental methods described in the paper.