Comparing genomic prediction accuracy from purebred,crossbred and combined purebred and crossbred reference populations in sheep

Background

The accuracy of genomic prediction depends largely on the number of animals with phenotypes and genotypes. In some industries, such as sheep and beef cattle, data are often available from a mixture of breeds, multiple strains within a breed or from crossbred animals. The objective of this study was to compare the accuracy of genomic prediction for several economically important traits in sheep when using data from purebreds, crossbreds or a combination of those in a reference population.

Methods

The reference populations were purebred Merinos, crossbreds of Border Leicester (BL), Poll Dorset (PD) or White Suffolk (WS) with Merinos and combinations of purebred and crossbred animals. Genomic breeding values (GBV) were calculated based on genomic best linear unbiased prediction (GBLUP), using a genomic relationship matrix calculated based on 48 599 Ovine SNP (single nucleotide polymorphisms) genotypes. The accuracy of GBV was assessed in a group of purebred industry sires based on the correlation coefficient between GBV and accurate estimated breeding values based on progeny records.

Results

The accuracy of GBV for Merino sires increased with a larger purebred Merino reference population, but decreased when a large purebred Merino reference population was augmented with records from crossbred animals. The GBV accuracy for BL, PD and WS breeds based on crossbred data was the same or tended to decrease when more purebred Merinos were added to the crossbred reference population. The prediction accuracy for a particular breed was close to zero when the reference population did not contain any haplotypes of the target breed, except for some low accuracies that were obtained when predicting PD from WS and vice versa.

Conclusions

This study demonstrates that crossbred animals can be used for genomic prediction of purebred animals using 50 k SNP marker density and GBLUP, but crossbred data provided lower accuracy than purebred data. Including data from distant breeds in a reference population had a neutral to slightly negative effect on the accuracy of genomic prediction. Accounting for differences in marker allele frequencies between breeds had only a small effect on the accuracy of genomic prediction from crossbred or combined crossbred and purebred reference populations.     

Bioenergetic properties of human sarcoma cells help define sensitivity to metabolic inhibitors

Sarcomas represent a diverse group of malignancies with distinct molecular and pathological features. A better understanding of the alterations associated with specific sarcoma subtypes is critically important to improve sarcoma treatment. Renewed interest in the metabolic properties of cancer cells has led to an exploration of targeting metabolic dependencies as a therapeutic strategy. In this study, we have characterized key bioenergetic properties of human sarcoma cells in order to identify metabolic vulnerabilities between sarcoma subtypes. We have also investigated the effects of compounds that inhibit glycolysis or mitochondrial respiration, either alone or in combination, and examined relationships between bioenergetic parameters and sensitivity to metabolic inhibitors. Using 2-deoxy-D-glucose (2-DG), a competitive inhibitor of glycolysis, oligomycin, an inhibitor of mitochondrial ATP synthase, and metformin, a widely used anti-diabetes drug and inhibitor of complex I of the mitochondrial respiratory chain, we evaluated the effects of metabolic inhibition on sarcoma cell growth and bioenergetic function. Inhibition of glycolysis by 2-DG effectively reduced the viability of alveolar rhabdomyosarcoma cells vs. embryonal rhabdomyosarcoma, osteosarcoma, and normal cells. Interestingly, inhibitors of mitochondrial respiration did not significantly affect viability, but were able to increase sensitivity of sarcomas to inhibition of glycolysis. Additionally, inhibition of glycolysis significantly reduced intracellular ATP levels, and sensitivity to 2-DG-induced growth inhibition was related to respiratory rates and glycolytic dependency. Our findings demonstrate novel relationships between sarcoma bioenergetics and sensitivity to metabolic inhibitors, and suggest that inhibition of metabolic pathways in sarcomas should be further investigated as a potential therapeutic strategy.     

The small-subunit ribosomal RNA gene sequences from the hypotrichous ciliates Oxytricha nova and Stylonychia pustulata

We have determined the complete nucleotide sequence of the small- subunit ribosomal RNA genes for the ciliate protozoans Stylonychia pustulata and Oxytricha nova. The sequences are homologous and sufficiently similar that these organisms must be closely related. In a phylogeny inferred from comparisons of several eukaryotic small-subunit ribosomal RNAs, the divergence of the ciliates from the eukaryotic line of descent is seen to coincide with the radiation of the plants, the animals, and the fungi. This radiation is preceded by the divergence of the slime mold, Dictyostelium discoideum.      

Effect of trapidil derivative AR 12456 on intracellular cholesterol homeostasis in human hepatoma cell line Hep G2

The effect of trapidil derivative AR12456 on intracellular cholesterol metabolism was investigated in human hepatoma cell line HepG2. AR12456 enhanced the uptake and degradation of¹²⁵I-LDL in a dose-dependent manner. The drug inhibited cholesterol synthesis and esterification without affecting cellular cholesterol content and bile acid synthesis; cholesterol efflux was slightly increased. These results show that the inhibition of cholesterol synthesis together with the enhanced expression of LDL receptors may partially explain the hypocholesterolemic activity of compound AR12456.     

