1.Quantitative genetic studies to identify markers of health
traits
- The rate limiting step in studies aiming to detect genetic markers for
health is invariably the collection of phenotypes, rather than
genotypes. This is a general problem in many genomic studies,
including studies on non-disease traits, and it is known generically
as the ’phenotype gap.’
- The situation is exacerbated for disease traits as phenotypes of
disease susceptibility/resistance to infectious diseases are often
more difficult and/or expensive to measure than those for performance
traits
- Some diseases are multifactorial. For example, mastitis may be caused
by many pathogens (e.g. Escherichia coli, Staphylococcus aureus,
Mycoplasma bovis, Streptococcus uberis, Streptococcus agalactiaeetc), and the pathogenesis resulting from these specific infections
may differ dramatically. Therefore, an important issue is whether with
these different forms of the disease it is possible to have generic
solutions to the disease or, conversely, pathogen-specific solutions
are required invoking considerable complexity in data recording.
- In many cases, disease outcomes may be the result of infection
coinciding with stress induced immune suppression in livestock. An
example is the respiratory diseases of livestock and poultry in
intensive animal production systems caused by several different
pathogens (viral and/or bacterial) in association with transport,
co-mingling of pooled animals, dietary changes and administration of
various veterinary treatments. Mastitis is another example of a
disease where clinical cases often have an underlying issue of immune
suppression in early lactation. In such cases, addressing animals’
ability to cope with stress may be as effective as concentrating on
animals’resistance to infection.
- Quantitative genetic studies require knowledge of animal pedigrees
relating to animals upon which selection is performed.
- To establish reference populations for all commercial and indigenous
breeds of economic interest in the region for the future
implementation of Genetic Selection (Pollak et al., 2012).
- So far, there are no reported experiences in the application of
full-scale GS in the SADC region, only arbitrary plans.
For new technologies to be successful and effective in small-holder
systems, it needs to fit into the existing system and be seen as a
priority intervention (Marshall et al., 2011).
Dense SNP chips (tens or hundreds of thousands of SNPs) are the key to
effective and portable genetic marker studies. Currently these are
costly and only truly available in species with a genome sequence
(e.g., man, mouse, chicken). Another significant issue with animal
genome sequences is the lack of annotation, which is mostly based on
homology to genes in other animal species and not actual experimental
testing in the species of interest.
The step from discovery of significant marker associations to
utilizable markers for animal health is long, difficult and expensive.