lessons from studies in genetics of heat...
TRANSCRIPT
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Lessons from studies in genetics of heat stress
Ignacy Misztal
University of Georgia
ADSA Resilience Symposium 2016
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Animal Breeding and Climate Change
• Remarkable success of breeding – Kg milk 1944-2007: 23% feed, 35% water, 37% CO2
(Capper et al., 2009) – Broiler 1957-2001: grows 3 times faster using 33%
feed (Havenstein et al., 2003) – … – > 50% gain via genetics (Shook, 2006; Havenstein et
al., 2003).
• Challenge of climate change • Do we need a special breeding for resilience?
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Selection as optimization
• Domestication
• Intensive selection
• Gains for preferred traits
• Correlated losses for other traits
• Effect of losses reduced/eliminated by management
• Very poor fitness of domesticated animals have when released back into the wild (Frankham, 2008).
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Climate change
• Greater variations
• Hotter
• Extensive literature on heat stress/tolerance
• Heat tolerance as proxy for resilience
• Can one select for heat tolerance?
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ADSA Resilience Symposium 2016
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Challenge of heat stress
• Perceived reduction of heat tolerance in hot areas
• Little observable heat stress with DHI data (e.g., Wright et al., 2015)
• Mainstream selection in Holsteins in milder/colder climates
• Selection against heat tolerance? – If so, can one select for heat tolerance?
ADSA Resilience Symposium 2016
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Assumption for heat stress model P
rod
uct
ion
/Rep
rod
uct
ion
Temperature humidity index (THI)
cow 2
cow 3
cow 1
Breeding value: BV = a + f(THI)*v
a – regular breeding value v – heat-tolerance breeding value
f(THI) – function of temperature humidity index
Ravagnolo et
al., 2001
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Effect of THI on daily milk production
48
49
50
51
52
53
54
55
56
57
58
59
55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85
slope= -0.46
lb
THI
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0.52
0.54
0.56
0.58
0.6
0.62
0.64
0.66
0.68
0.7
0.72
50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 80 82 84
THI
NR
45
Effect of THI on Non-return rate at 45 days
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Genetics results
• Heat stress begins at about 72F THI (22C at 100% humidity)
• Genetic variability for heat tolerance present but not big
• Relationship between regular and heat tolerance genetics antagonistic at ~ -0.4
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Heat stress across USA
Variation in heat tolerance across USA
Genetic evaluation for heat stress with national data
Do colder regions contribute information about heat stress?
Profile of heat tolerant bull
Can one identify heat-tolerant sires?
What are they?
Bohmanova et al. (2005 and 2006)
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Differences between most 100 and least
100 heat tolerant sires
Milk -1100kg
Fat% +0.2%
Pro% +0.1%
Dairy Form -1.4
Udder +0.7
Longevity +0.90
Fertility +1.6
Index +36
• Selection for fluid milk
detrimental to heat stress
• Low accuracy of active
sires for heat stress
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Heat stress in later parities (Aguilar
et al., 2009)
US test days
3-trait RR and RPT models
Heat stress effect
Estimation of parameters
National evaluation
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Variances for three-parity test-day repeatability
model
Milk
1 2 3
5.6 7.5 6.5
4.0 7.0 9.0
-0.46 -0.38 -0.47
Fat (kg*100)
1 2 3
74 94 109
37 75 142
-0.39 -0.39 -0.30
Protein (kg*100)
1 2 3
43 57 52.2
22 48 108
-0.43 -0.36 -0.50
Genetic variance for heat stress increases up to 5 times
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Genetic trends of daily milk yield for
3 parities – regular effect
First Second Third
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Genetic trends for heat stress effect
at 5.5o C over the threshold
First Second Third
• Improvement higher than deterioration
• Test days capture fraction of heat stress information (Freitas et al., 2005)
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K. Tokuhisa*, S. Tsuruta, and I. Misztal University of Georgia, Athens
# 709
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Mortality in SouthEast
0.10%
0.20%
0.30%
0.40%
0.50%
0.60%
0.70%
0.80%
0.90%
1 2 3 4 5 6 7 8 9 10 11 12
Mo
rta
lity
Month
SE Mortality (1-3rd parities) 1999-2008
1st parity
2nd parity
3rd parity
Tokuhisa et al. (2011)
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Is cost of heat stress higher than it seems?
• Low survival in SouthEast from parity to parity
• Due to increasing heat stress with parities?
