Untersuchungen zu Liegenischen für Milchziegen

The legislative rules of keeping ruminants on organic farms do not differentiate between the requirements of the different species for the housing systems. Thus, the types of locomotion typical for goats (e. g. climbing, jumping) have not to take in consideration in stables designed for goat keeping. Some farmers offer their animals elevated resting platforms (niches), but data concerning the preferences of the goats and the labour management of such areas are not available. A herd of non-lactating goats (breed: Bunte Deutsche Edelziege) was parted in six experimental groups with ten animals in each group. Over a period of seven days the animals were kept separated in a part of the stable furnished with resting niches. Twelve niches were arranged on three levels. Half of them contained a layer of deep-litter. The working time needed for cleaning of the niches was measured during each change of the groups. The cleanliness of the niches was documented by photography. Pictures were evaluated by means of an image processing system. Animal behaviour was registered by video-observation. The results showed a relationship between the labour time needed for cleaning of the niches and the preference of niches by the goats. Due to the necessary filling up with straw, the niches with the bedding of deep litter required the same amount of labour time as the niches without bedding, which needed more time for cleaning. The image processing system might be used to evaluate cleanliness of resting areas designed for other species, too

Diverse LEF/TCF Expression in Human Colorectal Cancer Correlates with Altered Wnt-Regulated Transcriptome in a Meta-Analysis of Patient Biopsies

Funding: CM acknowledges funding from the Scottish Government: Rural & Environment Science & Analytical Services. (RESAS). SH is a Royal Society/Leverhulme Trust Senior Research Fellow (SRF\R1\191017) and acknowledges research funding from the Biotechnology and Biological Sciences Research Council (BB/S018190/1, BB/M001695/1). Author Contributions: C.-D.M. and S.H. had conceived and supervised this project; C.-D.M. curated the data and carried out some analysis; S.M.L.G., carried out most of the analysis; F.A. wrote an original draft together with Stefan Hoppler. All authors have read and agreed to the published version of the manuscript. Supplementary Materials: The following are available online at www.mdpi.com/2073-4425/11/5/538/s1: Figure S1: Principal Component Analysis of selected studies, Figure S2: Principal Component Analysis of de-selected study, Table S1: Transcriptomics Data (Correlation Coefficients) Table S1A: Transcript correlation between eight selected genes (TCF7, LEF1, TCF7L1, TCF7L2, AXIN2, DKK1, FZD7, LGR5); Table S1B: The TCF7-correlated transcriptome; Table S1C: The LEF1correlated transcriptome; Table S1D: The TCF7L1-correlated transcriptome; Table S1E: The TCF7L2-correlated transcriptome; Table S1F: The AXIN2-correlated transcriptome; Table S1G: The DKK1-correlated transcriptome; Table S1H: The FZD7-correlated transcriptome; Table S1I: The LGR5-correlated transcriptome; Table S1J: Differences in LEF/TCF-correlated transcriptomes; Table S1K: Differences between AXIN2- and LEF/TCF-correlated transcriptomes, Table S2: Correlated Transcriptome in normal and tumor tissue, Table S3: Comparison of LEF/TCF-correlated transcriptomes, Table S4: Differences between AXIN1- and LEF/TCF-correlated transcriptomes.Peer reviewedPublisher PD

An evaluation of two-channel ChIP-on-chip and DNA methylation microarray normalization strategies

<p>Abstract</p> <p>Background</p> <p>The combination of chromatin immunoprecipitation with two-channel microarray technology enables genome-wide mapping of binding sites of DNA-interacting proteins (ChIP-on-chip) or sites with methylated CpG di-nucleotides (DNA methylation microarray). These powerful tools are the gateway to understanding gene transcription regulation. Since the goals of such studies, the sample preparation procedures, the microarray content and study design are all different from transcriptomics microarrays, the data pre-processing strategies traditionally applied to transcriptomics microarrays may not be appropriate. Particularly, the main challenge of the normalization of "regulation microarrays" is (i) to make the data of individual microarrays quantitatively comparable and (ii) to keep the signals of the enriched probes, representing DNA sequences from the precipitate, as distinguishable as possible from the signals of the un-enriched probes, representing DNA sequences largely absent from the precipitate.</p> <p>Results</p> <p>We compare several widely used normalization approaches (VSN, LOWESS, quantile, T-quantile, Tukey's biweight scaling, Peng's method) applied to a selection of regulation microarray datasets, ranging from DNA methylation to transcription factor binding and histone modification studies. Through comparison of the data distributions of control probes and gene promoter probes before and after normalization, and assessment of the power to identify known enriched genomic regions after normalization, we demonstrate that there are clear differences in performance between normalization procedures.</p> <p>Conclusion</p> <p>T-quantile normalization applied separately on the channels and Tukey's biweight scaling outperform other methods in terms of the conservation of enriched and un-enriched signal separation, as well as in identification of genomic regions known to be enriched. T-quantile normalization is preferable as it additionally improves comparability between microarrays. In contrast, popular normalization approaches like quantile, LOWESS, Peng's method and VSN normalization alter the data distributions of regulation microarrays to such an extent that using these approaches will impact the reliability of the downstream analysis substantially.</p

