Mesodern-inducing factors and mesodermal patterning

Identification of the signalling molecules involved in mesoderm formation in amphibian embryos still presents problems. None of the original candidates, such as activin, have been definitively ruled out, and the new factors, such as the nodal-related genes, have come on to the scene. Of the original candidates, activin has been definitively shown to act as a morphogen, whereas bone morphogenetic protein (BMP)-4 has emerged as a ventral inducer and an inhibitor of neural differentiation. The effects of BMP-4 are antagonized by chordin, a molecule related to the product of the Drosophila gene short gastrulation.     

Anonymous nuclear DNA markers in the American oyster and their implications for the heterozygote deficiency phenomenon in marine bivalves

A puzzling population-genetic phenomenon widely reported in allozyme surveys of marine bivalves is the occurrence of heterozygote deficits relative to Hardy-Weinberg expectations. Possible explanations for this pattern are categorized with respect to whether the effects should be confined to protein-level assays or are genomically pervasive and expected to be registered in both protein- and DNA-level assays. Anonymous nuclear DNA markers from the American oyster were employed to reexamine the phenomenon. In assays based on the polymerase chain reaction (PCR), two DNA-level processes were encountered that can lead to artifactual genotypic scorings: (a) differential amplification of alleles at a target locus and (b) amplification from multiple paralogous loci. We describe symptoms of these complications and prescribe methods that should generally help to ameliorate them. When artifactual scorings at two anonymous DNA loci in the American oyster were corrected, Hardy-Weinberg deviations registered in preliminary population assays decreased to nonsignificant values. Implications of these findings for the heterozygote-deficit phenomenon in marine bivalves, and for the general development and use of PCR-based assays, are discussed.      

Equivalence of multibreed animal models and hierarchical Bayes analysis for maternally influenced traits

Background

It has been argued that multibreed animal models should include a heterogeneous covariance structure. However, the estimation of the (co)variance components is not an easy task, because these parameters can not be factored out from the inverse of the additive genetic covariance matrix. An alternative model, based on the decomposition of the genetic covariance matrix by source of variability, provides a much simpler formulation. In this study, we formalize the equivalence between this alternative model and the one derived from the quantitative genetic theory. Further, we extend the model to include maternal effects and, in order to estimate the (co)variance components, we describe a hierarchical Bayes implementation. Finally, we implement the model to weaning weight data from an Angus × Hereford crossbred experiment.

Methods

Our argument is based on redefining the vectors of breeding values by breed origin such that they do not include individuals with null contributions. Next, we define matrices that retrieve the null-row and the null-column pattern and, by means of appropriate algebraic operations, we demonstrate the equivalence. The extension to include maternal effects and the estimation of the (co)variance components through the hierarchical Bayes analysis are then straightforward. A FORTRAN 90 Gibbs sampler was specifically programmed and executed to estimate the (co)variance components of the Angus × Hereford population.

Results

In general, genetic (co)variance components showed marginal posterior densities with a high degree of symmetry, except for the segregation components. Angus and Hereford breeds contributed with 50.26% and 41.73% of the total direct additive variance, and with 23.59% and 59.65% of the total maternal additive variance. In turn, the contribution of the segregation variance was not significant in either case, which suggests that the allelic frequencies in the two parental breeds were similar.

Conclusion

The multibreed maternal animal model introduced in this study simplifies the problem of estimating (co)variance components in the framework of a hierarchical Bayes analysis. Using this approach, we obtained for the first time estimates of the full set of genetic (co)variance components. It would be interesting to assess the performance of the procedure with field data, especially when interbreed information is limited.     

TETREUTREPTIA POMQUETENSIS (EUGLENOPHYTA), A PSYCHROPHILIC SPECIES: GROWTH AND FATTY ACID COMPOSITION

Tetreutreptia pomquetensis McLachlan, Fritz et Seguel, a quadriflagellated euglenoid isolated from a shallow-water embayment of the southeastern Gulf of St. Lawrence, is a common winter species where habitats are ice covered for 4 to 5 months. Growth in culture, which was similar to that of many euryhaline species, was limited at normal seawater salinities to temperatures between ∼0° and 7° C, and the alga could not be maintained at 10° C; thus, it is a strict psychrophile. The maximum growth rate (μ≅ 0.35·days⁻¹) was around 5° C and, given its size (∼100 μm length), high productivities are indicated. The major fatty acids (FAs) identified were 18:4ω3, 16:4ω3, 20:5ω3, and 16:0. The overall FA spectrum does not align closely to other euglenoids but may reflect more the low growth temperature. The presence of 18:5ω3 is unusual, as this FA had been known previously only from dinoflagellates and haptophytes. The two most abundant sulfoquinovosyl diacylglycerols (SQDGs) had pairings of [18:4/16:0] and [18:4/18:4] and together constituted 80% of the total SQDGs. The latter pairing is unique, not having been previously recognized. The FA data support the hypothesis that the degree of unsaturation is indicative of low temperatures and membrane integrity.     

Occurrence of Prorocentrum lima,a DSP toxin-producing species from the Atlantic coast of Canada

A species of Prorocentrum (Dinophyta, Prorocentrales), isolated from a phytoplankton net sample from the Atlantic coast of Nova Scotia, has been brought into unialgal culture. The sample was collected at an aquaculture site immediately following an incident of diarrhetic shellfish poisoning (DSP) due to the consumption of contaminated mussels. This clonal isolate has been identified as P. lima, based on its morphological characteristics. Analysis of the culture extract, using high performance liquid chromatography (HPLC) with fluorescence detection, indicated the presence of the DSP toxins, okadaic acid (OA) and dinophysistoxin-1 (DTX-1).     

Joint Modeling and Registration of Cell Populations in Cohorts of High-Dimensional Flow Cytometric Data

In biomedical applications, an experimenter encounters different potential sources of variation in data such as individual samples, multiple experimental conditions, and multivariate responses of a panel of markers such as from a signaling network. In multiparametric cytometry, which is often used for analyzing patient samples, such issues are critical. While computational methods can identify cell populations in individual samples, without the ability to automatically match them across samples, it is difficult to compare and characterize the populations in typical experiments, such as those responding to various stimulations or distinctive of particular patients or time-points, especially when there are many samples. Joint Clustering and Matching (JCM) is a multi-level framework for simultaneous modeling and registration of populations across a cohort. JCM models every population with a robust multivariate probability distribution. Simultaneously, JCM fits a random-effects model to construct an overall batch template – used for registering populations across samples, and classifying new samples. By tackling systems-level variation, JCM supports practical biomedical applications involving large cohorts. Software for fitting the JCM models have been implemented in an R package EMMIX-JCM, available from http://www.maths.uq.edu.au/~gjm/mix_soft/EMMIX-JCM/.     

Linker histone-DNA complexes: enhanced stability in the presence of aluminum lactate and implications for Alzheimer's disease

The binding of human brain linker histone proteins to a radiolabelled human Alu repetitive element was examined by mobility shift assay. Analysis of the complexes formed from protein extracts of whole neocortical nuclei, under physiological conditions in vitro revealed that linker histone H1(0) has the highest affinity for the Alu DNA sequence. The linker histone-DNA complexes assembled in the presence of aluminum lactate were more resistant to sodium chloride-induced dissociation than those formed in the presence of sodium lactate. The enhanced stability of deoxyribonucleoprotein (DNP) complexes in the presence of the aluminum cation may be of significance in neurodegenerative conditions such as Alzheimer's disease where aluminum preferentially associates with DNA containing structures of the nucleus.