Leading the way in Agriculture and Rural Research, Education and Consulting
What do new CT measurements tell us?
N. Clelland, L. Bunger, K.A. McLean,
S. Knott, C. Donaldson and N.R. Lambe
Sheep Breeders Round Table
Nottingham 2015
What CT already tells us
22/11/2015 2
Currently a two-stage selection method (US and CT
scanning) is used in UK terminal sire breeding programmes
Improve growth, carcass composition; overall fatness,
muscularity
Lambs US scanned at 21 weeks, selection candidates
are then CT scanned within 2 weeks
What CT already tells us
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• Predicted carcass tissue weights (Muscle/Fat/Bone)
• Killing out %
• Muscle to Bone ratio
• Muscle to Fat ratio
• Gigot shape
• Eye muscle Area/Width/Depth
• % Muscle in Leg/Loin/Chest (High value cuts)
Outline
• Spine Traits
– What is measured?
– Is there variation of spine characteristics in sheep?
– Are spine traits under genetic control?
• Meat quality
– Is it important?
– How is it measured?
– Are CT meat quality traits under genetic control?
22/11/2015 4
Background
• If novel CT traits (e.g. IMF, spine
length) are to be included in current
breeding programmes we need to
estimate
– Heritability (h2) of novel CT traits
– Genetic correlations (rg) with traits
in current genetic evaluations
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The Mammalian Spine
22/11/2015 6
• Consists of 5 regions
• Our focus: thoracolumbar region in sheep
• High quality loin muscle runs the length of the
region
22/11/2015 7
• Spine characteristics…
What Is Measured
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How It Is Measured
• X-ray computed tomography (CT)
Is there variation?
22/11/2015 9
• In pigs: selection for body length increased number of
vertebrae
– wild boar ancestors = 19
– commercial pig breeds = 21- 23
– highly heritable (h2 ~ 0.6)
– affects loin yield and meat:fat
• In sheep: CT shows variation in spine traits (length/vertebrae no.)
– between and within breeds
– Texel shortest spine; 17-21 TL vertebrae
– low-moderate h2 in research flock
– genetic associations?
Claire Donaldson, PhD thesis, 2015
22/11/2015 10
Data used
• 2,583 commercial Texel rams CT scanned– 94 flocks over 15 years
• CT data collected– predicted tissue weights, muscularity, [ IMF ]
– vertebrae number
– spine length
• Combined with data from breeding scheme– weights (8 and 21 weeks)
– ultrasound fat and muscle depths
• Genetic analysis (ASReml), animal model– adjusting for year, flock, litter size, dam age, CT
scanner, age or live weight, as appropriate
22/11/2015 11
Genetic Parameters
Spine Traits
• Genetic correlations
– Number of vertebrae in the entire region highly correlated with
lumbar and thoracic regions (rg 0.96, 0.69)
– Spine length in the entire region highly correlated with lumbar
and thoracic regions (rg 0.81, 0.80)
• Heritabilities
– Low for number of vertebra (h2 0.05-0.11)
– Moderate for spine length (h2 0.21-0.43)
𝑟𝑔 =𝐶𝑂𝑉 𝐴 (𝑡𝑟𝑎𝑖𝑡 1,2
𝑉 𝐴 (𝑡𝑟𝑎𝑖𝑡 1 ∗ 𝑉 𝐴(𝑡𝑟𝑎𝑖𝑡 2
22/11/2015 12
Genetic Parameters
Spine Traits vs Production traits/CT traits
• Low correlations with: growth traits; CT predicted tissue
weights and muscularity; US tissue depths (<± 0.25)
• Moderate with CT-predicted IMF (-0.2 – 0.45)
– Positive for lumbar number/length
– Negative for thoracic number/length
• Suggests selection for spine traits would not affect
current breeding goals
Measuring meat quality (IMF)
• IMF estimates are of interest as an objective proxy trait
for meat (eating) quality
• Accurate estimates of IMF were previously limited to
laboratory methods (post-mortem)
– Destructive/expensive
• In-vivo CT methods overcome previous
invasive/destructive methods
• CT scanning provides very accurate in-vivo estimates
of IMF (Adj R2 > 0.65, Clelland et al 2013; 2014; 2015)
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How it is measured
• X-Ray Computed Tomography (CT)• Separate carcass from non-carcass tissues
• Pixels allocated to fat, muscle or bone
22/11/2015 14
94 Models
Accuracies
• IMF >65%
