Interaction between calcofluor white and carbohydrates of alpha 1-acid glycoprotein.

Interactions between the fluorescent probe, calcofluor white, and human serum albumin (HSA) and alpha 1-acid glycoprotein (orosomucoid) are compared. The two proteins have comparable isoelectric points, but alpha 1-acid glycoprotein is highly glycosylated (40% of glycans by weight), while the serum albumin is not. Binding of calcofluor to the proteins induces an increase in both the fluorescence anisotropy and the fluorescence intensity of the fluorophore. Also, we found that the calcofluor exhibits a fluorescence emission with a maximum located at 432, 415 or 445 nm, respectively, in the absence of proteins, in the presence of HSA, and in the presence of alpha 1-acid glycoprotein. The stoichiometries of the calcofluor-serum albumin and calcofluor-alpha 1-acid glycoprotein complexes are 2:1 and 1:1, respectively. The association constants are 0.04 and 0.15 microM-1, respectively. The calcofluor does not interact with Lens culinaris agglutinin (LCA), although the protein has a hydrophobic site. Nevertheless, one cannot exclude that the binding of the fluorophore to the HSA is nonspecific. Our results, when compared with those obtained with calcofluor dissolved in the hydrophobic solvent isobutanol, and with the fluorescent probe, potassium 6-(p-toluidino)-2-naphthalenesulfonate (TNS), bound to alpha 1-acid glycoprotein, indicate that the emission of calcofluor bound to HSA occurs from a hydrophobic state, while that of calcofluor bound to alpha 1-acid glycoprotein occurs from a hydrophilic state. The fluorescence intensity of calcofluor decreases in the presence of carbohydrates isolated from alpha 1-acid glycoprotein, while it increases in the presence of alpha 1-cellulose. Thus, calcofluor interacts mainly with the glycan moiety of alpha 1-acid glycoprotein, and its fluorescence is sensitive to the secondary structure of the glycans.     

The development of ISSR-derived SCAR markers around the<Emphasis Type="Italic"> SEASONAL FLOWERING LOCUS</Emphasis> (<Emphasis Type="Italic">SFL</Emphasis>) in<Emphasis Type="Italic"> Fragaria vesca</Emphasis>

Fragaria vesca is a short-lived perennial with a seasonal-flowering habit. Seasonality of flowering is widespread in the Rosaceae and is also found in the majority of temperate polycarpic perennials. Genetic analysis has shown that seasonal flowering is controlled by a single gene in F. vesca, the SEASONAL FLOWERING LOCUS (SFL). Here, we report progress towards the marker-assisted selection and positional cloning of SFL, in which three ISSR markers linked to SFL were converted to locus-specific sequence-characterized amplified region (SCAR1–SCAR3) markers to allow large-scale screening of mapping progenies. We believe this is the first study describing the development of SCAR markers from ISSR profiles. The work also provides useful insight into the nature of polymorphisms generated by the ISSR marker system. Our results indicate that the ISSR polymorphisms originally detected were probably caused by point mutations in the positions targeted by primer anchors (causing differential PCR failure), by indels within the amplicon (leading to variation in amplicon size) and by internal sequence differences (leading to variation in DNA folding and so in band mobility). The cause of the original ISSR polymorphism was important in the selection of appropriate strategies for SCAR-marker development. The SCAR markers produced were mapped using a F. vesca f. vesca × F. vesca f. semperflorens testcross population. Marker SCAR2 was inseparable from the SFL, whereas SCAR1 mapped 3.0 cM to the north of the gene and SCAR3 1.7 cM to its south.Communicated by H. Nybom     

Clustering of T cell ligands on artificial APC membranes influences T cell activation and protein kinase C theta translocation to the T cell plasma membrane

