Comparison of Marker-based Pairwise Relatedness Estimators on a Pedigreed Plant Population

Several estimators have been proposed that use molecular marker data to infer the degree of relatedness for pairs of individuals. The objective of this study was to evaluate the performance of seven estimators when applied to marker data of a set of 33 key individuals from a large complex apple pedigree. The evaluation considered different scenarios of allele frequencies and different numbers of marker loci. The method of moments estimators were Similarity, Queller-Goodknight, Lynch-Ritland and Wang. The maximum likelihood estimators were Thompson, Anderson-Weir and Jacquard. The pedigree-based coancestry coefficients were taken as the point of reference in calculating correlations and root mean square error (RMSE). The marker data comprised 86 multi-allelic SSR markers on 17 linkage groups, covering 11 Morgans. Additionally, we simulated 10 datasets conditional on the real pedigree to support the results on the real dataset. None of the estimators outperformed the others. Knowledge of allele frequencies appeared to be the most influential, i.e., the highest correlations and lowest RMSE were found when frequencies from the founder population were available. When equal allele frequencies were used, all estimators resulted in very similar, but on average lower, correlations. The use of allele frequencies estimated from the set of 33 individuals gave, on average, the poorest results. The maximum likelihood estimators and the Lynch-Ritland estimator were the most sensitive to allele frequencies. The results from the simulation study fully supported the trends in results of the real dataset. This study indicated that high correlations (up to 0.90) and small RMSE (below 0.03), may be obtained when population allelic frequencies are available. In this scenario, the performances of the various estimators were similar, but seemed to favor the maximum likelihood estimators. In the absence of reliable allele frequencies the method of moments estimators were shown to be more robust. The number of marker loci influenced the average performance of the estimators; however, the ranking was not affected. Correlations up to 0.80 were obtained when two markers per chromosome and appropriate allele frequencies were available. Adding more markers to the current dataset may lead to marginal improvements

Assessment of allelic diversity in intron-containing Mal d 1 genes and their association to apple allergenicity

<p>Abstract</p> <p>Background</p> <p>Mal d 1 is a major apple allergen causing food allergic symptoms of the oral allergy syndrome (OAS) in birch-pollen sensitised patients. The <it>Mal d 1 </it>gene family is known to have at least 7 intron-containing and 11 intronless members that have been mapped in clusters on three linkage groups. In this study, the allelic diversity of the seven intron-containing <it>Mal d 1 </it>genes was assessed among a set of apple cultivars by sequencing or indirectly through pedigree genotyping. Protein variant constitutions were subsequently compared with <b>S</b>kin <b>P</b>rick <b>T</b>est (SPT) responses to study the association of deduced protein variants with allergenicity in a set of 14 cultivars.</p> <p>Results</p> <p>From the seven intron-containing <it>Mal d 1 </it>genes investigated, <it>Mal d 1.01 </it>and <it>Mal d 1.02 </it>were highly conserved, as nine out of ten cultivars coded for the same protein variant, while only one cultivar coded for a second variant. <it>Mal d 1.04</it>, <it>Mal d 1.05 </it>and <it>Mal d 1.06 A, B </it>and <it>C </it>were more variable, coding for three to six different protein variants. Comparison of <it>Mal d 1 </it>allelic composition between the high-allergenic cultivar Golden Delicious and the low-allergenic cultivars Santana and Priscilla, which are linked in pedigree, showed an association between the protein variants coded by the <it>Mal d 1.04 </it>and <it>-1.06A </it>genes (both located on linkage group 16) with allergenicity. This association was confirmed in 10 other cultivars. In addition, <it>Mal d 1.06A </it>allele dosage effects associated with the degree of allergenicity based on prick to prick testing. Conversely, no associations were observed for the protein variants coded by the <it>Mal d 1.01 </it>(on linkage group 13), -<it>1.02</it>, -<it>1.06B, -1.06C </it>genes (all on linkage group 16), nor by the <it>Mal d 1.05 </it>gene (on linkage group 6).</p> <p>Conclusion</p> <p>Protein variant compositions of Mal d 1.04 and -1.06A and, in case of <it>Mal d 1.06A</it>, allele doses are associated with the differences in allergenicity among fourteen apple cultivars. This information indicates the involvement of qualitative as well as quantitative factors in allergenicity and warrants further research in the relative importance of quantitative and qualitative aspects of <it>Mal d 1 </it>gene expression on allergenicity. Results from this study have implications for medical diagnostics, immunotherapy, clinical research and breeding schemes for new hypo-allergenic cultivars.</p

Detecting QTLs and putative candidate genes involved in budbreak and flowering time in an apple multiparental population

