Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Variability of gene expression profiles in human blood and lymphoblastoid cell lines

ABSTRACT: Readily accessible samples such as peripheral blood or cell lines are increasingly being used in large cohorts to characterise gene expression differences between a patient group and healthy controls. However, cell and RNA isolation procedures and the variety of cell types that make up whole blood can affect gene expression measurements. We therefore systematically investigated global gene expression profiles in peripheral blood from six individuals collected during two visits by comparing five of the following cell and RNA isolation methods: whole blood (PAXgene), peripheral blood mononuclear cells (PBMCs), lymphoblastoid cell lines (LCLs), CD19 and CD20 specific B-cell subsets. Gene expression measurements were clearly discriminated by isolation method although the reproducibility was high for all methods (range ρ = 0.90-1.00). The PAXgene samples showed a decrease in the number of expressed genes (P<1*10-16) with higher variability (P<1*10-16) compared to the other methods. Differentially expressed probes between PAXgene and PBMCs were correlated with the number of monocytes, lymphocytes, neutrophils or erythrocytes. The correlations (ρ =0.83; ρ =0.79) between the expression levels of detected probes were much lower compared to the two B-cell isolation methods (ρ =0.98). Gene ontology analysis of detected genes showed that genes involved in inflammatory responses are enriched in B-cells CD19 and CD20 whereas genes involved in alcohol metabolic process and the cell cycle were enriched in LCLs. Gene expression profiles in blood-based samples are strongly dependent on the predominant constituent cell type(s) and RNA isolation method. It is crucial to understand the differences and variability of gene expression measurements between cell and RNA isolation procedures, and their relevance to disease processes before application in large clinical studies. In the present study, we investigated variability and consistency in gene expression profiles between five of the most common post venipuncture methods of cell and RNA isolation: whole blood (PAXgene (PAX)), PBMCs, Epstein-Barr virus (EBV) transformed LCLs, CD19-specific B-cells subsets (B-cell CD19), CD20-specific B-cells subsets (B-cell CD20). Using samples from six individuals collected during two visits, we evaluated the differences and concordances of global gene expression profiles, the biological and technical variability seen in these approaches, cell-type specific gene expression signatures and their relevance to large-scale biobanking initiatives.

ORGANISM(S): Homo sapiens

SUBMITTER: Josine Min

PROVIDER: E-GEOD-30916 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Variability of gene expression profiles in human blood and lymphoblastoid cell lines.

Min Josine L JL Barrett Amy A Watts Tim T Pettersson Fredrik H FH Lockstone Helen E HE Lindgren Cecilia M CM Taylor Jennifer M JM Allen Maxine M Zondervan Krina T KT McCarthy Mark I MI

BMC genomics 20100208

<h4>Background</h4>Readily accessible samples such as peripheral blood or cell lines are increasingly being used in large cohorts to characterise gene expression differences between a patient group and healthy controls. However, cell and RNA isolation procedures and the variety of cell types that make up whole blood can affect gene expression measurements. We therefore systematically investigated global gene expression profiles in peripheral blood from six individuals collected during two visits ...[more]

PMID: 20141636

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Project description:Epstein-Barr virus (EBV) transformed lymphoblastoid cell lines (LCLs) are a widely used renewable resource for functional genomic studies in humans. The ability to accumulate multidimensional data pertaining to the same individual cell lines, from complete genomic sequences to detailed gene regulatory profiles, further enhances the utility of LCLs as a model system. However, the extent to which LCLs are a faithful model system is relatively unknown. We have previously shown that gene expression profiles of newly established LCLs maintain a strong individual component. Here, we extend our study to investigate the effect of freeze-thaw cycles on gene expression patterns in mature LCLs, especially in the context of inter-individual variation in gene regulation. We found a profound difference in the gene expression profiles of newly established and mature LCLs. Once newly established LCLs undergo a freeze-thaw cycle, the individual specific gene expression signatures become much less pronounced as the gene regulatory programs in LCLs from different individuals converge to a more uniform profile, which reflects a mature transformed B cell phenotype. As expected, previously identified eQTLs are enriched among the relatively few genes whose regulations in mature LCLs maintain marked individual signatures. We thus conclude that findings and insight drawn from gene regulatory studies in mature LCLs are generally not affected by artificial nature of the LCL model system and are likely to faithfully reflect regulatory interactions in primary tissues. However, our data indicate that many aspects of primary B cell biology cannot be observed and studied in mature LCL cultures. We obtained unpurified buffy coats (of a unit of blood) from six unrelated healthy individuals of Caucasian ethnicity (age range: 20-45). We isolated CD20+ B cells and established six independent cultures of LCLs between October 2009 and January 2010. From each of these samples, we obtained genome wide gene expression data using Illumina HumanHT-12 v3 Expression BeadChip arrays. We refer to data from these experiments as M-bM-^@M-^\cycle 0M-bM-^@M-^] to acknowledge the fact that the LCLs from this cycle were newly established and therefore not frozen/thawed. Between February 2011 and October 2012, we thawed each of these LCL cultures every 3 months and cultured them until obtaining ~10 million cells (February 2011=cycle 1, June 2011=cycle 2, October 2011=cycle 3, February 2012=cycle 4, June 2012=cycle 5, and October 2012=cycle 6). We used Illumina HumanHT-12 v4 Expression BeadChip arrays and obtained genome wide gene expression data on cycle 2, cycle 4 and cycle 6 LCLs. At each hybridization batch we included a subset of RNA samples that were also hybridized in a previous batch. This allowed us to effectively consider the batch effect on gene expression profiles. Our final dataset included genome wide gene expression data from 187 samples collected at 4 different time points.

Dataset Information

Variability of gene expression profiles in human blood and lymphoblastoid cell lines

Publications

Variability of gene expression profiles in human blood and lymphoblastoid cell lines.

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