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Genome to Phenome: Improving Animal Health, Production, and Well-Being

A new USDA Blueprint for Animal Genome Research 2018 – 2027

Comments (7) -

  • Fiona M McCarthy
    p.29 "developing cost-effective methods to carry out genome analyses"
    It is also worth explicitly stating here that cost effectiveness is at least partly reliant on data sharing and reproducibility.
    23 September 2019 - Reply
  • Fiona M McCarthy
    p. 29 "Genome-enabled parentage and traceability are used to address questions associated with species management and product quality."
    Tracebility can also address food safety concerns and tie in with "food to fork" initiatives but this has not really been addressed in US livestock production the same way it has in other countries (e.g., https://goo.gl/S8zYJ6).
    23 September 2019 - Reply
  • Fiona M McCarthy
    p.29 "To implement improvements in genome-enabled selection in more animal species...include trait-relevant transcriptomic, proteomic, and metabolomic information."
    Since genome-enabled technologies have been applied where there is a clear economic gain, then the argument needs to be made for the gain (and likewise investment) in these other species.
    23 September 2019 - Reply
  • Fiona M McCarthy
    p.29 Collect new and more extensive phenotypes:
    One of the major problems with the collection & integration of phenotype data is that this data must be available in an easily queryable common format for others to derive value from it. Phenotype and trait ontologies exist but are poorly utilized in animal genomics, and because of this much data is lost or unusable.
    23 September 2019 - Reply
  • Fiona M McCarthy
    p.30 Identify causal alleles:
    I agree with this statement but it does not specifically recognize that many important production traits are multigenic and that regulatory elements are largely undetermined.  Both of these factors create a gap in translating genotype to phenotype. For example, many SNPs linked with traits map to areas that currently annotated as "intergenic" but are likely to contain key regulatory elements.
    23 September 2019 - Reply
  • Fiona M McCarthy
    p.30 "1. Comprehensive collection of relevant environmental (including management), genotype, and phenotype information"

    Again, data (& metadata) about environment and phenotype need to be collected, analyzed, shared and stored in a common agreed upon formats that also allow comparative studies across conditions and species. It should be explicitly stated that increasing data acquisition without appropriate attention to data management is wasted time, money and effort.
    23 September 2019 - Reply
  • Fiona M McCarthy
    p.31. Resources required should include a workforce that is "data-savvy" - this is, if not specifically trained to do their own data analyses, then able to understand fundamentals of data management.
    23 September 2019 - Reply

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