Genotyping-by-sequencing of a melon (Cucumis melo L.) germplasm collection from a secondary center of diversity highlights patterns of genetic variation and genomic features of different gene pools.

BACKGROUND: Melon (Cucumis melo L.) is one of the most important horticultural species, which includes several taxonomic groups. With the advent of next-generation sequencing, single nucleotide polymorphism (SNP) markers are widely used in the study of genetic diversity and genomics. RESULTS: We report the first successful application of genotyping-by-sequencing (GBS) technology in melon. We detected 25,422 SNPs by the analysis of 72 accessions collected in Apulia, a secondary centre of diversity in Southern Italy. Analyses of genetic structure, principal components, and hierarchical clustering support the identification of three distinct subpopulations. One of them includes accessions known with the folk name of 'carosello', referable to the chate taxonomic group. This is one of the oldest domesticated forms of C. melo, once widespread in Europe and now exposed to the risk of genetic erosion. The second subpopulation contains landraces of 'barattiere', a regional vegetable production that was never characterized at the DNA level and we show was erroneously considered another form of chate melon. The third subpopulation includes genotypes of winter melon (C. melo var. inodorus). Genetic analysis within each subpopulation revealed patterns of diversity associated with fruit phenotype and geographical origin. We used SNP data to describe, for each subpopulation, the average linkage disequilibrium (LD) decay, and to highlight genomic regions possibly resulting from directional selection and associated with phenotypic variation. CONCLUSIONS: We used GBS to characterize patterns of genetic diversity and genomic features within C. melo. We provide useful information to preserve endangered gene pools and to guide the use of germplasm in breeding. Finally, our findings lay a foundation for molecular breeding approaches and the identification of genes underlying phenotypic traits.

Bioinformatics resources for pollen.

KEY MESSAGE: Bioinformatics for Pollen. Pollen plays a key role in crop production, and its development is the most delicate phase in reproduction. Different metabolic pathways are involved in pollen development, and changes in the level of some metabolites, as well as responses to stress, are correlated with the reduction in pollen viability, leading consequently to a decrease in the fruit production. However, studies on pollen may be hard because gamete development and fertilization are complex processes that occur during a short window of time. The rise of the so-called -omics sciences provided key strategies to promote molecular research in pollen tissues, starting from model organisms and moving to increasing number of species. An integrated multi-level approach based on investigations from genomics, transcriptomics, proteomics and metabolomics appears now feasible to clarify key molecular processes in pollen development and viability. To this aim, bioinformatics has a fundamental role for data production and analysis, contributing varied and ad hoc methodologies, endowed with different sensitivity and specificity, necessary for extracting added-value information from the large amount of molecular data achievable. Bioinformatics is also essential for data management, organization, distribution and integration in suitable resources. This is necessary to catch the biological features of the pollen tissues and to design effective approaches to identifying structural or functional properties, enabling the modeling of the major involved processes in normal or in stress conditions. In this review, we provide an overview of the available bioinformatics resources for pollen, ranging from raw data collections to complete databases or platforms, when available, which include data and/or results from -omics efforts on the male gametophyte. Perspectives in the fields will also be described.

Positive selection in the leucine-rich repeat domain of Gro1 genes in Solanum species.

In pathogen resistant plants, solvent-exposed residues in the leucine-rich repeat (LRR) proteins are thought to mediate resistance by recognizing plant pathogen elicitors. In potato, the gene Gro1-4 confers resistance to Globodera rostochiensis. The investigation of variability in different copies of this gene represents a good model for the verification of positive selection mechanisms. Two datasets of Gro1 LRR sequences were constructed, one derived from the Gro1-4 gene, belonging to different cultivated and wild Solanum species, and the other belonging to paralogues of a resistant genotype. Analysis of nonsynonymous to synonymous substitution rates (K(a)/K(s)) highlighted 14 and six amino acids with K(a)/K(s) >1 in orthologue and paralogue datasets, respectively. Selection analysis revealed that the leucine-rich regions accumulate variability in a very specific way, and we found that some combinations of amino acids in these sites might be involved in pathogen recognition. The results confirm previous studies on positive selection in the LRR domain of R protein in Arabidopsis and other model plants and extend these to wild Solanum species. Moreover, positively selected sites in the Gro1 LRR domain show that coevolution mainly occurred in two regions on the internal surface of the three-dimensional horseshoe structure of the domain, albeit with different evolutionary forces between paralogues and orthologues.