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Chronic stress with lack of reward presumably may impair brain reward circuit, leading to major depressive disorder (MDD). Most individuals experiencing chronic stress do not suffer from MDD, i.e., resilience, implying the presence of endogenous anti-depression in the brain. Molecular mechanisms underlying stress-induced depression versus resilience were investigated. Mice were treated by chronic unpredictable mild stress (CUMS) for four weeks. Their mood state was assessed by behavioral tasks, such as sucrose preference, Y-maze and forced swimming testes. To reveal comprehensive molecular profiles of major depression versus resilience, mRNA and microRNA profiles were analyzed by high-throughput sequencing in the ventral tegmental area (VTA) harvested from control, CUMS-susceptible and CUMS-resilience mice. In data analyses of control versus CUMS-susceptible mice as well as control versus CUMS-resilience mice, 1.5 fold ratio in reads per kilo-base per million reads was set as the threshold to judge the involvement of mRNAs and microRNAs in the CUMS, depression or resilience. The downregulation of synaptic vesicle cycle, neurotrophin, GABAergic synapse and morphine addiction as well as the upregulation of transmitter release, calcium signal and cAMP-dependent response element binding are associated to CUMS-susceptibility. The downregulation of tyrosine metabolism and protein process in endoplasmic reticulum as well as the upregulation of amino acid biosynthesis, neuroactive ligand-receptor interaction and dopaminergic synapse are associated to CUMS-resilience. Therefore, the impairment of neurons and GABA/dopaminergic synapses in the VTA is associated with major depression. The upregulation of these entities is associated with resilience. Consistent results obtained from analyzing mRNAs and microRNAs as well as using different approaches strengthen our finding and conclusion.
Pubmed ID: 29864451
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Software used for the identification of differentially expressed genes from count data or previously normalized count data. It empirically models the noise distribution of count changes by contrasting fold-change differences (M) and absolute expression differences (D) for all the features in samples within the same condition. This reference distribution is then used to assess whether the M-D values computed between two conditions for a given gene is likely to be part of the noise or represent a true differential expression.
View all literature mentionsSoftware platform for complex network analysis and visualization. Used for visualization of molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data.
View all literature mentionsCentral online repository for microRNA nomenclature, sequence data, annotation and target prediction.Collection of published miRNA sequences and annotation.
View all literature mentionsSoftware package to calculate sequence quality statistics and create visual representations of data quality for Illumina's second-generation sequencing technology.
View all literature mentionsSoftware ultrafast memory efficient tool for aligning sequencing reads. Bowtie is short read aligner.
View all literature mentionsWeb based gene set analysis toolkit designed for functional genomic, proteomic, and large-scale genetic studies from which large number of gene lists (e.g. differentially expressed gene sets, co-expressed gene sets etc) are continuously generated. WebGestalt incorporates information from different public resources and provides a way for biologists to make sense out of gene lists. This version of WebGestalt supports eight organisms, including human, mouse, rat, worm, fly, yeast, dog, and zebrafish.
View all literature mentionsThe Rfam database is a collection of RNA families, each represented by multiple sequence alignments, consensus secondary structures and covariance models (CMs). The families in Rfam break down into three broad functional classes: Non-coding RNA genes, structured cis-regulatory elements and self-splicing RNAs. Typically these functional RNAs often have a conserved secondary structure which may be better preserved than the RNA sequence. The CMs used to describe each family are a slightly more complicated relative of the profile hidden Markov models (HMMs) used by Pfam. CMs can simultaneously model RNA sequence and the structure in an elegant and accurate fashion. Rfam is also available via FTP. You can find data in Rfam in various ways... * Analyze your RNA sequence for Rfam matches * View Rfam family annotation and alignments * View Rfam clan details * Query Rfam by keywords * Fetch families or sequences by NCBI taxonomy * Enter any type of accession or ID to jump to the page for a Rfam family, sequence or genome
View all literature mentionsSoftware tool for fast and high throughput alignment of shotgun cDNA sequencing reads generated by transcriptomics technologies. Fast splice junction mapper for RNA-Seq reads. Aligns RNA-Seq reads to mammalian-sized genomes using ultra high-throughput short read aligner Bowtie, and then analyzes mapping results to identify splice junctions between exons.TopHat2 is accurate alignment of transcriptomes in presence of insertions, deletions and gene fusions.
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