This article introduces the second release of the Gypsy Database of Mobile Genetic Elements (GyDB 2.0): a research project devoted to the evolutionary dynamics of viruses and transposable elements based on their phylogenetic classification (per lineage and protein domain). The Gypsy Database (GyDB) is a long-term project that is continuously progressing, and that owing to the high molecular diversity of mobile elements requires to be completed in several stages. GyDB 2.0 has been powered with a wiki to allow other researchers participate in the project. The current database stage and scope are long terminal repeats (LTR) retroelements and relatives. GyDB 2.0 is an update based on the analysis of Ty3/Gypsy, Retroviridae, Ty1/Copia and Bel/Pao LTR retroelements and the Caulimoviridae pararetroviruses of plants. Among other features, in terms of the aforementioned topics, this update adds: (i) a variety of descriptions and reviews distributed in multiple web pages; (ii) protein-based phylogenies, where phylogenetic levels are assigned to distinct classified elements; (iii) a collection of multiple alignments, lineage-specific hidden Markov models and consensus sequences, called GyDB collection; (iv) updated RefSeq databases and BLAST and HMM servers to facilitate sequence characterization of new LTR retroelement and caulimovirus queries; and (v) a bibliographic server. GyDB 2.0 is available at http://gydb.org.

Salt tolerance has been analysed in two populations of F(7) lines developed from a salt sensitive genotype of Solanum lycopersicum var. cerasiforme, as female parent, and two salt tolerant lines, as male parents, from S. pimpinellifolium, the P population (142 lines), and S. cheesmaniae, the C population (116 lines). Salinity effects on 19 quantitative traits including fruit yield were investigated by correlation, principal component analysis, ANOVA and QTL analysis. A total of 153 and 124 markers were genotyped in the P and C populations, respectively. Some flowering time and salt tolerance candidate genes were included. Since most traits deviated from a normal distribution, results based on the Kruskal-Wallis non-parametric test were preferred. Interval mapping methodology and ANOVA were also used for QTL detection. Eight out of 15 QTLs at each population were detected for the target traits under both control and high salinity conditions, and among them, only average fruit weight (FW) and fruit number (FN) QTLs (fw1.1, fw2.1 and fn1.2) were detected in both populations. The individual contribution of QTLs were, in general, low. After leaf chloride concentration, flowering time is the trait most affected by salinity because different QTLs are detected and some of their QTLxE interactions have been found significant. Also reinforcing the interest on information provided by QTL analysis, it has been found that non-correlated traits may present QTL(s) that are associated with the same marker. A few salinity specific QTLs for fruit yield, not associated with detrimental effects, might be used to increase tomato salt tolerance. The beneficial allele at two of them, fw8.1 (in C) and tw8.1 (for total fruit weight in P) corresponds to the salt sensitive parent, suggesting that the effect of the genetic background is crucial to breed for wide adaptation using wild germplasm.