Biology subjects

Durel, C.-E.

Publications and source records attributed to Durel, C.-E..

8 recordsLinked to original sources

bioRxiv2026

Reduced confidence intervals and novel candidate genes for quantitative trait loci associated with apple scab resistance in Malus domestica

Apple scab, caused by Venturia inaequalis, remains one of the most damaging diseases in apple orchards, driving intensive pesticide use worldwide. Reducing this dependence requires the deployment of durable resistance, ideally through the combination of major resistance genes (R genes) with quantitative trait loci (QTL) that confer partial and potentially complementary protection. Yet, few apple scab QTLs have been functionally validated, and their underlying mechanisms remain largely unresolved. Here, we refined and functionally described, with transcriptomic data, five resistance QTLs in a biparental population of 1,970 individuals derived from the cross TN 10-8 x Fiesta. Using 43 newly developed KASP markers, QTL locations were substantially precised through high-resolution genotyping and phenotyping with two V. inaequalis isolates exhibiting contrasting virulence. Four QTL (qT1, qF11, qF17, qT13) were validated, while qF3 was not confirmed. Transcriptomic data comparison revealed the expression of candidate genes within the narrowed intervals, including receptor-like proteins in qT1, and RNAi- and signaling-related genes in qF11 and qF17, suggesting a diversified and complementary defense network. These findings refine the genetic architecture of apple scab resistance and suppose the existence of shared molecular pathways between major R gene, such as the well-described Rvi6 gene, and quantitative resistance, with for instance the QTL qT1. The identified loci and markers provide robust tools for marker-assisted and genomic breeding aimed at developing apple cultivars with complementary and potentially durable resistance pathways.

plant biology↗

bioRxiv2025

Gene flow from the European wild apple and selection shaped the domesticated apple (Malus domestica Borkh.) genome

How selection and demography shape genomes of long-lived crops remains largely unresolved. Using apple (Malus domestica) as a model, we integrate 218 whole genomes (68 cultivated dessert/cider; 150 wild: M. sieversii, M. orientalis, M. sylvestris), RNA-seq, and a flowering-time GWAS to resolve how these forces forged the cultivated apple genome. Despite weak neutral differentiation and widespread admixture, dessert and cider apples form distinct gene pools that derive primarily from M. sieversii-M. orientalis rather than European M. sylvestris. We find no evidence of a strong domestication bottleneck, as expected in perennials. Demography-aware selection scans reveal largely non-overlapping targets: dessert shows more hard sweeps at genes linked to fruit quality, disease resistance, and flowering, whereas cider shows proportionally more soft sweeps and balancing selection; RNA-seq differential expression supports these candidates. Wild-to-crop introgression from M. sylvestris is extensive but heterogeneous by context: some introgressed tracts concentrate in hard-sweep regions and approach fixation (consistent with rapid, targeted uptake), whereas others persist at intermediate frequencies with soft-sweep signatures (consistent with diffuse, recurrent introgression of adaptive alleles). Extending to the phenotype, the lead chromosome 9 flowering-time association lies within an introgressed segment near a transposable element and is separated from sweep peaks, consistent with regulatory/polygenic control. Cultivated apples carry a lower predicted deleterious load than wild relatives. Together, these results provide one of the most comprehensive population genomic portraits of a perennial fruit tree domestication, clarifying how selection and adaptive introgression jointly shaped the cultivated apple genome architecture and yielding actionable targets for breeding and conservation. Significance statementPerennial crops are underexplored compared to annuals, leaving open the question of how selection, gene flow, and demography shape their genomes. Using the apple tree (Malus domestica), we analyzed 218 genomes, along with expression and trait data. Despite weak genome-wide differences, dessert and cider apples form distinct gene pools. Widespread gene flow from the European wild apple supplied adaptive alleles, with contrasting dynamics: in cider, a few introgressed DNA segments rose rapidly; in dessert, many variants shifted gradually. Cultivated apples also carry a lower predicted burden of harmful mutations than wild relatives. Together, these results redefine perennial domestication and pinpoint genomic targets to accelerate breeding and conservation.

