A phased genome of the highly heterozygous 'Texas' almond uncovers patterns of allele-specific expression linked to heterozygous structural variants.

The vast majority of traditional almond varieties are self-incompatible, and the level of variability of the species is very high, resulting in a high-heterozygosity genome. Therefore, information on the different haplotypes is particularly relevant to understand the genetic basis of trait variability in this species. However, although reference genomes for several almond varieties exist, none of them is phased and has genome information at the haplotype level. Here, we present a phased assembly of genome of the almond cv. Texas. This new assembly has 13% more assembled sequence than the previous version of the Texas genome and has an increased contiguity, in particular in repetitive regions such as the centromeres. Our analysis shows that the 'Texas' genome has a high degree of heterozygosity, both at SNPs, short indels, and structural variants level. Many of the SVs are the result of heterozygous transposable element insertions, and in many cases, they also contain genic sequences. In addition to the direct consequences of this genic variability on the presence/absence of genes, our results show that variants located close to genes are often associated with allele-specific gene expression, which highlights the importance of heterozygous SVs in almond.

Genomic analysis of fruit size and shape traits in apple: unveiling candidate genes through GWAS analysis.

Genomic tools facilitate the efficient selection of improved genetic materials within a breeding program. Here, we focus on two apple fruit quality traits: shape and size. We utilized data from 11 fruit morphology parameters gathered across three years of harvest from 355 genotypes of the apple REFPOP collection, which serves as a representative sample of the genetic variability present in European-cultivated apples. The data were then employed for genome-wide association studies (GWAS) using the FarmCPU and the BLINK models. The analysis identified 59 SNPs associated with fruit size and shape traits (35 with FarmCPU and 45 with BLINK) responsible for 71 QTNs. These QTNs were distributed across all chromosomes except for chromosomes 10 and 15. Thirty-four QTNs, identified by 27 SNPs, were related for size traits, and 37 QTNs, identified by 26 SNPs, were related to shape attributes. The definition of the haploblocks containing the most relevant SNPs served to propose candidate genes, among them the genes of the ovate family protein MdOFP17 and MdOFP4 that were in a 9.7kb haploblock on Chromosome 11. RNA-seq data revealed low or null expression of these genes in the oblong cultivar "Skovfoged" and higher expression in the flat "Grand'mere." The Gene Ontology enrichment analysis support a role of OFPs and hormones in shape regulation. In conclusion, this comprehensive GWAS analysis of the apple REFPOP collection has revealed promising genetic markers and candidate genes associated with apple fruit shape and size attributes, providing valuable insights that could enhance the efficiency of future breeding programs.

PERSEUS: an interactive and intuitive web-based tool for pedigree visualization.

SUMMARY: Pedigree-based analyses' prime role is to unravel relationships between individuals in breeding programs and germplasms. This is critical information for decoding the genetics underlying main inherited traits of relevance, and unlocking the genotypic variability of a species to carry out genomic selections and predictions. Despite the great interest, current lineage visualizations become quite limiting in terms of public display, exploration, and tracing of traits up to ancestral donors. PERSEUS is a user-friendly, intuitive, and interactive web-based tool for pedigree visualizations represented as directed graph networks distributed using a force-repulsion method. The visualizations do not only showcase individual relationships among accessions, but also facilitate a seamless search and download of phenotypic traits along the pedigrees. PERSEUS is a promising tool for breeders and scientists, advantageous for evolutionary, genealogy, and diversity analyses among related accessions and species. AVAILABILITY AND IMPLEMENTATION: PERSEUS is freely accessible at https://bioinformatics.cragenomica.es/perseus and GitHub code is available at https://github.com/aranzana-lab/PERSEUS.

LeTra: a leaf tracking workflow based on convolutional neural networks and intersection over union.

