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MicroRNA expression profiles from eggs of different qualities associated with post-ovulatory ageing in rainbow trout (Oncorhynchus mykiss).

Hao Ma | Gregory M Weber | Mark A Hostuttler | Hairong Wei | Lei Wang | Jianbo Yao
BMC genomics | 2015

Egg quality is an important aspect in rainbow trout farming. Post-ovulatory aging is one of the most important factors affecting egg quality. MicroRNAs (miRNAs) are the major regulators in various biological processes and their expression profiles could serve as reliable biomarkers for various pathological and physiological conditions. The objective of this study was to identify miRNAs that are associated with egg qualities in rainbow trout using post-ovulatory aged eggs.

Pubmed ID: 25885637

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This is a list of tools and resources that we have found mentioned in this publication.


miRBase (tool)

RRID:SCR_003152

Central online repository for microRNA nomenclature, sequence data, annotation and target prediction.Collection of published miRNA sequences and annotation.

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Blast2GO (tool)

RRID:SCR_005828

An ALL in ONE tool for functional annotation of (novel) sequences and the analysis of annotation data. Blast2GO (B2G) joins in one universal application similarity search based GO annotation and functional analysis. B2G offers the possibility of direct statistical analysis on gene function information and visualization of relevant functional features on a highlighted GO direct acyclic graph (DAG). Furthermore B2G includes various statistics charts summarizing the results obtained at BLASTing, GO-mapping, annotation and enrichment analysis (Fisher''''s Exact Test). All analysis process steps are configurable and data import and export are supported at any stage. The application also accepts pre-existing BLAST or annotation files and takes them to subsequent steps. The tool offers a very suitable platform for high throughput functional genomics research in non-model species. B2G is a species-independent, intuitive and interactive desktop application which allows monitoring and comprehending the whole annotation and analysis process supported by additional features like GO Slim integration, evidence code (EC) consideration, a Batch-Mode or GO-Multilevel-Pies. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

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Rfam (tool)

RRID:SCR_007891

The 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

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PITA (tool)

RRID:SCR_010853

Catalogs of predicted microRNA targets in worm (based on ce6 genome assembly), fly (dm3), mouse (mm9) and human (hg18). We follow standard seed parameter settings and consider seeds of length 6-8 bases, beginning at position 2 of the microRNA. No mismatches or loops are allowed, but a single G:U wobble is allowed in 7- or 8-mers. In genes missing a 3' UTR annotation, 500 bp (fly), 800 bp (human and mouse) or 300 bp (worm) downstream of the annotated end of the coding sequence were used as the predicted UTR. For each organism, a catalog with zero flank and with a flank of 3 and 15 bases upstream and downstream.

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LIMMA (tool)

RRID:SCR_010943

Software package for the analysis of gene expression microarray data, especially the use of linear models for analyzing designed experiments and the assessment of differential expression.

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