genetics↗

bioRxiv2025

WISER: an innovative and efficient method for correcting population structure in omics-based prediction and selection

This work introduces WISER (whitening and successive least squares estimation refinement), an innovative and efficient method designed to enhance phenotype estimation by addressing population structure. WISER outperforms traditional methods such as least squares (LS) means and best linear unbiased prediction (BLUP) in phenotype estimation, offering a more accurate approach for omics-based selection and having the potential to improve association studies. Unlike existing approaches that correct for population structure, WISER provides a generalized framework applicable across diverse experimental setups, species, and omics datasets, including single nucleotide polymorphisms (SNPs), metabolomics, and near-infrared spectroscopy (NIRS) used as phenomic predictors. Central to WISER is the concept of whitening, a statistical transformation that removes correlations between variables and standardizes their variances. Within its framework, WISER extends classical methods that use eigen-information as fixed-effect covariates to correct for population structure, by relaxing their assumptions and implementing a true whitening matrix instead of a pseudo-whitening matrix. This approach corrects fixed effects (e.g., environmental effects) for the genetic covariance structure embedded within the experimental design, thereby minimizing confounding factors between fixed and genetic effects. To support its practical application, a user-friendly R package named wiser has been developed. The WISER method has been employed in analyses for genomic prediction and heritability estimation across four species and 33 traits using multiple datasets, including rice, maize, apple, and Scots pine. Results indicate that genomic predictive abilities based on WISER-estimated phenotypes consistently outperform the LS-means and BLUP approaches for phenotype estimation, regardless of the predictive model applied. This underscores WISERs potential to advance omics analyses and related research fields by capturing stronger genetic signals.

genetics↗

bioRxiv2025

WISER: an innovative and efficient method for correcting population structure in omics-based selection and association studies

This work introduces WISER (whitening and successive least squares estimation refinement), an innovative and efficient method designed to enhance phenotype estimation by addressing population structure. WISER outperforms traditional methods such as least squares (LS) means and best linear unbiased prediction (BLUP) in phenotype estimation, offering a more accurate approach for omics-based selection and association studies. Unlike existing approaches which correct for population structure, WISER offers a generalized framework that can be applied across diverse experimental setups, species, and omics datasets, such as single nucleotide polymorphisms (SNPs), near-infrared spectroscopy (NIRS), and metabolomics. Within its framework, WISER extends classical methods that use eigen-information as fixed-effect covariates to correct for population structure, by relaxing their assumptions and implementing a true whitening matrix instead of a pseudo-whitening matrix. This approach corrects fixed effects (e.g., environmental effects) for the genetic covariance structure embedded within the experimental design, thereby removing confounding factors between fixed and genetic effects. To support its practical application, a user-friendly R package named wiser has been developed. The WISER method has been employed in analyses for genomic prediction and heritability estimation across four species and 33 traits using multiple datasets, including rice, maize, apple, and Scots pine. Results indicate that genomic predictive abilities based on WISER-estimated phenotypes consistently outperform the LS-means and BLUP approaches for phenotype estimation, regardless of the predictive model applied. This underscores WISERs potential to advance omics analyses and related research fields by capturing stronger genetic signals.

genetics↗

bioRxiv2021

Combining genetic resources and elite material populations to improve the accuracy of genomic prediction in apple

Genomic selection is an attractive strategy for apple breeding that could reduce the length of breeding cycles. A possible limitation to the practical implementation of this approach lies in the creation of a training set large and diverse enough to ensure accurate predictions. In this study, we investigated the potential of combining two available populations, i.e. genetic resources and elite material, in order to obtain a large training set with a high genetic diversity. We compared the predictive ability of genomic predictions within-population, across-population or when combining both populations, and tested a model accounting for population-specific marker effects in this last case. The obtained predictive abilities were moderate to high according to the studied trait and were always highest when the two populations were combined into a unique training set. We also investigated the potential of such a training set to predict hybrids resulting from crosses between the two populations, with a focus on the method to design the training set and the best proportion of each population to optimize predictions. The measured predictive abilities were very similar for all the proportions, except for the extreme cases where only one of the two populations was used in the training set, in which case predictive abilities could be lower than when using both populations. Using an optimization algorithm to choose the genotypes in the training set also led to higher predictive abilities than when the genotypes were chosen at random. Our results provide guidelines to initiate breeding programs that use genomic selection when the implementation of the training set is a limitation.

