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Abstract The objective was to evaluate the potential use of genotype probabilities to handle records of non-genotyped animals in the context of survival analysis. To do so, the risks associated with the PrP genotype and other transmission factors in relation to clinical scrapie were estimated. Data from 4049 Romanov sheep affected by natural scrapie were analyzed using survival analysis techniques. The original data set included 1310 animals with missing genotypes; five of those had uncensored records. Different missing genotype-information patterns were simulated for uncensored and censored records. Three strategies differing in the way genotype information was handled were tested. Firstly, records with unknown genotypes were discarded (P1); secondly, those records were grouped in an unknown class (P2). Finally the probabilities of genotypes were assigned (P3). Whatever the strategy, the ranking of relative risks for the most susceptible genotypes (VRQ-VRQ, ARQ-VRQ and ARQ-ARQ) was similar even when the non-genotyped animals were not a negligible part of uncensored records. However, P3 had a more efficient way of handling missing genotype information. As compared to P1, either P2 or P3 avoided discarding the records of non-genotyped animals; however, P3 eliminated the unknown class and the risk associated with this group. Genotype probabilities were shown to be a useful technique to handle records of individuals with unknown genotype.

Abstract A project of QTL detection was carried out in the French Holstein, Normande, and Montbéliarde dairy cattle breeds. This granddaughter design included 1 548 artificial insemination bulls distributed in 14 sire families and evaluated after a progeny-test for 24 traits (production, milk composition, persistency, type, fertility, mastitis resistance, and milking ease). These bulls were also genotyped for 169 genetic markers, mostly microsatellites. The QTL were analysed by within-sire linear regression of daughter yield deviations or deregressed proofs on the probability that the son receives one or the other paternal QTL allele, given the marker information. QTL were detected for all traits, including those with a low heritability. One hundred and twenty QTL with a chromosome-wise significance lower than 3% were tabulated. This threshold corresponded to a 15% false discovery rate. Amongst them, 32 were genome-wise significant. Estimates of their contribution to genetic variance ranged from 6 to 40%. Most substitution effects ranged from 0.6 to 1.0 genetic standard deviation. For a given QTL, only 1 to 5 families out of 14 were informative. The confidence intervals of the QTL locations were large and always greater than 20 cM. This experiment confirmed several already published QTL but most of them were original, particularly for non-production traits.

Abstract Genetic analysis for mastitis resistance was studied from two data sets. Firstly, risk factors for different mastitis traits, i.e. culling due to clinical or chronic mastitis and subclinical mastitis predicted from somatic cell count (SCC), were explored using data from 957 first lactation Lacaune ewes of an experimental INRA flock composed of two divergent lines for milk yield. Secondly, genetic parameters for SCC were estimated from 5 272 first lactation Lacaune ewes recorded among 38 flocks, using an animal model. In the experimental flock, the frequency of culling due to clinical mastitis (5%) was lower than that of subclinical mastitis (10%) predicted from SCC. Predicted subclinical mastitis was unfavourably associated with the milk yield level. Such an antagonism was not detected for clinical mastitis, which could result, to some extent, from its low frequency or from the limited amount of data. In practice, however, selection for mastitis resistance could be limited in a first approach to selection against subclinical mastitis using SCC. The heritability estimate of SCC was 0.15 for the lactation mean trait and varied from 0.04 to 0.12 from the first to the fifth test-day. The genetic correlation between lactation SCC and milk yield was slightly positive (0.15) but showed a strong evolution during lactation, i.e. from favourable (-0.48) to antagonistic (0.27). On a lactation basis, our results suggest that selection for mastitis resistance based on SCC is feasible. Patterns for genetic parameters within first lactation, however, require further confirmation and investigation.

