MyoMiner: explore gene co-expression in normal and pathological muscle

International audienceBackground: High-throughput transcriptomics measures mRNA levels for thousands of genes in a biological sample. Most gene expression studies aim to identify genes that are differentially expressed between different biological conditions, such as between healthy and diseased states. However, these data can also be used to identify genes that are co-expressed within a biological condition. Gene co-expression is used in a guilt-by-association approach to prioritize candidate genes that could be involved in disease, and to gain insights into the functions of genes, protein relations, and signaling pathways. Most existing gene co-expression databases are generic, amalgamating data for a given organism regardless of tissue-type.Methods: To study muscle-specific gene co-expression in both normal and pathological states, publicly available gene expression data were acquired for 2376 mouse and 2228 human striated muscle samples, and separated into 142 categories based on species (human or mouse), tissue origin, age, gender, anatomic part, and experimental condition. Co-expression values were calculated for each category to create the MyoMiner database.Results: Within each category, users can select a gene of interest, and the MyoMiner web interface will return all correlated genes. For each co-expressed gene pair, adjusted p-value and confidence intervals are provided as measures of expression correlation strength. A standardized expression-level scatterplot is available for every gene pair r-value. MyoMiner has two extra functions: (a) a network interface for creating a 2-shell correlation network, based either on the most highly correlated genes or from a list of genes provided by the user with the option to include linked genes from the database and (b) a comparison tool from which the users can test whether any two correlation coefficients from different conditions are significantly different.Conclusions: These co-expression analyses will help investigators to delineate the tissue-, cell-, and pathology-specific elements of muscle protein interactions, cell signaling and gene regulation. Changes in co-expression between pathologic and healthy tissue may suggest new disease mechanisms and help define novel therapeutic targets. Thus, MyoMiner is a powerful muscle-specific database for the discovery of genes that are associated with related functions based on their co-expression. MyoMiner is freely available at https://www.sys-myo.com/myominer

Bcl-2 and N-Myc Coexpression Increases IGF-IR and Features of Malignant Growth in Neuroblastoma Cell Lines

The bcl-2 and c-myc oncogenes cooperate to transform multiple cell types. In the pediatric malignancy NB(2), Bcl-2 is highly expressed. In tumors with a poor prognosis, N-Myc, a protein homologous to c-Myc, is overexpressed as a result of gene amplification. The present study was designed to determine whether Bcl-2 cooperates with N-Myc to bestow a tumorigenic phenotype to neuroblastoma (NB) cells. NB cell lines that at baseline express neither Bcl-2 nor N-Myc were stably transfected to express these gene products. In this model, we found Bcl-2 rescues N-Myc-expressing cells from apoptosis induced by serum withdrawal. Coexpression of Bcl-2 and N-Myc supports growth in low serum conditions and anchorage-independent growth in soft agar. Similarly, in vivo tumorigenic and angiogenic activity was dependent on coexpression. Our data further suggests that the mechanism underlying these changes involves the receptor for insulin growth factor type I (IGF-IR)