Global DNA methylation and transcriptional analyses of human ESC-derived cardiomyocytes
Ying Gu, Guang-Hui Liu, Nongluk Plongthongkum, Christopher Benner, Fei Yi, Jing Qu, Keiichiro Suzuki, Jiping Yang, Weiqi Zhang, Mo Li, Nuria Montserrat, Isaac Crespo, Antonio del Sol, Concepcion Rodriguez Esteban, Kun Zhang, Juan Carlos Izpisua Belmonte
Global DNA methylation and transcriptional analyses of human ESC-derived cardiomyocytes
With defined culture protocol, human embryonic stem cells (hESCs) are able to generate cardiomyocytes in vitro, therefore providing a great model for human heart development, and holding great potential for cardiac disease therapies. In this study, we successfully generated a highly pure population of human cardiomyocytes (hCMs) (>95% cTnT+) from hESC line, which enabled us to identify and characterize an hCM-specific signature, at both the gene expression and DNA methylation levels. Gene functional association network and gene-disease network analyses of these hCM-enriched genes provide new insights into the mechanisms of hCM transcriptional regulation, and stand as an informative and rich resource for investigating cardiac gene functions and disease mechanisms. Moreover, we show that cardiac-structural genes and cardiac-transcription factors have distinct epigenetic mechanisms to regulate their gene expression, providing a better understanding of how the epigenetic machinery coordinates to regulate gene expression in different cell types.
human cardiomyocyte / DNA methylation / microarray / heart development
[1] |
Bauer-MehrenA, RautschkaM, SanzF, FurlongLI (2010) DisGe-NET: a Cytoscape plugin to visualize, integrate, search and analyze gene-disease networks. Bioinformatics26: 2924-2926
CrossRef
Google scholar
|
[2] |
BeqqaliA, KlootsJ, Ward-van OostwaardD, MummeryC, PassierR (2006) Genome-wide transcriptional profiling of human embryonic stem cells differentiating to cardiomyocytes. Stem Cells24: 1956-1967
CrossRef
Google scholar
|
[3] |
CaoF, WagnerRA, WilsonKD, XieX, FuJD, DrukkerM, LeeA, LiRA, GambhirSS, WeissmanIL
CrossRef
Google scholar
|
[4] |
CrespoI, KrishnaA, Le BechecA, del SolA (2013) Predicting missing expression values in gene regulatory networks using a discrete logic modeling optimization guided by network stable states. Nucleic Acids Res41: e8
CrossRef
Google scholar
|
[5] |
DaraseliaN, YuryevA, EgorovS, NovichkovaS, NikitinA, MazoI (2004) Extracting human protein interactions from MEDLINE using a full-sentence parser. Bioinformatics20: 604-611
CrossRef
Google scholar
|
[6] |
DiepD, PlongthongkumN, GoreA, FungHL, ShoemakerR, ZhangK (2012) Library-free methylation sequencing with bisulfite padlock probes. Nat Methods9: 270-272
CrossRef
Google scholar
|
[7] |
GargA, XenariosI, MendozaL, DeMicheliG (2007) Lecture notes in computer science vol. 4453. In: Speed T, Huang H (eds). Springer, Berlin, p62-76
|
[8] |
GargA, Di CaraA, XenariosI, MendozaL, De MicheliG (2008) Synchronous versus asynchronous modeling of gene regulatory networks. Bioinformatics24: 1917-1925
CrossRef
Google scholar
|
[9] |
JohnsonDB (1975) Finding all the elementary circuits of a directed graph. SIAM J Comput4: 77-84
CrossRef
Google scholar
|
[10] |
KattmanSJ, WittyAD, GagliardiM, DuboisNC, NiapourM, HottaA, EllisJ, KellerG (2011) Stage-specific optimization of activin/nodal and BMP signaling promotes cardiac differentiation of mouse and human pluripotent stem cell lines. Cell Stem Cell8: 228-240
CrossRef
Google scholar
|
[11] |
LianX, HsiaoC, WilsonG, ZhuK, HazeltineLB, AzarinSM, RavalKK, ZhangJ, KampTJ, PalecekSP (2012) Robust cardiomyocyte differentiation from human pluripotent stem cells via temporal modulation of canonical Wnt signaling. Proc Natl Acad Sci USA109: E1848-E1857
CrossRef
Google scholar
|
[12] |
LiuGH, BarkhoBZ, RuizS, DiepD, QuJ, YangSL, PanopoulosAD, SuzukiK, KurianL, WalshC
CrossRef
Google scholar
|
[13] |
LiuGH, QuJ, SuzukiK, NivetE, LiM, MontserratN, YiF, XuX, RuizS, ZhangW
CrossRef
Google scholar
|
[14] |
MaereS, HeymansK, KuiperM (2005) BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks. Bioinformatics21: 3448-3449
CrossRef
Google scholar
|
[15] |
MontojoJ, ZuberiK, RodriguezH, KaziF, WrightG, DonaldsonSL, MorrisQ, BaderGD (2010) GeneMANIA Cytoscape plugin: fast gene function predictions on the desktop. Bioinformatics26: 2927-2928
CrossRef
Google scholar
|
[16] |
NovichkovaS, EgorovS, DaraseliaN (2003) MedScan, a natural language processing engine for MEDLINE abstracts. Bioinformatics19: 1699-1706
CrossRef
Google scholar
|
[17] |
PaigeSL, ThomasS, Stoick-CooperCL, WangH, MavesL, SandstromR, PabonL, ReineckeH, PrattG, KellerG
CrossRef
Google scholar
|
[18] |
ShannonP, MarkielA, OzierO, BaligaNS, WangJT, RamageD, AminN, SchwikowskiB, IdekerT (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res13: 2498-2504
CrossRef
Google scholar
|
[19] |
SynnergrenJ, AkessonK, DahlenborgK, VidarssonH, AmeenC, SteelD, LindahlA, OlssonB, SartipyP (2008) Molecular signature of cardiomyocyte clusters derived from human embryonic stem cells. Stem Cells26: 1831-1840
CrossRef
Google scholar
|
[20] |
WillemsE, Cabral-TeixeiraJ, SchadeD, CaiW, ReevesP, BushwayPJ, LanierM, WalshC, KirchhausenT, Izpisua BelmonteJC
CrossRef
Google scholar
|
[21] |
XieW, SchultzMD, ListerR, HouZ, RajagopalN, RayP, WhitakerJW, TianS, HawkinsRD, LeungD
CrossRef
Google scholar
|
[22] |
YangL, SoonpaaMH, AdlerED, RoepkeTK, KattmanSJ, KennedyM, HenckaertsE, BonhamK, AbbottGW, LindenRM
CrossRef
Google scholar
|
[23] |
ZhangJ, KlosM, WilsonGF, HermanAM, LianX, RavalKK, BarronMR, HouL, SoerensAG, YuJ
CrossRef
Google scholar
|
/
〈 | 〉 |