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

Les campagnes de communication gouvernementales de lutte contre les violences faites aux femmes.

Ce travail se centre sur les campagnes publiques de lutte contre les violences faites aux femmes. Ces campagnes reposent sur une composante de l'action publique. Elles permettront d'obtenir une compréhension du phénomène sur plusieurs années et d'appréhender les tendances actuelles des politiques publiques sur les violences

Development and evaluation of a 9K SNP array for peach by internationally coordinated SNP detection and validation in breeding germplasm

Although a large number of single nucleotide polymorphism (SNP) markers covering the entire genome are needed to enable molecular breeding efforts such as genome wide association studies, fine mapping, genomic selection and marker-assisted selection in peach [Prunus persica (L.) Batsch] and related Prunus species, only a limited number of genetic markers, including simple sequence repeats (SSRs), have been available to date. To address this need, an international consortium (The International Peach SNP Consortium; IPSC) has pursued a coordinated effort to perform genome-scale SNP discovery in peach using next generation sequencing platforms to develop and characterize a high-throughput Illumina Infinium® SNP genotyping array platform. We performed whole genome re-sequencing of 56 peach breeding accessions using the Illumina and Roche/454 sequencing technologies. Polymorphism detection algorithms identified a total of 1,022,354 SNPs. Validation with the Illumina GoldenGate® assay was performed on a subset of the predicted SNPs, verifying ∼75% of genic (exonic and intronic) SNPs, whereas only about a third of intergenic SNPs were verified. Conservative filtering was applied to arrive at a set of 8,144 SNPs that were included on the IPSC peach SNP array v1, distributed over all eight peach chromosomes with an average spacing of 26.7 kb between SNPs. Use of this platform to screen a total of 709 accessions of peach in two separate evaluation panels identified a total of 6,869 (84.3%) polymorphic SNPs.The almost 7,000 SNPs verified as polymorphic through extensive empirical evaluation represent an excellent source of markers for future studies in genetic relatedness, genetic mapping, and dissecting the genetic architecture of complex agricultural traits. The IPSC peach SNP array v1 is commercially available and we expect that it will be used worldwide for genetic studies in peach and related stone fruit and nut species

Variable response of three Trifolium repens ecotypes to soil flooding by seawater.

BACKGROUND AND AIMS: Despite concerns about the impact of rising sea levels and storm surge events on coastal ecosystems, there is remarkably little information on the response of terrestrial coastal plant species to seawater inundation. The aim of this study was to elucidate responses of a glycophyte (white clover, Trifolium repens) to short-duration soil flooding by seawater and recovery following leaching of salts. METHODS: Using plants cultivated from parent ecotypes collected from a natural soil salinity gradient, the impact of short-duration seawater soil flooding (8 or 24 h) on short-term changes in leaf salt ion and organic solute concentrations was examined, together with longer term impacts on plant growth (stolon elongation) and flowering. KEY RESULTS: There was substantial Cl(-) and Na(+) accumulation in leaves, especially for plants subjected to 24 h soil flooding with seawater, but no consistent variation linked to parent plant provenance. Proline and sucrose concentrations also increased in plants following seawater flooding of the soil. Plant growth and flowering were reduced by longer soil immersion times (seawater flooding followed by drainage and freshwater inputs), but plants originating from more saline soil responded less negatively than those from lower salinity soil. CONCLUSIONS: The accumulation of proline and sucrose indicates a potential for solute accumulation as a response to the osmotic imbalance caused by salt ions, while variation in growth and flowering responses between ecotypes points to a natural adaptive capacity for tolerance of short-duration seawater soil flooding in T. repens. Consequently, it is suggested that selection for tolerant ecotypes is possible should the predicted increase in frequency of storm surge flooding events occur

Almond population genomics and non-additive GWAS reveal new insights into almond dissemination history and candidate genes for nut traits and blooming time

