Deep characterization of blood cell miRNomes by NGS. Schwarz, E. C, Backes, C., Knörck, A., Ludwig, N., Leidinger, P., Hoxha, C., Schwär, G., Grossmann, T., Müller, S. C, Hart, M., Haas, J., Galata, V., Müller, I., Fehlmann, T., Eichler, H., Franke, A., Meder, B., Meese, E., Hoth, M., & Keller, A. Cellular and molecular life sciences : CMLS, 73:3169–3181, August, 2016.
doi  abstract   bibtex   1 download  
A systematic understanding of different factors influencing cell type specific microRNA profiles is essential for state-of-the art biomarker research. We carried out a comprehensive analysis of the biological variability and changes in cell type pattern over time for different cell types and different isolation approaches in technical replicates. All combinations of the parameters mentioned above have been measured, resulting in 108 miRNA profiles that were evaluated by next-generation-sequencing. The largest miRNA variability was due to inter-individual differences (34 %), followed by the cell types (23.4 %) and the isolation technique (17.2 %). The change over time in cell miRNA composition was moderate (<3 %) being close to the technical variations (<1 %). Largest variability (including technical and biological variance) was observed for CD8 cells while CD3 and CD4 cells showed significantly lower variations. ANOVA highlighted that 51.5 % of all miRNAs were significantly influenced by the purification technique. While CD4 cells were least affected, especially miRNA profiles of CD8 cells were fluctuating depending on the cell purification approach. To provide researchers access to the profiles and to allow further analyses of the tested conditions we implemented a dynamic web resource.
@Article{Schwarz2016,
  author          = {Schwarz, Eva C and Backes, Christina and Knörck, Arne and Ludwig, Nicole and Leidinger, Petra and Hoxha, Cora and Schwär, Gertrud and Grossmann, Thomas and Müller, Sabine C and Hart, Martin and Haas, Jan and Galata, Valentina and Müller, Isabelle and Fehlmann, Tobias and Eichler, Hermann and Franke, Andre and Meder, Benjamin and Meese, Eckart and Hoth, Markus and Keller, Andreas},
  title           = {Deep characterization of blood cell miRNomes by NGS.},
  journal         = {Cellular and molecular life sciences : CMLS},
  year            = {2016},
  volume          = {73},
  pages           = {3169--3181},
  month           = aug,
  issn            = {1420-9071},
  abstract        = {A systematic understanding of different factors influencing cell type specific microRNA profiles is essential for state-of-the art biomarker research. We carried out a comprehensive analysis of the biological variability and changes in cell type pattern over time for different cell types and different isolation approaches in technical replicates. All combinations of the parameters mentioned above have been measured, resulting in 108 miRNA profiles that were evaluated by next-generation-sequencing. The largest miRNA variability was due to inter-individual differences (34 %), followed by the cell types (23.4 %) and the isolation technique (17.2 %). The change over time in cell miRNA composition was moderate (<3 %) being close to the technical variations (<1 %). Largest variability (including technical and biological variance) was observed for CD8 cells while CD3 and CD4 cells showed significantly lower variations. ANOVA highlighted that 51.5 % of all miRNAs were significantly influenced by the purification technique. While CD4 cells were least affected, especially miRNA profiles of CD8 cells were fluctuating depending on the cell purification approach. To provide researchers access to the profiles and to allow further analyses of the tested conditions we implemented a dynamic web resource.},
  chemicals       = {MicroRNAs},
  citation-subset = {IM},
  completed       = {2017-08-03},
  country         = {Switzerland},
  doi             = {10.1007/s00018-016-2154-9},
  issn-linking    = {1420-682X},
  issue           = {16},
  keywords        = {Base Sequence; Blood Cells, metabolism; Cluster Analysis; Gene Expression Profiling, methods; High-Throughput Nucleotide Sequencing, methods; Humans; MicroRNAs, genetics, isolation & purification; Principal Component Analysis; Blood cells; FACS; Next-generation sequencing; microRNA},
  nlm-id          = {9705402},
  owner           = {NLM},
  pii             = {10.1007/s00018-016-2154-9},
  pmid            = {26874686},
  pubmodel        = {Print-Electronic},
  pubstatus       = {ppublish},
  revised         = {2018-01-30},
}

Downloads: 1