Electronic structure of nanoscale iron oxide particles measured by scanning tunneling and photoelectron spectroscopies

We have investigated the electronic structure of nano-sized iron oxide by scanning tunnelling microscopy (STM) and spectroscopy (STS) as well as by photoelectron spectroscopy. Nano particles were produced by thermal treatment of Ferritin molecules containing a self-assembled core of iron oxide. Depending on the thermal treatment we were able to prepare different phases of iron oxide nanoparticles resembling gamma-Fe2O3, alpha-Fe2O3, and a phase which apparently contains both gamma-Fe2O3 and alpha-Fe2O3. Changes to the electronic structure of these materials were studied under reducing conditions. We show that the surface band gap of the electronic excitation spectrum can differ from that of bulk material and is dominated by surface effects.Comment: REVTeX, 6 pages, 10 figures, submitted to PR

QTL mapping of egg albumen quality in egg layers

BACKGROUND: A fresh, good quality egg has a firm and gelatinous albumen that anchors the yolk and restricts growth of microbiological pathogens. As the egg ages, the gel-like structure collapses, resulting in thin and runny albumen. Occasionally thin albumen is found in a fresh egg, giving the impression of a low quality product. A mapping population consisting of 1599 F(2) hens from a cross between White Rock and Rhode Island Red lines was set up, to identify loci controlling albumen quality. The phenotype for albumen quality was evaluated by albumen height and in Haugh units (HU) measured on three consecutive eggs from each F(2) hen at the age of 40 weeks. For the fine-mapping analysis, albumen height and HU were used simultaneously to eliminate contribution of the egg size to the phenotype. RESULTS: Linkage analysis in a small population of seven half-sib families (668 F(2)) with 162 microsatellite markers spread across 27 chromosomes revealed two genome-wide significant regions with additive effects for HU on chromosomes 7 and Z. In addition, two putative genome-wide quantitative trait loci (QTL) regions were identified on chromosomes 4 and 26. The QTL effects ranged from 2 to 4% of the phenotypic variance. The genome-wide significant QTL regions on chromosomes 7 and Z were selected for fine-mapping in the full set composed of 16 half-sib families. In addition, their existence was confirmed by an association analysis in an independent commercial Hy-Line pure line. CONCLUSIONS: We identified four chicken genomic regions that affect albumen quality. Our results also suggest that genes that affect albumen quality act both directly and indirectly through several different mechanisms. For instance, the QTL regions on both fine-mapped chromosomes 7 and Z overlapped with a previously reported QTL for eggshell quality, indicating that eggshell membranes may play a role in albumen quality

Linkage disequilibrium reveals different demographic history in egg laying chickens

<p>Abstract</p> <p>Background</p> <p>The availability of larger-scale SNP data sets in the chicken genome allows to achieve a higher resolution of the pattern of linkage disequilibrium (LD). In this study, 36 k and 57 k genotypes from two independent genotyping chips were used to systematically characterize genome-wide extent and structure of LD in the genome of four chicken populations. In total, we analyzed genotypes of 454 animals from two commercial and two experimental populations of white and brown layers which allows to some extent a generalization of the results.</p> <p>Results</p> <p>The number of usable SNPs in this study was 19 k to 37 k in brown layers and 8 k to 19 k in white layers. Our analyzes showed a large difference of LD between the lines of white and brown layers. A mean value of <it>r²</it>= 0.73 ± 0.36 was observed in pair-wise distances of < 25 Kb for commercial white layers, and it dropped to 0.60 ± 0.38 with distances of 75 to 120 Kb, the interval which includes the average inter-marker space in this line. In contrast, an overall mean value of <it>r²= </it>0.32 ± 0.33 was observed for SNPs less than 25 Kb apart from each other and dropped to 0.21 ± 0.26 at a distance of 100 kb in commercial brown layers. There was a remarkable similarity of the LD patterns among the two populations of white layers. The same was true for the two populations of brown layers, while the LD pattern between white and brown layers was clearly different. Inferring the population demographic history from LD data resulted in a larger effective population size in brown than white populations, reflecting less inbreeding among brown compared to white egg layers.</p> <p>Conclusions</p> <p>We report comprehensive LD map statistics for the genome of egg laying chickens with an up to 3 times higher resolution compared to the maps available so far. The results were found to be consistent between analyzes based on the parallel SNP chips and across different populations (commercial vs. experimental) within the brown and the white layers. It is concluded that the current density of usable markers in this study is sufficient for association mapping and the implementation of genomic selection in these populations to achieve a similar accuracy as in implementations of association mapping and genomic selection in mammalian farm animals.</p

