Sus scrofa
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ABSTRACT:
PROVIDER: PRJNA309904 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:The porcine microRNA transcriptome response to porcine cytomegalovirus infection
| PRJNA306494 | ENA
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Project description:Porcine spleen_Haemophilus Parasuis infected_7days
| PRJNA105983 | ENA
Project description:In this study, we applied the isobaric tags for relative and absolute quantitation (iTRAQ) technique to detect alterations in the proteomic profile of the jejunal mucosa using a porcine model in which piglets were offered the protein-limited (PL) diet. Protein identification and quantification for iTRAQ experiments were performed using ProteinPilot (v4.0.8085) software. The LC-MS/MS data were searched against the UniProtKB (sus scrofa). To minimize the false discovery rate (FDR), a threshold for protein identification was applied, with the confident value > 95% (amount to the confident value “unused ProtScore” > 1.3 in ProteinPilot software), and at least one unique peptide was considered for protein identification. Proteins that were quantified with fold change > 2.0 were considered to be differentially expressed proteins. We identified 5275 proteins, 202 of which were differentially expressed. Furthermore, we adopted function annotation analysis of all identified proteins and function enrichment analysis of all differentially expressed proteins to explore more meaningful proteins and pathways.
2016-12-22 | PXD004069 | Pride
Project description:BACKGROUND:In animal breeding, identification of causative genetic variants is of major importance and high economical value. Usually, the number of candidate variants exceeds the number of variants that can be validated. One way of prioritizing probable candidates is by evaluating their potential to have a deleterious effect, e.g. by predicting their consequence. Due to experimental difficulties to evaluate variants that do not cause an amino-acid substitution, other prioritization methods are needed. For human genomes, the prediction of deleterious genomic variants has taken a step forward with the introduction of the combined annotation dependent depletion (CADD) method. In theory, this approach can be applied to any species. Here, we present pCADD (p for pig), a model to score single nucleotide variants (SNVs) in pig genomes. RESULTS:To evaluate whether pCADD captures sites with biological meaning, we used transcripts from miRNAs and introns, sequences from genes that are specific for a particular tissue, and the different sites of codons, to test how well pCADD scores differentiate between functional and non-functional elements. Furthermore, we conducted an assessment of examples of non-coding and coding SNVs, which are causal for changes in phenotypes. Our results show that pCADD scores discriminate between functional and non-functional sequences and prioritize functional SNVs, and that pCADD is able to score the different positions in a codon relative to their redundancy. Taken together, these results indicate that based on pCADD scores, regions with biological relevance can be identified and distinguished according to their rate of adaptation. CONCLUSIONS:We present the ability of pCADD to prioritize SNVs in the pig genome with respect to their putative deleteriousness, in accordance to the biological significance of the region in which they are located. We created scores for all possible SNVs, coding and non-coding, for all autosomes and the X chromosome of the pig reference sequence Sscrofa11.1, proposing a toolbox to prioritize variants and evaluate sequences to highlight new sites of interest to explain biological functions that are relevant to animal breeding.
| S-EPMC7006094 | biostudies-literature