Prunus species are important crops in temperate regions. In these regions, drought periods are predicted to occur more frequently due to climate change. In this sense, to reduce the impact of climate warming, obtaining new tolerant/resistant cultivars and rootstocks is a mandatory goal in Prunus breeding. Therefore, the current study assembled three Prunus species including almond, (P. dulcis Mill D.A. Webb), apricot (P. armeniaca L.) and peach (P. persica L.) to model the temporal effects of drought. A hybrid peach × almond and a wild almond-relative species Prunus webbii were also included in the study. Physiological traits associated with photosynthetic activity, leaf water status, and chlorophyll content were assessed under three watering treatments. Results showed that effects of time, genotype, and treatment interact significantly in all traits. In addition, results confirmed that P. webbii have a greater tolerance to drought than commercial rootstocks. However, “Real Fino” apricot showed the fastest recovery after re-irrigation while being one of the most affected cultivars. In addition, from the better response to these watering treatments by the almond genotypes, two different trends were observed after re-irrigation treatment that clearly differentiate the response of the almond cultivar “Garrigue” from the rest of Prunus genotypes. A better characterization of the short-term drought response in Prunus, an accurate and more efficient evaluation of the genotype effect was obtained from the use of mixed models considering appropriate variance–covariance structures. Although the advantages of these approaches are rarely used in Prunus breeding, these methodologies should be undertaken in the future by breeders to increase efficiency in developing new breeding materials.

The floral perianth, comprising sepals and petals, conceals the sexual organs and attracts pollinators. The coordination of growth and scent emission is not fully understood. We have analyzed the effect of knocking down CHANEL (PhCHL), the ZEITLUPE ortholog in petunia (PhCHL) by hairpin RNAs. Plants with low PhCHL mRNA had overall decreased size. Growth evaluation using time lapse image analysis showed that early leaf movement was not affected by RNAi:PhCHL, but flower angle movement was modified, moving earlier during the day in knockdown plants than in wild types. Despite differences in stem length, growth rate was not significantly affected by loss of PhCHL. In contrast, petal growth displayed lower growth rate in RNAi:PhCHL. Decreased levels of PhCHL caused strongly modified scent profiles, including changes in composition and timing of emission resulting in volatile profiles highly divergent from the wild type. Our results show a role of PhCHL in controlling growth and development of vegetative and reproductive organs in petunia. The different effects of PhCHL on organ development indicate an organ-specific interpretation of the down regulation of PhCHL. Through the control of both timing and quantitative volatile emissions, PhCHL appears to be a major coordinator of scent profiles.

Loss of genetic variability is a steadily increasing challenge in tree breeding programs due to the repeated use of a reduced number of founder genotypes. High-quality pedigree data of 222 almond [ Prunus dulcis (Miller) D.A. Webb, syn. P. amygdalus (L) Batsch] cultivars and breeding selections were used to study global genetic variability in modern breeding programs from Argentina, Australia, France, Greece, Israel, Italy, Russia, Spain and the USA. Inbreeding coefficients, pairwise relatedness and genetic contribution were calculated for these genotypes. The results reveal two mainstream breeding lines based on three cultivars from two different geographical regions: ‘Tuono’-‘Cristomorto’ (local landraces from Puglia, Italy) and ‘Nonpareil’ (chance seedling selected in California, USA, from French original stock). Direct descendants from ‘Tuono’ or ‘Cristomorto’ number 75 (sharing 30 descendants), while ‘Nonpareil’ has 72 direct descendants. The mean inbreeding coefficient of the analyzed genotypes was 0.036, with 13 genotypes presenting a high inbreeding coefficient, over 0.250. Breeding programs from the USA, France and Spain showed inbreeding coefficients of 0.067, 0.050 and 0.034, respectively. According to their genetic contribution, modern cultivars from Israel, France, the USA, Spain and Australia, trace back to six, five, four, four and two main founding genotypes respectively. Among the group of 65 genotypes carrying the S _f allele for self-compatibility, the mean relatedness coefficient was 0.133, with ‘Tuono’ as the main founding genotype (23.75% of total genetic contribution). Increasing as well as preserving current genetic variability is required in almond breeding programs worldwide to assure genetic gain and continuing breeding progress. Breeding objectives, apart from high and efficient productivity, should include disease resistance and adaptation to climate change. Ultimately, any new commercial almond cultivar has to be economically viable and breeders play a critical role in achieving this goal.

Transcriptomics studies generate enormous amounts of biological information. Nowadays, representing this complex data as gene coexpression networks (GCNs) is becoming commonplace. Peach is a model for Prunus genetics and genomics, but identifying and validating genes associated to peach breeding traits is a complex task. A GCN capable of capturing stable gene-gene relationships would help researchers overcome the intrinsic limitations of peach genetics and genomics approaches and outline future research opportunities. In this study, we created the first large-scale GCN in peach, applying aggregated and non-aggregated methods to create four GCNs from 604 Illumina RNA-Seq libraries. We evaluated the performance of every GCN in predicting functional annotations using a machine-learning algorithm based on the ‘guilty-by-association’ principle. The GCN with the best performance was COO300, encompassing 21,956 genes and an average AUROC of 0.746. To validate its performance predicting gene function, we used two well-characterized genes involved in fruit flesh softening in peach: the endopolygalacturonases PpPG21 and PpPG22 . Genes coexpressing with PpPG21 and PpPG22 were extracted and named as melting flesh (MF) subnetwork. Finally, we performed an enrichment analysis of MF subnetwork and compared the results with the current knowledge regarding peach fruit softening process. The MF subnetwork mainly included genes involved in cell wall expansion and remodeling, with expression triggered by ripening-related phytohormones such as ethylene, auxin and methyl jasmonates. All these processes are closely related with peach fruit softening and therefore related to the function of PpPG21 and PpPG22 . These results validate COO300 as a powerful tool for peach and Prunus research. COO300, renamed as PeachGCN v1.0, and the scripts necessary to perform a function prediction analysis using it, are available at https://github.com/felipecobos/PeachGCN .