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The maturation of the brain involves the coordinated expression of thousands of genes, proteins and regulatory elements over time. In sensory pathways, gene expression profiles are modified by age and sensory experience in a manner that differs between brain regions and cell types. In the auditory system of altricial animals, neuronal activity increases markedly after the opening of the ear canals, initiating events that culminate in the maturation of auditory circuitry in the brain. This window provides a unique opportunity to study how gene expression patterns are modified by the onset of sensory experience through maturity. As a tool for capturing these features, next-generation sequencing of total RNA (RNAseq) has tremendous utility, because the entire transcriptome can be screened to index expression of any gene. To date, whole transcriptome profiles have not been generated for any central auditory structure in any species at any age. In the present study, RNAseq was used to profile two regions of the mouse auditory forebrain (A1, primary auditory cortex; MG, medial geniculate) at key stages of postnatal development (P7, P14, P21, adult) before and after the onset of hearing (~P12). Hierarchical clustering, differential expression, and functional geneset enrichment analyses (GSEA) were used to profile the expression patterns of all genes. Selected genesets related to neurotransmission, developmental plasticity, critical periods and brain structure were highlighted. An accessible repository of the entire dataset was also constructed that permits extraction and screening of all data from the global through single-gene levels. To our knowledge, this is the first whole transcriptome sequencing study of the forebrain of any mammalian sensory system. Although the data are most relevant for the auditory system, they are generally applicable to forebrain structures in the visual and somatosensory systems, as well.
Pubmed ID: 26271746 RIS Download
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Worldwide authority that approves standardized nomenclature to gene name and symbol, short form abbreviation, for each known human gene and stores all approved symbols in HGNC database. Approved human gene nomenclature. Database of gene symbols. Manually curated genes into family sets based on shared characteristics such as homology, function or phenotype. Data for protein-coding genes, pseudogenes, non-coding RNAs, phenotypes and genomic features.
View all literature mentionsData analysis service to predict the function of your favorite genes and gene sets. Indexing 1,421 association networks containing 266,984,699 interactions mapped to 155,238 genes from 7 organisms. GeneMANIA interaction networks are available for download in plain text format. GeneMANIA finds other genes that are related to a set of input genes, using a very large set of functional association data. Association data include protein and genetic interactions, pathways, co-expression, co-localization and protein domain similarity. You can use GeneMANIA to find new members of a pathway or complex, find additional genes you may have missed in your screen or find new genes with a specific function, such as protein kinases. Your question is defined by the set of genes you input. If members of your gene list make up a protein complex, GeneMANIA will return more potential members of the protein complex. If you enter a gene list, GeneMANIA will return connections between your genes, within the selected datasets. GeneMANIA suggests annotations for genes based on Gene Ontology term enrichment of highly interacting genes with the gene of interest. GeneMANIA is also a gene recommendation system. GeneMANIA is also accessible via a Cytoscape plugin, designed for power users. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
View all literature mentionsInternational database for laboratory mouse. Data offered by The Jackson Laboratory includes information on integrated genetic, genomic, and biological data. MGI creates and maintains integrated representation of mouse genetic, genomic, expression, and phenotype data and develops reference data set and consensus data views, synthesizes comparative genomic data between mouse and other mammals, maintains set of links and collaborations with other bioinformatics resources, develops and supports analysis and data submission tools, and provides technical support for database users. Projects contributing to this resource are: Mouse Genome Database (MGD) Project, Gene Expression Database (GXD) Project, Mouse Tumor Biology (MTB) Database Project, Gene Ontology (GO) Project at MGI, and MouseCyc Project at MGI.
View all literature mentionsSoftware package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software Python package that provides infrastructure to process data from high-throughput sequencing assays. While the main purpose of HTSeq is to allow you to write your own analysis scripts, customized to your needs, there are also a couple of stand-alone scripts for common tasks that can be used without any Python knowledge.
View all literature mentionsSoftware package that identifies differential expression in high-throughput ''count'' data, such as that derived from next-generation sequencing machines.
View all literature mentionsHuman Genome Organisation (HUGO) is the international organization of scientists involved in human genetics. HUGO was conceived in 1988, at the first meeting on genome mapping and sequencing at Cold Spring Harbor. From a 42 scientists of 17 countries membership association, HUGO has increased its membership base to over 1,200 members, both established and aspiring of 69 countries after two decades. HUGO has, over the years, played an essential role behind the scenes of the human genome project. With its mission to promote international collaborative effort to study the human genome and the myriad issues raised by knowledge of the genome, HUGO has had noteworthy successes in some of the less glamorous, but nonetheless vital, aspects of the human genome project. As a truly international organization, HUGO is entering its 20th year of its history by making an inflection in its direction seeking the biological meaning of its information content. To this end, HUGO is focusing on the medical implications of genomic knowledge. Moving forward, HUGO is also working to enhance the genomic capabilities in the emerging countries of the world. The excitement and interest in genomic sciences in Asia, Middle East, South America and Africa are palpable and the hope is that these technologies will help in national development and health.
View all literature mentionsBioconductor software package for Empirical analysis of Digital Gene Expression data in R. Used for differential expression analysis of RNA-seq and digital gene expression data with biological replication.
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