Purification of brain D2 dopamine receptor.

D2 dopamine receptors have been extracted from bovine brain using the detergent cholate and purified approximately 20,000-fold by affinity chromatography on haloperidol-sepharose and wheat germ agglutinin-agarose columns. The purified preparation contains D2 dopamine receptors as judged by the pharmacological specificity of [3H]spiperone binding to the purified material. The sp. act. of [3H]spiperone binding in the purified preparation is 2.5 nmol/mg protein. The purified preparation shows a major diffuse band at Mr 95,000 upon SDS-polyacrylamide gel electrophoresis and there is evidence for microheterogeneity either at the protein or glycosylation level. Photoaffinity labelling of D2 dopamine receptors also shows a species of Mr 95,000. The D2 dopamine receptor therefore is a glycoprotein of Mr 95,000.     

Functional and historical drivers of leaf shape evolution in palms (Arecaceae)

Aim

Leaves display a remarkable variety of shapes, each with potential ecological advantages in specific climates. While the relations between leaf shape and either climate or height have been relatively well studied in eudicots, the macroecological drivers of shape remain poorly known in monocots. Here, we investigated the associations between climate and plant height with the evolution of leaf shape in a clade with high species and morphological diversity.

Location

Global.

Time period

Cretaceous to contemporary.

Major taxa studied

Palms (Arecaceae).

Methods

We apply a Bayesian phylogenetic mixed model to test for associations between climate and leaf shape (all – entire-leaved, pinnate-dissected, palmate-dissected and costapalmate). We further reconstruct the ancestral leaf shape using multistate speciation and extinction models and compare the frequency of shapes with global temperatures through time.

Results

We find that plant height associates with dissected leaves and that annual precipitation associates with pinnate shapes. The ancestral leaf shape is unclear, but early diversification was dominated by pinnate-dissected palms, which has remained the most species-rich form of leaves throughout palm history.

Main Conclusions

Palms that are tall and live in humid regions are more likely to have pinnate leaves. Through geological time scales, temperature did not play an obvious role in determining leaf shapes. This study contributes to our understanding of how the diversity of leaf shapes is linked to biological and climatic factors.     

Biochemical evidence for the co-association of three N-methyl-D-aspartate (NMDA) R2 subunits in recombinant NMDA receptors.

Functional characterization of wild-type and mutant cloned N-methyl-D-aspartate (NMDA) receptors has been used to deduce their subunit stoichiometry and quaternary structure. However, the results reported from different groups have been at variance and are thus inconclusive. This study has employed a biochemical approach to determine the number of NMDA R2 (NR2) subunits/receptor together with the NMDA R1 (NR1)/NR2 subunit ratio of both cloned and native NMDA receptors. Thus, human embryonic kidney 293 cells were transfected with the NR1-1a and NR2A NMDA receptor subunits in combination with both FLAG- and c-Myc epitope-tagged NR2B subunits. The expressed receptors were detergent-extracted and subjected to double immunoaffinity purification using anti-NR2A and anti-FLAG antibody immunoaffinity columns in series. Immunoblotting of the double immunopurified NR2A/NR2B(FLAG)-containing material demonstrated the presence of anti-NR1, anti-NR2A, anti-FLAG, and, more important, anti-c-Myc antibody immunoreactivities. The presence of anti-c-Myc antibody immunoreactivity in the double immunoaffinity-purified material showed the co-assembly of three NR2 subunits, i.e. NR2A/NR2B(FLAG)/NR2B(c-Myc), within the same NMDA receptor complex. Control experiments excluded the possibility that the co-immunopurification of the three NR2 subunits was an artifact of the solubilization procedure. These results, taken together with those previously described that showed two NR1 subunits/oligomer, suggest that the NMDA receptor is at least pentameric.     

