Dataset Information

NextGen Consortium: The iPSCORE (iPSC Collection for Omic Research) Resource

ABSTRACT:

The iPSCORE Resource of human induced pluripotent stem cells (hiPSCs) was created as part of the Next-Gen Consortium funded by the NHLBI. The overarching purpose of the iPSCORE Resource is to provide a large collection of hiPSCs for use in studying the impact of genetic variation on molecular and physiological phenotypes. This Resource is being used in a number of ongoing studies for which genomic data will be generated and deposited into public repositories and linked through dbGaP. A total of 273 individuals have participated in the study for which 222 have had hiPSCs generated from fibroblasts (available through WiCell (http://www.wicell.org/)). Of the 273 individuals, 181 are part of 55 families that include 24 monozygotic twin pairs and 5 dizygotic twin pairs, allowing for the incorporation of familial relationships into genetic analyses. Germline DNA has been sequenced from blood or fibroblast samples for all 273 individuals (see phs001325) and other genomic data (RNA-seq, DNA methylation, and genotype arrays) has been generated from the 222 hiPSCs derived from a subset of these individuals (phs000924). Current studies include differentiation of these hiPSCs to other cell types, including cardiomyocytes and retinal pigment epithelium, and the generation of additional genomic data.

PROVIDER: phs000924 | dbGaP |

SECONDARY ACCESSION(S): PRJNA285375PRJNA285374

REPOSITORIES: dbGaP

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	GapExchange_phs000924.v1.p1.xml	Xml
	dbGaPEx2.1.5.xsd	Other
	phs000924.v1-Documents.zip	Other
	Study_Report.phs000924.iPSCORE.v1.p1.MULTI.pdf	Pdf
	manifest_phs000924.iPSCORE.v1.p1.c1.GRU.pdf	Pdf

Items per page:

1 - 5 of 80

Similar Datasets

Project description:DNA methylation appears to play an essential mechanistic role in the pathogenesis of ALL, thereby potentiate its use as a biomarker for diagnosis and prognosis (Milani, Lundmark et al. 2010; Geng, Brennan et al. 2012; Sandoval, Heyn et al. 2013), and even a potential target of novel therapeutic approaches in ALL. In present study, we collected blood specimens for 4 pairs of monozygotic twins (MZ) and 1 pair of dizygotic twin (DZ) that are discordant for ALL. We sought to comprehensively assess the magnitude of genetic and epigenetic differences between ALL-affected and unaffected twins. we conducted whole genome and whole methylome sequencing on these five pairs of ALL-discordant twins. We also examined both the MZ and DZ twins using whole-genome bisulfite sequencing (WGBS). At first, the methylation differences across the genome were addressed globally by Circos software. And then tried to characterize the co-twin methylation divergence in specific genomic regions between ALL-discordant twin pairs. These patterns of dynamic co-twin methylation changes in these discordant ALL samples were generally consistent among MZ and DZ twins, indicating similarities of methylation abnormalities. As a result, 780, 566, 309, 293 and 2110 DMRs were identified, with a similar distribution pattern across different genomic elements among the five twin pairs.Then we annotate whether these DMRs were located in regulatory elements and identification of genes with recurring methylation alterations in a cohort of ALL patients. We collected blood specimens from 4 pairs of MZ twins and 1 pair of DZ twin that are discordant for ALL. At first, the methylation differences across the genome were addressed globally by Circos software. And then tried to characterize the co-twin methylation divergence in specific genomic regions and differentially methylated gene regions (DMRs) were identified between ALL-discordant twin pairs. Then we annotate whether these DMRs were located in regulatory elements and identification of genes with recurring methylation alterations in a cohort of ALL patients.

Dataset Information

NextGen Consortium: The iPSCORE (iPSC Collection for Omic Research) Resource

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets