Gene expression patterns in anterior pituitary associated with quantitative measure of oestrous behaviour in dairy cows

Intensive selection for high milk yield in dairy cows has raised production levels substantially but at the cost of reduced fertility, which manifests in different ways including reduced expression of oestrous behaviour. The genomic regulation of oestrous behaviour in bovines remains largely unknown. Here, we aimed to identify and study those genes that were associated with oestrous behaviour among genes expressed in the bovine anterior pituitary either at the start of oestrous cycle or at the mid-cycle (around day 12 of cycle), or regardless of the phase of cycle. Oestrous behaviour was recorded in each of 28 primiparous cows from 30 days in milk onwards till the day of their sacrifice (between 77 and 139 days in milk) and quantified as heat scores. An average heat score value was calculated for each cow from heat scores observed during consecutive oestrous cycles excluding the cycle on the day of sacrifice. A microarray experiment was designed to measure gene expression in the anterior pituitary of these cows, 14 of which were sacrificed at the start of oestrous cycle (day 0) and 14 around day 12 of cycle (day 12). Gene expression was modelled as a function of the orthogonally transformed average heat score values using a Bayesian hierarchical mixed model on data from day 0 cows alone (analysis 1), day 12 cows alone (analysis 2) and the combined data from day 0 and day 12 cows (analysis 3). Genes whose expression patterns showed significant linear or non-linear relationships with average heat scores were identified in all three analyses (177, 142 and 118 genes, respectively). Gene ontology terms enriched among genes identified in analysis 1 revealed processes associated with expression of oestrous behaviour whereas the terms enriched among genes identified in analysis 2 and 3 were general processes which may facilitate proper expression of oestrous behaviour at the subsequent oestrus. Studying these genes will help to improve our understanding of the genomic regulation of oestrous behaviour, ultimately leading to better management strategies and tools to improve or monitor reproductive performance in bovines

Methods for interpreting lists of affected genes obstained in a DNA microarray experiment

Background - The aim of this paper was to describe and compare the methods used and the results obtained by the participants in a joint EADGENE (European Animal Disease Genomic Network of Excellence) and SABRE (Cutting Edge Genomics for Sustainable Animal Breeding) workshop focusing on post analysis of microarray data. The participating groups were provided with identical lists of microarray probes, including test statistics for three different contrasts, and the normalised log-ratios for each array, to be used as the starting point for interpreting the affected probes. The data originated from a microarray experiment conducted to study the host reactions in broilers occurring shortly after a secondary challenge with either a homologous or heterologous species of Eimeria. Results - Several conceptually different analytical approaches, using both commercial and public available software, were applied by the participating groups. The following tools were used: Ingenuity Pathway Analysis, MAPPFinder, LIMMA, GOstats, GOEAST, GOTM, Globaltest, TopGO, ArrayUnlock, Pathway Studio, GIST and AnnotationDbi. The main focus of the approaches was to utilise the relation between probes/genes and their gene ontology and pathways to interpret the affected probes/genes. The lack of a well-annotated chicken genome did though limit the possibilities to fully explore the tools. The main results from these analyses showed that the biological interpretation is highly dependent on the statistical method used but that some common biological conclusions could be reached. Conclusion - It is highly recommended to test different analytical methods on the same data set and compare the results to obtain a reliable biological interpretation of the affected genes in a DNA microarray experimen

Refinement of Bos taurus sequence assembly based on BAC-FISH experiments

<p>Abstract</p> <p>Background</p> <p>The sequencing of the cow genome was recently published (Btau_4.0 assembly). A second, alternate cow genome assembly (UMD2), based on the same raw sequence data, was also published. The two assemblies have been subsequently updated to Btau_4.2 and UMD3.1, respectively.</p> <p>Results</p> <p>We compared the Btau_4.2 and UMD3.1 alternate assemblies. Inconsistencies were grouped into three main categories: (i) DNA segments showing almost coincidental chromosomal mapping but discordant orientation (inversions); (ii) DNA segments showing a discordant map position along the same chromosome; and (iii) sequences present in one chromosomal assembly but absent in the corresponding chromosome of the other assembly. The latter category mainly consisted of large amounts of scaffolds that were unassigned in Btau_4.2 but successfully mapped in UMD3.1. We sampled 70 inconsistencies and identified appropriate cow BACs for each of them. These clones were then utilized in FISH experiments on cow metaphase or interphase nuclei in order to disambiguate the discrepancies. In almost all instances the FISH results agreed with the UMD3.1 assembly. Occasionally, however, the mapping data of both assemblies were discordant with the FISH results.</p> <p>Conclusions</p> <p>Our work demonstrates how FISH, which is assembly independent, can be efficiently used to solve assembly problems frequently encountered using the shotgun approach.</p

Infection, colonization and shedding of Campylobacter and Salmonella in animals and their contribution to human disease: A review

Livestock meat and offal contribute significantly to human nutrition as sources of high‐quality protein and micronutrients. Livestock products are increasingly in demand, particularly in low‐ and middle‐income settings where economies are growing and meat is increasingly seen as an affordable and desirable food item. Demand is also driving intensification of livestock keeping and processing. An unintended consequence of intensification is increased exposure to zoonotic agents, and a contemporary emerging problem is infection with Campylobacter and Salmonella spp. from livestock (avian and mammalian), which can lead to disease, malabsorption and undernutrition through acute and chronic diarrhoea. This can occur at the farm, in households or through the food chain. Direct infection occurs when handling livestock and through bacteria shed into the environment, on food preparation surfaces or around the house and surroundings. This manuscript critically reviews Campylobacter and Salmonella infections in animals, examines the factors affecting colonization and faecal shedding of bacteria of these two genera as well as risk factors for human acquisition of the infection from infected animals or environment and analyses priority areas for preventive actions with a focus on resource‐poor settings

Exploring genetic control of swine responses to viral diseases.

Our goal is to understand genomic control of viral disease responses focusing on the economically most important disease of pigs, porcine reproductive and respiratory syndrome

Methods for interpreting lists of affected genes obtained in a DNA microarray experiment

BACKGROUND: The aim of this paper was to describe and compare the methods used and the results obtained by the participants in a joint EADGENE (European Animal Disease Genomic Network of Excellence) and SABRE (Cutting Edge Genomics for Sustainable Animal Breeding) workshop focusing on post analysis of microarray data. The participating groups were provided with identical lists of microarray probes, including test statistics for three different contrasts, and the normalised log-ratios for each array, to be used as the starting point for interpreting the affected probes. The data originated from a microarray experiment conducted to study the host reactions in broilers occurring shortly after a secondary challenge with either a homologous or heterologous species of Eimeria. RESULTS: Several conceptually different analytical approaches, using both commercial and public available software, were applied by the participating groups. The following tools were used: Ingenuity Pathway Analysis, MAPPFinder, LIMMA, GOstats, GOEAST, GOTM, Globaltest, TopGO, ArrayUnlock, Pathway Studio, GIST and AnnotationDbi. The main focus of the approaches was to utilise the relation between probes/genes and their gene ontology and pathways to interpret the affected probes/genes. The lack of a well-annotated chicken genome did though limit the possibilities to fully explore the tools. The main results from these analyses showed that the biological interpretation is highly dependent on the statistical method used but that some common biological conclusions could be reached. CONCLUSION: It is highly recommended to test different analytical methods on the same data set and compare the results to obtain a reliable biological interpretation of the affected genes in a DNA microarray experimen