Development of a high density 600K SNP genotyping array for chicken

Background: High density (HD) SNP genotyping arrays are an important tool for genetic analyses of animals and plants. Although the chicken is one of the most important farm animals, no HD array is yet available for high resolution genetic analysis of this species.Results: We report here the development of a 600 K Affymetrix® Axiom® HD genotyping array designed using SNPs segregating in a wide variety of chicken populations. In order to generate a large catalogue of segregating SNPs, we re-sequenced 243 chickens from 24 chicken lines derived from diverse sources (experimental, commercial broiler and layer lines) by pooling 10-15 samples within each line. About 139 million (M) putative SNPs were detected by mapping sequence reads to the new reference genome (Gallus_gallus_4.0) of which ~78 M appeared to be segregating in different lines. Using criteria such as high SNP-quality score, acceptable design scores predicting high conversion performance in the final array and uniformity of distribution across the genome, we selected ~1.8 M SNPs for validation through genotyping on an independent set of samples (n = 282). About 64% of the SNPs were polymorphic with high call rates (>98%), good cluster separation and stable Mendelian inheritance. Polymorphic SNPs were further analysed for their population characteristics and genomic effects. SNPs with extreme breach of Hardy-Weinberg equilibrium (P < 0.00001) were excluded from the panel. The final array, designed on the basis of these analyses, consists of 580,954 SNPs and includes 21,534 coding variants. SNPs were selected to achieve an essentially uniform distribution based on genetic map distance for both broiler and layer lines. Due to a lower extent of LD in broilers compared to layers, as reported in previous studies, the ratio of broiler and layer SNPs in the array was kept as 3:2. The final panel was shown to genotype a wide range of samples including broilers and layers with over 100 K to 450 K informative SNPs per line. A principal component analysis was used to demonstrate the ability of the array to detect the expected population structure which is an important pre-investigation step for many genome-wide analyses.Conclusions: This Affymetrix® Axiom® array is the first SNP genotyping array for chicken that has been made commercially available to the public as a product. This array is expected to find widespread usage both in research and commercial application such as in genomic selection, genome-wide association studies, selection signature analyses, fine mapping of QTLs and detection of copy number variants

A high resolution genome-wide scan for significant selective sweeps: an application to pooled sequence data in laying chickens

In most studies aimed at localizing footprints of past selection, outliers at tails of the empirical distribution of a given test statistic are assumed to reflect locus-specific selective forces. Significance cutoffs are subjectively determined, rather than being related to a clear set of hypotheses. Here, we define an empirical p-value for the summary statistic by means of a permutation method that uses the observed SNP structure in the real data. To illustrate the methodology, we applied our approach to a panel of 2.9 million autosomal SNPs identified from re-sequencing a pool of 15 individuals from a brown egg layer line. We scanned the genome for local reductions in heterozygosity, suggestive of selective sweeps. We also employed a modified sliding window approach that accounts for gaps in the sequence and increases scanning resolution by moving the overlapping windows by steps of one SNP only, and suggest to call this a "creeping window" strategy. The approach confirmed selective sweeps in the region of previously described candidate genes, i.e. TSHR, PRL, PRLHR, INSR, LEPR, IGF1, and NRAMP1 when used as positive controls. The genome scan revealed 82 distinct regions with strong evidence of selection (genome-wide p-value<0.001), including genes known to be associated with eggshell structure and immune system such as CALB1 and GAL cluster, respectively. A substantial proportion of signals was found in poor gene content regions including the most extreme signal on chromosome 1. The observation of multiple signals in a highly selected layer line of chicken is consistent with the hypothesis that egg production is a complex trait controlled by many genes

