Slides to accompany the Genomics, shaping the future from the Past by Prof Emmeline Hill, CSOm Plusvital.
This presentation was delivered as a keynote at the inaugural HorseTech Conference on the 18th October 2017 hosted by the Royal Veterinary College London.
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Genomics. Shaping the future from the past.
1. Genomics:
shaping the
future from the
past
Emmeline Hill
Associate Professor of Equine Science, UCD School
of Agriculture and Food Science
Chief Science Officer, Plusvital Ltd
3. For hundreds of years
Breeders have evaluated pedigree to
best guess the genes that have been
passed down from ancestors in the
pedigree
4. The Horse Genome was sequenced in
2007
Providing a novel technology allowing the
development of platform tools on a par
with modern human genomics medicine
that now enable researchers to identify
gene contributing to inherited traits in
horses
6. Thoroughbred ancestry
• Small number of founders
• 95% paternal lineages trace to 1 stallion
• 72% maternal lineages trace to 10 mares
• Closed stud book
• Intense selection for traits of importance
Byerley Turk (1686) Darley Arabian (1700)Godolphin Barb (1721)
8. • Myostatin - a negative regulator of muscle development
• Mutations in the myostatin (MSTN) gene cause unusual muscle
characteristics in mammalian species
10. Best race distance
• The three genetic types are strongly associated with best race distance:
C:C – short-distance
C:T – middle-distance
T:T – middle/long-distance
• Best race distance (BRD) distance of the highest grade of race won.
12. Unusually large
genomic
influence on race
distance
The ‘Speed Gene’
has a major, almost
singular, influence on
distance aptitude in
Thoroughbreds
13. Muscle fiber type proportions
Petersen JL, Mickelson JR, Rendahl AK, Valberg SJ, et al. (2013) Genome-Wide Analysis Reveals
Selection for Important Traits in Domestic Horse Breeds. PLoS Genet 9(1): e1003211.
doi:10.1371/journal.pgen.1003211
C:C horses
had 9.5%
more Type 2B
muscle fibres
than T:T
horses
Type 2B muscle
fibres =
fast glycolytic
Very short duration
high intensity bursts
of power = sprints
15. Mitochondrial function
Complex 1+3/CitSyn Complex 2+3/CitSyn
Complex 1+3+Ub/CitSyn Complex 2+3+Ub/CitSyn
C:C horses had
2x greater
mitochondrial
complex
activity than
T:T horses
M Rooney, R Porter, L Katz, E Hill (2017)
Skeletal muscle mitochondrial bioenergetics
and associations with myostatin genotypes in
the Thoroughbred horse (In press).
16. Precocity
C:C horses had their first start on average 80 days (2.5
months) earlier than T:T horses
C:C horses had their best race on average 144 days (5
months) earlier than T:T horses
G. Farries, P. A. McGettigan, K. F. Gough, B. A. McGivney, D. E. MacHugh, L. M. Katz,
E. W. Hill (2017) Genetic contributions to precocity traits in racing Thoroughbreds
18. C T
C
T CT
CT
T T
CCFull siblings,
completely
different type
19. “Having done a genetic test,
it’s implications have
opened my eyes into
thinking about what the
optimum distance for a
horse could be and how it
can contradict the normal
assumptions that might be
based on pedigree”
Hugo Palmer, trainer of
Galileo Gold (2,000 Guineas
winner, 2016)
20. Reduced % of T:T in foal crop from 16%+ to less than 5% within first
year of use (2011 foals)
Subsequently producing one to two T:T foals per annum out of crop of
seventy
Two-year-old strike rate went from 9% to 18% and earnings/run more
than doubled
Breeding for Speed and Precocity
2yo Year Wins Runs Wins/Runs Total Earnings (£) Earnings (£)/ Run
2015 29 159 18% £682,394 £4,292
2014 14 129 11% £346,719 £2,688
2013 13 138 9% £219,020 £1,587
21. Impact of selection for The Speed Gene – half
the number of T:T horses in Australia
25.20%
53.38%
21.42%
0%
10%
20%
30%
40%
50%
60%
C:C C:T T:T
44.63% 44.08%
11.29%
0%
10%
20%
30%
40%
50%
60%
C:C C:T T:T
Europe n = 1,111
Australia n = 363
28. • Technologies are rapidly advancing
• Data modelling is becoming more sophisticated and efficient in terms of
sorting the large amount of genetic information produced
• Approaches have been well established in other livestock production
industries
• Growing awareness and interest from global industry
Use of genomic prediction tools for performance and health
will become standard practice in coming 5-10 years
29. “Although man does not cause variability
and cannot even prevent it, he can select,
preserve, and accumulate the
variations given to him by the hand of
nature in any way which he chooses;
and thus he can certainly produce a
great result.”
Charles Darwin
30. Prof Emmeline Hill, Dr Jim Bolger, Prof David MacHugh, Dr Beatrice McGivney, Prof
Andrew Parnell, Prof Lisa Katz, Prof Richard Porter, Amy Holtby, Gabriella Farries,
Charlotte Herdan, Mary Rooney