BACKGROUND: The study of plant photosynthesis is essential for productivity and yield. Thanks to the development of high-throughput phenotyping (HTP) facilities, based on chlorophyll fluorescence imaging, photosynthetic traits can be measured in a reliable, reproducible and efficient manner. In most state-of-the-art HTP platforms, these traits are automatedly analyzed at individual plant level, but information at leaf level is often restricted by the use of manual annotation. Automated leaf tracking over time is therefore highly desired. Methods for tracking individual leaves are still uncommon, convoluted, or require large datasets. Hence, applications and libraries with different techniques are required. New phenotyping platforms are initiated now more frequently than ever; however, the application of advanced computer vision techniques, such as convolutional neural networks, is still growing at a slow pace. Here, we provide a method for leaf segmentation and tracking through the fine-tuning of Mask R-CNN and intersection over union as a solution for leaf tracking on top-down images of plants. We also provide datasets and code for training and testing on both detection and tracking of individual leaves, aiming to stimulate the community to expand the current methodologies on this topic. RESULTS: We tested the results for detection and segmentation on 523 Arabidopsis thaliana leaves at three different stages of development from which we obtained a mean F-score of 0.956 on detection and 0.844 on segmentation overlap through the intersection over union (IoU). On the tracking side, we tested nine different plants with 191 leaves. A total of 161 leaves were tracked without issues, accounting to a total of 84.29% correct tracking, and a Higher Order Tracking Accuracy (HOTA) of 0.846. In our case study, leaf age and leaf order influenced photosynthetic capacity and photosynthetic response to light treatments. Leaf-dependent photosynthesis varies according to the genetic background. CONCLUSION: The method provided is robust for leaf tracking on top-down images. Although one of the strong components of the method is the low requirement in training data to achieve a good base result (based on fine-tuning), most of the tracking issues found could be solved by expanding the training dataset for the Mask R-CNN model.

GenoDrawing: An Autoencoder Framework for Image Prediction from SNP Markers.

Advancements in genome sequencing have facilitated whole-genome characterization of numerous plant species, providing an abundance of genotypic data for genomic analysis. Genomic selection and neural networks (NNs), particularly deep learning, have been developed to predict complex traits from dense genotypic data. Autoencoders, an NN model to extract features from images in an unsupervised manner, has proven to be useful for plant phenotyping. This study introduces an autoencoder framework, GenoDrawing, for predicting and retrieving apple images from a low-depth single-nucleotide polymorphism (SNP) array, potentially useful in predicting traits that are difficult to define. GenoDrawing demonstrates proficiency in its task using a small dataset of shape-related SNPs. Results indicate that the use of SNPs associated with visual traits has substantial impact on the generated images, consistent with biological interpretation. While using substantial SNPs is crucial, incorporating additional, unrelated SNPs results in performance degradation for simple NN architectures that cannot easily identify the most important inputs. The proposed GenoDrawing method is a practical framework for exploring genomic prediction in fruit tree phenotyping, particularly beneficial for small to medium breeding companies to predict economically substantial heritable traits. Although GenoDrawing has limitations, it sets the groundwork for future research in image prediction from genomic markers. Future studies should focus on using stronger models for image reproduction, SNP information extraction, and dataset balance in terms of phenotypes for more precise outcomes.

An LTR retrotransposon in the promoter of a PsMYB10.2 gene associated with the regulation of fruit flesh color in Japanese plum.

Japanese plums exhibit wide diversity of fruit coloration. The red to black hues are caused by the accumulation of anthocyanins, while their absence results in yellow, orange or green fruits. In Prunus, MYB10 genes are determinants for anthocyanin accumulation. In peach, QTLs for red plant organ traits map in an LG3 region with three MYB10 copies (PpMYB10.1, PpMYB10.2 and PpMYB10.3). In Japanese plum the gene copy number in this region differs with respect to peach: there are at least three copies of PsMYB10.1, with the expression of one of them (PsMYB10.1a) correlating with fruit skin color. The objective of this study was to determine a possible role of LG3-PsMYB10 genes in the natural variability of the flesh color trait and to develop a molecular marker for marker-assisted selection (MAS). We explored the variability within the LG3-PsMYB10 region using long-range sequences obtained in previous studies through CRISPR-Cas9 enrichment sequencing. We found that the PsMYB10.2 gene was only expressed in red flesh fruits. Its role in promoting anthocyanin biosynthesis was validated by transient overexpression in Japanese plum fruits. The analysis of long-range sequences identified an LTR retrotransposon in the promoter of the expressed PsMYB10.2 gene that explained the trait in 93.1% of the 145 individuals analyzed. We hypothesize that the LTR retrotransposon may promote the PsMYB10.2 expression and activate the anthocyanin biosynthesis pathway. We propose for the first time the PsMYB10.2 gene as candidate for the flesh color natural variation in Japanese plum and provide a molecular marker for MAS.