Application of Genomic Information to Longitudinal Traits

Random regression models are commonly used for analysis of longitudinal traits measured across time such as egg production in chickens and milk production in cattle. In this study, we include genomic information for evaluation of longitudinal traits using a random regression reduced animal model with a genomic relationship matrix. Substantial increases in accuracy of estimated breeding values were observed when applying the proposed method to egg production records in chickens

Acute paretic syndrome in juvenile White Leghorn chickens resembles late stages of acute inflammatory demyelinating polyneuropathies in humans

Background: Sudden limb paresis is a common problem in White Leghorn flocks, affecting about 1% of the chicken population before achievement of sexual maturity. Previously, a similar clinical syndrome has been reported as being caused by inflammatory demyelination of peripheral nerve fibres. Here, we investigated in detail the immunopathology of this paretic syndrome and its possible resemblance to human neuropathies. Methods: Neurologically affected chickens and control animals from one single flock underwent clinical and neuropathological examination. Peripheral nervous system (PNS) alterations were characterised using standard morphological techniques, including nerve fibre teasing and transmission electron microscopy. Infiltrating cells were phenotyped immunohistologically and quantified by flow cytometry. The cytokine expression pattern was assessed by quantitative real-time PCR (qRT-PCR). These investigations were accomplished by MHC genotyping and a PCR screen for Marek’s disease virus (MDV). Results: Spontaneous paresis of White Leghorns is caused by cell-mediated, inflammatory demyelination affecting multiple cranial and spinal nerves and nerve roots with a proximodistal tapering. Clinical manifestation coincides with the employment of humoral immune mechanisms, enrolling plasma cell recruitment, deposition of myelinbound IgG and antibody-dependent macrophageal myelin-stripping. Disease development was significantly linked to a 539 bp microsatellite in MHC locus LEI0258. An aetiological role for MDV was excluded. Conclusions: The paretic phase of avian inflammatory demyelinating polyradiculoneuritis immunobiologically resembles the late-acute disease stages of human acute inflammatory demyelinating polyneuropathy, and is characterised by a Th1-to-Th2 shift

Subgroup detection in genotype data using invariant coordinate selection

BioMed Central open acces

A scale-corrected comparison of linkage disequilibrium levels between genic and non-genic regions

The understanding of non-random association between loci, termed linkage disequilibrium (LD), plays a central role in genomic research. Since causal mutations are generally not included in genomic marker data, LD between those and available markers is essential for capturing the effects of causal loci on localizing genes responsible for traits. Thus, the interpretation of association studies requires a detailed knowledge of LD patterns. It is well known that most LD measures depend on minor allele frequencies (MAF) of the considered loci and the magnitude of LD is influenced by the physical distances between loci. In the present study, a procedure to compare the LD structure between genomic regions comprising several markers each is suggested. The approach accounts for different scaling factors, namely the distribution of MAF, the distribution of pair-wise differences in MAF, and the physical extent of compared regions, reflected by the distribution of pair-wise physical distances. In the first step, genomic regions are matched based on similarity in these scaling factors. In the second step, chromosome- and genome-wide significance tests for differences in medians of LD measures in each pair are performed. The proposed framework was applied to test the hypothesis that the average LD is different in genic and non-genic regions. This was tested with a genome-wide approach with data sets for humans (Homo sapiens), a highly selected chicken line (Gallus gallus domesticus) and the model plant Arabidopsis thaliana. In all three data sets we found a significantly higher level of LD in genic regions compared to non-genic regions. About 31% more LD was detected genome-wide in genic compared to non-genic regions in Arabidopsis thaliana, followed by 13.6% in human and 6% chicken. Chromosome-wide comparison discovered significant differences on all 5 chromosomes in Arabidopsis thaliana and on one third of the human and of the chicken chromosomes