• Shear force ~ 14%
Data used
• Performance records from 1,971 entire male Texel lambs over 12 years
525 Sires, 1,576 Dams, 70 Flocks
– US records (Fat depth, Muscle depth), Live weights (8 weeks, 21
weeks), CT records (Fat weight, Muscle weight, Muscularity and Eye
muscle area)
– CT-predicted IMF (including carcass fat = PIMF1, and excluding
carcass fat = PIMF2)
• Genetic analysis (ASReml), animal model
– adjusting for Birth type, Dam age, Scanner, Flock, Year, Flock x Year
(Age at US/CT)
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22/11/2015 16
CT predicted IMF
• Genetic correlations
– CT fat weight highly correlated with PIMF1 and PIMF2 (rg 0.88,
rg 0.68)
– PIMF1 and PIMF2 highly correlated (rg 0.92)
• Heritabilities
– Moderate for both PIMF1 and PIMF2 (h2 0.42 and 0.31)
Genetic Parameters
22/11/2015 17
Genetic Parameters
CT IMF vs Production traits/CT traits
• Moderate/High correlations with: growth traits
(rg 0.27 – 0.62)
• High correlation with USFD (~0.57)
• PIMF1 Low correlations with US and CT muscularity
– rg 0.22-0.38
• PIMF2 non-significant for US and CT muscularity
Conclusions
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• Genetic selection for spine traits and IMF possible
– spine region lengths as selection criteria (more heritable)
• Genetic results suggest selection for spine traits would not affect
current breeding goals
– Heritability estimates for CT-predicted IMF (PIMF1, PIMF2) similar
to chemical IMF in previous studies (h2 = 0.32-0.48)
• Indicative of the CT measurement accuracy in PIMF
• CT IMF is heritable and partially under different
genetic control from fat weight
– Potential to select for ‘correlation breakers’
0
0.5
1
1.5
2
2.5
3
3.5
4
0 2 4 6 8 10 12
CT
IM
F
CT Carcass fat
22/11/2015 19
‘Correlation breakers’
Conclusions
• Including spine traits/IMF in breeding programmes
– minimal extra expense; measured on existing images from routine CT of
elite rams; adding value ££££
– unlikely to affect current breeding goals (growth, carcass fat and muscle,
gigot muscularity)
– could increase % meat yield from high-priced loin cut & carcass value of
slaughter lambs
– Potential to select candidates for leanness and optimal IMF (‘Correlation
breakers’)
22/11/2015 20
Leading the way in Agriculture and Rural Research, Education and Consulting
Research is funded by the joint levy bodies AHDB beef and lamb, HCC and QMS
With acknowledgments to the Texel society for access to performance records
ASDA and BBSRC during Claire Donaldson’s PhD
SRUC receives financial support from the Scottish Government
Leading the way in Agriculture and Rural Research, Education and Consulting
Genetic Parameters
22/11/2015 23
Trait 8WWT 21WWT USFD USMD CTFW CTMW CTmusc CTema PIMF1 PIMF2
8WWT 0.30 (0.07) 0.61
(0.02)
0.17 (0.03) 0.20
(0.03)
0.52
(0.02)
0.53
(0.02)
0.11 (0.03) 0.30
(0.02)
0.43
(0.02)
0.29
(0.02)
21WWT 0.76 (0.08) 0.43
(0.06)
0.45 (0.02) 0.43
(0.02)
0.73
(0.01)
0.80
(0.01)
0.22 (0.03) 0.48
(0.02)
0.58
(0.02)
0.38
(0.02)
USFD 0.39 (0.15) 0.42
(0.11)
0.39 (0.07) 0.27
(0.02)
0.65
(0.02)
0.30
(0.02)
0.08 (0.03) 0.21
(0.03)
0.57
(0.02)
0.51
(0.02)
USMD 0.39 (0.16) 0.52
(0.12)
0.24 (0.13) 0.34
(0.06)
0.33
(0.02)
0.49
(0.02)
0.24 (0.02) 0.65
(0.02)
0.18
(0.03)
0.09
(0.03)
CTFW 0.84 (0.09) 0.71
(0.06)
0.60 (0.08) 0.49
(0.12)
0.39
(0.07)
0.61
(0.02)
0.18 (0.03) 0.40
(0.02)
0.89
(0.01)
0.73
(0.01)
CTMW 0.57 (0.10) 0.77
(0.05)
0.26 (0.12) 0.71
(0.09)
0.57
(0.09)
0.41
(0.06)
0.28 (0.02) 0.68
(0.01)
0.43
(0.02)
0.21
(0.02)
CTmus
c
0.25 (0.14) 0.37
(0.12)
ns 0.39
(0.12)
0.32
(0.13)
0.49
(0.11)
0.39 (0.06) 0.35
(0.02)
0.12
(0.03)
0.07
(0.03)
CTema 0.54 (0.12) 0.54
(0.09)
0.28 (0.12) 0.87
(0.06)
0.54
(0.11)
0.74
(0.06)
0.47 (0.10) 0.40
(0.06)
0.21
(0.03)
0.09
(0.03)
PIMF1 0.62 (0.12) 0.54
(0.09)
0.58 (0.09) 0.29
(0.13)
0.88
(0.03)
0.38
(0.12)
0.22 (0.13) 0.24
(0.13)
0.42
(0.07)
0.91
(0.01)
PIMF2 0.38 (0.15) 0.27
(0.13)
0.56 (0.11) ns 0.68
(0.08)
ns ns ns 0.92
(0.02)
0.31
(0.07)
22/11/2015 24
0
0.5
1
1.5
2
2.5
3
3.5
4
0 2 4 6 8 10 12
CT
IM
F
CT Carcass fat