• Selection for survival but not for mortality
• Available data only from better farms
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Days open in Thai crosses
Boonkum et al., 2011
Small effect for milk
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Iranian Holsteins
35
40
45
50
55
Jan
Feb
Mar
ch
Ap
r
May Jun
Jul
Au
g
Sep
Oct
No
v
Dec
Mokhtar et al, 2012
Small effect for milk
Co
nce
pti
on
rat
e
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THI
Heat production
Rectal temperature
Milk
Fertility
Mortality/ Morbidity
Profile of a “heat-tolerant cow”
Partially based on Dikmen et al. (2012)
• What is a heat tolerant cow? • Milk as long as
possible?
• Reduces production when dangerous?
• Reduces production early to maintain reproduction
• Thresholds management specific
• Match genotype to environment
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Genetics of growth in pigs under different
heat loads (Zumbach et al., 2007)
• Pigs in NC or TX exposed to heat stress
• Heat stress affect growth
• How to model heat stress for growth?
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Theoretical and realized heat loads
80
82
84
86
88
90
92
94
96
98
2005
/05
2005
/06
2005
/07
2005
/08
2005
/09
2005
/10
2005
/11
2005
/12
2006
/01
2006
/02
2006
/03
2006
/04
2006
/05
2006
/06
2006
/07
2006
/08
2006
/09
2006
/10
2006
/11
2006
/12
Year-Month of slaughter
Ca
rca
ss
we
igh
t (k
g)
10
12
14
16
18
20
22
24
26
28
30
-He
at
Lo
ad
*0.1
5+
24
CW H
Zumbach et al., 2007 ADSA Resilience Symposium
2016
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Variances during cold and hot periods
Genetic
Litter
Error
h2
rhot,cold
Hot
28
17.0
55
0.28
0.42
Cold
14
19.2
66
0.14
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Heat stress in purebred and crossbred pigs
9kg 2 kg
Crossbred Purebred
Better environment almost eliminates heat stress
Fragomeni et al., 2016)
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Beef
• Annual economic losses from heat stress (St-Pierre et al., 2003)
– $87 million for beef cows
– $282 million for finishing cattle
• Limited quantifiable heat stress for Angus in US (Bradford et al., 2016)
– Adaptation of beef industry for local condition
• Timing of breeding
• Crossbreeding
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-0.2
0
0.2
0.4
0.6
0.8
1
2001 2003 2005 2007 2009 2011 2013
Ge
net
ic S
D u
nit
s
Birth year
THI ≤ 75 THI = 80 THI = 85
WW Direct Genetic Trend for Angus in Southeast
Bradford et al., 2016
No heat stress
High heat stress
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Is beef resilient
• Research by Don Spiers (Missouri)
– 3 days in heat chamber without water
– Removing hair by torches
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QTL for heat stress
• Slick hair gene (Olsen et al., 2010)
• Gene for spring shedding in beef?
• Markers for rectal temperature (Dikmen et al., 2013) – Max 0.44% for 1 Mbase region
• Studies in AZ (Collier et al., 2012) – 500 SNP from microarray studies
– 500 SNP from GWAS
– 5 in common
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ssGBLUP for Heat Stress in
Holsteins (Aguilar, 2011)
• Multiple-Trait Test-Day model, heat stress
as random regression • ~ 90 millions records, ~ 9 millions pedigrees
• ~ 3,800 genotyped bulls
Regular effect -first parity Heat stress effect – first parity
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ADSA Resilience Symposium
2016
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Example – Intensive selection for
growth in broiler chicken
• Unlimited appetite / obesity artificial lightning
• Different maturity rate of males and females separation of sexes
• Poor survival of males male supplementation
• Increased susceptibility to diseases antibiotics
• Low hatchability alternate heating/cooling of incubators
• …
Selection for main traits with improved management for secondary traits
Eitan and Soller, 2014 ADSA Resilience Symposium
2016
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Resilience and management intensity R
esili
ence
Management intensity
Beef
Dairy
Pigs
Chicken
Energy distribution Pigs and selection for RFI (Dekkers, 2015)
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Heat tolerant lines?
• Needs several generations of selection
• Market for heat tolerant animals small
• Improved management simpler
• Selection and production environments
• Interbull and dairy cattle
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Conclusions
• Selection as optimization –winner and
loser traits
• Management compensates for “losers”
– Capabilities different by species
• Optimal management for each
environment
• Current selection OK if selection and
production environments similar
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