Background: Though most of the transcripts are long non-coding RNAs (lncRNAs), little is known about their functions. lncRNAs usually function through interactions with proteins, which implies the importance of identifying the binding proteins of lncRNAs in understanding the molecular mechanisms underlying the functions of lncRNAs. Only a few approaches are available for predicting interactions between lncRNAs and proteins. In this study, we introduce a new method lncPro.Results: By encoding RNA and protein sequences into numeric vectors, we used matrix multiplication to score each RNA–protein pair. This score can be used to measure the interactions between an RNA–protein pair. This method effectively discriminates interacting and non-interacting RNA–protein pairs and predicts RNA–protein interactions within a given complex. Applying this method on all human proteins, we found that the long non-coding RNAs we collected tend to interact with nuclear proteins and RNA-binding proteins.Conclusions: Compared with the existing approaches, our method shortens the time for training matrix and obtains optimal results based on the model being used. The ability of predicting the associations between lncRNAs and proteins has also been enhanced. Our method provides an idea on how to integrate different information into the prediction process.

Long non-coding RNAs (lncRNAs) are important regulators of diverse biological processes. Here we report on functional identification and characterization of a novel long intergenic non-coding RNA with MyoD-regulated and skeletal muscle-restricted expression that promotes the activation of the myogenic program, and is therefore termed Linc-RAM (Linc-RNA Activator of Myogenesis). Linc-RAM is transcribed from an intergenic region of myogenic cells and its expression is upregulated during myogenesis. Notably, in vivo functional studies show that Linc-RAM knockout mice display impaired muscle regeneration due to the differentiation defect of satellite cells. Mechanistically, Linc-RAM regulates expression of myogenic genes by directly binding MyoD, which in turn promotes the assembly of the MyoD–Baf60c–Brg1 complex on the regulatory elements of target genes. Collectively, our findings reveal the functional role and molecular mechanism of a lineage-specific Linc-RAM as a regulatory lncRNA required for tissues-specific chromatin remodelling and gene expression.

Background: Functional studies have demonstrated that microRNAs (miRNAs or miRs) play critical roles in a wide spectrum of biological processes including development and disease pathogenesis. To investigate the functional roles that miRNAs play during chicken skeletal muscle development, the miRNA transcriptomes of skeletal muscles from broiler and layer chickens were profiled using Solexa deep sequencing. Results: Some miRNAs have multiple isoforms and several miRNAs* are present at higher levels than their corresponding miRNAs. Thirty three novel and 189 known chicken miRNAs were identified using computational approaches. Subsequent miRNA transcriptome comparisons and real-time PCR validation experiments revealed 17 miRNAs that were differentially expressed between broilers and layers, and a number of targets of these miRNAs have been implicated in myogenesis regulation. Using integrative miRNA target-prediction and network-analysis approaches an interaction network of differentially expressed and muscle-related miRNAs and their putative targets was constructed, and miRNAs that could contribute to the divergent muscle growth of broiler and layer chickens by targeting the ACVR2B gene were identified, which can causes dramatic increases in muscle mass. Conclusions: The present study provides the first transcriptome profiling-based evaluation of miRNA function during skeletal muscle development in chicken. Systematic predictions aided the identification of potential miRNAs and their targets, which could contribute to divergent muscle growth in broiler and layer chickens. Furthermore, these predictions generated information that can be utilized in further research investigating the involvement of interaction networks, containing miRNAs and their targets, in the regulation of muscle development.

The genome exists as an organized, three-dimensional (3D) dynamic architecture, and each cell type has a unique 3D genome organization that determines its cell identity. An unresolved question is how cell type-specific 3D genome structures are established during development. Here, we analyzed 3D genome structures in muscle cells from mice lacking the muscle lineage transcription factor (TF), MyoD, versus wild-type mice. We show that MyoD functions as a “genome organizer” that specifies 3D genome architecture unique to muscle cell development, and that H3K27ac is insufficient for the establishment of MyoD-induced chromatin loops in muscle cells. Moreover, we present evidence that other cell lineage-specific TFs might also exert functional roles in orchestrating lineage-specific 3D genome organization during development.