Bone responds with increased bone formation to mechanical loading, and the time course of bone formation after initiating mechanical loading is well characterized. However, the regulatory activities governing the loading-dependent changes in gene expression are not well understood. The goal of this study was to identify the time-dependent regulatory mechanisms that governed mechanical loading-induced gene expression in bone using a predictive bioinformatics algorithm. A standard model for bone loading in rodents was employed in which the right forelimb was loaded axially for three minutes per day, while the left forearm served as a non-loaded, contralateral control. Animals were subjected to loading sessions every day, with 24 hours between sessions. Ulnas were sampled at 11 time points, from 4 hours to 32 days after beginning loading. Using a predictive bioinformatics algorithm, we created a linear model of gene expression and identified 44 transcription factor binding motifs and 29 microRNA binding sites that were predicted to regulate gene expression across the time course. Known and novel transcription factor binding motifs were identified throughout the time course, as were several novel microRNA binding sites. These time-dependent regulatory mechanisms may be important in controlling the loading-induced bone formation process.
PDF (2.43 MB PDF FORMAT)
RIS citation (ENDNOTE, REFERENCE MANAGER, PROCITE, REFWORKS)
BibTex citation (BIBDESK, LATEX)
Since my first enquiry about publishing in Gene Regulation And Systems Biology until the last moment of completing all the steps for publishing my paper, I was always taken seriously as author. All my questions and concerns were answered in a very professional way. The review process was quick and very fair. Reviewers stick to the facts and declare their points of view like a clear thread through the manuscript. I always had an enthusiastic ...
All authors are surveyed after their articles are published. Authors are asked to rate their experience in a variety of areas, and their responses help us to monitor our performance. Presented here are their responses in some key areas. No 'poor' or 'very poor' responses were received; these are represented in the 'other' category.See Our Results
Copyright © 2014 Libertas Academica Ltd (except open access articles and accompanying metadata and supplementary files.)