Relationship between some molecular phenotypes for key physiological traits (based on epigenomic and chromatin / DNA methylation analysis) and genome haplotypes

Leaders: Claire Wathes (Royal Veterinary College) and Michel Georges (University of Liège)

Task 5.1. Generation of appropriate tissues for genomic analyses
Four trait-relevant tissues will be utilized in these experiments, sourced from 150 cows in WP3 for which genotypes and extensive phenotype analysis will be available. Samples will be obtained at key stages in early lactation and their analysis assigned to laboratories that are recognized experts in the four targeted areas of physiology. These will be: (i) liver, a major driver in the onset of metabolic diseases; (ii) PMBC, relevant to all disease and also sensitive to stress response; (iii) mammary gland biopsies relevant to mastitis and milk-production and (iv) endometrial biopsies, to monitor the inflammatory status of the endometrium, key to the return to fertility postpartum.

Task 5.2. Statistical genomics
The statistical genomics team will: (i) Use state-of-the-art tools to impute sequence data based on SNP genotypes. These are available from the 1,000 Bulls project and from 10,000 cows previously genotyped by consortium members (WP4). (ii) Develop and apply multivariate models to identify clusters of variants that have independent effects on ETs. (iii) Identify the most likely causative SNPs (iv) Generate a standardized pipeline for RNA-Seq based eQTL analysis and provide support for its utilization to the consortium. (v) Test the effect of preferential inclusion of candidate causative SNPs on GS accuracy using standard approaches as benchmark.

Task 5.3. Epigenomics
The epigenomics team will generate genome-wide maps of bovine cis-acting regulatory elements based on DNase I hypersensitivity sites (DHS) in a panel of the 4 trait-relevant tissue types. This method will identify regulatory elements within the genome and provide information relevant to functional specificity.

Task 5.4. Transcriptomics
The transcriptomics team will generate genome-wide RNA-Seq data to perform eQTL analyses in the 4 trait-relevant tissues. This will be analysed with respect to different disease phenotypes, as characterised in detail in WP3.

Task 5.5. Functional assays
Individual animals from WP3 with different genotypes for the candidate genes associated with an innate immune response will be selected. Cells will be isolated, cultured in vitro and stimulated with key ligands from either Gram-negative or Gram-positive bacteria, to obtain comparative data between animals of differing genotypes on the expression levels of candidate genes. As read-out systems we will focus on such parameters as production of anti-bacterial oxygen-/nitrogen radicals, as well as pro-inflammatory mediators known to stimulate the innate and adaptive immune responses, which are involved in processes such as inflammasome activation and autophagy. Together this will validate our SNPs by enabling us to determine how changes in the expression level of the candidate gene affects the key pathways by which innate immune cells respond to a bacterial pathogen.

Task 5.6. Bioinformatics & data-sharing
The datasets that will be generated in Tasks 5.2, 5.3 & 5.4 will not only feed into Task 5.1 but will also be of great value to the scientific community at large. The consortium will inform public databases including ENSEMBL and the bovine Genome Database. The new data from the project will be integrated into genome annotation as part of task 8.1 and will be publicly available. The ENCODE data will be stored in ENSEMBL and made available to the community via its genome browser and associated accessing tools.

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