Deep characterization of blood cell miRNomes by NGS

Cellular and Molecular Life Sciences

Volumn 73, Issue 16, 2016, Pages 3169-3181

  Schwarz, Eva C ^a   Backes, Christina ^b   Knörck, Arne ^a   Ludwig, Nicole ^a   Leidinger, Petra ^a   Hoxha, Cora ^a   Schwär, Gertrud ^a   Grossmann, Thomas ^b   Müller, Sabine C ^b   Hart, Martin ^a   Haas, Jan ^c,d,e   Galata, Valentina ^b   Müller, Isabelle ^a   Fehlmann, Tobias ^b   Eichler, Hermann ^a   Franke, Andre ^f   Meder, Benjamin ^c,d,e   Meese, Eckart ^a   Hoth, Markus ^a   Keller, Andreas ^b  

^a SAARLAND UNIVERSITY   (Germany)

^b SAARLAND UNIVERSITY   (Germany)

^c UNIVERSITY HOSPITAL HEIDELBERG   (Germany)

^d DZHK GERMAN CENTRE FOR CARDIOVASCULAR RESEARCH   (Germany)

^e Klaus Tschira Institute for Integrative Computational Cardiology   (Germany)

^f UNIVERSITY OF KIEL   (Germany)

Author keywords

Blood cells; FACS; microRNA; Next generation sequencing

Indexed keywords

MICRORNA; MICRORNA 138 5P; MICRORNA 151B; MICRORNA 21; MICRORNA 21 5P; MICRORNA 345 5P; MICRORNA 628 3P; UNCLASSIFIED DRUG;

ARTICLE; BLOOD CELL; CD3+ T LYMPHOCYTE; CD4+ T LYMPHOCYTE; CD8+ T LYMPHOCYTE; CELL SUBPOPULATION; CELLS BY BODY ANATOMY; GENE CLUSTER; GENE CONTROL; GENE EXPRESSION PROFILING; GENETIC VARIABILITY; HUMAN; ISOLATION PROCEDURE; NEXT GENERATION SEQUENCING; PURIFICATION; REPRODUCIBILITY; RNA ANALYSIS; CLUSTER ANALYSIS; GENETICS; HIGH THROUGHPUT SEQUENCING; ISOLATION AND PURIFICATION; METABOLISM; NUCLEOTIDE SEQUENCE; PRINCIPAL COMPONENT ANALYSIS; PROCEDURES;

BASE SEQUENCE; BLOOD CELLS; CLUSTER ANALYSIS; GENE EXPRESSION PROFILING; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; MICRORNAS; PRINCIPAL COMPONENT ANALYSIS;

EID: 84957945292     PISSN: 1420682X     EISSN: 14209071     Source Type: Journal    
DOI: 10.1007/s00018-016-2154-9     Document Type: Article

References (18)

1. Beliakova-Bethell N et al (2014) The effect of cell subset isolation method on gene expression in leukocytes. Cytometry A 85(1):94–104
2. Lyons PA et al (2007) Microarray analysis of human leucocyte subsets: the advantages of positive selection and rapid purification. BMC Genom 8:64
3. Leidinger P et al (2014) The blood-borne miRNA signature of lung cancer patients is independent of histology but influenced by metastases. Mol Cancer 13(1):202
4. Meder B et al (2011) MicroRNA signatures in total peripheral blood as novel biomarkers for acute myocardial infarction. Basic Res Cardiol 106(1):13–23
5. Leidinger P et al (2013) A blood based 12-miRNA signature of Alzheimer disease patients. Genome Biol 14(7):R78
6. Keller A et al (2009) Multiple sclerosis: microRNA expression profiles accurately differentiate patients with relapsing-remitting disease from healthy controls. PLoS One 4(10):e7440
7. Bloomston M et al (2007) MicroRNA expression patterns to differentiate pancreatic adenocarcinoma from normal pancreas and chronic pancreatitis. J Am Med Assoc 297(17):1901–1908
8. Roth P et al (2015) Differentially regulated miRNAs as prognostic biomarkers in the blood of primary CNS lymphoma patients. Eur J Cancer 51(3):382–390
9. Keller A et al (2014) Comprehensive analysis of microRNA profiles in multiple sclerosis including next-generation sequencing. Mult Scler 20(3):295–303
10. Joerger M et al (2014) Circulating microRNA profiling in patients with advanced non-squamous NSCLC receiving bevacizumab/erlotinib followed by platinum-based chemotherapy at progression (SAKK 19/05). Lung Cancer 85(2):306–313
11. Leidinger P et al (2014) What makes a blood cell based miRNA expression pattern disease specific?—a miRNome analysis of blood cell subsets in lung cancer patients and healthy controls. Oncotarget 5(19):9484–9497
12. Leidinger P et al (2014) The human miRNA repertoire of different blood compounds. BMC Genom 15:474
13. Griffiths-Jones S et al (2006) miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res 34(Database issue):D140–D144
14. Backes C et al (2015) Prioritizing and selecting likely novel miRNAs from NGS data. Nucleic Acids Res. doi:10.1093/nar/gkv1335
15. + T cell immunoselection. Exp Hematol 42(1):11–13
16. Kummerow C et al (2014) A simple, economic, time-resolved killing assay. Eur J Immunol 44(6):1870–1872
17. Friedländer MR et al (2012) miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades. Nucleic Acids Res 40:37–52
18. Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B Methodol 57(1):289–300