Dataset Information

Cross-platform ultradeep transcriptomic profiling of human reference RNA samples by RNA-Seq.

ABSTRACT: Whole-transcriptome sequencing ('RNA-Seq') has been drastically changing the scale and scope of genomic research. In order to fully understand the power and limitations of this technology, the US Food and Drug Administration (FDA) launched the third phase of the MicroArray Quality Control (MAQC-III) project, also known as the SEquencing Quality Control (SEQC) project. Using two well-established human reference RNA samples from the first phase of the MAQC project, three sequencing platforms were tested across more than ten sites with built-in truths including spike-in of external RNA controls (ERCC), titration data and qPCR verification. The SEQC project generated over 30 billion sequence reads representing the largest RNA-Seq data ever generated by a single project on individual RNA samples. This extraordinarily ultradeep transcriptomic data set and the known truths built into the study design provide many opportunities for further research and development to advance the improvement and application of RNA-Seq.

SUBMITTER: Xu J

PROVIDER: S-EPMC4322577 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Cross-platform ultradeep transcriptomic profiling of human reference RNA samples by RNA-Seq.

Xu Joshua J Su Zhenqiang Z Hong Huixiao H Thierry-Mieg Jean J Thierry-Mieg Danielle D Kreil David P DP Mason Christopher E CE Tong Weida W Shi Leming L

Scientific data 20140826

Whole-transcriptome sequencing ('RNA-Seq') has been drastically changing the scale and scope of genomic research. In order to fully understand the power and limitations of this technology, the US Food and Drug Administration (FDA) launched the third phase of the MicroArray Quality Control (MAQC-III) project, also known as the SEquencing Quality Control (SEQC) project. Using two well-established human reference RNA samples from the first phase of the MAQC project, three sequencing platforms were ...[more]

PMID: 25977777

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Project description:Adipose-derived stromal/stem cells (ASCs) are multipotent in nature that can be differentiated into various cells lineages such as adipogenic, osteogenic, and chondrogenic. The commitment of a cell to differentiate into a particular lineage is regulated by the interplay between various intracellular pathways and their resultant secretome. Similarly, the interactions of cells with the extracellular matrix (ECM) and the ECM bound growth factors instigate several signal transducing events that ultimately determine ASC differentiation. In this study, RNA-sequencing (RNA-Seq) was performed to identify the transcriptome profile of osteogenic induced ASCs to understand the associated genotype changes. Gene ontology (GO) functional annotations analysis using Database for Annotation Visualization and Integrated Discovery (DAVID) bioinformatics resources on the differentially expressed genes demonstrated the enrichment of pathways mainly associated with ECM organization and angiogenesis. We, therefore, studied the expression of genes coding for matrisome proteins (glycoproteins, collagens, proteoglycans, ECM-affiliated, regulators, and secreted factors) and ECM remodeling enzymes (MMPs, integrins, ADAMTSs) and the expression of angiogenic markers during the osteogenesis of ASCs. The upregulation of several pro-angiogenic ELR+ chemokines and other angiogenic inducers during osteogenesis indicates the potential role of the secretome from differentiating ASCs in the vascular development and its integration with the bone tissue. Furthermore, the increased expression of regulatory genes such as CTNNB1, TGBR2, JUN, FOS, GLI3, and MAPK3 involved in the WNT, TGF-?, JNK, HedgeHog and ERK1/2 pathways suggests the regulation of osteogenesis through interplay between these pathways. The RNA-Seq data was also validated by performing QPCR on selected up- and down-regulated genes (COL10A1, COL11A1, FBLN, FERMT1, FN1, FOXF1, LAMA3, LAMA4, LAMB1, IGF1, WNT10B, MMP1, MMP3, MMP16, ADAMTS6, and ADAMTS14).

Dataset Information

Cross-platform ultradeep transcriptomic profiling of human reference RNA samples by RNA-Seq.

Publications

Cross-platform ultradeep transcriptomic profiling of human reference RNA samples by RNA-Seq.

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