An efficient CRISPR-Cas9 enrichment sequencing strategy for characterizing complex and highly duplicated genomic regions. A case study in the Prunus salicina LG3-MYB10 genes cluster.

BACKGROUND: Genome complexity is largely linked to diversification and crop innovation. Examples of regions with duplicated genes with relevant roles in agricultural traits are found in many crops. In both duplicated and non-duplicated genes, much of the variability in agronomic traits is caused by large as well as small and middle scale structural variants (SVs), which highlights the relevance of the identification and characterization of complex variability between genomes for plant breeding. RESULTS: Here we improve and demonstrate the use of CRISPR-Cas9 enrichment combined with long-read sequencing technology to resolve the MYB10 region in the linkage group 3 (LG3) of Japanese plum (Prunus salicina). This region, which has a length from 90 to 271 kb according to the P. salicina genomes available, is associated with fruit color variability in Prunus species. We demonstrate the high complexity of this region, with homology levels between Japanese plum varieties comparable to those between Prunus species. We cleaved MYB10 genes in five plum varieties using the Cas9 enzyme guided by a pool of crRNAs. The barcoded fragments were then pooled and sequenced in a single MinION Oxford Nanopore Technologies (ONT) run, yielding 194 Mb of sequence. The enrichment was confirmed by aligning the long reads to the plum reference genomes, with a mean read on-target value of 4.5% and a depth per sample of 11.9x. From the alignment, 3261 SNPs and 287 SVs were called and phased. A de novo assembly was constructed for each variety, which also allowed detection, at the haplotype level, of the variability in this region. CONCLUSIONS: CRISPR-Cas9 enrichment is a versatile and powerful tool for long-read targeted sequencing even on highly duplicated and/or polymorphic genomic regions, being especially useful when a reference genome is not available. Potential uses of this methodology as well as its limitations are further discussed.

Genetic architecture and genomic predictive ability of apple quantitative traits across environments.

Implementation of genomic tools is desirable to increase the efficiency of apple breeding. Recently, the multi-environment apple reference population (apple REFPOP) proved useful for rediscovering loci, estimating genomic predictive ability, and studying genotype by environment interactions (G × E). So far, only two phenological traits were investigated using the apple REFPOP, although the population may be valuable when dissecting genetic architecture and reporting predictive abilities for additional key traits in apple breeding. Here we show contrasting genetic architecture and genomic predictive abilities for 30 quantitative traits across up to six European locations using the apple REFPOP. A total of 59 stable and 277 location-specific associations were found using GWAS, 69.2% of which are novel when compared with 41 reviewed publications. Average genomic predictive abilities of 0.18-0.88 were estimated using main-effect univariate, main-effect multivariate, multi-environment univariate, and multi-environment multivariate models. The G × E accounted for up to 24% of the phenotypic variability. This most comprehensive genomic study in apple in terms of trait-environment combinations provided knowledge of trait biology and prediction models that can be readily applied for marker-assisted or genomic selection, thus facilitating increased breeding efficiency.

Characterization of Japanese Plum (Prunus salicina) PsMYB10 Alleles Reveals Structural Variation and Polymorphisms Correlating With Fruit Skin Color.