Solvent-induced free energy landscape and solute-solvent dynamic coupling in a multielement solute

Molecular dynamics simulations using a simple multielement model solute with internal degrees of freedom and accounting for solvent-induced interactions to all orders in explicit water are reported. The potential energy landscape of the solute is flat in vacuo. However, the sole untruncated solvent-induced interactions between apolar (hydrophobic) and charged elements generate a rich landscape of potential of mean force exhibiting typical features of protein landscapes. Despite the simplicity of our solute, the depth of minima in this landscape is not far in size from free energies that stabilize protein conformations. Dynamical coupling between configurational switching of the system and hydration reconfiguration is also elicited. Switching is seen to occur on a time scale two orders of magnitude longer than that of the reconfiguration time of the solute taken alone, or that of the unperturbed solvent. Qualitatively, these results are unaffected by a different choice of the water-water interaction potential. They show that already at an elementary level, solvent-induced interactions alone, when fully accounted for, can be responsible for configurational and dynamical features essential to protein folding and function.     

Molecular Dissection of Native Mammalian Forebrain NMDA Receptors Containing the NR1 C2 Exon: Direct Demonstration of NMDA Receptors Comprising NR1, NR2A, and NR2B Subunits Within the Same Complex

Abstract: The subunit compositions of the NR1 C2 exon-containing N -methyl- d -aspartate (NMDA) receptors of adult mammalian forebrain were determined by using a combination of immunoaffinity chromatography and immunoprecipitation studies with NMDA receptor subunit-specific antibodies. NMDA receptors were solubilised by sodium deoxycholate, pH 9, and purified by anti-NR1 C2 antibody affinity chromatography. The purified receptor subpopulation showed immunoreactivity with anti-NR1 C2, anti-NR1 N1, anti-NR1 C2', anti-NR2A, and anti-NR2B NMDA receptor antibodies. The NR1 C2-receptor subpopulation was subjected to immunoprecipitation using anti-NR2B antibodies and the resultant immune pellets analysed by immunoblotting where anti-NR1 C2, anti-NR1 C2', anti-NR2A, and anti-NR2B immunoreactivities were all found. Quantification of the immunoblots showed that 46% of the NR1 C2 immunoreactivity was associated with the NR2B subunit. Of this, 87% (i.e., 40% of total) were NR1 C2/NR2B receptors and 13% (6% of total) were NR1 C2/NR2A/NR2B, thus identifying the triple combination as a minor receptor subset. These results demonstrate directly, for the first time, the coexistence of the NR2A and NR2B subunits in native NMDA receptors. They show the coexistence of two splice forms of the NR1 subunit, i.e., NR1 C2 and NR1 C2', in native receptors and, in addition, they imply an NMDA receptor subpopulation containing four types of NMDA receptor subunit, NR1 C2, NR1 C2', NR2A, and NR2B, which, in accord with molecular size determinations, predicts that the NMDA receptor is at least tetrameric. These results are the first quantitative study of NMDA receptor subtypes and demonstrate molecular heterogeneity for both the NR1 and the NR2 subunits in native forebrain NMDA receptors.     

Ultrastructure of the sodium pump: Comparison of thin sectioning, negative staining, and freeze-fracture of purified, membrane-bound (Na+, K+)-ATPase

Purified (Na+, K+)-ATPase was studied by electron microscopy after thin sectioning, negative staining, and freeze-fracturing, particular emphasis being paid to the dimensions and frequencies of substructures in the membranes. Ultrathin sections show exclusively flat or cup-shaped membrane fragments which are triple-layered along much of their length and have diameters of 0.1-0.6 μm. Negative staining revealed a distinct substructure of particles with diameters between 30 and 50 A and with a frequency of 12,500 +/- 2,400 (SD) per μm(2). Comparisons with sizes of the protein components suggest that each surface particle contains as its major component one large catalytic chain with mol wt close to 100,000 and that two surface particles unite to form the unit of (Na+,K+)-ATPase which binds one molecule of ATP or ouabain. The further observations that the surface particles protrude from the membrane surface and are observed on both membrane surfaces in different patterns and degrees of clustering suggest that protein units span the membrane and are capable of lateral mobility. Freeze-fracturing shows intramembranous particles with diameters of 90-110 A and distributed on both concave and convex fracture faces with a frequency of 3,410 +/- 370 per μm(2) and 390 +/- 170 per μm(2), respectively. The larger diameters and three to fourfold smaller frequency of the intramembranous particles as compared to the surface particles seen after negative staining may reflect technical differences between methods, but it is more likely that the intramembranous particle is an oliogomer composed of two or even more of the protein units which form the surface particles.     