Abstract Background S. aureus is one of the main pathogens responsible for the intra-mammary infection in dairy ruminants. Although much work has been carried out to understand the complex physiological and cellular events that occur in the mammary gland in response to S. aureus, the protective mechanisms are still poorly understood. The objectives of the present study were to investigate gene expression during the early response of the goat mammary gland to an experimental challenge with S. aureus, in order to better understand the local and systemic response and to compare them in two divergent lines of goat selected for high and low milk somatic cell scores. Results No differences in gene expression were found between high and low SCS (Somatic Cells Score) selection lines. Analysing the two groups together, an expression of 300 genes were found to change from T0 before infection, and T4 at 24 hours and T5 at 30 hours following challenge. In blood derived white blood cells 8 genes showed increased expression between T0 and T5 and 1 gene has reduced expression. The genes showing the greatest increase in expression following challenge (5.65 to 3.16 fold change) play an important role in (i) immune and inflammatory response (NFKB1, TNFAIP6, BASP1, IRF1, PLEK, BATF3); (ii) the regulation of innate resistance to pathogens (PTX3); and (iii) the regulation of cell metabolism (CYTH4, SLC2A6, ARG2). The genes with reduced expression (−1.5 to −2.5 fold) included genes involved in (i) lipid metabolism (ABCG2, FASN), (ii) chemokine, cytokine and intracellular signalling (SPPI), and (iii) cell cytoskeleton and extracellular matrix (KRT19). Conclusions Analysis of genes with differential expression following infection showed an inverse relationship between immune response and lipid metabolism in the early response of the mammary gland to the S. aureus challenge. PTX3 showed a large change in expression in both milk and blood, and is therefore a candidate for further studies on immune response associated with mastitis.

Abstract Background Gene expression profiling studies of mastitis in ruminants have provided key but fragmented knowledge for the understanding of the disease. A systematic combination of different expression profiling studies via meta-analysis techniques has the potential to test the extensibility of conclusions based on single studies. Using the program Pointillist, we performed meta-analysis of transcription-profiling data from six independent studies of infections with mammary gland pathogens, including samples from cattle challenged in vivo with S. aureus, E. coli, and S. uberis, samples from goats challenged in vivo with S. aureus, as well as cattle macrophages and ovine dendritic cells infected in vitro with S. aureus. We combined different time points from those studies, testing different responses to mastitis infection: overall (common signature), early stage, late stage, and cattle-specific. Results Ingenuity Pathway Analysis of affected genes showed that the four meta-analysis combinations share biological functions and pathways (e.g. protein ubiquitination and polyamine regulation) which are intrinsic to the general disease response. In the overall response, pathways related to immune response and inflammation, as well as biological functions related to lipid metabolism were altered. This latter observation is consistent with the milk fat content depression commonly observed during mastitis infection. Complementarities between early and late stage responses were found, with a prominence of metabolic and stress signals in the early stage and of the immune response related to the lipid metabolism in the late stage; both mechanisms apparently modulated by few genes, including XBP1 and SREBF1. The cattle-specific response was characterized by alteration of the immune response and by modification of lipid metabolism. Comparison of E. coli and S. aureus infections in cattle in vivo revealed that affected genes showing opposite regulation had the same altered biological functions and provided evidence that E. coli caused a stronger host response. Conclusions This meta-analysis approach reinforces previous findings but also reveals several novel themes, including the involvement of genes, biological functions, and pathways that were not identified in individual studies. As such, it provides an interesting proof of principle for future studies combining information from diverse heterogeneous sources.

Abstract Background The existence of a genetic basis for host responses to bacterial intramammary infections has been widely documented, but the underlying mechanisms and the genes are still largely unknown. Previously, two divergent lines of sheep selected for high/low milk somatic cell scores have been shown to be respectively susceptible and resistant to intramammary infections by Staphylococcus spp. Transcriptional profiling with an 15K ovine-specific microarray of the milk somatic cells of susceptible and resistant sheep infected successively by S. epidermidis and S. aureus was performed in order to enhance our understanding of the molecular and cellular events associated with mastitis resistance. Results The bacteriological titre was lower in the resistant than in the susceptible animals in the 48 hours following inoculation, although milk somatic cell concentration was similar. Gene expression was analysed in milk somatic cells, mainly represented by neutrophils, collected 12 hours post-challenge. A high number of differentially expressed genes between the two challenges indicated that more T cells are recruited upon inoculation by S. aureus than S. epidermidis. A total of 52 genes were significantly differentially expressed between the resistant and susceptible animals. Further Gene Ontology analysis indicated that differentially expressed genes were associated with immune and inflammatory responses, leukocyte adhesion, cell migration, and signal transduction. Close biological relationships could be established between most genes using gene network analysis. Furthermore, gene expression suggests that the cell turn-over, as a consequence of apoptosis/granulopoiesis, may be enhanced in the resistant line when compared to the susceptible line. Conclusions Gene profiling in resistant and susceptible lines has provided good candidates for mapping the biological pathways and genes underlying genetically determined resistance and susceptibility towards Staphylococcus infections, and opens new fields for further investigation.