Angel V. Fernández i Martí

Genetic Diversity and Relatedness of Sweet Cherry (Prunus Avium L.) Cultivars Based on Single Nucleotide Polymorphic Markers

Most previous studies on genetic fingerprinting and cultivar relatedness in sweet cherry were based on isoenzyme, RAPD, and simple sequence repeat (SSR) markers. This study was carried out to assess the utility of single nucleotide polymorphism (SNP) markers generated from 3′ untranslated regions (UTR) for genetic fingerprinting in sweet cherry. A total of 114 sweet cherry germplasm representing advanced selections, commercial cultivars, and old cultivars imported from different parts of the world were screened with seven SSR markers developed from other Prunus species and with 40 SNPs obtained from 3′ UTR sequences of Rainier and Bing sweet cherry cultivars. Both types of marker study had 99 accessions in common. The SSR data was used to validate the SNP results. Results showed that the average number of alleles per locus, mean observed heterozygosity, expected heterozygosity, and polymorphic information content values were higher in SSRs than in SNPs although both set of markers were similar in their grouping of the sweet cherry accessions as shown in the dendrogram. SNPs were able to distinguish sport mutants from their wild type germplasm. For example, “Stella” was separated from “Compact Stella.” This demonstrates the greater power of SNPs for discriminating mutants from their original parents than SSRs. In addition, SNP markers confirmed parentage and also determined relationships of the accessions in a manner consistent with their pedigree relationships. We would recommend the use of 3′ UTR SNPs for genetic fingerprinting, parentage verification, gene mapping, and study of genetic diversity in sweet cherry.

Mapping quantitative trait loci for kernel composition in almond

Background: Almond breeding is increasingly taking into account kernel quality as a breeding objective. Information on the parameters to be considered in evaluating almond quality, such as protein and oil content, as well as oleic acid and tocopherol concentration, has been recently compiled. The genetic control of these traits has not yet been studied in almond, although this information would improve the efficiency of almond breeding programs. Results: A map with 56 simple sequence repeat or microsatellite (SSR) markers was constructed for an almond population showing a wide range of variability for the chemical components of the almond kernel. A total of 12 putative quantitative trait loci (QTL) controlling these chemical traits have been detected in this analysis, corresponding to seven genomic regions of the eight almond linkage groups (LG). Some QTL were clustered in the same region or shared the same molecular markers, according to the correlations already found between the chemical traits. The logarithm of the odds (LOD) values for any given trait ranged from 2.12 to 4.87, explaining from 11.0 to 33.1 % of the phenotypic variance of the trait. Conclusions: The results produced in the study offer the opportunity to include the new genetic information in almond breeding programs. Increases in the positive traits of kernel quality may be looked for simultaneously whenever they are genetically independent, even if they are negatively correlated. We have provided the first genetic framework for the chemical components of the almond kernel, with twelve QTL in agreement with the large number of genes controlling their metabolism.BackgroundAlmond breeding is increasingly taking into account kernel quality as a breeding objective. Information on the parameters to be considered in evaluating almond quality, such as protein and oil content, as well as oleic acid and tocopherol concentration, has been recently compiled. The genetic control of these traits has not yet been studied in almond, although this information would improve the efficiency of almond breeding programs.ResultsA map with 56 simple sequence repeat or microsatellite (SSR) markers was constructed for an almond population showing a wide range of variability for the chemical components of the almond kernel. A total of 12 putative quantitative trait loci (QTL) controlling these chemical traits have been detected in this analysis, corresponding to seven genomic regions of the eight almond linkage groups (LG). Some QTL were clustered in the same region or shared the same molecular markers, according to the correlations already found between the chemical traits. The logarithm of the odds (LOD) values for any given trait ranged from 2.12 to 4.87, explaining from 11.0 to 33.1 % of the phenotypic variance of the trait.ConclusionsThe results produced in the study offer the opportunity to include the new genetic information in almond breeding programs. Increases in the positive traits of kernel quality may be looked for simultaneously whenever they are genetically independent, even if they are negatively correlated. We have provided the first genetic framework for the chemical components of the almond kernel, with twelve QTL in agreement with the large number of genes controlling their metabolism.BACKGROUND Almond breeding is increasingly taking into account kernel quality as a breeding objective. Information on the parameters to be considered in evaluating almond quality, such as protein and oil content, as well as oleic acid and tocopherol concentration, has been recently compiled. The genetic control of these traits has not yet been studied in almond, although this information would improve the efficiency of almond breeding programs. RESULTS A map with 56 simple sequence repeat or microsatellite (SSR) markers was constructed for an almond population showing a wide range of variability for the chemical components of the almond kernel. A total of 12 putative quantitative trait loci (QTL) controlling these chemical traits have been detected in this analysis, corresponding to seven genomic regions of the eight almond linkage groups (LG). Some QTL were clustered in the same region or shared the same molecular markers, according to the correlations already found between the chemical traits. The logarithm of the odds (LOD) values for any given trait ranged from 2.12 to 4.87, explaining from 11.0 to 33.1 % of the phenotypic variance of the trait. CONCLUSIONS The results produced in the study offer the opportunity to include the new genetic information in almond breeding programs. Increases in the positive traits of kernel quality may be looked for simultaneously whenever they are genetically independent, even if they are negatively correlated. We have provided the first genetic framework for the chemical components of the almond kernel, with twelve QTL in agreement with the large number of genes controlling their metabolism.