Genomic prediction based on data from three layer lines: a comparison between linear methods

Background

The prediction accuracy of several linear genomic prediction models, which have previously been used for within-line genomic prediction, was evaluated for multi-line genomic prediction.

Methods

Compared to a conventional BLUP (best linear unbiased prediction) model using pedigree data, we evaluated the following genomic prediction models: genome-enabled BLUP (GBLUP), ridge regression BLUP (RRBLUP), principal component analysis followed by ridge regression (RRPCA), BayesC and Bayesian stochastic search variable selection. Prediction accuracy was measured as the correlation between predicted breeding values and observed phenotypes divided by the square root of the heritability. The data used concerned laying hens with phenotypes for number of eggs in the first production period and known genotypes. The hens were from two closely-related brown layer lines (B1 and B2), and a third distantly-related white layer line (W1). Lines had 1004 to 1023 training animals and 238 to 240 validation animals. Training datasets consisted of animals of either single lines, or a combination of two or all three lines, and had 30 508 to 45 974 segregating single nucleotide polymorphisms.

Results

Genomic prediction models yielded 0.13 to 0.16 higher accuracies than pedigree-based BLUP. When excluding the line itself from the training dataset, genomic predictions were generally inaccurate. Use of multiple lines marginally improved prediction accuracy for B2 but did not affect or slightly decreased prediction accuracy for B1 and W1. Differences between models were generally small except for RRPCA which gave considerably higher accuracies for B2. Correlations between genomic predictions from different methods were higher than 0.96 for W1 and higher than 0.88 for B1 and B2. The greater differences between methods for B1 and B2 were probably due to the lower accuracy of predictions for B1 (~0.45) and B2 (~0.40) compared to W1 (~0.76).

Conclusions

Multi-line genomic prediction did not affect or slightly improved prediction accuracy for closely-related lines. For distantly-related lines, multi-line genomic prediction yielded similar or slightly lower accuracies than single-line genomic prediction. Bayesian variable selection and GBLUP generally gave similar accuracies. Overall, RRPCA yielded the greatest accuracies for two lines, suggesting that using PCA helps to alleviate the “n ≪ p” problem in genomic prediction.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-014-0057-5) contains supplementary material, which is available to authorized users.     

Long-term response to genomic selection: effects of estimation method and reference population structure for different genetic architectures

Background

Genomic selection has become an important tool in the genetic improvement of animals and plants. The objective of this study was to investigate the impacts of breeding value estimation method, reference population structure, and trait genetic architecture, on long-term response to genomic selection without updating marker effects.

Methods

Three methods were used to estimate genomic breeding values: a BLUP method with relationships estimated from genome-wide markers (GBLUP), a Bayesian method, and a partial least squares regression method (PLSR). A shallow (individuals from one generation) or deep reference population (individuals from five generations) was used with each method. The effects of the different selection approaches were compared under four different genetic architectures for the trait under selection. Selection was based on one of the three genomic breeding values, on pedigree BLUP breeding values, or performed at random. Selection continued for ten generations.

Results

Differences in long-term selection response were small. For a genetic architecture with a very small number of three to four quantitative trait loci (QTL), the Bayesian method achieved a response that was 0.05 to 0.1 genetic standard deviation higher than other methods in generation 10. For genetic architectures with approximately 30 to 300 QTL, PLSR (shallow reference) or GBLUP (deep reference) had an average advantage of 0.2 genetic standard deviation over the Bayesian method in generation 10. GBLUP resulted in 0.6% and 0.9% less inbreeding than PLSR and BM and on average a one third smaller reduction of genetic variance. Responses in early generations were greater with the shallow reference population while long-term response was not affected by reference population structure.

