bioRxivDevelopmental BiologyPreprint
Cardiac differentiation at single cell resolution reveals a requirement of hypertrophic signaling for HOPX transcription
Clayton E. FriedmaniD, Quan Hoang NguyeniD, Samuel W. LukowskiiD, Han Sheng ChiuiD, Abbigail HelferiD, Jason Wayne MiklasiD, Shengbao SuoiD, Jing‐Dong J. HaniD, Pierre OsteiliD, Guangdun PengiD, Naihe JingiD, Gregory J. BaillieiD, Anne SenabouthiD, Angelika N. ChristiD, Timothy J. C. BruxneriD, Charles E. MurryiD, Emily S. W. WongiD, Jun DingiD, Yuliang Wang, James E. HudsoniD, Hannele Ruohola‐BakeriD, Ziv Bar‐JosephiD, Patrick TamiD, Joseph E. PowelliD, Nathan J. PalpantiD
Abstract
Differentiation into diverse cell lineages requires the orchestration of gene regulatory networks guiding diverse cell fate choices. Utilizing human pluripotent stem cells, we measured expression dynamics of 17,718 genes from 43,168 cells across five time points over a thirty day time-course of in vitro cardiac-directed differentiation. Unsupervised clustering and lineage prediction algorithms were used to map fate choices and transcriptional networks underlying cardiac differentiation. We leveraged this resource to identify strategies for controlling in vitro differentiation as it occurs in vivo. HOPX, a non-DNA binding homeodomain protein essential for heart development in vivo was identified as dys-regulated in in vitro derived cardiomyocytes. Utilizing genetic gain and loss of function approaches, we dissect the transcriptional complexity of the HOPX locus and identify the requirement of hypertrophic signaling for HOPX transcription in hPSC-derived cardiomyocytes. This work provides a single cell dissection of the transcriptional landscape of cardiac differentiation for broad applications of stem cells in cardiovascular biology.
- organism: human
- assay: bulk RNA-seq
- research focus: clustering
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 2
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