Colonization of the rhizosphere of crop plants by plant-beneficial pseudomonads

Abstract: Efficient colonization of the plant root is thought to be crucial for the plant-beneficial effect of particular Pseudomonas strains. Since root colonization is often the limiting step for successful plant growth stimulation, this process needs improvement. It is therefore important to acquire more information as regards (i) the conditions in the rhizosphere, and (ii) the bacterial traits that are involved in colonization. This review discusses some recent studies that focus on these two issues.     

Versterven bij een psychiatrische pati?nt: hindernissen voor pati?nt, familie en behandelteam

In this case-report we present a patient with a psychiatric history of a chronic depressive disorder. After a period of several years of ambivalence, he decided to refuse nutrition and hydration because he--in the words of the Royal Dutch Medical Association--was "suffering from life". There was no request for euthanasia or physician assisted suicide. His first attempt, that lasted six weeks, did not result in his death. A second attempt, four months later, ended successfully. We describe the pitfalls that the patient, his family and the professional caregivers faced in both trajectories. The premorbid psychiatric disorder with polypharmacy and several psychotropic drugs as a result, the enormous complaints of thirst, the role of his wife and the dilemmas faced by the professionals made this case very complex. These issues make such cases very challenging for professional teams that have to provide good palliative care.     

Genome-wide association analysis and genetic architecture of egg weight and egg uniformity in layer chickens

The pioneering work by Professor Soller et al., among others, on the use of genetic markers to analyze quantitative traits has provided opportunities to discover their genetic architecture in livestock by identifying quantitative trait loci (QTL). The recent availability of high-density single nucleotide polymorphism (SNP) panels has advanced such studies by capitalizing on population-wide linkage disequilibrium at positions across the genome. In this study, genomic prediction model Bayes-B was used to identify genomic regions associated with the mean and standard deviation of egg weight at three ages in a commercial brown egg layer line. A total of 24,425 segregating SNPs were evaluated simultaneously using over 2900 genotyped individuals or families. The corresponding phenotypic records were represented as individual measurements or family means from full-sib progeny. A novel approach using the posterior distribution of window variances from the Monte Carlo Markov Chain samples was used to describe genetic architecture and to make statistical inferences about regions with the largest effects. A QTL region on chromosome 4 was found to explain a large proportion of the genetic variance for the mean (30%) and standard deviation (up to 16%) of the weight of eggs laid at specific ages. Additional regions with smaller effects on chromosomes 2, 5, 6, 8, 20, 23, 28 and Z showed suggestive associations with mean egg weight and a region on chromosome 13 with the standard deviation of egg weight at 26-28 weeks of age. The genetic architecture of the analyzed traits was characterized by a limited number of genes or genomic regions with large effects and many regions with small polygenic effects. The region on chromosome 4 can be used to improve both the mean and standard deviation of egg weight by marker-assisted selection.     

Genomic selection of purebreds for crossbred performance

Background

One of the main limitations of many livestock breeding programs is that selection is in pure breeds housed in high-health environments but the aim is to improve crossbred performance under field conditions. Genomic selection (GS) using high-density genotyping could be used to address this. However in crossbred populations, 1) effects of SNPs may be breed specific, and 2) linkage disequilibrium may not be restricted to markers that are tightly linked to the QTL. In this study we apply GS to select for commercial crossbred performance and compare a model with breed-specific effects of SNP alleles (BSAM) to a model where SNP effects are assumed the same across breeds (ASGM). The impact of breed relatedness (generations since separation), size of the population used for training, and marker density were evaluated. Trait phenotype was controlled by 30 QTL and had a heritability of 0.30 for crossbred individuals. A Bayesian method (Bayes-B) was used to estimate the SNP effects in the crossbred training population and the accuracy of resulting GS breeding values for commercial crossbred performance was validated in the purebred population.

Results

Results demonstrate that crossbred data can be used to evaluate purebreds for commercial crossbred performance. Accuracies based on crossbred data were generally not much lower than accuracies based on pure breed data and almost identical when the breeds crossed were closely related breeds. The accuracy of both models (ASGM and BSAM) increased with marker density and size of the training data. Accuracies of both models also tended to decrease with increasing distance between breeds. However the effect of marker density, training data size and distance between breeds differed between the two models. BSAM only performed better than AGSM when the number of markers was small (500), the number of records used for training was large (4000), and when breeds were distantly related or unrelated.

Conclusion

In conclusion, GS can be conducted in crossbred population and models that fit breed-specific effects of SNP alleles may not be necessary, especially with high marker density. This opens great opportunities for genetic improvement of purebreds for performance of their crossbred descendents in the field, without the need to track pedigrees through the system.     

Comparing linkage disequilibrium-based methods for fine mapping quantitative trait loci

Recently, a method for fine mapping quantitative trait loci (QTL) using linkage disequilibrium was proposed to map QTL by modeling covariance between individuals, due to identical-by-descent (IBD) QTL alleles, on the basis of the similarity of their marker haplotypes under an assumed population history. In the work presented here, the advantage of using marker haplotype information for fine mapping QTL was studied by comparing the IBD-based method with 10 markers to regression on a single marker, a pair of markers, or a two-locus haplotype under alternative population histories. When 10 markers were genotyped, the IBD-based method estimated the position of the QTL more accurately than did single-marker regression in all populations. When 20 markers were genotyped for regression, as single-marker methods do not require knowledge of haplotypes, the mapping accuracy of regression in all populations was similar to or greater than that of the IBD-based method using 10 markers. Thus for populations similar to those simulated here, the IBD-based method is comparable to single-marker regression analysis for fine mapping QTL.     