T cell activation is associated with active clustering of relevant molecules in membrane microdomains defined as the supramolecular activation cluster. The contact area between these regions on the surface of T cells and APC is defined as the immunological synapse. It has been recently shown that preclustering of MHC-peptide complexes in membrane microdomains on the APC surface affects the efficiency of immune synapse formation and the related T cell activation. Disruption of such clusters may reduce the efficiency of stimulation. We describe here an entirely artificial system for Ag-specific, ex vivo stimulation of human polyclonal T cells (artificial APC (aAPC)). aAPC are based on artificial membrane bilayers containing discrete membrane microdomains encompassing T cell ligands (i.e., appropriate MHC-peptide complexes in association with costimulatory molecules). We show here that preclustering of T cell ligands triggered a degree of T cell activation significantly higher than the one achieved when we used either soluble tetramers or aAPC in which MHC-peptide complexes were uniformly distributed within artificial bilayer membranes. This increased efficiency in stimulation was mirrored by increased translocation from the cytoplasm to the membrane of protein kinase theta, a T cell signaling molecule that colocalizes with the TCR within the supramolecular activation cluster, thus indicating efficient engagement of T cell activation pathways. Engineered aAPC may have immediate application for basic and clinical immunology studies pertaining to modulation of T cells ex vivo.     

Use of chromomycin A3 staining in bovine sperm cells for detection of protamine deficiency

Sperm chromatin integrity is essential for accurate transmission of male genetic information, and normal sperm chromatin structure is important for fertilization. Protamine is a nuclear protein that plays a key role in sperm DNA integrity, because it is responsible for sperm DNA stability and packing until the paternal genome is delivered into the oocyte during fertilization. Our aim was to investigate protamine deficiency in sperm cells of Bos indicus bulls (Nelore) using chromomycin A₃ (CMA₃) staining. Frozen semen from 14 bulls were thawed, then fixed in Carnoy's solution. Smears were prepared and analyzed by microscopy. As a positive control of CMA₃ staining, sperm from one bull was subjected to deprotamination of nuclei. The percentage of CMA₃-positive bovine sperm did not vary among batches. Only two bulls showed a higher percentage of CMA₃-positive sperm cells compared to the others. CMA₃ is a simple and useful tool for detecting sperm protamine deficiency in bulls.     

Reference genes for quantitative reverse transcription-polymerase chain reaction expression studies in wild and cultivated peanut

Background

Molecular genetic studies on rare tumour entities, such as bone tumours, often require the use of decalcified, formalin-fixed, paraffin-embedded tissue (dFFPE) samples. Regardless of which decalcification procedure is used, this introduces a vast breakdown of DNA that precludes the possibility of further molecular genetic testing. We set out to establish a robust protocol that would overcome these intrinsic hurdles for bone tumour research.

Findings

The goal of our study was to establish a protocol, using a modified DNA isolation procedure and quality controls, to select decalcified samples suitable for array-CGH testing. Archival paraffin blocks were obtained from 9 different pathology departments throughout Europe, using different fixation, embedding and decalcification procedures, in order to preclude a bias for certain lab protocols. Isolated DNA samples were subjected to direct chemical labelling and enzymatic labelling systems and were hybridised on a high resolution oligonucleotide chip containing 44,000 reporter elements. Genomic alterations (gains and losses) were readily detected in most of the samples analysed. For example, both homozygous deletions of 0.6 Mb and high level of amplifications of 0.7 Mb were identified.

Conclusions

We established a robust protocol for molecular genetic testing of dFFPE derived DNA, irrespective of fixation, decalcification or sample type used. This approach may greatly facilitate further genetic testing on rare tumour entities where archival decalcified, formalin fixed samples are the only source.     

Genomic selection of purebred animals for crossbred performance in the presence of dominant gene action

Background

Genomic selection is an appealing method to select purebreds for crossbred performance. In the case of crossbred records, single nucleotide polymorphism (SNP) effects can be estimated using an additive model or a breed-specific allele model. In most studies, additive gene action is assumed. However, dominance is the likely genetic basis of heterosis. Advantages of incorporating dominance in genomic selection were investigated in a two-way crossbreeding program for a trait with different magnitudes of dominance. Training was carried out only once in the simulation.