The red to blue hue of plant organs is caused due to anthocyanins, which are water-soluble flavonoid pigments. The accumulation of these pigments is regulated by a complex of R2R3-MYB transcription factors (TFs), basic-helix-loop-helix (bHLH), and WD-repeat (WDR) proteins (MBW complex). In Rosaceae species, R2R3-MYBs, particularly MYB10 genes, are responsible for part of the natural variation in anthocyanin colors. Japanese plum cultivars, which are hybrids of Prunus salicina, have high variability in the color hue and pattern, going from yellow-green to red and purple-blue, probably as a result of the interspecific hybridization origin of the crop. Because of such variability, Japanese plum can be considered as an excellent model to study the color determination in Rosaceae fruit tree species. Here, we cloned and characterized the alleles of the PsMYB10 genes in the linkage group LG3 region where quantitative trait loci (QTLs) for the organ color have been mapped to other Prunus species. Allele segregation in biparental populations as well as in a panel of varieties, combined with the whole-genome sequence of two varieties with contrasting fruit color, allowed the organization of the MYB10 alleles into haplotypes. With the help of this strategy, alleles were assigned to genes and at least three copies of PsMYB10.1 were identified in some varieties. In total, we observed six haplotypes, which were able to characterize 91.36% of the cultivars. In addition, two alleles of PsMYB10.1 were found to be highly associated with anthocyanin and anthocyanin-less skin. Their expression during the fruit development confirms their role in the fruit skin coloration. Here, we provide a highly efficient molecular marker for the early selection of colored or non-colored fruits in Japanese plum breeding programs.

The apple REFPOP-a reference population for genomics-assisted breeding in apple.

Breeding of apple is a long-term and costly process due to the time and space requirements for screening selection candidates. Genomics-assisted breeding utilizes genomic and phenotypic information to increase the selection efficiency in breeding programs, and measurements of phenotypes in different environments can facilitate the application of the approach under various climatic conditions. Here we present an apple reference population: the apple REFPOP, a large collection formed of 534 genotypes planted in six European countries, as a unique tool to accelerate apple breeding. The population consisted of 269 accessions and 265 progeny from 27 parental combinations, representing the diversity in cultivated apple and current European breeding material, respectively. A high-density genome-wide dataset of 303,239 SNPs was produced as a combined output of two SNP arrays of different densities using marker imputation with an imputation accuracy of 0.95. Based on the genotypic data, linkage disequilibrium was low and population structure was weak. Two well-studied phenological traits of horticultural importance were measured. We found marker-trait associations in several previously identified genomic regions and maximum predictive abilities of 0.57 and 0.75 for floral emergence and harvest date, respectively. With decreasing SNP density, the detection of significant marker-trait associations varied depending on trait architecture. Regardless of the trait, 10,000 SNPs sufficed to maximize genomic prediction ability. We confirm the suitability of the apple REFPOP design for genomics-assisted breeding, especially for breeding programs using related germplasm, and emphasize the advantages of a coordinated and multinational effort for customizing apple breeding methods in the genomics era.

The Multisite PeachRefPop Collection: A True Cultural Heritage and International Scientific Tool for Fruit Trees.

Plants have evolved a range of adaptive mechanisms that adjust their development and physiology to variable external conditions, particularly in perennial species subjected to long-term interplay with the environment. Exploiting the allelic diversity within available germplasm and leveraging the knowledge of the mechanisms regulating genotype interaction with the environment are crucial to address climatic challenges and assist the breeding of novel cultivars with improved resilience. The development of multisite collections is of utmost importance for the conservation and utilization of genetic materials and will greatly facilitate the dissection of genotype-by-environment interaction. Such resources are still lacking for perennial trees, especially with the intrinsic difficulties of successful propagation, material exchange, and living collection maintenance. This work describes the concept, design, and realization of the first multisite peach (Prunus persica) reference collection (PeachRefPop) located across different European countries and sharing the same experimental design. Other than an invaluable tool for scientific studies in perennial species, PeachRefPop provides a milestone in an international collaborative project for the conservation and exploitation of European peach germplasm resources and, ultimately, as a true heritage for future generations.

Prunus genetics and applications after de novo genome sequencing: achievements and prospects.

