A class of Bayesian methods to combine large numbers of genotyped and non-genotyped animals for whole-genome analyses

Background

To obtain predictions that are not biased by selection, the conditional mean of the breeding values must be computed given the data that were used for selection. When single nucleotide polymorphism (SNP) effects have a normal distribution, it can be argued that single-step best linear unbiased prediction (SS-BLUP) yields a conditional mean of the breeding values. Obtaining SS-BLUP, however, requires computing the inverse of the dense matrix G of genomic relationships, which will become infeasible as the number of genotyped animals increases. Also, computing G requires the frequencies of SNP alleles in the founders, which are not available in most situations. Furthermore, SS-BLUP is expected to perform poorly relative to variable selection models such as BayesB and BayesC as marker densities increase.

Methods

A strategy is presented for Bayesian regression models (SSBR) that combines all available data from genotyped and non-genotyped animals, as in SS-BLUP, but accommodates a wider class of models. Our strategy uses imputed marker covariates for animals that are not genotyped, together with an appropriate residual genetic effect to accommodate deviations between true and imputed genotypes. Under normality, one formulation of SSBR yields results identical to SS-BLUP, but does not require computing G or its inverse and provides richer inferences. At present, Bayesian regression analyses are used with a few thousand genotyped individuals. However, when SSBR is applied to all animals in a breeding program, there will be a 100 to 200-fold increase in the number of animals and an associated 100 to 200-fold increase in computing time. Parallel computing strategies can be used to reduce computing time. In one such strategy, a 58-fold speedup was achieved using 120 cores.

Discussion

In SSBR and SS-BLUP, phenotype, genotype and pedigree information are combined in a single-step. Unlike SS-BLUP, SSBR is not limited to normally distributed marker effects; it can be used when marker effects have a t distribution, as in BayesA, or mixture distributions, as in BayesB or BayesC π. Furthermore, it has the advantage that matrix inversion is not required. We have investigated parallel computing to speedup SSBR analyses so they can be used for routine applications.

Electronic supplementary material

The online version of this article (doi:10.1186/1297-9686-46-50) contains supplementary material, which is available to authorized users.     

Groundwater input affecting plant distribution by controlling ammonium and iron availability

Question: How does groundwater input affect plant distribution in Alnus glutinosa (black alder) carrs? Location: Alder carrs along the river Meuse, SE Netherlands. Methods: Three types of site, characterized by groundwater flow, were sampled in 17 A. glutinosa carrs. Vegetation and abiotic data (soil and water chemistry) were collected and analysed using a Canonical Correspondence Analysis. Based on the results, a laboratory experiment tested the effect of groundwater input (Ca²⁺) on pore water chemistry (NH₄⁺ availability). Results: Environmental factors indicating groundwater input (Ca²⁺ and Fe²⁺), correlating with the NH⁺₄ concentration in the pore water, best explained the variation in plant distribution. NH₄⁺ availability was determined by Ca²⁺ input via the groundwater and subsequent competition for exchange sites in the sediment. As a result, nutrient‐poor seepage locations fully fed by groundwater were dominated by small iron resistant plants such as Caltha palustris and Equisetum fluviatile. More nutrient‐rich locations, fed by a combination of groundwater and surface water, allowed the growth of taller iron resistant plant species such as Carex paniculata. Nutrient‐rich locations with stagnating surface water were hardly fed by groundwater, allowing the occurrence of fast growing and less iron tolerant wetland grasses such as Glyceria fluitans and G. maxima. Conclusion: Groundwater input affects plant composition in A. glutinosa carrs along the river Meuse by determining nutrient availability (ammonium) and concentrations of toxic iron.     

Ultrastructural localization of amiloride-sensitive sodium channels and Na+,K(+)-ATPase in the rat's olfactory epithelial surface

Several studies have indicated that olfactory responses are impeded by amiloride. Therefore, it was of interest to see whether, and if so which, olfactory epithelial cellular compartments have amiloride- sensitive structures. Using ultrastructural methods that involved rapid freezing, freeze-substitution and low temperature embedding of olfactory epithelia, this study shows that, in the rat, this tissue is immunoreactive to antibodies against amiloride sensitive Na(+)- channels. However, microvilli of olfactory supporting cells, as opposed to receptor cilia, contained most of the immunoreactive sites. Apices from which the microvilli sprout and receptor cell dendritic knobs had much less if any of the amiloride-antibody binding sites. Using a direct ligand-binding cytochemical method, this study also confirms earlier ones that showed that olfactory receptor cell cilia have Na+, K(+)-ATPase. It is proposed that supporting cell microvilli and the receptor cilia themselves have mechanisms, different but likely complementary, that participate in regulating the salt concentration around the receptor cell cilia. In this way, both structures help to provide the ambient mucous environment for receptor cells to function properly. This regulation of the salt concentration of an ambient fluid environment is a function that the olfactory epithelium shares with cells of transporting epithelia, such as those of kidney.      

Cupin: A candidate molecular structure for the Nep1-like protein family

Background  

NEP1-like proteins (NLPs) are a novel family of microbial elicitors of plant necrosis. Some NLPs induce a hypersensitive-like response in dicot plants though the basis for this response remains unclear. In addition, the spatial structure and the role of these highly conserved proteins are not known.     

Disruption of chromosome 11 in canine fibrosarcomas highlights an unusual variability of CDKN2B in dogs

Background  

In dogs in the western world neoplasia constitutes the most frequently diagnosed cause of death. Although there appear to be similarities between canine and human cancers, rather little is known about the cytogenetic and molecular alterations in canine tumours. Different dog breeds are susceptible to different types of cancer, but the genetic basis of the great majority of these predispositions has yet to be discovered. In some retriever breeds there is a high incidence of soft tissue sarcomas and we have previously reported alterations of chromosomes 11 and 30 in two poorly differentiated fibrosarcomas. Here we extend our observations and present a case report on detail rearrangements on chromosome 11 as well as genetic variations in a tumour suppressor gene in normal dogs.     

Functional implications of the microbial community structure of undefined mesophilic starter cultures

This review describes the recent advances made in the studies of the microbial community of complex and undefined cheese starter cultures. We report on work related to the composition of the cultures at the level of genetic lineages, on the presence and activity of bacteriophages and on the population dynamics during cheese making and during starter culture propagation. Furthermore, the link between starter composition and starter functionality will be discussed. Finally, recent advances in predictive metabolic modelling of the multi-strain cultures will be discussed in the context of microbe-microbe interactions.