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The rumen is an important digestive organ in ruminants. Numerous regulatory factors including microRNAs (miRNAs) are involved in embryonic organ development. In the present study, miRNAs expressed in the rumens of goats (Capra hircus) and their potential roles in the pathways involved in rumen development were identified using high-throughput sequencing. Histological morphology revealed a distinct difference in each layer of rumen during the period from embryonic day 60 (E60) to embryonic day 135 (E135). We determined the expression profiles of miRNAs in the goat rumen, and identified 423 known miRNAs and 559 potentially novel miRNAs in the E60 and E135 embryonic rumen, respectively. Bioinformatics analysis annotated the 42 differentially expressed miRNAs and the top 10 most highly expressed miRNAs of the two libraries to 48 and 38 gene ontology categories, as well as to 168 and 71 Kyoto Encyclopedia of Genes and Genomes pathways, respectively. The expression patterns of eight randomly selected miRNAs were validated by stem-loop quantitative reverse transcription PCR, suggesting that the sequencing data were reliable. We profiled the genome-wide expression of rumen-expressed miRNAs at different prenatal stages of rumen tissues, revealing that a subset of miRNAs might play important roles in the formation of the rumen layers. Taken together, these findings will aid the investigation of dominant rumen-related miRNA sets and help understand the genetic control of rumen development in goats.
Pubmed ID: 29123545
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Computable knowledge regarding functions of genes and gene products. GO resources include biomedical ontologies that cover molecular domains of all life forms as well as extensive compilations of gene product annotations to these ontologies that provide largely species-neutral, comprehensive statements about what gene products do. Used to standardize representation of gene and gene product attributes across species and databases.
View all literature mentionsCommercial instrument and chemical vendor. Developer and manufacturer of specialized technological products for life science research and clinical diagnostics markets.
View all literature mentionsIntegrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.
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 mentionsA database of protein families, each represented by multiple sequence alignments and hidden Markov models (HMMs). Users can analyze protein sequences for Pfam matches, view Pfam family annotation and alignments, see groups of related families, look at the domain organization of a protein sequence, find the domains on a PDB structure, and query Pfam by keywords. There are two components to Pfam: Pfam-A and Pfam-B. Pfam-A entries are high quality, manually curated families that may automatically generate a supplement using the ADDA database. These automatically generated entries are called Pfam-B. Although of lower quality, Pfam-B families can be useful for identifying functionally conserved regions when no Pfam-A entries are found. Pfam also generates higher-level groupings of related families, known as clans (collections of Pfam-A entries which are related by similarity of sequence, structure or profile-HMM).
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 package for differential gene expression analysis based on the negative binomial distribution. Used for analyzing RNA-seq data for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates.
View all literature mentionsWelcome to the Neuroscience Information Framework Project, designed to serve the biomedical research community. NIF maintains the largest searchable collection of neuroscience data, the largest catalog of biomedical resources, and the largest ontology for neuroscience on the web. We welcome all feedback and suggestions and are actively looking for resource providers to make their resources accessible through NIF. Learn about the tools available to help you share your data and discover a dynamic inventory of Web-based neuroscience resources.