Prior to the availability of whole-genome sequences, our understanding of the structural and functional aspects of Prunus tree genomes was limited mostly to molecular genetic mapping of important traits and development of EST resources. With public release of the peach genome and others that followed, significant advances in our knowledge of Prunus genomes and the genetic underpinnings of important traits ensued. In this review, we highlight key achievements in Prunus genetics and breeding driven by the availability of these whole-genome sequences. Within the structural and evolutionary contexts, we summarize: (1) the current status of Prunus whole-genome sequences; (2) preliminary and ongoing work on the sequence structure and diversity of the genomes; (3) the analyses of Prunus genome evolution driven by natural and man-made selection; and (4) provide insight into haploblocking genomes as a means to define genome-scale patterns of evolution that can be leveraged for trait selection in pedigree-based Prunus tree breeding programs worldwide. Functionally, we summarize recent and ongoing work that leverages whole-genome sequences to identify and characterize genes controlling 22 agronomically important Prunus traits. These include phenology, fruit quality, allergens, disease resistance, tree architecture, and self-incompatibility. Translationally, we explore the application of sequence-based marker-assisted breeding technologies and other sequence-guided biotechnological approaches for Prunus crop improvement. Finally, we present the current status of publically available Prunus genomics and genetics data housed mainly in the Genome Database for Rosaceae (GDR) and its updated functionalities for future bioinformatics-based Prunus genetics and genomics inquiry.

Attention sports fans! The far-reaching contributions of bud sport mutants to horticulture and plant biology.

A bud sport is a lateral shoot, inflorescence or single flower/fruit with a visibly different phenotype from the rest of the plant. The new phenotype is often caused by a stable somatic mutation in a single cell that is passed on to its clonal descendants and eventually populates part or all of a meristem. In many cases, a bud sport can be vegetatively propagated, thereby preserving the novel phenotype without sexual reproduction. Bud sports provide new characteristics while retaining the desirable qualities of the parent plant, which is why many bud sports have been developed into popular cultivars. We present an overview of the history of bud sports, the causes and methods of detecting somaclonal variation, and the types of mutant phenotypes that have arisen spontaneously. We focus on examples where the molecular or cytological changes causing the phenotype have been identified. Analysis of these sports has provided valuable insight into developmental processes, gene function and regulation, and in some cases has revealed new information about layer-specific roles of some genes. Examination of the molecular changes causing a phenotype and in some cases reversion back to the original state has contributed to our understanding of the mechanisms that drive genomic evolution.

An integrated approach for increasing breeding efficiency in apple and peach in Europe.

Despite the availability of whole genome sequences of apple and peach, there has been a considerable gap between genomics and breeding. To bridge the gap, the European Union funded the FruitBreedomics project (March 2011 to August 2015) involving 28 research institutes and private companies. Three complementary approaches were pursued: (i) tool and software development, (ii) deciphering genetic control of main horticultural traits taking into account allelic diversity and (iii) developing plant materials, tools and methodologies for breeders. Decisive breakthroughs were made including the making available of ready-to-go DNA diagnostic tests for Marker Assisted Breeding, development of new, dense SNP arrays in apple and peach, new phenotypic methods for some complex traits, software for gene/QTL discovery on breeding germplasm via Pedigree Based Analysis (PBA). This resulted in the discovery of highly predictive molecular markers for traits of horticultural interest via PBA and via Genome Wide Association Studies (GWAS) on several European genebank collections. FruitBreedomics also developed pre-breeding plant materials in which multiple sources of resistance were pyramided and software that can support breeders in their selection activities. Through FruitBreedomics, significant progresses were made in the field of apple and peach breeding, genetics, genomics and bioinformatics of which advantage will be made by breeders, germplasm curators and scientists. A major part of the data collected during the project has been stored in the FruitBreedomics database and has been made available to the public. This review covers the scientific discoveries made in this major endeavour, and perspective in the apple and peach breeding and genomics in Europe and beyond.

A deletion affecting an LRR-RLK gene co-segregates with the fruit flat shape trait in peach.