The effect of using approximate gametic variance covariance matrices on marker assisted selection by BLUP

Under additive inheritance, the Henderson mixed model equations (HMME) provide an efficient approach to obtaining genetic evaluations by marker assisted best linear unbiased prediction (MABLUP) given pedigree relationships, trait and marker data. For large pedigrees with many missing markers, however, it is not feasible to calculate the exact gametic variance covariance matrix required to construct HMME. The objective of this study was to investigate the consequences of using approximate gametic variance covariance matrices on response to selection by MABLUP. Two methods were used to generate approximate variance covariance matrices. The first method (Method A) completely discards the marker information for individuals with an unknown linkage phase between two flanking markers. The second method (Method B) makes use of the marker information at only the most polymorphic marker locus for individuals with an unknown linkage phase. Data sets were simulated with and without missing marker data for flanking markers with 2, 4, 6, 8 or 12 alleles. Several missing marker data patterns were considered. The genetic variability explained by marked quantitative trait loci (MQTL) was modeled with one or two MQTL of equal effect. Response to selection by MABLUP using Method A or Method B were compared with that obtained by MABLUP using the exact genetic variance covariance matrix, which was estimated using 15 000 samples from the conditional distribution of genotypic values given the observed marker data. For the simulated conditions, the superiority of MABLUP over BLUP based only on pedigree relationships and trait data varied between 0.1% and 13.5% for Method A, between 1.7% and 23.8% for Method B, and between 7.6% and 28.9% for the exact method. The relative performance of the methods under investigation was not affected by the number of MQTL in the model.     

Sources of organic carbon in the littoral of Lake Gooimeer as indicated by stable carbon isotope and carbohydrate compositions

The relative importance of potential carbon sources in the littoral of Lake Gooimeer, a lake in the centre of the Netherlands, was studied using a combination of ¹³C/¹²C-ratio analysis and carbohydrate composition analysis. The littoral is covered on the land side by a 80 m wide Phragmites australis bed. Potential carbon sources were macrophyte litter, seston and benthic algae. Samples of potential carbon sources, sediments and benthic macrofauna from inside and outside the bed were analyzed for their¹³C/¹²C-ratio and some for their carbohydrate composition. Results indicate that inside the bed, macrophyte litter was the main source of carbon for both the sediment organic matter and the benthic macrofauna, and that algal material was of minor importance. Outside the bed, production by benthic algae was the main carbon source, with seston as a second source. No macrophyte derived material could be detected outside the reed bed.Abbreviations DOC (Dissolved Organic Carbon) - SOM (Sediment Organic Matter)     

Distinct localization of the complement C5b‐9 complex on Gram‐positive bacteria

The plasma proteins of the complement system fulfil important immune defence functions, including opsonization of bacteria for phagocytosis, generation of chemo‐attractants and direct bacterial killing via the Membrane Attack Complex (MAC or C5b‐9). The MAC is comprised of C5b, C6, C7, C8, and multiple copies of C9 that generate lytic pores in cellular membranes. Gram‐positive bacteria are protected from MAC‐dependent lysis by their thick peptidoglycan layer. Paradoxically, several Gram‐positive pathogens secrete small proteins that inhibit C5b‐9 formation. In this study, we found that complement activation on Gram‐positive bacteria in serum results in specific surface deposition of C5b‐9 complexes. Immunoblotting revealed that C9 occurs in both monomeric and polymeric (SDS‐stable) forms, indicating the presence of ring‐structured C5b‐9. Surprisingly, confocal microscopy demonstrated that C5b‐9 deposition occurs at specialized regions on the bacterial cell. On Streptococcus pyogenes, C5b‐9 deposits near the division septum whereas on Bacillus subtilis the complex is located at the poles. This is in contrast to C3b deposition, which occurs randomly on the bacterial surface. Altogether, these results show a previously unrecognized interaction between the C5b‐9 complex and Gram‐positive bacteria, whichmight ultimately lead to a new model of MAC assembly and functioning.     

Controlling the proportion of false positives in multiple dependent tests

Genome scan mapping experiments involve multiple tests of significance. Thus, controlling the error rate in such experiments is important. Simple extension of classical concepts results in attempts to control the genomewise error rate (GWER), i.e., the probability of even a single false positive among all tests. This results in very stringent comparisonwise error rates (CWER) and, consequently, low experimental power. We here present an approach based on controlling the proportion of false positives (PFP) among all positive test results. The CWER needed to attain a desired PFP level does not depend on the correlation among the tests or on the number of tests as in other approaches. To estimate the PFP it is necessary to estimate the proportion of true null hypotheses. Here we show how this can be estimated directly from experimental results. The PFP approach is similar to the false discovery rate (FDR) and positive false discovery rate (pFDR) approaches. For a fixed CWER, we have estimated PFP, FDR, pFDR, and GWER through simulation under a variety of models to illustrate practical and philosophical similarities and differences among the methods.