The Expanding Menagerie of Prunus-Infecting Luteoviruses.

Members of the genus Luteovirus are responsible for economically destructive plant diseases worldwide. Over the past few years, three luteoviruses infecting Prunus trees have been characterized. However, the biological properties, prevalence, and genetic diversity of those viruses have not yet been studied. High-throughput sequencing of samples of various wild, cultivated, and ornamental Prunus species enabled the identification of four novel species in the genus Luteovirus for which we obtained complete or nearly complete genomes. Additionally, we identified another new putative species recovered from Sequence Read Archive data. Furthermore, we conducted a survey on peach-infecting luteoviruses in eight European countries. Analyses of 350 leaf samples collected from germplasm, production orchards, and private gardens showed that peach-associated luteovirus (PaLV), nectarine stem pitting-associated virus (NSPaV), and a novel luteovirus, peach-associated luteovirus 2 (PaLV2), are present in all countries; the most prevalent virus was NSPaV, followed by PaLV. The genetic diversity of these viruses was also analyzed. Moreover, the biological indexing on GF305 peach indicator plants demonstrated that PaLV and PaLV2, like NSPaV, are transmitted by graft at relatively low rates. No clear viral symptoms have been observed in either graft-inoculated GF305 indicators or different peach tree varieties observed in an orchard. The data generated during this study provide a broader overview of the genetic diversity, geographical distribution, and prevalence of peach-infecting luteoviruses and suggest that these viruses are likely asymptomatic in peach under most circumstances.

SSR-Based Analysis of Genetic Diversity and Structure of Sweet Cherry (Prunus avium L.) from 19 Countries in Europe.

Sweet cherry (Prunus avium L.) is a temperate fruit species whose production might be highly impacted by climate change in the near future. Diversity of plant material could be an option to mitigate these climate risks by enabling producers to have new cultivars well adapted to new environmental conditions. In this study, subsets of sweet cherry collections of 19 European countries were genotyped using 14 SSR. The objectives of this study were (i) to assess genetic diversity parameters, (ii) to estimate the levels of population structure, and (iii) to identify germplasm redundancies. A total of 314 accessions, including landraces, early selections, and modern cultivars, were monitored, and 220 unique SSR genotypes were identified. All 14 loci were confirmed to be polymorphic, and a total of 137 alleles were detected with a mean of 9.8 alleles per locus. The average number of alleles (N = 9.8), PIC value (0.658), observed heterozygosity (Ho = 0.71), and expected heterozygosity (He = 0.70) were higher in this study compared to values reported so far. Four ancestral populations were detected using STRUCTURE software and confirmed by Principal Coordinate Analysis (PCoA), and two of them (K1 and K4) could be attributed to the geographical origin of the accessions. A N-J tree grouped the 220 sweet cherry accessions within three main clusters and six subgroups. Accessions belonging to the four STRUCTURE populations roughly clustered together. Clustering confirmed known genealogical data for several accessions. The large genetic diversity of the collection was demonstrated, in particular within the landrace pool, justifying the efforts made over decades for their conservation. New sources of diversity will allow producers to face challenges, such as climate change and the need to develop more sustainable production systems.

Towards a Joint International Database: Alignment of SSR Marker Data for European Collections of Cherry Germplasm.

The objective of our study was the alignment of microsatellite or simple sequence repeat (SSR) marker data across germplasm collections of cherry within Europe. Through the European Cooperative program for Plant Genetic Resources ECPGR, a number of European germplasm collections had previously been analysed using standard sets of SSR loci. However, until now these datasets remained unaligned. We used a combination of standard reference genotypes and ad-hoc selections to compile a central dataset representing as many alleles as possible from national datasets produced in France, Great Britain, Germany, Italy, Sweden and Switzerland. Through the comparison of alleles called in data from replicated samples we were able to create a series of alignment factors, supported across 448 different allele calls, that allowed us to align a dataset of 2241 SSR profiles from six countries. The proportion of allele comparisons that were either in agreement with the alignment factor or confounded by null alleles ranged from 67% to 100% and this was further improved by the inclusion of a series of allele-specific adjustments. The aligned dataset allowed us to identify groups of previously unknown matching accessions and to identify and resolve a number of errors in the prior datasets. The combined and aligned dataset represents a significant step forward in the co-ordinated management of field collections of cherry in Europe.

The walnut genetic resources of INRA: chronological phenotypic data and ontology.

OBJECTIVES: Persian walnut (Juglans regia L.), the walnut species cultivated for nut production, is grown worldwide in temperate areas. In this work, chronological phenotypic data have been collected regarding a part of the walnut genetic resources of the French National Institute for Agricultural Research (INRA) of Bordeaux. Using a well described ontology, these data have been collected in order to assess the phenotypic variations among the accessions, and to better manage the germplasm collection. These data can also be helpful for any breeding program as they provide a clear phenotypic characterization of the main cultivars. DATA DESCRIPTION: This paper introduces a dataset collected for 150 J. regia accessions for a period from 1965 to 2016, and for 3 observation sites, released as comma separated value spreadsheet. It includes observations about phenological traits (e.g. flowering dates), traits related to in-shell walnut (e.g. weight and size), and traits related to kernel (e.g. color). It can be used by other researchers particularly for multi-site phenological studies in the context of climate change since climate data files are also available. In addition, a complete walnut ontology was deposited in this repository and can assist to standardize the management of any walnut germplasm collection.