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Published on: August 4, 2022
Transcriptional Variabilities in Human hiPSC-derived Cardiomyocytes: All Genes Are Not Equal and Their Robustness May
Insights
Human induced pluripotent stem cells (hiPSCs) offer a robust model for studying genetic diseases like left ventricular hypertrophy (LVH). hiPSC-derived cardiomyocytes reveal that biological variability, not technical noise, drives disease modeling insights.
Area of Science:
- Cardiovascular Biology
- Stem Cell Biology
- Genetics
Background:
- Human induced pluripotent stem cells (hiPSCs) are crucial for disease modeling, but understanding transcriptional variability is key.
- Left ventricular hypertrophy (LVH) is a complex cardiac condition requiring accurate cellular models.
Approach:
- Assessed transcriptional variability in hiPSC-derived cardiomyocytes (hiPSC-CMs) from 7 HyperGEN donors with LVH.
- Differentiated hiPSC-CMs multiple times and applied a cardiac stimulant to evaluate reprogramming, differentiation, and pathological response variability.
- Quantified technical vs. biological variability across gene expression profiles.
Key Points:
- For most genes (73.3%–85.5%), biological variability exceeded technical variability in hiPSC-CMs.
- Identified distinct sets of "noise" (high technical variability) and "signal" (high biological variability) genes.
- Findings support a "genetic robustness" hypothesis in disease modeling with hiPSC-derived cells.
Conclusions:
- hiPSC-CMs serve as a valid model for studying cardiac hypertrophy.
- This model effectively distinguishes between technical transcriptional noise and disease-relevant biological signals.
Abstract:
Human induced pluripotent stem cells (hiPSCs) are frequently used to study disease-associated variations. We characterized transcriptional variability from a hiPSC-derived cardiomyocyte (hiPSC-CM) study of left ventricular hypertrophy (LVH) using donor samples from the HyperGEN study. Multiple hiPSC-CM differentiations over reprogramming events (iPSC generation) across 7 donors were used to assess variabilities from reprogramming, differentiation, and donor LVH status. Variability arising from pathological alterations was assessed using a cardiac stimulant applied to the hiPSC-CMs to trigger hypertrophic responses. We found that for most genes (73.3%~85.5%), technical variability was smaller than biological variability. Further, we identified and characterized lists of "noise" genes showing greater technical variability and "signal" genes showing greater biological variability. Together, they support a "genetic robustness" hypothesis of disease-modeling whereby cellular response to relevant stimuli in hiPSC-derived somatic cells from diseased donors tends to show more transcriptional variability. Our findings suggest that hiPSC-CMs can provide a valid model for cardiac hypertrophy and distinguish between technical and disease-relevant transcriptional changes.
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