Genetic Evaluation of Calving Traits in US Holsteins

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J.B. ColeJ.B. Cole
Animal Improvement Programs Laboratory
Agricultural Research Service, USDA, Beltsville, MD
jcole@aipl.arsusda.gov
Genetic Evaluation of CalvingGenetic Evaluation of Calving
Traits in US HolsteinsTraits in US Holsteins

CSU 2006 – Breeding and Genetics Seminar (2) Cole
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IntroductionIntroduction
 A national evaluation was implemented
for calving ease (CE) in August 2002 and
for stillbirth (SB) for Holstein in August
2006.
 A calving ability index (CA$) which
includes SB and calving ease (CE) was
developed.
 Some challenges with the CE and SB
evaluations remain

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Calving Ease DefinitionCalving Ease Definition
 Reported on a five-point scale:
1 = No problem
2 = Slight problem
3 = Needed assistance
4 = Considerable force
5 = Extreme difficulty
 Scores of 4 and 5 are combined

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Stillbirth DefinitionStillbirth Definition
 Reported on a three-point scale:
 Scores of 2 and 3 are combined
1 = calf born alive,
2 = calf born dead,
3 = calf died within 48 h of
parturition.

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Distribution of Stillbirth and CalvingDistribution of Stillbirth and Calving
Ease ScoresEase Scores
7,484,30929,320348,6775,348,0291,758,283Total
96,0871,27232,19638,92923,6905
207,2421,74037,851108,03759,6144
633,0293,35370,522375,203183,9513
738,8532,53749,858482,720203,7382
5,809,09820,418158,2504,343,1401,287,2901
Total3210
CalvingEaseScore
Stillbirth Score

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Stillbirth Records by LactationStillbirth Records by Lactation
0
100
200
300
400
500
1980 1990 2000
Birth Year
NumberofRecords(thousands)
3
2
1

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Detecting Stillbirth Data ErrorsDetecting Stillbirth Data Errors
0
5
10
15
1980
1983
1986
1989
1992
1995
1998
2001
2004
Birth Year
Percentage
%SB
%DB

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Data and EditsData and Edits
 7 million SB records were available for
Holstein cows calving since 1980
 Herds needed ≥10 calving records
with SB scores of 2 or 3 for inclusion
 Herd-years were required to include
≥20 records
 Only single births were used (no
twins)

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Sire-MGS Threshold ModelSire-MGS Threshold Model
 Implemented for calving ease (Aug
2002) and stillbirth (Aug 2006)
 Sire effects allow for corrective
matings in heifers to avoid large
calves
 MGS effects control against
selection for small animals which
would have difficulty calving

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Genetic Evaluation ModelGenetic Evaluation Model
 A sire-maternal grandsire (MGS)
threshold model was used:
• Fixed: year-season, parity-sex, sire and
MGS birth year
• Random: herd-year, sire, MGS
 (Co)variance components were
estimated by Gibbs sampling
• Heritabilities are 3.0% (direct) and 6.5%
(MGS)
ijklnoprnplonlkjiijklnopr emsBMBSPSYShyy +++++++= ijklnoprnplonlkjiijklnopr emsBMBSPSYShyy +++++++= ijklnoprnplonlkjiijklnopr emsBMBSPSYShyy +++++++=

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Trait DefinitionTrait Definition
 PTA are expressed as the expected
percentage of stillbirths
 Direct SB measures the effect of the calf
itself
 Maternal SB measures the effect of a
particular cow (daughter)
 A base of 8% was used for both traits:
 Direct: bulls born 1996–2000
 Maternal: bulls born 1991–1995

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Phenotypic Trend for StillbirthsPhenotypic Trend for Stillbirths
0
2
4
6
8
10
12
14
1980
1983
1986
1989
1992
1995
1998
2001
2004
Birth Year
%Stillbirth
Heifers
Cows
All animals

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Genetic Trend for StillbirthsGenetic Trend for Stillbirths
5.0
6.0
7.0
8.0
9.0
10.0
1980 1985 1990 1995 2000
Birth Year
%SBH
Direct
Maternal

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Distribution of PTADistribution of PTA
0
5
10
15
20
25
30
35
40
6.1-6.56.6-7.07.1-7.57.6-8.08.1-8.58.6-9.09.1-9.59.6-10.010.1-10.510.6-11.011.1-11.511.6-12.0
>12.0
%SBH
PercentofScores
Direct
Maternal

