Simultaneous miRNA and mRNA transcriptome profiling of human myoblasts reveals a novel set of myogenic differentiation-associated miRNAs and their target genes

Abstract

BackgroundmiRNA profiling performed in myogenic cells and biopsies from skeletal muscles has previously identified miRNAs involved in myogenesis.ResultsHere, we have performed miRNA transcriptome profiling in human affinity-purified CD56+ myoblasts induced to differentiate in vitro. In total, we have identified 60 miRNAs differentially expressed during myogenic differentiation. Many were not known for being differentially expressed during myogenic differentiation. Of these, 14 (miR-23b, miR-28, miR-98, miR-103, miR-107, miR-193a, miR-210, miR-324-5p, miR-324-3p, miR-331, miR-374, miR-432, miR-502, and miR-660) were upregulated and 6 (miR-31, miR-451, miR-452, miR-565, miR-594 and miR-659) were downregulated. mRNA transcriptome profiling performed in parallel resulted in identification of 6,616 genes differentially expressed during myogenic differentiation.ConclusionsThis simultaneous miRNA/mRNA transcriptome profiling allowed us to predict with high accuracy target genes of myogenesis-related microRNAs and to deduce their functions.

The microRNA-205-5p is correlated to metastatic potential of 21T series: A breast cancer progression model

“…The level of expression of miRNA targets in a system is relevant for increasing the success rate in the target prediction [10]. By selecting just the mRNAs that were overexpressed in the transition in situ to metastatic cells, we take into consideration the specific cellular context allowing a more precise prediction.…”

“…To perform microarray data analysis we used R language and the Limma package on Bioconductor software essentially as described in [10]. Data were background corrected using AgiMicroRNA algorithm and normalized between arrays by the quantile method in order to compensate for systematic technical differences between probe affinity and arrays.…”

“…To increase the accuracy in miR-205-5p in silico target prediction we used as approach a combined miRNA and mRNA transcriptome profiling [10]. First, the mRNAs that had the expression increased more than two fold in 21T cells during the transition in situ to metastatic tumor (21MT1 vs 21NT) were selected from a published database [8].…”

Novel Therapeutic Strategy for the Prevention of Bone Fractures

“…The data shown in Fig. 15a suggest that myostatin propeptide may stimulate myogenesis by upregulating miR-23b, as miR-23b is known as a myogenic miRNA (Dmitriev et al, 2013). The myostatin propeptide also upregulates let-7e, and the let-7 group of miRNAs are known to suppress cell proliferation.…”

Response to the letter to the editor by Kristensen MM, Helge JW and Dela F

“…miR23a, 30b, 98, 101, 148b, 206, 145, 199a and let-7 have in silico-predicted targets that are involved in the insulin signalling pathway), it is difficult to determine which of the suggested miRNAs are false positive and which are the true positive. Data from animal studies, muscular disease models, exercise experiments and ageing research by other groups also support, to various extent, the involvement of miR-206, miR-23a, miR23b, miR-30b and miR-98 in muscle atrophy (Drummond et al 2008, Granjon et al 2009, Jeng et al 2009, McCarthy et al 2009, Williams et al 2009, Nakasa et al 2010, Nielsen et al 2010, Wada et al 2011, Liu et al 2012, Dmitriev et al 2013. Recently, a study analysing the expression of miRNA in different mouse models of muscle atrophy showed that each model has a different signature of miRNA changes and, more importantly, that there is a temporal change in miRNA expression (Soares et al 2014).…”