Association mapping for kernel phytosterol content in almond

Almond kernels are a rich source of phytosterols, which are important compounds for human nutrition. The genetic control of phytosterol content has not yet been documented in almond. Association mapping (AM), also known as linkage disequilibrium (LD), was applied to an almond germplasm collection in order to provide new insight into the genetic control of total and individual sterol contents in kernels. Population structure analysis grouped the accessions into two principal groups, the Mediterranean and the non-Mediterranean. There was a strong subpopulation structure with LD decaying with increasing genetic distance, resulting in lower levels of LD between more distant markers. A significant impact of population structure on LD in the almond cultivar groups was observed. The mean r2-value for all intra-chromosomal loci pairs was 0.040, whereas, the r2 for the inter-chromosomal loci pairs was 0.036. For analysis of association between the markers and phenotypic traits five models were tested. The mixed linear model (MLM) approach using co-ancestry values from population structure and kinship estimates (K model) as covariates identified a maximum of 13 significant associations. Most of the associations found appeared to map within the interval where many candidate genes involved in the sterol biosynthesis pathway are predicted in the peach genome. These findings provide a valuable foundation for quality gene identification and molecular marker assisted breeding in almond.

Molecular analyses of evolution and population structure in a worldwide almond [Prunus dulcis (Mill.) D.A. Webb syn. P. amygdalus Batsch] pool assessed by microsatellite markers

A total of 158 almond accessions representative of the diversity of almond across the five continents were included for analysis using 17 microsatellite polymorphic markers. Genetic relationships among genotypes were estimated using cluster analysis, allowing their differentiation in two main groups, one with the domesticated almond cultivars and selections and the other with all wild Prunus species close to almond. The unweighted pair group method average tree drawn from this analysis classified the genotypes according to their geographical origin, confirming the particular evolution of different almond ecotypes. Structure analysis showed a strong subpopulation structure and linkage disequilibrium decaying with increasing genetic linkage distance. Analysis of molecular variance confirmed that most of the genetic variability was within populations. Therefore the connection structure between the different populations and the possible bottlenecks in the expansion of almond cultivars could be established.

Identification of Genetic Loci Associated with Quality Traits in Almond via Association Mapping

To design an appropriate association study, we need to understand population structure and the structure of linkage disequilibrium within and among populations as well as in different regions of the genome in an organism. In this study, we have used a total of 98 almond accessions, from five continents located and maintained at the Centro de Investigación y Tecnología Agroalimentaria de Aragón (CITA; Spain), and 40 microsatellite markers. Population structure analysis performed in ‘Structure’ grouped the accessions into two principal groups; the Mediterranean (Western-Europe) and the non-Mediterranean, with K = 3, being the best fit for our data. There was a strong subpopulation structure with linkage disequilibrium decaying with increasing genetic distance resulting in lower levels of linkage disequilibrium between more distant markers. A significant impact of population structure on linkage disequilibrium in the almond cultivar groups was observed. The mean r2 value for all intra-chromosomal loci pairs was 0.040, whereas, the r2 for the inter-chromosomal loci pairs was 0.036. For analysis of association between the markers and phenotypic traits, five models comprising both general linear models and mixed linear models were selected to test the marker trait associations. The mixed linear model (MLM) approach using co-ancestry values from population structure and kinship estimates (K model) as covariates identified a maximum of 16 significant associations for chemical traits and 12 for physical traits. This study reports for the first time the use of association mapping for determining marker-locus trait associations in a world-wide almond germplasm collection. It is likely that association mapping will have the most immediate and largest impact on the tier of crops such as almond with the greatest economic value.

Pollen Tube Growth and Self-Compatibility in Almond

Although pollen tube growth has been an important criterion for self-compatibility evaluation in almond, there is not a clear-cut separation between positive and negative growth of pollen tubes in the different genotypes. The examination of pollen tube growth after selfing almond seedlings has allowed establishing different levels of compatibility, but not a clear-cut separation between self-compatible (SC) and self-incompatible (SI) genotypes, related to the presence of pseudo-self-compatibility in almond. Consequently, a relationship between pollen tube growth and self-compatibility in almond may be established for evaluating the seedlings in breeding programs.

