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APID (Agile Protein Interactomes DataServer) is an interactive web server that provides unified generation and delivery of protein interactomes mapped to their respective proteomes. This resource is a new, fully redesigned server that includes a comprehensive collection of protein interactomes for more than 400 organisms (25 of which include more than 500 interactions) produced by the integration of only experimentally validated protein-protein physical interactions. For each protein-protein interaction (PPI) the server includes currently reported information about its experimental validation to allow selection and filtering at different quality levels. As a whole, it provides easy access to the interactomes from specific species and includes a global uniform compendium of 90,379 distinct proteins and 678,441 singular interactions. APID integrates and unifies PPIs from major primary databases of molecular interactions, from other specific repositories and also from experimentally resolved 3D structures of protein complexes where more than two proteins were identified. For this purpose, a collection of 8,388 structures were analyzed to identify specific PPIs. APID also includes a new graph tool (based on Cytoscape.js) for visualization and interactive analyses of PPI networks. The server does not require registration and it is freely available for use at http://apid.dep.usal.es. ; Spanish Government, Ministerio de Economía y Competitividad, Instituto de Salud Carlos III [PI12/00624 and PI15/00328 to Dr J. De Las Rivas group]; and EU Joint Programme, JPND [AC14/00024 to Dr J. De Las Rivas group]. Regional Government, Junta de Castilla y León [BIO/SA68/13 to Dr J. De Las Rivas group]. ; Peer Reviewed

[Background]: The development of large-scale technologies for quantitative transcriptomics has enabled comprehensive analysis of the gene expression profiles in complete genomes. RNA-Seq allows the measurement of gene expression levels in a manner far more precise and global than previous methods. Studies using this technology are altering our view about the extent and complexity of the eukaryotic transcriptomes. In this respect, multiple efforts have been done to determine and analyse the gene expression patterns of human cell types in different conditions, either in normal or pathological states. However, until recently, little has been reported about the evolutionary marks present in human protein-coding genes, particularly from the combined perspective of gene expression and protein evolution. [Results]: We present a combined analysis of human protein-coding gene expression profiling and time-scale ancestry mapping, that places the genes in taxonomy clades and reveals eight evolutionary major steps (>hallmarks>), that include clusters of functionally coherent proteins. The human expressed genes are analysed using a RNA-Seq dataset of 116 samples from 32 tissues. The evolutionary analysis of the human proteins is performed combining the information from: (i) a database of orthologous proteins (OMA), (ii) the taxonomy mapping of genes to lineage clades (from NCBI Taxonomy) and (iii) the evolution time-scale mapping provided by TimeTree (Timescale of Life). The human protein-coding genes are also placed in a relational context based in the construction of a robust gene coexpression network, that reveals tighter links between age-related protein-coding genes and finds functionally coherent gene modules. [Conclusions]: Understanding the relational landscape of the human protein-coding genes is essential for interpreting the functional elements and modules of our active genome. Moreover, decoding the evolutionary history of the human genes can provide very valuable information to reveal or uncover their origin and function. ; We acknowledge the funding provided to Dr. J. De Las Rivas group by the Local Government, "Junta de Castilla y Leon" (JCyL, Valladolid, Spain, grant number BIO/SA08/14); and by the Spanish Government, "Ministerio de Economia y Competitividad" (MINECO) with grants of the ISCiii co-funded by FEDER (grant references PI12/00624 and PI15/00328). We also acknowledge a research grant to K.P. Lopes as visiting PhD student at the CiC-IMBCC (from January 2015 to January 2016) provided by the Brazilian National Council of Technological and Scientific Development (CNPq). We also acknowledge a PhD research grant to F.J. Campos-Laborie ("Ayudas a la contratación de Personal Investigador") provided by the JCyL with the support of the "Fondo Social Europeo" (FSE). ; Peer Reviewed