genomics↗

bioRxiv2020

Integration of Infinium and Axiom SNP array data in the outcrossing species Malus x domestica and causes for seemingly incompatible calls

BackgroundSingle nucleotide polymorphism (SNP) array technology has been increasingly used to generate large quantities of SNP data for use in genetic studies. As new arrays are developed to take advantage of new technology and of improved probe design using new genome sequence and panel data, a need to integrate data from different arrays and array platforms has arisen. This study was undertaken in view of our need for an integrated high-quality dataset of Illumina Infinium(R) 20K and Affymetrix Axiom(R) 480K SNP array data in apple (Malus x domestica). In this study, we qualify and quantify the compatibility of SNP calling, defined as SNP calls that are both accurate and concordant, across both arrays by two approaches. First, the concordance of SNP calls was evaluated using a set of 417 duplicate individuals genotyped on both arrays starting from a set of 10,295 robust SNPs on the Infinium array. Next, the accuracy of the SNP calls was evaluated on additional germplasm (n=3,141) from both arrays using Mendelian inconsistent and consistent errors across thousands of pedigree links. While performing this work, we took the opportunity to evaluate reasons for probe failure and observed discordant SNP calls. ResultsConcordance among the duplicate individuals was on average of 97.1% across 10,295 SNPs. Of these SNPs, 35% had discordant call(s) that were further curated, leading to a final set of 8,412 (81.7%) SNPs that were deemed compatible. Compatibility was highly influenced by the presence of alternate probe binding locations and secondary polymorphisms. The impact of the latter was highly influenced by their number and proximity to the 3 end of the probe. ConclusionsThe Infinium and Axiom SNP array data were mostly compatible. However, data integration required intense data filtering and curation. This work resulted in a workflow and information that may be of use in other data integration efforts. Such an in-depth analysis of array concordance and accuracy as ours has not been previously described in literature and will be useful in future work on SNP array data integration and interpretation, and in probe/platform development.

genetics↗

bioRxiv2019

Pyrus Communis chromosome scale assembly

We report an improved assembly and scaffolding of the European pear (Pyrus communis L.) genome (referred to as BartlettDHv2.0), obtained using a combination of Pacific Biosciences RSII Long read sequencing (PacBio), Bionano optical mapping, chromatin interaction capture (Hi-C), and genetic mapping. A total of 496.9 million bases (Mb) corresponding to 97% of the estimated genome size were assembled into 494 scaffolds. Hi-C data and a high-density genetic map allowed us to anchor and orient 87% of the sequence on the 17 chromosomes of the pear genome. About 50% (247 Mb) of the genome consists of repetitive sequences. Comparison with previous assemblies of Pyrus communis and Pyrus x bretschneideri confirmed the presence of 37,445 protein-coding genes, which is 13% fewer than previously predicted.

bioinformatics↗

bioRxiv2019

Pseudo-chromosome length genome assembly of a double haploid ‘Bartlett’ pear (Pyrus communis L.)

We report an improved assembly and scaffolding of the European pear (Pyrus communis L.) genome (referred to as BartlettDHv2.0), obtained using a combination of Pacific Biosciences RSII Long read sequencing (PacBio), Bionano optical mapping, chromatin interaction capture (Hi-C), and genetic mapping. A total of 496.9 million bases (Mb) corresponding to 97% of the estimated genome size were assembled into 494 scaffolds. Hi-C data and a high-density genetic map allowed us to anchor and orient 87% of the sequence on the 17 chromosomes of the pear genome. About 50% (247 Mb) of the genome consists of repetitive sequences. Comparison with previous assemblies of Pyrus communis. and Pyrus x bretschneideri confirmed the presence of 37,445 protein-coding genes, which is 13% fewer than previously predicted.

plant biology↗