EORNA, a barley gene and transcript abundance database

A high-quality, barley gene reference transcript dataset (BaRTv1.0), was used to quantify gene and transcript abundances from 22 RNA-seq experiments, covering 843 separate samples. Using the abundance data we developed a Barley Expression Database (EORNA*) to underpin a visualisation tool that displays comparative gene and transcript abundance data on demand as transcripts per million (TPM) across all samples and all the genes. EORNA provides gene and transcript models for all of the transcripts contained in BaRTV1.0, and these can be conveniently identified through either BaRT or HORVU gene names, or by direct BLAST of query sequences. Browsing the quantification data reveals cultivar, tissue and condition specific gene expression and shows changes in the proportions of individual transcripts that have arisen via alternative splicing. TPM values can be easily extracted to allow users to determine the statistical significance of observed transcript abundance variation among samples or perform meta analyses on multiple RNA-seq experiments. * Eòrna is the Scottish Gaelic word for Barley.</p

Predictive gene signatures:molecular markers distinguishing colon adenomatous polyp and carcinoma

Funding: This study was supported by the Scottish Government's Rural and Environment Science and Analytical Services Division Food, Land and People Programme GT403 (http://www.scotland.gov.uk/Topics/Research/About/EBAR/StrategicResearch/future-research-strategy/Themes), Scottish Universities Life Science Alliance Translational Biology Studentship 10/09, (http://www.sulsa.ac.uk/), NHS Grampian Endowment Fund 12/07 (http://www.nhsgrampian.co.uk/nhsgrampian/gra_display_hospital.jsp?pContentID=65&p_applic=CCC&p_service=Content.show&). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Data Availability: The authors confirm that all data underlying the findings are fully available without restriction. All relevant data are within the paper and its Supporting Information files.Peer reviewedPublisher PD

Environmentally-acquired bacteria influence microbial diversity and natural innate immune responses at gut surfaces

Background: Early microbial colonization of the gut reduces the incidence of infectious, inflammatory and autoimmune diseases. Recent population studies reveal that childhood hygiene is a significant risk factor for development of inflammatory bowel disease, thereby reinforcing the hygiene hypothesis and the potential importance of microbial colonization during early life. The extent to which early-life environment impacts on microbial diversity of the adult gut and subsequent immune processes has not been comprehensively investigated thus far. We addressed this important question using the pig as a model to evaluate the impact of early-life environment on microbe/host gut interactions during development. Results: Genetically-related piglets were housed in either indoor or outdoor environments or in experimental isolators. Analysis of over 3,000 16S rRNA sequences revealed major differences in mucosa-adherent microbial diversity in the ileum of adult pigs attributable to differences in early-life environment. Pigs housed in a natural outdoor environment showed a dominance of Firmicutes, in particular Lactobacillus, whereas animals housed in a hygienic indoor environment had reduced Lactobacillus and higher numbers of potentially pathogenic phylotypes. Our analysis revealed a strong negative correlation between the abundance of Firmicutes and pathogenic bacterial populations in the gut. These differences were exaggerated in animals housed in experimental isolators. Affymetrix microarray technology and Real-time Polymerase Chain Reaction revealed significant gut-specific gene responses also related to early-life environment. Significantly, indoor-housed pigs displayed increased expression of Type 1 interferon genes, Major Histocompatibility Complex class I and several chemokines. Gene Ontology and pathway analysis further confirmed these results. Conclusion: Early-life environment significantly affects both microbial composition of the adult gut and mucosal innate immune function. We observed that a microbiota dominated by lactobacilli may function to maintain mucosal immune homeostasis and limit pathogen colonization

Dietary fibers inhibit obesity in mice, but host responses in the cecum and liver appear unrelated to fiber-specific changes in cecal bacterial taxonomic composition

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Bioaccumulation in aquatic systems: methodological approaches, monitoring and assessment

Bioaccumulation, the accumulation of a chemical in an organism relative to its level in the ambient medium, is of major environmental concern. Thus, monitoring chemical concentrations in biota are widely and increasingly used for assessing the chemical status of aquatic ecosystems. In this paper, various scientific and regulatory aspects of bioaccumulation in aquatic systems and the relevant critical issues are discussed. Monitoring chemical concentrations in biota can be used for compliance checking with regulatory directives, for identification of chemical sources or event related environmental risk assessment. Assessing bioaccumulation in the field is challenging since many factors have to be considered that can effect the accumulation of a chemical in an organism. Passive sampling can complement biota monitoring since samplers with standardised partition properties can be used over a wide temporal and geographical range. Bioaccumulation is also assessed for regulation of chemicals of environmental concern whereby mainly data from laboratory studies on fish bioaccumulation are used. Field data can, however, provide additional important information for regulators. Strategies for bioaccumulation assessment still need to be harmonised for different regulations and groups of chemicals. To create awareness for critical issues and to mutually benefit from technical expertise and scientific findings, communication between risk assessment and monitoring communities needs to be improved. Scientists can support the establishment of new monitoring programs for bioaccumulation, e.g. in the frame of the amended European Environmental Quality Standard Directive

SARS-CoV-2 RNA levels in Scotland’s wastewater

Nationwide, wastewater-based monitoring was newly established in Scotland to track the levels of SARS-CoV-2 viral RNA shed into the sewage network, during the COVID-19 pandemic. We present a curated, reference dataset produced by this national programme, from May 2020 to February 2022. Viral levels were analysed by RT-qPCR assays of the N1 gene, on RNA extracted from wastewater sampled at 162 locations. Locations were sampled up to four times per week, typically once or twice per week, and in response to local needs. We report sampling site locations with geographical coordinates, the total population in the catchment for each site, and the information necessary for data normalisation, such as the incoming wastewater flow values and ammonia concentration, when these were available. The methodology for viral quantification and data analysis is briefly described, with links to detailed protocols online. These wastewater data are contributing to estimates of disease prevalence and the viral reproduction number (R) in Scotland and in the UK