Id4, a New Candidate Gene for Senile Osteoporosis, Acts as a Molecular Switch Promoting Osteoblast Differentiation

Excessive accumulation of bone marrow adipocytes observed in senile osteoporosis or age-related osteopenia is caused by the unbalanced differentiation of MSCs into bone marrow adipocytes or osteoblasts. Several transcription factors are known to regulate the balance between adipocyte and osteoblast differentiation. However, the molecular mechanisms that regulate the balance between adipocyte and osteoblast differentiation in the bone marrow have yet to be elucidated. To identify candidate genes associated with senile osteoporosis, we performed genome-wide expression analyses of differentiating osteoblasts and adipocytes. Among transcription factors that were enriched in the early phase of differentiation, Id4 was identified as a key molecule affecting the differentiation of both cell types. Experiments using bone marrow-derived stromal cell line ST2 and Id4-deficient mice showed that lack of Id4 drastically reduces osteoblast differentiation and drives differentiation toward adipocytes. On the other hand knockdown of Id4 in adipogenic-induced ST2 cells increased the expression of Pparγ2, a master regulator of adipocyte differentiation. Similar results were observed in bone marrow cells of femur and tibia of Id4-deficient mice. However the effect of Id4 on Pparγ2 and adipocyte differentiation is unlikely to be of direct nature. The mechanism of Id4 promoting osteoblast differentiation is associated with the Id4-mediated release of Hes1 from Hes1-Hey2 complexes. Hes1 increases the stability and transcriptional activity of Runx2, a key molecule of osteoblast differentiation, which results in an enhanced osteoblast-specific gene expression. The new role of Id4 in promoting osteoblast differentiation renders it a target for preventing the onset of senile osteoporosis

Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism