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A comprehensive, cell specific microRNA catalogue of human peripheral blood.

Juzenas, Simonas, Venkatesh, Geetha, Hübenthal, Matthias, Hoeppner, Marc P., Du, Zhipei Gracie, Paulsen, Maren, Rosenstiel, Philip, Senger, Philipp, Hofmann-Apitius, Martin, Keller, Andreas, Kupcinskas, Limas, Franke, Andre, Hemmrich-Stanisak, Georg·2017·Nucleic Acids Research
DOI 10.1093/nar/gkx706PMC PMC5766192
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Figure 1. Simplified human hematopoietic tree of different cell compounds (modified from Häggström (69)). The miRNA expression profiles were generated for natural killer (NK) cell (CD56+), B lymphocyte (CD19+), cytotoxic T cell (CD8+), T helper cell (CD4+), monocyte (CD14+), neutrophil (CD15+) and erythrocyte (CD235a+) populations (highlighted in red).
Figure 1. Simplified human hematopoietic tree of different cell compounds (modified from Häggström (69)). The miRNA expression profiles were generated for natural killer (NK) cell (CD56+), B lymphocyte (CD19+), cytotoxic T cell (CD8+), T helper cell (CD4+), monocyte (CD14+), neutrophil (CD15+) and erythrocyte (CD235a+) populations (highlighted in red).CC BY-NC · PubMed Central
Figure 2. The presence of miRNAs in erythrocytes (RBCs), exosomes and serum. The barplot shows the log2 transformed median read counts of the most abundant miRNAs in RBCs. The heatmap represents presence (blue) or absence (red) of miRNAs in specific blood compounds. Only the miRNAs which were detected (expression value > 5) in at least 85% of the samples in at least one of the blood compound were considered as being present.
Figure 2. The presence of miRNAs in erythrocytes (RBCs), exosomes and serum. The barplot shows the log2 transformed median read counts of the most abundant miRNAs in RBCs. The heatmap represents presence (blue) or absence (red) of miRNAs in specific blood compounds. Only the miRNAs which were detected (expression value > 5) in at least 85% of the samples in at least one of the blood compound were considered as being present.CC BY-NC · PubMed Central
Figure 3. The distributions of isomiR modification types across different blood compounds. (A) 5′ end trimming modification distribution; (B) 3′ end trimming modification distribution; (C) nucleotide substitution modification distribution; (D) 3′ end addition modification distribution. Each dot represents individual sample colored by group. The size of dots indicates the abundance which corresponds to the relative number of molecule copies per modification type and position present in a given sample. The dash (–) symbol indicates the mean frequency of unique sequences per group. The smoothing in figure C was performed using the generalized additive model (GAM) method.
Figure 3. The distributions of isomiR modification types across different blood compounds. (A) 5′ end trimming modification distribution; (B) 3′ end trimming modification distribution; (C) nucleotide substitution modification distribution; (D) 3′ end addition modification distribution. Each dot represents individual sample colored by group. The size of dots indicates the abundance which corresponds to the relative number of molecule copies per modification type and position present in a given sample. The dash (–) symbol indicates the mean frequency of unique sequences per group. The smoothing in figure C was performed using the generalized additive model (GAM) method.CC BY-NC · PubMed Central
Figure 4. The composition of 3′ added nucleotides across the blood compounds. A hierarchical average linkage clustering was used to generate a dendrogram based on relative frequencies of bases per position of the unique sequences, which then were visualized as sequence logos.
Figure 4. The composition of 3′ added nucleotides across the blood compounds. A hierarchical average linkage clustering was used to generate a dendrogram based on relative frequencies of bases per position of the unique sequences, which then were visualized as sequence logos.CC BY-NC · PubMed Central
Figure 5. The similarity structure of human blood cell miRNA transcriptomes. MDS plot showing three clearly resolved clusters corresponding to lymphoid cells (NK cells, B cells, T cells and Th cells), myeloid cells (monocytes and neutrophils) and anucleate erythrocytes. The analysis was performed on miRNA count data using Spearman's correlation distance (1 – correlation coefficient). The dots represent samples coloured by group, while the centre of ellipses corresponds to the group mean and the shapes are defined by the covariance within group.
Figure 5. The similarity structure of human blood cell miRNA transcriptomes. MDS plot showing three clearly resolved clusters corresponding to lymphoid cells (NK cells, B cells, T cells and Th cells), myeloid cells (monocytes and neutrophils) and anucleate erythrocytes. The analysis was performed on miRNA count data using Spearman's correlation distance (1 – correlation coefficient). The dots represent samples coloured by group, while the centre of ellipses corresponds to the group mean and the shapes are defined by the covariance within group.CC BY-NC · PubMed Central
Figure 6. (A) Differentially expressed miRNAs between lymphoid and myeloid cell lineage; (B) expression levels of blood cell lineage-specific miRNAs. Each row of the heatmaps represents a sample corresponding to the one of the blood cell types, and each column represents an individual miRNA-arm. All miRNAs were statistically differentially expressed (FDR ≤ 0.001 and |log2FC| > 1). The Z-score in the heatmaps represents standardized normalized expression values. The unsupervised (agglomerative) hierarchical clustering of miRNAs was performed using Spearman's correlation distance (1 – correlation coefficient) as metric and average linkage clustering as linkage criterion.
Figure 6. (A) Differentially expressed miRNAs between lymphoid and myeloid cell lineage; (B) expression levels of blood cell lineage-specific miRNAs. Each row of the heatmaps represents a sample corresponding to the one of the blood cell types, and each column represents an individual miRNA-arm. All miRNAs were statistically differentially expressed (FDR ≤ 0.001 and |log2FC| > 1). The Z-score in the heatmaps represents standardized normalized expression values. The unsupervised (agglomerative) hierarchical clustering of miRNAs was performed using Spearman's correlation distance (1 – correlation coefficient) as metric and average linkage clustering as linkage criterion.CC BY-NC · PubMed Central

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Metadata

Authors
Juzenas, S., Venkatesh, G., Hübenthal, M., Hoeppner, M. P., Du, Z. G., Paulsen, M., Rosenstiel, P., Senger, P., Hofmann-Apitius, M., Keller, A., Kupcinskas, L., Franke, A., & Hemmrich-Stanisak, G.
ORCID
Venue
Nucleic Acids Research
Publisher
Oxford University Press (OUP)
Published
2017-08-11
Volume
45
Issue
16
Pages
9290-9301
ISSN
  • 0305-1048
  • 1362-4962
DOI
10.1093/nar/gkx706
PMC
PMC5766192
Cited by
181
References
8
Language
en
Licence
creativecommons.org/licenses/by-nc/4.0/ (vor)

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Juzenas, S., Venkatesh, G., Hübenthal, M., Hoeppner, M. P., Du, Z. G., Paulsen, M., Rosenstiel, P., Senger, P., Hofmann-Apitius, M., Keller, A., Kupcinskas, L., Franke, A., & Hemmrich-Stanisak, G. (2017). A comprehensive, cell specific microRNA catalogue of human peripheral blood. Nucleic Acids Research. https://doi.org/10.1093/nar/gkx706