Shelf life and biochemical changes of ready-to-eat arils among nineteen Iranian pomegranate cultivars (Punica granatum L.) during storage.

The objective of this study was to investigate the shelf life of arils and the changes in their biochemical compounds in nineteen Iranian pomegranate cultivars during storage. Fruits were harvested when commercially mature and the arils were removed, packaged and stored at 5 ± 1 °C, at 85-90% relative humidity in a cold room. Samples of the stored arils were examined for biochemical features in temporal checkpoints throughout a storage period that lasted for 35 days. By using the onset of decay as an index, the shelf life of arils varied among cultivars, ranging from 7 days to approximately 21 days. Considering the quality attributes of ready-to-eat arils at the beginning of the experiment, substantial variations were observed among the cultivars with regard to their titratable acidity (0.50-8.47%), total soluble solids (13-18.66 °Brix), DPPH radical scavenging activity (63-87.44%), Gallic-acid-equivalent (2.64-6.95 mg/ml) and ascorbic acid (12.21-75.09 mg/l). In general, the decay of arils gradually increased during storage, but several cultivars-which exhibited a very slow process of decay-contained the highest content of titratable acidity, Gallic-acid-equivalent and total soluble solids (since the signs of decay appeared on around the twenty-first day of storage). In addition, titratable acidity increased slightly by the end of storage, whereas the ascorbic acid content, total soluble solids and Gallic-acid-equivalent were cultivar-dependent and did not show consistent patterns of change during storage.

Comparative genomics analysis in Prunoideae to identify biologically relevant polymorphisms.

Prunus is an economically important genus with a wide range of physiological and biological variability. Using the peach genome as a reference, sequencing reads from four almond accessions and one sweet cherry cultivar were used for comparative analysis of these three Prunus species. Reference mapping enabled the identification of many biological relevant polymorphisms within the individuals. Examining the depth of the polymorphisms and the overall scaffold coverage, we identified many potentially interesting regions including hundreds of small scaffolds with no coverage from any individual. Non-sense mutations account for about 70 000 of the 13 million identified single nucleotide polymorphisms (SNPs). Blast2GO analyses on these non-sense SNPs revealed several interesting results. First, non-sense SNPs were not evenly distributed across all gene ontology terms. Specifically, in comparison with peach, sweet cherry is found to have non-sense SNPs in two 1-aminocyclopropane-1-carboxylate synthase (ACS) genes and two 1-aminocyclopropane-1-carboxylate oxidase (ACO) genes. These polymorphisms may be at the root of the nonclimacteric ripening of sweet cherry. A set of candidate genes associated with bitterness in almond were identified by comparing sweet and bitter almond sequences. To the best of our knowledge, this is the first report in plants of non-sense SNP abundance in a genus being linked to specific GO terms.

Rapid gene-based SNP and haplotype marker development in non-model eukaryotes using 3'UTR sequencing.

BACKGROUND: Sweet cherry (Prunus avium L.), a non-model crop with narrow genetic diversity, is an important member of sub-family Amygdoloideae within Rosaceae. Compared to other important members like peach and apple, sweet cherry lacks in genetic and genomic information, impeding understanding of important biological processes and development of efficient breeding approaches. Availability of single nucleotide polymorphism (SNP)-based molecular markers can greatly benefit breeding efforts in such non-model species. RNA-seq approaches employing second generation sequencing platforms offer a unique avenue to rapidly identify gene-based SNPs. Additionally, haplotype markers can be rapidly generated from transcript-based SNPs since they have been found to be extremely utile in identification of genetic variants related to health, disease and response to environment as highlighted by the human HapMap project. RESULTS: RNA-seq was performed on two sweet cherry cultivars, Bing and Rainier using a 3' untranslated region (UTR) sequencing method yielding 43,396 assembled contigs. In order to test our approach of rapid identification of SNPs without any reference genome information, over 25% (10,100) of the contigs were screened for the SNPs. A total of 207 contigs from this set were identified to contain high quality SNPs. A set of 223 primer pairs were designed to amplify SNP containing regions from these contigs and high resolution melting (HRM) analysis was performed with eight important parental sweet cherry cultivars. Six of the parent cultivars were distantly related to Bing and Rainier, the cultivars used for initial SNP discovery. Further, HRM analysis was also performed on 13 seedlings derived from a cross between two of the parents. Our analysis resulted in the identification of 84 (38.7%) primer sets that demonstrated variation among the tested germplasm. Reassembly of the raw 3'UTR sequences using upgraded transcriptome assembly software yielded 34,620 contigs containing 2243 putative SNPs in 887 contigs after stringent filtering. Contigs with multiple SNPs were visually parsed to identify 685 putative haplotypes at 335 loci in 301 contigs. CONCLUSIONS: This approach, which leverages the advantages of RNA-seq approaches, enabled rapid generation of gene-linked SNP and haplotype markers. The general approach presented in this study can be easily applied to other non-model eukaryotes irrespective of the ploidy level to identify gene-linked polymorphisms that are expected to facilitate efficient Gene Assisted Breeding (GAB), genotyping and population genetics studies. The identified SNP haplotypes reveal some of the allelic differences in the two sweet cherry cultivars analyzed. The identification of these SNP and haplotype markers is expected to significantly improve the genomic resources for sweet cherry and facilitate efficient GAB in this non-model crop.

Draft genome data of Prunus avium cv 'Stella'.

