Protein Function Easily Investigated by Genomics Data Mining Using the ProteINSIDE Online Tool

Abstract

Nowadays, genomic and proteomic studies produce vast amounts of data. To get the biological meaning of these data and to generate testable new hypothesis, scientists must use several tools often not designed for ruminant studies. Here we present ProteINSIDE: an online tool to analyse lists of protein or gene identifiers from well-annotated species (human, rat, and mouse) and ruminants (cow, sheep, and goat). The aims of ProteINSIDE modules are to gather biological information stores in well-updated public databases, to proceed to annotations according to the Gene Ontology consortium, to predict potentially secreted proteins, and to search for proteins interactions. ProteINSIDE provides results from several software and databases in a single query. From a list of identifiers, ProteINSIDE uses orthologs or homologs to extend analyses and biological information retrieval. As a tutorial, we presented how to launch, to recover, to view, and to interpret the results provided by the two types of analysis available with ProteINSIDE (basic and custom analyses). ProteINSIDE is freely available using an internet browser at www.proteinside.org. The results of this article are provided on the home page of ProteINSIDE website as the example of an analysis result.

Proteomic Analysis of Two Weight Classes of Mule Duck “foie gras” at the End of an Overfeeding Period

“…For all the proteins identified as variants, a gene ontology (GO) analysis was performed with the ProteINSIDE webservice ( Kaspric et al, 2015 ) to identify the associated biologicals processes. Based on the fact that, in the used database (Canard_ Anas_Caïrina 190524), the majority of the identified proteins are unreviewed proteins, all variant proteins were evaluated one by one and the ones not related to a function in the liver were deleted before GO analysis.…”

Expression Marker-Based Strategy to Improve Beef Quality

“…Relevant information in beef is often lacking due to the incompleteness of annotation of the genome. Alternative strategies are to mine genome-wide sets of data from international databases ( in silico approach) thanks to online and interactive workflows and databases [ 42 , 43 ] or to use model species ( in vivo and in vitro approaches). This is useful to reveal gene networks involved in the construction of the quality phenotype, for example, regarding the development of muscle and adipose tissues that determine the lean to fat ratio [ 44 ].…”

Integrated data mining of transcriptomic and proteomic datasets to predict the secretome of adipose tissue and muscle in ruminants

“…with pre-set cut-offs of 0.45 and 0.34 in the basic and custom analysis, respectively 38 . ProteINSIDE then checks that predicted secreted proteins are annotated with GO terms related to secretion.…”