Estimating genomic breeding values from the QTL-MAS Workshop Data using a single SNP and haplotype/IBD approach

Two models that estimated genomic estimated breeding values (EBVs) were applied: one used constructed haplotypes (based on alleles of 20 markers) and IBD matrices, another used single SNP regression. Both models were applied with or without polygenic effect. A fifth model included only polygenic effects and no genomic information. The models needed to estimate 366,959 effects for the haplotype/IBD approach, but only 11,850 effects for the single SNP approach. The four genomic models identified 11 to 14 regions that had a posterior QTL probability >0.1. Accuracies of genomic selection breeding values for animals in generations 4¿6 ranged from 0.84 to 0.87 (haplotype/IBD vs. SNP). It can be concluded that including a polygenic effect in the genomic model had no effect on the accuracy of the total EBVs or prediction of the QTL positions. The SNP model yielded slightly higher accuracies for the total EBVs, while both models were able to detect nearly all QTL that explained at least 0.5% of the total phenotypic varianc

Comparison of potato varieties between seasons and their potential for acrylamide formation

BACKGROUND: Acrylamide is a probable human carcinogen produced during food preparation, including frying of potato products. The aim of this study was to investigate the impact of seasonal variation on tuber composition and its acrylamide generation potential. RESULTS: The chemical composition of potato varieties used respectively for French fry (Bintje and Ramos) and crisp (Lady Rosetta and Saturna) production was studied throughout a storage period of 9 months during two growing seasons (2003 and 2004), in addition to their acrylamide generation potential during preparation of French fries. A significant impact of variable climatological conditions on the reducing sugar, dry matter, total free amino acid and free asparagine contents of tubers was observed. Exceptionally warm summers gave rise to a lower reducing sugar content (expressed on a dry matter basis) and thus a lower susceptibility to acrylamide generation during frying. CONCLUSION: It cannot be excluded that potato growers and the potato-processing industry are confronted with some harvests that are more prone to acrylamide generation than others owing to climatological variability, thus confirming the importance of a multifactorial approach to mitigate acrylamide generation in potato products.</p

Across population genomic prediction scenarios in which Bayesian variable selection outperforms GBLUP

<p>Background: The use of information across populations is an attractive approach to increase the accuracy of genomic prediction for numerically small populations. However, accuracies of across population genomic prediction, in which reference and selection individuals are from different populations, are currently disappointing. It has been shown for within population genomic prediction that Bayesian variable selection models outperform GBLUP models when the number of QTL underlying the trait is low. Therefore, our objective was to identify across population genomic prediction scenarios in which Bayesian variable selection models outperform GBLUP in terms of prediction accuracy. In this study, high density genotype information of 1033 Holstein Friesian, 105 Groningen White Headed, and 147 Meuse-Rhine-Yssel cows were used. Phenotypes were simulated using two changing variables: (1) the number of QTL underlying the trait (3000, 300, 30, 3), and (2) the correlation between allele substitution effects of QTL across populations, i.e. the genetic correlation of the simulated trait between the populations (1.0, 0.8, 0.4). Results: The accuracy obtained by the Bayesian variable selection model was depending on the number of QTL underlying the trait, with a higher accuracy when the number of QTL was lower. This trend was more pronounced for across population genomic prediction than for within population genomic prediction. It was shown that Bayesian variable selection models have an advantage over GBLUP when the number of QTL underlying the simulated trait was small. This advantage disappeared when the number of QTL underlying the simulated trait was large. The point where the accuracy of Bayesian variable selection and GBLUP became similar was approximately the point where the number of QTL was equal to the number of independent chromosome segments (M _e) across the populations. Conclusion: Bayesian variable selection models outperform GBLUP when the number of QTL underlying the trait is smaller than M _e. Across populations, M _e is considerably larger than within populations. So, it is more likely to find a number of QTL underlying a trait smaller than M _e across populations than within population. Therefore Bayesian variable selection models can help to improve the accuracy of across population genomic prediction.</p

Selective medium for culture of Mycoplasma hyopneumoniae

The fastidious porcine respiratory pathogen Mycoplasma hyopneumoniae has proven difficult to culture since it was first isolated in 1965. A reliable solid medium has been particularly challenging. Moreover, clinical and pathological samples often contain the fast-growing M. hyorhinis which contaminates and overgrows M. hyopneumoniae in primary culture. The aim of this study was to optimise the culture medium for recovery of M. hyopneumoniae and to devise a medium for selection of M. hyopneumoniae from clinical samples also containing M. hyorhinis. The solid medium devised by Niels Friis was improved by use of Purified agar and incorporation of DEAE-dextran. Addition of glucose or neutralization of acidity in liquid medium with NaOH did not improve the final yield of viable organisms or alter the timing of peak viability. Analysis of the relative susceptibility of M. hyopneumoniae and M. hyorhinis strains to four antimicrobials showed that M. hyopneumoniae is less susceptible than M. hyorhinis to kanamycin. This was consistent in all UK and Danish strains tested. A concentration of 2 μg/ml of kanamycin selectively inhibited the growth of all M. hyorhinis tested, while M. hyopneumoniae was able to grow. This forms the basis of an effective selective culture medium for M. hyopneumoniae.(Résumé d'auteur

CEReS -Co-processing of Coal Mine & Electronic Wastes: Novel Resources for a Sustainable Future

