Maria José Aranzana

Microsatellite variability in peach (Prunus persica (L.) Batsch): cultivar identification, marker mutation, pedigree inferences and population structure

Abstract.A collection of 212 peach and nectarine cultivars covering a wide variation of the species were studied with 16 polymorphic single-locus microsatellite, or simple-sequence repeat (SSR), markers. The average number of alleles per locus was 7.3, 35% of the cultivar × locus combinations analyzed were heterozygous and 87% of the cultivars studied could be individually identified. Most of the groups where two or more cultivars had the same SSR fingerprint included known peach mutants or possible synonymies. Pedigree information was tested with the SSR data. Five unexpected genotypes, due to a mutation at five SSR loci were found when comparing the SSR fingerprint of 14 known mutant cultivars and putative synonymous cultivars. The pedigree data were not consistent with the observed data in 11 out of 38 cases that could be analyzed. The group of non-melting fruit flesh cultivars, generally used by the canning industry, was more variable and genetically distant than the rest of the cultivars tested. Based on their level of homozygosity it was possible to separate those cultivars that were obtained by modern breeding technologies from those that were selected from traditional orchards after generations of seed propagation. The former had a distribution of genotypic frequencies close to a random mating model while the latter had a higher level of homozygosity. The implications of these data for the use of SSR fingerprints in breeders rights protection and peach breeding are discussed.

Whole-Genome Analysis of Diversity and SNP-Major Gene Association in Peach Germplasm.

Peach was domesticated in China more than four millennia ago and from there it spread world-wide. Since the middle of the last century, peach breeding programs have been very dynamic generating hundreds of new commercial varieties, however, in most cases such varieties derive from a limited collection of parental lines (founders). This is one reason for the observed low levels of variability of the commercial gene pool, implying that knowledge of the extent and distribution of genetic variability in peach is critical to allow the choice of adequate parents to confer enhanced productivity, adaptation and quality to improved varieties. With this aim we genotyped 1,580 peach accessions (including a few closely related Prunus species) maintained and phenotyped in five germplasm collections (four European and one Chinese) with the International Peach SNP Consortium 9K SNP peach array. The study of population structure revealed the subdivision of the panel in three main populations, one mainly made up of Occidental varieties from breeding programs (POP1OCB), one of Occidental landraces (POP2OCT) and the third of Oriental accessions (POP3OR). Analysis of linkage disequilibrium (LD) identified differential patterns of genome-wide LD blocks in each of the populations. Phenotypic data for seven monogenic traits were integrated in a genome-wide association study (GWAS). The significantly associated SNPs were always in the regions predicted by linkage analysis, forming haplotypes of markers. These diagnostic haplotypes could be used for marker-assisted selection (MAS) in modern breeding programs.

A first insight into peach [Prunus persica (L.) Batsch] SNP variability

Three factors may have reduced the diversity at both individual gene and whole genome levels in cultivated peach: its self-compatible mating system, the narrow genetic basis of most commercial cultivars, and the recent strong selection towards agronomically interesting traits. Previous diversity analyses with markers such as simple sequence repeats (SSRs) have revealed low levels of genetic variability. Here, we sequenced 23 genome-wide distributed DNA fragments in 47 occidental peach varieties, also observing reduced variability levels. On average, there was one single nucleotide polymorphism (SNP) every 598 bp and one indel every 4,189 bp. As expected, variability was higher in non-coding than in coding regions (one SNP every 390 non-coding bp versus one in 1,850 bp in coding DNA). In general, SNPs were observed at relatively high frequency, mean minor allele frequency = 0.225, meaning that a large proportion of the SNPs discovered by sequencing similar germplasm will be useful for other purposes, such as association mapping. The average heterozygosity of the varieties was 0.28, with a low correlation between SSR and SNP heterozygosity. The whole sequence of two candidate genes, a pectate lyase 1 candidate for fruit firmness (CGPAA2668) and a sucrose synthase 1 candidate for sugar content (CGPPB6189), in the 47 varieties revealed that they both may have suffered a process of balancing selection.

ASSIsT: an automatic SNP scoring tool for in- and outbreeding species

ASSIsT (Automatic SNP ScorIng Tool) is a user-friendly customized pipeline for efficient calling and filtering of SNPs from Illumina Infinium arrays, specifically devised for custom genotyping arrays. Illumina has developed an integrated software for SNP data visualization and inspection called GenomeStudio® (GS). ASSIsT builds on GS-derived data and identifies those markers that follow a bi-allelic genetic model and show reliable genotype calls. Moreover, ASSIsT re-edits SNP calls with null alleles or additional SNPs in the probe annealing site. ASSIsT can be employed in the analysis of different population types such as full-sib families and mating schemes used in the plant kingdom (backcross, F1, F2), and unrelated individuals. The final result can be directly exported in the format required by the most common software for genetic mapping and marker–trait association analysis. ASSIsT is developed in Python and runs in Windows and Linux. Availability and implementation: The software, example data sets and tutorials are freely available at http://compbiotoolbox.fmach.it/assist/. Contact: eric.vandeweg@wur.nl

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.

Identifying SNP markers tightly associated with six major genes in peach [Prunus persica (L.) Batsch] using a high-density SNP array with an objective of marker-assisted selection (MAS)

One of the applications of genomics is to identify genetic markers linked to loci responsible for variation in phenotypic traits, which could be used in breeding programs to select individuals with favorable alleles, particularly at the seedling stage. With this aim, in the framework of the European project FruitBreedomics, we selected five main peach fruit characters and a resistance trait, controlled by major genes with Mendelian inheritance: fruit flesh color Y, fruit skin pubescence G, fruit shape S, sub-acid fruit D, stone adhesion-flesh texture F-M, and resistance to green peach aphid Rm2. They were all previously mapped in Prunus. We then selected three F1 and three F2 progenies segregating for these characters and developed genetic maps of the linkage groups including the major genes, using the single nucleotide polymorphism (SNP) genome-wide scans obtained with the International Peach SNP Consortium (IPSC) 9K SNP array v1. We identified SNPs co-segregating with the characters in all cases. Their positions were in agreement with the known positions of the major genes. The number of SNPs linked to each of these, as well as the size of the physical regions encompassing them, varied depending on the maps. As a result, the number of useful SNPs for marker-assisted selection varied accordingly. As a whole, this study establishes a sound basis for further development of MAS on these characters. Additionally, we also discussed some limitations that were observed regarding the SNP array efficiency.

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

BackgroundHighly 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.ResultsA 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).ConclusionsThis 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.

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.

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.Genomics: New resources for apple and pear breedingA Europe-led effort to bridge the gap between genomics and breeding offers a new resource to support apple and peach production. A team led by François Laurens from the Research Institute in Horticulture and Seeds (IRHS) in Angers, France, review the tools, methodologies and scientific discoveries made through FruitBreedomics, a project that ran between 2011 and 2015 and involved 28 different research and private companies from around the world. These new molecular and bioinformatics tools include DNA arrays for mapping genetic diversity, computer software for analyzing genetic information and novel methods for understanding commercially important traits such as fruit quality and resistance to stresses. The project’s materials should help apple and peach producers better plan their breeding programs so as to meet grower and consumer demand for high-quality fruit with desired characteristics.