In peach, the flat phenotype is caused by a partially dominant allele in heterozygosis (Ss), fruits from homozygous trees (SS) abort a few weeks after fruit setting. Previous research has identified a SSR marker (UDP98-412) highly associated with the trait, found suitable for marker assisted selection (MAS). Here we report a ∼10 Kb deletion affecting the gene PRUPE.6G281100, 400 Kb upstream of UDP98-412, co-segregating with the trait. This gene is a leucine-rich repeat receptor-like kinase (LRR-RLK) orthologous to the Brassinosteroid insensitive 1-associated receptor kinase 1 (BAK1) group. PCR markers suitable for MAS confirmed its strong association with the trait in a collection of 246 cultivars. They were used to evaluate the DNA from a round fruit derived from a somatic mutation of the flat variety 'UFO-4', revealing that the mutation affected the flat associated allele (S). Protein BLAST alignment identified significant hits with genes involved in different biological processes. Best protein hit occurred with AtRLP12, which may functionally complement CLAVATA2, a key regulator that controls the stem cell population size. RT-PCR analysis revealed the absence of transcription of the partially deleted allele. The data support PRUPE.6G281100 as a candidate gene for flat shape in peach.

Integrated QTL detection for key breeding traits in multiple peach progenies.

BACKGROUND: Peach (Prunus persica (L.) Batsch) is a major temperate fruit crop with an intense breeding activity. Breeding is facilitated by knowledge of the inheritance of the key traits that are often of a quantitative nature. QTLs have traditionally been studied using the phenotype of a single progeny (usually a full-sib progeny) and the correlation with a set of markers covering its genome. This approach has allowed the identification of various genes and QTLs but is limited by the small numbers of individuals used and by the narrow transect of the variability analyzed. In this article we propose the use of a multi-progeny mapping strategy that used pedigree information and Bayesian approaches that supports a more precise and complete survey of the available genetic variability. RESULTS: Seven key agronomic characters (data from 1 to 3 years) were analyzed in 18 progenies from crosses between occidental commercial genotypes and various exotic lines including accessions of other Prunus species. A total of 1467 plants from these progenies were genotyped with a 9 k SNP array. Forty-seven QTLs were identified, 22 coinciding with major genes and QTLs that have been consistently found in the same populations when studied individually and 25 were new. A substantial part of the QTLs observed (47%) would not have been detected in crosses between only commercial materials, showing the high value of exotic lines as a source of novel alleles for the commercial gene pool. Our strategy also provided estimations on the narrow sense heritability of each character, and the estimation of the QTL genotypes of each parent for the different QTLs and their breeding value. CONCLUSIONS: The integrated strategy used provides a broader and more accurate picture of the variability available for peach breeding with the identification of many new QTLs, information on the sources of the alleles of interest and the breeding values of the potential donors of such valuable alleles. These results are first-hand information for breeders and a step forward towards the implementation of DNA-informed strategies to facilitate selection of new cultivars with improved productivity and quality.

Genome-enabled predictions for fruit weight and quality from repeated records in European peach progenies.

BACKGROUND: Highly polygenic traits such as fruit weight, sugar content and acidity strongly influence the agroeconomic value of peach varieties. Genomic Selection (GS) can accelerate peach yield and quality gain if predictions show higher levels of accuracy compared to phenotypic selection. The available IPSC 9K SNP array V1 allows standardized and highly reliable genotyping, preparing the ground for GS in peach. RESULTS: A repeatability model (multiple records per individual plant) for genome-enabled predictions in eleven European peach populations is presented. The analysis included 1147 individuals derived from both commercial and non-commercial peach or peach-related accessions. Considered traits were average fruit weight (FW), sugar content (SC) and titratable acidity (TA). Plants were genotyped with the 9K IPSC array, grown in three countries (France, Italy, Spain) and phenotyped for 3-5 years. An analysis of imputation accuracy of missing genotypic data was conducted using the software Beagle, showing that two of the eleven populations were highly sensitive to increasing levels of missing data. The regression model produced, for each trait and each population, estimates of heritability (FW:0.35, SC:0.48, TA:0.53, on average) and repeatability (FW:0.56, SC:0.63, TA:0.62, on average). Predictive ability was estimated in a five-fold cross validation scheme within population as the correlation of true and predicted phenotypes. Results differed by populations and traits, but predictive abilities were in general high (FW:0.60, SC:0.72, TA:0.65, on average). CONCLUSIONS: This study assessed the feasibility of Genomic Selection in peach for highly polygenic traits linked to yield and fruit quality. The accuracy of imputing missing genotypes was as high as 96%, and the genomic predictive ability was on average 0.65, but could be as high as 0.84 for fruit weight or 0.83 for titratable acidity. The estimated repeatability may prove very useful in the management of the typical long cycles involved in peach productions. All together, these results are very promising for the application of genomic selection to peach breeding programmes.