Results

When the dominance variance and heterosis were large and overdominance was present, a dominance model including both additive and dominance SNP effects gave substantially greater cumulative response to selection than the additive model. Extra response was the result of an increase in heterosis but at a cost of reduced purebred performance. When the dominance variance and heterosis were realistic but with overdominance, the advantage of the dominance model decreased but was still significant. When overdominance was absent, the dominance model was slightly favored over the additive model, but the difference in response between the models increased as the number of quantitative trait loci increased. This reveals the importance of exploiting dominance even in the absence of overdominance. When there was no dominance, response to selection for the dominance model was as high as for the additive model, indicating robustness of the dominance model. The breed-specific allele model was inferior to the dominance model in all cases and to the additive model except when the dominance variance and heterosis were large and with overdominance. However, the advantage of the dominance model over the breed-specific allele model may decrease as differences in linkage disequilibrium between the breeds increase. Retraining is expected to reduce the advantage of the dominance model over the alternatives, because in general, the advantage becomes important only after five or six generations post-training.

Conclusion

Under dominance and without retraining, genomic selection based on the dominance model is superior to the additive model and the breed-specific allele model to maximize crossbred performance through purebred selection.     

Accuracies of genomic breeding values in American Angus beef cattle using K-means clustering for cross-validation

Background

Genomic selection is a recently developed technology that is beginning to revolutionize animal breeding. The objective of this study was to estimate marker effects to derive prediction equations for direct genomic values for 16 routinely recorded traits of American Angus beef cattle and quantify corresponding accuracies of prediction.

Methods

Deregressed estimated breeding values were used as observations in a weighted analysis to derive direct genomic values for 3570 sires genotyped using the Illumina BovineSNP50 BeadChip. These bulls were clustered into five groups using K-means clustering on pedigree estimates of additive genetic relationships between animals, with the aim of increasing within-group and decreasing between-group relationships. All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training. Bivariate animal models were used for each trait to estimate the genetic correlation between deregressed estimated breeding values and direct genomic values.

Results

Accuracies of direct genomic values ranged from 0.22 to 0.69 for the studied traits, with an average of 0.44. Predictions were more accurate when animals within the validation group were more closely related to animals in the training set. When training and validation sets were formed by random allocation, the accuracies of direct genomic values ranged from 0.38 to 0.85, with an average of 0.65, reflecting the greater relationship between animals in training and validation. The accuracies of direct genomic values obtained from training on older animals and validating in younger animals were intermediate to the accuracies obtained from K-means clustering and random clustering for most traits. The genetic correlation between deregressed estimated breeding values and direct genomic values ranged from 0.15 to 0.80 for the traits studied.

Conclusions

These results suggest that genomic estimates of genetic merit can be produced in beef cattle at a young age but the recurrent inclusion of genotyped sires in retraining analyses will be necessary to routinely produce for the industry the direct genomic values with the highest accuracy.     

Breeding value prediction for production traits in layer chickens using pedigree or genomic relationships in a reduced animal model

Background

Genomic selection involves breeding value estimation of selection candidates based on high-density SNP genotypes. To quantify the potential benefit of genomic selection, accuracies of estimated breeding values (EBV) obtained with different methods using pedigree or high-density SNP genotypes were evaluated and compared in a commercial layer chicken breeding line.

Methods

The following traits were analyzed: egg production, egg weight, egg color, shell strength, age at sexual maturity, body weight, albumen height, and yolk weight. Predictions appropriate for early or late selection were compared. A total of 2,708 birds were genotyped for 23,356 segregating SNP, including 1,563 females with records. Phenotypes on relatives without genotypes were incorporated in the analysis (in total 13,049 production records).The data were analyzed with a Reduced Animal Model using a relationship matrix based on pedigree data or on marker genotypes and with a Bayesian method using model averaging. Using a validation set that consisted of individuals from the generation following training, these methods were compared by correlating EBV with phenotypes corrected for fixed effects, selecting the top 30 individuals based on EBV and evaluating their mean phenotype, and by regressing phenotypes on EBV.

Results

Using high-density SNP genotypes increased accuracies of EBV up to two-fold for selection at an early age and by up to 88% for selection at a later age. Accuracy increases at an early age can be mostly attributed to improved estimates of parental EBV for shell quality and egg production, while for other egg quality traits it is mostly due to improved estimates of Mendelian sampling effects. A relatively small number of markers was sufficient to explain most of the genetic variation for egg weight and body weight.