Improved titanium dioxide enrichment of phosphopeptides from HeLa cells and high confident phosphopeptide identification by cross-validation of MS/MS and MS/MS/MS spectra

Enrichment is essential for phosphoproteome analysis because phosphorylated proteins are usually present in cells in low abundance. Recently, titanium dioxide (TiO2) has been demonstrated to enrich phosphopeptides from simple peptide mixtures with high specificity; however, the technology has not been optimized. In the present study, significant non-specific bindings were observed when proteome samples were applied to TiO2 columns. Column wash with an NH4Glu solution after loading peptide mixtures significantly increased the efficiency of TiO2 phosphopeptide enrichment with a recovery of up to 84%. Also, for proteome samples, more than a 2-fold increase in unique phosphopeptide identifications has been achieved. The use of NH4Glu for a TiO2 column wash does not significantly reduce the phosphopeptide recovery. A total of 858 phosphopeptides corresponding to 1034 distinct phosphosites has been identified from HeLa cells using the improved TiO2 enrichment procedure in combination with data-dependent neutral loss nano-RPLC-MS2-MS3 analysis. While 41 and 35% of the phosphopeptides were identified only by MS2 and MS3, respectively, 24% was identified by both MS2 and MS3. Cross-validation of the phosphopeptide assignment by MS2 and MS3 scans resulted in the highest confidence in identification (99.5%). Many phosphosites identified in this study appear to be novel, including sites from antigen Ki-67, nucleolar phosphoprotein p130, and Treacle protein. The study also indicates that evaluation of confidence levels for phosphopeptide identification via the reversed sequence database searching strategy might underestimate the false positive rate.     

Mapping carcass and meat quality QTL on Sus Scrofa chromosome 2 in commercial finishing pigs

Quantitative trait loci (QTL) affecting carcass and meat quality located on SSC2 were identified using variance component methods. A large number of traits involved in meat and carcass quality was detected in a commercial crossbred population: 1855 pigs sired by 17 boars from a synthetic line, which where homozygous (A/A) for IGF2. Using combined linkage and linkage disequilibrium mapping (LDLA), several QTL significantly affecting loin muscle mass, ham weight and ham muscles (outer ham and knuckle ham) and meat quality traits, such as Minolta-L* and -b*, ultimate pH and Japanese colour score were detected. These results agreed well with previous QTL-studies involving SSC2. Since our study is carried out on crossbreds, different QTL may be segregating in the parental lines. To address this question, we compared models with a single QTL-variance component with models allowing for separate sire and dam QTL-variance components. The same QTL were identified using a single QTL variance component model compared to a model allowing for separate variances with minor differences with respect to QTL location. However, the variance component method made it possible to detect QTL segregating in the paternal line (e.g. HAMB), the maternal lines (e.g. Ham) or in both (e.g. pHu). Combining association and linkage information among haplotypes improved slightly the significance of the QTL compared to an analysis using linkage information only.     

Adverse environmental conditions influence age-related innate immune responsiveness

Background-  

The innate immune system plays an important role in the recognition and induction of protective responses against infectious pathogens, whilst there is increasing evidence for a role in mediating chronic inflammatory diseases at older age. Despite indications that environmental conditions can influence the senescence process of the adaptive immune system, it is not known whether the same holds true for the innate immune system. Therefore we studied whether age-related innate immune responses are similar or differ between populations living under very diverse environmental conditions.     

Patterns of inflammation and the use of reversibility testing in smokers with airway complaints

Background

Although both smoking and respiratory complaints are very common, tools to improve diagnostic accuracy are scarce in primary care. This study aimed to reveal what inflammatory patterns prevail in clinically established diagnosis groups, and what factors are associated with eosinophilia.

Method

Induced sputum and blood plasma of 59 primary care patients with COPD (n = 17), asthma (n = 11), chronic bronchitis (CB, n = 14) and smokers with no respiratory complaints ('healthy smokers', n = 17) were collected, as well as lung function, smoking history and clinical work-up. Patterns of inflammatory markers per clinical diagnosis and factors associated with eosinophilia were analyzed by multiple regression analyses, the differences expressed in odds ratios (OR) with 95% confidence intervals.

Results

Multivariately, COPD was significantly associated with raised plasma-LBP (OR 1.2 [1.04–1.37]) and sTNF-R55 in sputum (OR 1.01 [1.001–1.01]), while HS expressed significantly lowered plasma-LBP (OR 0.8 [0.72–0.95]). Asthma was characterized by higher sputum eosinophilic counts (OR 1.3 [1.05–1.54]), while CB showed a significantly higher proportion of sputum lymphocytic counts (OR 1.5 [1.12–1.9]). Sputum eosinophilia was significantly associated with reversibility after adjusting for smoking, lung function, age, gender and allergy.

Conclusion

Patterns of inflammatory markers in a panel of blood plasma and sputum cells and mediators were discernable in clinical diagnosis groups of respiratory disease. COPD and so-called healthy smokers showed consistent opposite associations with plasma LBP, while chronic bronchitics showed relatively predominant lymphocytic inflammation compared to other diagnosis groups. Only sputum eosinophilia remained significantly associated with reversibility across the spectrum of respiratory disease in smokers with airway complaints.     

An efficient model development strategy for bioprocesses based on neural networks in macroscopic balances: Part II

There is a need for efficient modeling strategies which quickly lead to reliable mathematical models that can be applied for design and optimization of (bio)-chemical processes. The serial gray box modeling strategy is potentially very efficient because no detailed knowledge is needed to construct the white box part of the model and because covenient black box modeling techniques like neural networks can be used for the black box part of the model. This paper shows for a typical biochemical conversion how the serial gray box modeling strategy can be applied efficiently to obtain a model with good frequency extrapolation properties. Models with good frequency extrapolation properties can be applied under dynamic conditions that were not present during the identification experiments. For a given application domain of a model, this property can be used to considerably reduce the number of identification experiments. The serial gray box modeling strategy is demonstrated to be successful for the modeling of the enzymatic conversion of penicillin G In the concentration range of 10-100 mM and temperature range of 298-335 K. Frequency extrapolation is shown by using only constant temperatures in the (batch) identification experiments, while the model can be used reliable with varying temperatures during the (batch) validation experiments. No reliable frequency extrapolation properties could be obtained for a black box model, and for a more knowledge-driven white box model reliable frequency extrapolation properties could only be obtained by incorporating more knowledge in the model. Copyright 1999 John Wiley & Sons, Inc.