Abbreviations CI: confidence interval; COPD: chronic obstructive pulmonary disease; DC: dendritic cell; E2: 17β-oestradiol; E3: oestriol; HBV: hepatitis B virus; OR: odds ratio; P4: progesterone; pDC: plasmacytoid DC; RR: relative risk; Th1: helper T cell type 1; Th2: helper T cell type 2. PhEVER: a database for the global exploration of virus–host evolutionary relationships Fast viral adaptation and the implication of this rapid evolution in the emergence of several new infectious diseases have turned this issue into a major challenge for various research domains. Indeed, viruses are involved in the development of a wide range of pathologies and understanding how viruses and host cells interact in the context of adaptation remains an open question. In order to provide insights into the complex interactions between viruses and their host organisms and namely in the acquisition of novel functions through exchanges of genetic material, we developed the PhEVER database. This database aims at providing accurate evolutionary and phylogenetic information to analyse the nature of virus–virus and virus–host lateral gene transfers. PhEVER (http://pbil.univ-lyon1.fr/databases/phever) is a unique database of homologous families both (i) between sequences from different viruses and (ii) between viral sequences and sequences from cellular organisms. PhEVER integrates extensive data from up-to-date completely sequenced genomes (2426 non-redundant viral genomes, 1007 non-redundant prokaryotic genomes, 43 eukaryotic genomes ranging from plants to vertebrates) and offers a clustering of proteins into homologous families containing at least one viral sequences, as well as alignments and phylogenies for each of these families. Public access to PhEVER is available through its webpage and through all dedicated ACNUC retrieval systems. Viruses are responsible for a large number of infectious diseases and cancers. Recently, new viral diseases have emerged leading to severe consequences on human activities. The emergence of many of these new viruses can be attributed to recombining viruses as well as to host species jump (1) (2) (3) . Therefore, understanding how viruses interact with their hosts and more specifically how the complex interactions between viruses and their host organisms are acquired and maintained throughout evolution, remains a major challenge (4) (5) (6) (7) . In order to assess this question, it is of prime importance to be able to detect and quantify the occurrence of lateral gene transfer events, and the impact of these events on viralhost co-evolution. Indeed, the mechanisms behind fast viral adaptation are far from being elucidated. Thus, we developed a global approach aimed at providing accurate evolutionary and phylogenetic information to tackle these questions.