Genetic Structure of Modern Durum Wheat Cultivars and Mediterranean Landraces Matches with Their Agronomic Performance.

A collection of 172 durum wheat landraces from 21 Mediterranean countries and 20 modern cultivars were phenotyped in 6 environments for 14 traits including phenology, biomass, yield and yield components. The genetic structure of the collection was ascertained with 44 simple sequence repeat markers that identified 448 alleles, 226 of them with a frequency lower than 5%, and 10 alleles per locus on average. In the modern cultivars all the alleles were fixed in 59% of the markers. Total genetic diversity was HT = 0.7080 and the genetic differentiation value was GST = 0.1730. STRUCTURE software allocated 90.1% of the accessions in five subpopulations, one including all modern cultivars, and the four containing landrace related to their geographic origin: eastern Mediterranean, eastern Balkans and Turkey, western Balkans and Egypt, and western Mediterranean. Mean yield of subpopulations ranged from 2.6 t ha-1 for the western Balkan and Egyptian landraces to 4.0 t ha-1 for modern cultivars, with the remaining three subpopulations showing similar values of 3.1 t ha-1. Modern cultivars had the highest number of grains m-2 and harvest index, and the shortest cycle length. The diversity was lowest in modern cultivars (HT = 0.4835) and highest in landraces from the western Balkans and Egypt (HT = 0.6979). Genetic diversity and AMOVA indicated that variability between subpopulations was much lower (17%) than variability within them (83%), though all subpopulations had similar biomass values in all growth stages. A dendrogram based on simple sequence repeat data matched with the clusters obtained by STRUCTURE, improving this classification for some accessions that have a large admixture. landraces included in the subpopulation from the eastern Balkans and Turkey were separated into two branches in the dendrogram drawn with phenotypic data, suggesting a different origin for the landraces collected in Serbia and Macedonia. The current study shows a reliable relationship between genetic and phenotypic population structures, and the connection of both with the geographic origin of the landraces.

High-density mapping suggests cytoplasmic male sterility with two restorer genes in almond × peach progenies.

Peach (Prunus persica) and almond (Prunus dulcis) are two sexually compatible species that produce fertile offspring. Almond, a highly polymorphic species, is a potential source of new genes for peach that has a strongly eroded gene pool. Here we describe the genetics of a male sterile phenotype that segregated in two almond ('Texas') × peach ('Earlygold') progenies: an F2 (T×E) and a backcross one (T1E) to the 'Earlygold' parent. High-density maps were developed using a 9k peach SNP chip and 135 simple-sequence repeats. Three highly syntenic and collinear maps were obtained: one for the F2 (T×E) and two for the backcross, T1E (for the hybrid) and E (for 'Earlygold'). A major reduction of recombination was observed in the interspecific maps (T×E and T1E) compared to the intraspecific parent (E). The E map also had extensive monomorphic genomic regions suggesting the presence of large DNA fragments identical by descent. Our data for the male sterility character were consistent with the existence of cytoplasmic male sterility, where individuals having the almond cytoplasm required the almond allele in at least one of two independent restorer genes, Rf1 and Rf2, to be fertile. The restorer genes were located in a 3.4 Mbp fragment of linkage group 2 (Rf1) and 1.4 Mbp of linkage group 6 (Rf2). Both fragments contained several genes coding for pentatricopeptide proteins, demonstrated to be responsible for restoring fertility in other species. The implications of these results for using almond as a source of novel variability in peach are discussed.