Domestication drastically changed crop genomes, fixing alleles of interest and creating different genetic populations. Genome-wide association studies (GWASs) are a powerful tool to detect these alleles of interest (and so QTLs). In this study, we explored the genetic structure as well as additive and non-additive genotype–phenotype associations in a collection of 243 almond accessions. Our genetic structure analysis strongly supported the subdivision of the accessions into five ancestral groups, all formed by accessions with a common origin. One of these groups was formed exclusively by Spanish accessions, while the rest were mainly formed by accessions from China, Italy, France, and the USA. These results agree with archaeological and historical evidence that separate modern almond dissemination into four phases: Asiatic, Mediterranean, Californian, and southern hemisphere. In total, we found 13 independent QTLs for nut weight, crack-out percentage, double kernels percentage, and blooming time. Of the 13 QTLs found, only one had an additive effect. Through candidate gene analysis, we proposed Prudul26A013473 as a candidate gene responsible for the main QTL found in crack-out percentage, Prudul26A012082 and Prudul26A017782 as candidate genes for the QTLs found in double kernels percentage, and Prudul26A000954 as a candidate gene for the QTL found in blooming time. Our study enhances our knowledge of almond dissemination history and will have a great impact on almond breeding.We acknowledge Dr. Vincent Segura for his incisive comments reviewing this paper, substantially improving it. We acknowledge financial support from the grants SEV-2015-0533 and CEX2019- 000902-S, PID2019-110599RR-I00, and PID2020-118612RR-I00 (Better Almonds) funded by MCIN/AEI/ 10.13039/501100011033; the Grant RTA2017-00084-00-00 funded by MCIN/AEI/ 10.13039/ 501100011033 and by ‘ESF Investing in your future’; the Grant PCI2019-103670 funded by MCIN/AEI/ 10.13039/501100011033 and co-financed by the European Union; and to the project ANR-18-PRIM-0001 (FREECLIMB) funded by the French National Research Agency. Finally, the grant of F.P.C. PRE2018-086724 funded by MCIN/AEI/ 10.13039/501100011033 and by ‘ESF Investing in your future’. This work has been carried out within the framework of F.P.C.’s PhD in Plant Biology and Biotechnology at the Autonomous University of Barcelona.info:eu-repo/semantics/publishedVersio

Almond population genomics and non-additive GWAS reveal new insights into almond dissemination history and candidate genes for nut traits and blooming time

Domestication drastically changed crop genomes, fixing alleles of interest and creating different genetic populations. Genome-wide association studies (GWASs) are a powerful tool to detect these alleles of interest (and so QTLs). In this study, we explored the genetic structure as well as additive and non-additive genotype-phenotype associations in a collection of 243 almond accessions. Our genetic structure analysis strongly supported the subdivision of the accessions into five ancestral groups, all formed by accessions with a common origin. One of these groups was formed exclusively by Spanish accessions, while the rest were mainly formed by accessions from China, Italy, France, and the USA. These results agree with archaeological and historical evidence that separate modern almond dissemination into four phases: Asiatic, Mediterranean, Californian, and southern hemisphere. In total, we found 13 independent QTLs for nut weight, crack-out percentage, double kernels percentage, and blooming time. Of the 13 QTLs found, only one had an additive effect. Through candidate gene analysis, we proposed Prudul26A013473 as a candidate gene responsible for the main QTL found in crack-out percentage, Prudul26A012082 and Prudul26A017782 as candidate genes for the QTLs found in double kernels percentage, and Prudul26A000954 as a candidate gene for the QTL found in blooming time. Our study enhances our knowledge of almond dissemination history and will have a great impact on almond breeding

Combining ecophysiological modelling and quantitative trait locus analysis to identify key elementary processes underlying tomato fruit sugar concentration

A mechanistic model predicting the accumulation of tomato fruit sugars was developed in order (i) to dissect the relative influence of three underlying processes: assimilate supply (S), metabolic transformation of sugars into other compounds (M), and dilution by water uptake (D); and (ii) to estimate the genetic variability of S, M, and D. The latter was estimated in a population of 20 introgression lines derived from the introgression of a wild tomato species (Solanum chmielewskii) into S. lycopersicum, grown under two contrasted fruit load conditions. Low load systematically decreased D in the whole population, while S and M were targets of genotype×fruit load interactions. The sugar concentration positively correlated to S and D when the variation was due to genetic introgressions, while it positively correlated to S and M when the variation was due to changes in fruit load. Co-localizations between quantitative trait loci (QTLs) for sugar concentration and QTLs for S, M, and D allowed hypotheses to be proposed on the processes putatively involved at the QTLs. Among the five QTLs for sugar concentration, four co-localized with QTLs for S, M, and D with similar allele effects. Moreover, the processes underlying QTLs for sugar accumulation changed according to the fruit load condition. Finally, for some genotypes, the processes underlying sugar concentration compensated in such a way that they did not modify the sugar concentration. By uncoupling genetic from physiological relationships between processes, these results provide new insights into further understanding of tomato fruit sugar accumulation

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 henotypes. 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.info:eu-repo/semantics/publishedVersio