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.
Department of Medical Biochemistry, Oslo University Hospital, Oslo, Norway. kristin.jensen@medisin.uio.no
Kristin
K
Jensen
Berit Sletbakk
BS
Brusletto
Hans Christian Dalsbotten
HC
Aass
Ole K
OK
Olstad
Peter
P
Kierulf
Kaare M
KM
Gautvik
D000367:Age Factors; D016175:B-Lymphocyte Subsets / Q000166:cytology / Q000378:metabolism; D001854:Bone Marrow Cells / Q000166:cytology / Q000378:metabolism*; D002454:Cell Differentiation / Q000235:genetics; D016000:Cluster Analysis; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D014644:Genetic Variation; D006801:Humans; D007223:Infant; D035683:MicroRNAs / Q000235:genetics*; D008875:Middle Aged; D054448:Precursor Cells, B-Lymphoid / Q000166:cytology / Q000378:metabolism*; D062085:RNA, Long Noncoding; D012333:RNA, Messenger / Q000235:genetics*
C568997:MIR17HG, human; D035683:MicroRNAs; D062085:RNA, Long Noncoding; D012333:RNA, Messenger