From sheep SNP chips, genome sequences and transcriptomes via mechanisms to improved sheep breeding and management — ASN Events

From sheep SNP chips, genome sequences and transcriptomes via mechanisms to improved sheep breeding and management (#30)

Brian P Dalrymple 1 , Hutton V Oddy 2 , John C McEwan 3 , James W Kijas 1 , Ruidong Xiang 1 , Jude Bond 2 , Noelle Cockett 4 , Kim Worley 5 , Tim Smith 6 , Philip E Vercoe 7
  1. Agriculture Flagship, CSIRO, St Lucia, QLD, Australia
  2. Beef Industry Centre, NSW Department of Primary Industries, Armidale, NSW, Australia
  3. AgResearch, Invermay, Otago, New Zealand
  4. Utah State University, Logan, Utah, USA
  5. Human Genome Sequencing Center, Baylor College of Medicine, Huston, Texas, USA
  6. MARC, USDA, Clay Center, Nebraska, USA
  7. Institute of Agriculture, University of Western Australia, Peth, Western Australia, Australia

SNP chips are transforming animal breeding; low cost “assay-by-sequencing” methodologies and high quality reference genome sequences provide the opportunity for further significant improvement in both breeding and management. The Functional Annotation of ANimal Genomes (FAANG) consortium is applying methods developed by the human ENCODE project to annotate the genomes of livestock (sheep, cattle, pigs, etc.) with functional information including the probability that variation at a particular nucleotide has a causal role in any phenotype. We will contribute the detailed annotation of the transcriptome of the gastrointestinal tract of sheep to FAANG. We will combine the analysis of the interaction between variation in genome sequence, transcription, gastrointestinal tract phenotypes and the environment across ~100 animals, a developmental time course of the gastrointestinal tract transcriptome from 30 days post conception to weaning, and an in-depth analysis of the gastrointestinal tract transcriptome from the new reference sheep, a North American Rambouillet. From this, and public FAANG data, we will estimate the probability that variation in a particular nucleotide has an impact on gastrointestinal phenotypes of interest (methane, nutrition, infection, microbial population) and identify the biological processes underlying the phenotype. This information will inform breeding schemes, identify management options, define phenotypes more precisely.

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