PANTHER in 2013: modeling the evolution of gene function, and other gene attributes, in the context of phylogenetic trees

Abstract

The data and tools in PANTHER—a comprehensive, curated database of protein families, trees, subfamilies and functions available at http://pantherdb.org—have undergone continual, extensive improvement for over a decade. Here, we describe the current PANTHER process as a whole, as well as the website tools for analysis of user-uploaded data. The main goals of PANTHER remain essentially unchanged: the accurate inference (and practical application) of gene and protein function over large sequence databases, using phylogenetic trees to extrapolate from the relatively sparse experimental information from a few model organisms. Yet the focus of PANTHER has continually shifted toward more accurate and detailed representations of evolutionary events in gene family histories. The trees are now designed to represent gene family evolution, including inference of evolutionary events, such as speciation and gene duplication. Subfamilies are still curated and used to define HMMs, but gene ontology functional annotations can now be made at any node in the tree, and are designed to represent gain and loss of function by ancestral genes during evolution. Finally, PANTHER now includes stable database identifiers for inferred ancestral genes, which are used to associate inferred gene attributes with particular genes in the common ancestral genomes of extant species.

Early differences in islets from prediabetic NOD mice: combined microarray and proteomic analysis

“…Ranking of the differentially expressed mouse proteins based on their assignment to type 1 diabetes relevant protein complexes was performed as described previously [23]. PANTHER was used to classify genes and proteins by biological processes [24]. Gene ontology (GO) enrichment analysis was performed by AmiGO [25] (full details of these analyses are described in ESM Methods).…”

A high-quality carrot genome assembly provides new insights into carotenoid accumulation and asterid genome evolution

“…Functional annotation of genes within this module was determined by BLASTP search of protein sequences within this module against the A. thaliana TAIR10 (ref. 128) predictions, and GO enrichment analysis based on BLASTP best hits to TAIR10 was performed using AgriGO 129 and PANTHER 130 .…”

Expression Profiles of the Individual Genes Corresponding to the Genes Generated by Cytotoxicity Experiments with Bortezomib in Multiple Myeloma

“…In order to identify individual genes whose expression profiles matched that of the one generated by cytotoxicity experiments for bortezomib, we used a linear regression-based approach, where we searched for statistically significant correlations between gene expression values and IC50 data [17,18,19]. The intersections of the genes were identified in 7 cell lines and used for further analysis.…”

“…We used an in silico literature mining approach to identify potential biomarkers by creating a summarized set of metadata derived from relevant information [17,18,19]. To do that, a linear regression model was used to discover genes whose expression profiles correlated with bortezomib sensitivity as measured for 7 myeloma cell lines by IC50 values from the Genomics of Drug Sensitivity in Cancer database.…”