Application of genomic technologies to the breeding of trees

The recent introduction of next generation sequencing (NGS) technologies represents a major revolution in providing new tools for identifying the genes and/or genomic intervals controlling important traits for selection in breeding programs. In perennial fruit trees with long generation times and large sizes of adult plants, the impact of these techniques is even more important. High-throughput DNA sequencing technologies have provided complete annotated sequences in many important tree species. Most of the high-throughput genotyping platforms described are being used for studies of genetic diversity and population structure. Dissection of complex traits became possible through the availability of genome sequences along with phenotypic variation data, which allow to elucidate the causative genetic differences that give rise to observed phenotypic variation. Association mapping facilitates the association between genetic markers and phenotype in unstructured and complex populations, identifying molecular markers for assisted selection and breeding. Also, genomic data provide in silico identification and characterization of genes and gene families related to important traits, enabling new tools for molecular marker assisted selection in tree breeding. Deep sequencing of transcriptomes is also a powerful tool for the analysis of precise expression levels of each gene in a sample. It consists in quantifying short cDNA reads, obtained by NGS technologies, in order to compare the entire transcriptomes between genotypes and environmental conditions. The miRNAs are non-coding short RNAs involved in the regulation of different physiological processes, which can be identified by high-throughput sequencing of RNA libraries obtained by reverse transcription of purified short RNAs, and by in silico comparison with known miRNAs from other species. All together, NGS techniques and their applications have increased the resources for plant breeding in tree species, closing the former gap of genetic tools between trees and annual species.

Genomic Sequencing of Japanese Plum (Prunus salicina Lindl.) Mutants Provides a New Model for Rosaceae Fruit Ripening Studies

It has recently been described that the Japanese plum “Santa Rosa” bud sport series contains variations in ripening pattern: climacteric, suppressed-climacteric and non-climacteric types. This provides an interesting model to study the role of ethylene and other key mechanisms governing fruit ripening, softening and senescence. The aim of the current study was to investigate such differences at the genomic level, using this series of plum bud sports, with special reference to genes involved in ethylene biosynthesis, signal transduction, and sugar metabolism. Genomic DNA, isolated from leaf samples of six Japanese plum cultivars (“Santa Rosa”, “July Santa Rosa”, “Late Santa Rosa”, “Sweet Miriam”, “Roysum”, and “Casselman”), was used to construct paired-end standard Illumina libraries. Sequences were aligned to the Prunus persica genome, and genomic variations (SNPs, INDELS, and CNVs) were investigated. Results determined 12 potential candidate genes with significant copy number variation (CNV), being associated with ethylene perception and signal transduction components. Additionally, the Maximum Likelihood (ML) phylogenetic tree showed two sorbitol dehydrogenase genes grouping into a distinct clade, indicating that this natural group is well-defined and presents high sequence identity among its members. In contrast, the ethylene group, which includes ACO1, ACS1, ACS4, ACS5, CTR1, ERF1, ERF3, and ethylene-receptor genes, was widely distributed and clustered into 10 different groups. Thus, ACS, ERF, and sorbitol dehydrogenase proteins potentially share a common ancestor for different plant genomes, while the expansion rate may be related to ancestral expansion rather than species-specific events. Based on the distribution of the clades, we suggest that gene function diversification for the ripening pathway occurred prior to family extension. We herein report all the frameshift mutations in genes involved in sugar transport and ethylene biosynthesis detected as well as the gene CNV implicated in ripening differences.

Molecular modeling of S-RNases involved in almond self-incompatibility

Gametophytic self-incompatibility (GSI) is a mechanism in flowering plants, to prevent inbreeding and promote outcrossing. GSI is under the control of a specific locus, known as the S-locus, which contains at least two genes, the RNase and the SFB. Active S-RNases in the style are essential for rejection of haploid pollen, when the pollen S-allele matches one of two S-alleles of the diploid pistil. However, the nature of their mutual interactions at genetic and biochemical levels remain unclear. Thus, detailed understanding of the protein structure involved in GSI may help in discovering how the proteins involved in GSI may function and how they fulfill their biological roles. To this end, 3D models of the SC (Sf) and two SI (S8 and S23) S-RNases of almond were constructed, using comparative modeling tools. The modeled structures consisted of mixed α and β folds, with six helices and six β-strands. However, the self-compatible (Sf) RNase contained an additional extended loop between the conserved domains RC4 and C5, which may be involved in the manifestation of self-compatibility in almond.