Prunus avium cv. 'Stella' total cellular DNA was isolated from emerging leaf tissue and sequenced using Roche 454 GS FLX Titanium, and Illumina HiSeq 2000 High Throughput Sequencing (HTS) technologies. Sequence data were filtered and trimmed to retain nucleotides corresponding to Phred score 30, and assembled with CLC Genomics Workbench v.6.0.1. A total of 107,531 contigs were assembled with 185 scaffolds with a maximum length of 132,753 nucleotides and an N50 value of 4,601. The average depth of coverage was 135.87 nucleotides with a median depth of coverage equal to 31.50 nucleotides. The draft 'Stella' genome presented here covers 77.8% of the estimated 352.9Mb P. avium genome and is expected to facilitate genetics and genomics research focused on identifying genes and quantitative trait loci (QTL) underlying important agronomic and consumer traits.

Prediction of genetic value for sweet cherry fruit maturity among environments using a 6K SNP array.

The timing of fruit maturity is an important trait in sweet cherry production and breeding. Phenotypic variation for phenology of fruit maturity in sweet cherry appears to be under strong genetic control, but that control might be complicated by phenotypic instability across environments. Although such genotype-by-environment interaction (G × E) is a common phenomenon in crop plants, knowledge about it is lacking for fruit maturity timing and other sweet cherry traits. In this study, 1673 genome-wide SNP markers were used to estimate genomic relationships among 597 weakly pedigree-connected individuals evaluated over two seasons at three locations in Europe and one location in the USA, thus sampling eight 'environments'. The combined dataset enabled a single meta-analysis to investigate the environmental stability of genomic predictions. Linkage disequilibrium among marker loci declined rapidly with physical distance, and ordination of the relationship matrix suggested no strong structure among germplasm. The most parsimonious G × E model allowed heterogeneous genetic variance and pairwise covariances among environments. Narrow-sense genomic heritability was very high (0.60-0.83), as was accuracy of predicted breeding values (>0.62). Average correlation of additive effects among environments was high (0.96) and breeding values were highly correlated across locations. Results indicated that genomic models can be used in cherry to accurately predict date of fruit maturity for untested individuals in new environments. Limited G × E for this trait indicated that phenotypes of individuals will be stable across similar environments. Equivalent analyses for other sweet cherry traits, for which multiple years of data are commonly available among breeders and cultivar testers, would be informative for predicting performance of elite selections and cultivars in new environments.

Mapping a candidate gene (MdMYB10) for red flesh and foliage colour in apple.

BACKGROUND: Integrating plant genomics and classical breeding is a challenge for both plant breeders and molecular biologists. Marker-assisted selection (MAS) is a tool that can be used to accelerate the development of novel apple varieties such as cultivars that have fruit with anthocyanin through to the core. In addition, determining the inheritance of novel alleles, such as the one responsible for red flesh, adds to our understanding of allelic variation. Our goal was to map candidate anthocyanin biosynthetic and regulatory genes in a population segregating for the red flesh phenotypes. RESULTS: We have identified the Rni locus, a major genetic determinant of the red foliage and red colour in the core of apple fruit. In a population segregating for the red flesh and foliage phenotype we have determined the inheritance of the Rni locus and DNA polymorphisms of candidate anthocyanin biosynthetic and regulatory genes. Simple Sequence Repeats (SSRs) and Single Nucleotide Polymorphisms (SNPs) in the candidate genes were also located on an apple genetic map. We have shown that the MdMYB10 gene co-segregates with the Rni locus and is on Linkage Group (LG) 09 of the apple genome. CONCLUSION: We have performed candidate gene mapping in a fruit tree crop and have provided genetic evidence that red colouration in the fruit core as well as red foliage are both controlled by a single locus named Rni. We have shown that the transcription factor MdMYB10 may be the gene underlying Rni as there were no recombinants between the marker for this gene and the red phenotype in a population of 516 individuals. Associating markers derived from candidate genes with a desirable phenotypic trait has demonstrated the application of genomic tools in a breeding programme of a horticultural crop species.

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.

Phenolic compounds in Rosaceae fruit and nut crops.

The demand for new fruit cultivars with high levels of phytochemicals, in particular phenolic compounds, has received increasing attention from biochemists, pharmaceutical companies, plant breeders, and the general public due to their health benefits. This review focuses on the economically important Rosaceae, which contains varying proportions and concentrations of these compounds. The paper discusses the common phenolics in the Rosaceae including phenolic acids, flavonols, flavanols, anthocyanins, and dihydrochalcones. The nonextractable phenolics are also presented but not discussed in detail. The metabolism and bioavailability of phenolics, as well as human and environmental factors that affect their concentration and composition, are highlighted. Furthermore, the paper presents different approaches for biofortification and posits that breeding may be the most viable and sustainable option as it improves other fruit quality traits simultaneously and increases confidence in adoption of new cultivars with enhanced consumer appeal.

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.

Heritability and genetic and phenotypic correlations of apple (Malus x domestica) fruit volatiles in a genetically diverse breeding population.

Flavor is an important quality trait of fruit and a target for improvement through plant breeding. Eighty-nine flavor volatiles from 240 apple (Malus domestica) genotypes from a highly diverse breeding population were measured by headspace gas chromatography-mass spectrometry (GC-MS) over 2 years. Heritabilities and phenotypic and genetic correlations were calculated for 23 flavor volatiles. Genetic correlations showed coinheritance of five groups of volatiles, ethyl esters, alcohols and alpha-farnesene, propyl and butyl esters, propanoate and 2-methylbutanoate esters, and acetate esters, consistent with our knowledge of volatile biosynthesis in apple. This work demonstrates a genetic structure underlying the highly variable volatile profiles observed for apple fruit and the potential of GC-MS volatile profiling for the genetic analysis of aroma volatiles in genetically diverse populations.