Transcriptional profiling of mRNAs and microRNAs in human bone marrow precursor B cells identifies subset- and age-specific variations.

BACKGROUND

Molecular mechanisms explaining age-related changes in the bone marrow with reduced precursor B cell output are poorly understood.

METHODS

We studied the transcriptome of five precursor B cell subsets in individual bone marrow samples from 4 healthy children and 4 adults employing GeneChip® Human Exon 1.0 ST Arrays (Affymetrix®) and TaqMan® Array MicroRNA Cards (Life Technologies™).

RESULTS

A total of 1796 mRNAs (11%) were at least once differentially expressed between the various precursor B cell subsets in either age group (FDR 0.1%, p≤1.13×10(-4)) with more marked cell stage specific differences than those related to age. In contrast, microRNA profiles of the various precursor B cell subsets showed less hierarchical clustering as compared to the corresponding mRNA profiles. However, 17 of the 667 microRNA assays (2.5%) were at least once differentially expressed between the subsets (FDR 10%, p≤0.004). From target analysis (Ingenuity® Systems), functional assignment between postulated interacting mRNAs and microRNAs showed especially association to cellular growth, proliferation and cell cycle regulation. One functional network connected up-regulation of the differentiation inhibitor ID2 mRNA to down-regulation of the hematopoiesis- or cell cycle regulating miR-125b-5p, miR-181a-5p, miR-196a-5p, miR-24-3p and miR-320d in adult PreBII large cells. Noteworthy was also the stage-dependent expression of the growth promoting miR-17-92 cluster, showing a partly inverse trend with age, reaching statistical significance at the PreBII small stage (up 3.1-12.9 fold in children, p = 0.0084-0.0270).

CONCLUSIONS

The global mRNA profile is characteristic for each precursor B cell developmental stage and largely similar in children and adults. The microRNA profile is much cell stage specific and not changing much with age. Importantly, however, specific age-dependent differences involving key networks like differentiation and cellular growth may indicate biological divergence and possibly also altered production potential with age.