International audienceMany coal mines produce waste which causes acid mine drainage (AMD) potentially resulting in severe environmental damage. This drainage can be treated, but most wastes will continue to produce such drainage for hundreds of years. Therefore, longer term, permanent solutions are needed. At the same time, the pace of technological development means most electrical and electronic equipment becomes obsolete within a matter of years. This results in the generation of vast and growing quantities of electronic waste (e-waste) every year. Where this cannot be recycled, it must be discarded. CEReS was a 3.2 M€ RFCS-funded project comprising eight partners from five countries. It targeted the development of a co-processing approach to treat these waste streams to produce metals and other valuable products, while eliminating their environmental impact. This brings together two waste streams from opposite ends of the supply chain (for which no alternative treatment option exists); turning each into a novel resource in a single, coherent 'grave-to-cradle' process. This industrial ecology approach is key to supporting a circular economy while securing the sustainable supply of critical raw materials. The project successfully elaborated a novel co-processing flow-sheet comprising: (i) the accelerated weathering of AMD-generating coal production wastes to generate a biolixiviant; (ii) the pyrolysis and catalytic cracking of low-grade PCBs to produce hydrocarbon fuel, a halogen brine a Cu-rich char; (iii) the leaching of base metals from the char using the biolixiviant; (iv) the reuse of the stabilised coal wastes; and (v) the recovery of valuable metal while concentrating precious and critical metals into enriched substrates. These individual process units were demonstrated individually at lab-pilot scale. The data were then used to validate the entire flow-sheet in an integrated process simulator. Finally an LCA approach was used to demonstrate the environmental benefits of the CEReS process over the status quo

Sensitivity of methods for estimating breeding values using genetic markers to the number of QTL and distribution of QTL variance

The objective of this simulation study was to compare the effect of the number of QTL and distribution of QTL variance on the accuracy of breeding values estimated with genomewide markers (MEBV). Three distinct methods were used to calculate MEBV: a Bayesian Method (BM), Least Angle Regression (LARS) and Partial Least Square Regression (PLSR). The accuracy of MEBV calculated with BM and LARS decreased when the number of simulated QTL increased. The accuracy decreased more when QTL had different variance values than when all QTL had an equal variance. The accuracy of MEBV calculated with PLSR was affected neither by the number of QTL nor by the distribution of QTL variance. Additional simulations and analyses showed that these conclusions were not affected by the number of individuals in the training population, by the number of markers and by the heritability of the trait. Results of this study show that the effect of the number of QTL and distribution of QTL variance on the accuracy of MEBV depends on the method that is used to calculate MEBV

Introducing ribosomal tandem repeat barcoding for fungi

Sequence comparison and analysis of the various ribosomal genetic markers are the dominant molecular methods for identification and description of fungi. However, new environmental fungal lineages known only from DNA data reveal significant gaps in our sampling of the fungal kingdom in terms of both taxonomy and marker coverage in the reference sequence databases. To facilitate the integration of reference data from all of the ribosomal markers, we present three sets of general primers that allow for amplification of the complete ribosomal operon from the ribosomal tandem repeats. The primers cover all ribosomal markers: ETS, SSU, ITS1, 5.8S, ITS2, LSU and IGS. We coupled these primers successfully with third-generation sequencing (PacBio and Nanopore sequencing) to showcase our approach on authentic fungal herbarium specimens (Basidiomycota), aquatic chytrids (Chytridiomycota) and a poorly understood lineage of early diverging fungi (Nephridiophagidae). In particular, we were able to generate high-quality reference data with Nanopore sequencing in a high-throughput manner, showing that the generation of reference data can be achieved on a regular desktop computer without the involvement of any large-scale sequencing facility. The quality of the Nanopore generated sequences was 99.85%, which is comparable with the 99.78% accuracy described for Sanger sequencing. With this work, we hope to stimulate the generation of a new comprehensive standard of ribosomal reference data with the ultimate aim to close the huge gaps in our reference datasets

Genomic breeding value prediction and QTL mapping of QTLMAS2011 data using Bayesian and GBLUP methods

Background: The goal of this study was to apply Bayesian and GBLUP methods to predict genomic breeding values (GEBV), map QTL positions and explore the genetic architecture of the trait simulated for the 15 QTL-MAS workshop. Methods. Three methods with models considering dominance and epistasis inheritances were used to fit the data: (i) BayesB with a proportion = 0.995 of SNPs assumed to have no effect, (ii) BayesC, where is considered as unknown, and (iii) GBLUP, which directly fits animal genetic effects using a genomic relationship matrix. Results: BayesB, BayesC and GBLUP with various fitted models detected 6, 5, and 4 out of 8 simulated QTL, respectively. All five additive QTL were detected by Bayesian methods. When two QTL were in either coupling or repulsion phase, GBLUP only detected one of them and missed the other. In addition, GBLUP yielded more false positives. One imprinted QTL was detected by BayesB and GBLUP despite that only additive gene action was assumed. This QTL was missed by BayesC. None of the methods found two simulated additive-by-additive epistatic QTL. Variance components estimation correctly detected no evidence for dominance gene-action. Bayesian methods predicted additive genetic merit more accurately than GBLUP, and similar accuracies were observed between BayesB and BayesC. Conclusions: Bayesian methods and GBLUP mapped QTL to similar chromosome regions but Bayesian methods gave fewer false positives. Bayesian methods can be superior to GBLUP in GEBV prediction when genomic architecture is unknown