Conclusions

The ranking of estimation methods was different with than without selection. Under selection, applying GBLUP led to lower inbreeding and a smaller reduction of genetic variance while a similar response to selection was achieved. The reference population structure had a limited effect on long-term accuracy and response. Use of a shallow reference population, most closely related to the selection candidates, gave early benefits while in later generations, when marker effects were not updated, the estimation of marker effects based on a deeper reference population did not pay off.     

Accuracy of imputation to whole-genome sequence data in Holstein Friesian cattle

Background

The use of whole-genome sequence data can lead to higher accuracy in genome-wide association studies and genomic predictions. However, to benefit from whole-genome sequence data, a large dataset of sequenced individuals is needed. Imputation from SNP panels, such as the Illumina BovineSNP50 BeadChip and Illumina BovineHD BeadChip, to whole-genome sequence data is an attractive and less expensive approach to obtain whole-genome sequence genotypes for a large number of individuals than sequencing all individuals. Our objective was to investigate accuracy of imputation from lower density SNP panels to whole-genome sequence data in a typical dataset for cattle.

Methods

Whole-genome sequence data of chromosome 1 (1737 471 SNPs) for 114 Holstein Friesian bulls were used. Beagle software was used for imputation from the BovineSNP50 (3132 SNPs) and BovineHD (40 492 SNPs) beadchips. Accuracy was calculated as the correlation between observed and imputed genotypes and assessed by five-fold cross-validation. Three scenarios S40, S60 and S80 with respectively 40%, 60%, and 80% of the individuals as reference individuals were investigated.

Results

Mean accuracies of imputation per SNP from the BovineHD panel to sequence data and from the BovineSNP50 panel to sequence data for scenarios S40 and S80 ranged from 0.77 to 0.83 and from 0.37 to 0.46, respectively. Stepwise imputation from the BovineSNP50 to BovineHD panel and then to sequence data for scenario S40 improved accuracy per SNP to 0.65 but it varied considerably between SNPs.

Conclusions

Accuracy of imputation to whole-genome sequence data was generally high for imputation from the BovineHD beadchip, but was low from the BovineSNP50 beadchip. Stepwise imputation from the BovineSNP50 to the BovineHD beadchip and then to sequence data substantially improved accuracy of imputation. SNPs with a low minor allele frequency were more difficult to impute correctly and the reliability of imputation varied more. Linkage disequilibrium between an imputed SNP and the SNP on the lower density panel, minor allele frequency of the imputed SNP and size of the reference group affected imputation reliability.     

Molecular characterization of D2 dopamine-like receptors from brain and from the pituitary gland.

D2 dopamine-like receptors have been purified from five bovine brain regions (caudate nucleus, putamen, olfactory tubercle, frontal cortex, cerebellum) and the anterior and neurointermediate lobes of the pituitary gland using a combined ligand-affinity and lectin-affinity chromatography procedure. In all the brain regions except cerebellum and in the neurointermediate lobe of the pituitary gland the purified species appeared as a M(r) 95,000 doublet on SDS-PAGE. In the anterior lobe of the pituitary an additional M(r) 142,000-145,000 species was seen. The M(r) 95,000 species had a low affinity for the lectin wheat germ agglutinin (WGA) whereas the M(r) 142,000-145,000 species had a higher affinity for WGA and additionally showed some affinity for concanavalin A. It is concluded that both the M(r) 95,000 and 142,000-145,000 species are D2 dopamine-like receptors and that the differences between the species are mainly at the oligosaccharide level. Some evidence was also obtained for heterogeneity at the protein level which may correspond to the D2(short) and D2(long) isoforms of these receptors.