UMR AGAP - équipe AFEF - Architecture et fonctionnement des espèces fruitièresIn temperate trees, growth resumption in spring time results from chilling and heat requirements, and is an adaptive trait under global warming. Here, the genetic determinism of budbreak and flowering time was deciphered using five related full-sib apple families. Both traits were observed over 3 years and two sites and expressed in calendar and degree-days. Best linear unbiased predictors of genotypic effect or interaction with climatic year were extracted from mixed linear models and used for quantitative trait locus (QTL) mapping, performed with an integrated genetic map containing 6849 single nucleotide polymorphisms (SNPs), grouped into haplotypes, and with a Bayesian pedigree-based analysis. Four major regions, on linkage group (LG) 7, LG10, LG12, and LG9, the latter being the most stable across families, sites, and years, explained 5.6–21.3% of trait variance. Co-localizations for traits in calendar days or growing degree hours (GDH) suggested common genetic determinism for chilling and heating requirements. Homologs of two major flowering genes, AGL24 and FT, were predicted close to LG9 and LG12 QTLs, respectively, whereas Dormancy Associated MADs-box (DAM) genes were near additional QTLs on LG8 and LG15. This suggests that chilling perception mechanisms could be common among perennial and annual plants. Progenitors with favorable alleles depending on trait and LG were identified and could benefit new breeding strategies for apple adaptation to temperature increase

Hyperferritinaemia in Dengue Virus Infected Patients Is Associated with Immune Activation and Coagulation Disturbances

During a dengue outbreak on the Caribbean island Aruba, highly elevated levels of ferritin were detected in dengue virus infected patients. Ferritin is an acute-phase reactant and hyperferritinaemia is a hallmark of diseases caused by extensive immune activation, such as haemophagocytic lymphohistiocytosis. The aim of this study was to investigate whether hyperferritinaemia in dengue patients was associated with clinical markers of extensive immune activation and coagulation disturbances.Levels of ferritin, standard laboratory markers, sIL-2R, IL-18 and coagulation and fibrinolytic markers were determined in samples from patients with uncomplicated dengue in Aruba. Levels of ferritin were significantly increased in dengue patients compared to patients with other febrile illnesses. Moreover, levels of ferritin associated significantly with the occurrence of viraemia. Hyperferritinaemia was also significantly associated with thrombocytopenia, elevated liver enzymes and coagulation disturbances. The results were validated in a cohort of dengue virus infected patients in Brazil. In this cohort levels of ferritin and cytokine profiles were determined. Increased levels of ferritin in dengue virus infected patients in Brazil were associated with disease severity and a pro-inflammatory cytokine profile.Altogether, we provide evidence that ferritin can be used as a clinical marker to discriminate between dengue and other febrile illnesses. The occurrence of hyperferritinaemia in dengue virus infected patients is indicative for highly active disease resulting in immune activation and coagulation disturbances. Therefore, we recommend that patients with hyperferritinaemia are monitored carefully

Diversity arrays technology (DArT) markers in apple for genetic linkage maps

Diversity Arrays Technology (DArT) provides a high-throughput whole-genome genotyping platform for the detection and scoring of hundreds of polymorphic loci without any need for prior sequence information. The work presented here details the development and performance of a DArT genotyping array for apple. This is the first paper on DArT in horticultural trees. Genetic mapping of DArT markers in two mapping populations and their integration with other marker types showed that DArT is a powerful high-throughput method for obtaining accurate and reproducible marker data, despite the low cost per data point. This method appears to be suitable for aligning the genetic maps of different segregating populations. The standard complexity reduction method, based on the methylation-sensitive PstI restriction enzyme, resulted in a high frequency of markers, although there was 52–54% redundancy due to the repeated sampling of highly similar sequences. Sequencing of the marker clones showed that they are significantly enriched for low-copy, genic regions. The genome coverage using the standard method was 55–76%. For improved genome coverage, an alternative complexity reduction method was examined, which resulted in less redundancy and additional segregating markers. The DArT markers proved to be of high quality and were very suitable for genetic mapping at low cost for the apple, providing moderate genome coverage

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Analysis of genetic control of fruit size in apple using both multiple, pedigree-related and single full-sib families

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PediHaplotyper : software for consistent assignment of marker haplotypes in pedigrees

In the study of large outbred pedigrees with many founders, individual bi-allelic markers, such as SNP markers, carry little information. After phasing the marker genotypes, multi-allelic loci consisting of groups of closely linked markers can be identified, which are called “haploblocks”. Here, we describe PediHaplotyper, an R package capable of assigning consistent alleles to such haploblocks, allowing for missing and incorrect SNP data. These haploblock genotypes are much easier to interpret by the human investigator than the original SNP data and also allow more efficient QTL analyses that require less memory and computation time.</p