当前位置： SCI文献检索 > PHYSIOLOGICAL GENOMICS期刊下所有文献 > Temporal analysis of reciprocal miRNA-mRNA expression patterns predicts regulatory networks during differentiation in human skeletal muscle cells.

Temporal analysis of reciprocal miRNA-mRNA expression patterns predicts regulatory networks during differentiation in human skeletal muscle cells.

Abstract：

:microRNAs (miRNAs) are short noncoding RNAs that regulate gene expression through posttranscriptional repression of target genes. miRNAs exert a fundamental level of control over many developmental processes, but their role in the differentiation and development of skeletal muscle from myogenic progenitor cells in humans remains incompletely understood. Using primary cultures established from human skeletal muscle satellite cells, we performed microarray profiling of miRNA expression during differentiation of myoblasts (day 0) into myotubes at 48 h intervals (day 2, 4, 6, 8, and 10). Based on a time-course analysis, we identified 44 miRNAs with altered expression [false discovery rate (FDR) < 5%, fold change > ±1.2] during differentiation, including the marked upregulation of the canonical myogenic miRNAs miR-1, miR-133a, miR-133b, and miR-206. Microarray profiling of mRNA expression at day 0, 4, and 10 identified 842 and 949 genes differentially expressed (FDR < 10%) at day 4 and 10, respectively. At day 10, 42% of altered transcripts demonstrated reciprocal expression patterns in relation to the directional change of their in silico predicted regulatory miRNAs based on analysis using Ingenuity Pathway Analysis microRNA Target Filter. Bioinformatic analysis predicted networks of regulation during differentiation including myomiRs miR-1/206 and miR-133a/b, miRNAs previously established in differentiation including miR-26 and miR-30, and novel miRNAs regulated during differentiation of human skeletal muscle cells such as miR-138-5p and miR-20a. These reciprocal expression patterns may represent new regulatory nodes in human skeletal muscle cell differentiation. This analysis serves as a reference point for future studies of human skeletal muscle differentiation and development in healthy and disease states.

journal_name

Physiol Genomics

journal_title

Physiological genomics

authors

Sjögren RJ,Egan B,Katayama M,Zierath JR,Krook A

doi

10.1152/physiolgenomics.00037.2014

subject

Has Abstract

pub_date

2015-03-01 00:00:00

pages

45-57

issue

eissn

1094-8341

issn

1531-2267

pii

physiolgenomics.00037.2014

journal_volume

pub_type

杂志文章

在线工具

Temporal analysis of reciprocal miRNA-mRNA expression patterns predicts regulatory networks during differentiation in human skeletal muscle cells.