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Distribution of ReliabilitiesDistribution of Reliabilities
0
5
10
15
20
25
30
35
40
45
50 41-45
46-50
51-55
56-60
61-65
66-70
71-75
76-80
81-85
86-90
91-95
96-99
Reliability
Percentage
Direct
Maternal

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Dystocia and StillbirthDystocia and Stillbirth
 Meyer et al. (2001) make a strong argument for
the inclusion of dystocia in models for SB
 Difficulty of interpretation - formidable
educational challenge
 Interbull trait harmonization - none of the
March 2006 test run participants included
dystocia in their models
 Changes in sire and MGS solutions on the
underlying scale between models were small

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Evaluation ConclusionsEvaluation Conclusions
 Reliabilities for SB averaged 45%
versus 60% for CE
 Phenotypic and genetic trends
from 1980 to 2005 were both small
 An industry-wide effort is
underway to improve recording of
calf livability

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Index DataIndex Data
 7 million SB records were available for
Holstein cows calving since 1980
 Calvings with unknown MGS were
eliminated for VCE
 Records with sire and MGS among the
2,600 most-frequently appearing bulls
were selected

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Data (cont’d)Data (cont’d)
 Herds needed ≥10 calving records with SB
scores of 2 or 3 in the database to be
included
 Herd-years were required to include ≥20
records and only single births were used
 Inclusion of all records for a cow was not
guaranteed
 The final dataset included 2,083,979 calving
records from 5,765 herds and 33,304 herd-
years

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SamplingSampling
 Six datasets ofSix datasets of ~250,000~250,000 records each wererecords each were
created by randomly sampling herd codescreated by randomly sampling herd codes
without replacementwithout replacement
 Datasets ranged fromDatasets ranged from 239,192239,192 toto 286,794286,794
observations, and all averagedobservations, and all averaged 7%7% stillbirthsstillbirths
 A common pedigree file was used to facilitateA common pedigree file was used to facilitate
comparisons between sire and MGS solutionscomparisons between sire and MGS solutions

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Bayesian (co)variance componentsBayesian (co)variance components
estimatesestimates
Var(Sire) Var(MGS) Cov(S-MGS)
Sample Mean SD Mean SD Mean SD
1 0.010 0.002 0.018 0.002 0.004 0.001
2 0.007 0.002 0.017 0.002 0.005 0.001
3 0.009 0.001 0.019 0.002 0.005 0.001
4 0.008 0.001 0.019 0.002 0.004 0.001
5 0.008 0.001 0.018 0.002 0.002 0.001
6 0.009 0.002 0.017 0.002 0.004 0.001
Mean 0.009 0.002 0.018 0.002 0.004 0.001

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HeritabilitiesHeritabilities
 Calving Ease (Direct) 8.6%
 Calving Ease (MGS) 3.6%
 Stillbirth (Direct) 3.0%
 Stillbirth (MGS) 6.5%

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Genetic Correlations Among SB and CEGenetic Correlations Among SB and CE
Trait
CE SB
Direct Maternal Direct Maternal
CE
Direct 1.00 0.46 0.67 0.25
Maternal 1.00 0.29 0.63
SB
Direct 1.00 0.28
Maternal 1.00

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Economic AssumptionsEconomic Assumptions
 Newborn calf value
 Expenses per difficult birth (CE ≥4)
$450 for females
$150 for males
$75 labor and veterinary
$100 reduced milk yield
$75 reduced fertility and longevity
1.5% chance of cow death ($1800)

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Calving Ability IndexCalving Ability Index
 CA$ has a genetic correlation of 0.85 with
the combined direct and maternal CE
values in 2003 NM$ and 0.77 with
maternal CE in TPI
 Calving traits receive 6% of the total
emphasis in NM$ (August 2006 revision)
(DCE ) (MCE ) (DSB ) (MSCA$ B )= − − − − − − − −4 8 3 8 4 8 8 8

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Breeds Other Than HolsteinBreeds Other Than Holstein
 Brown Swiss economic values are
−6 for SCE and −8 for DCE
• Separate SB evaluations are not
available
• CE values include the correlated
response in SB
 Other breeds will be assigned CA$
of 0

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Calving Ease Genetic CorrelationsCalving Ease Genetic Correlations
Service sire above diagonal, daughter belowService sire above diagonal, daughter below
Ctry CAN DNK FRA ITA NLD SWE USA
CAN .87 .81 .70 .80 .86 .75
DNK .84 .93 .77 .86 .96 .90
FRA .80 .80 .74 .84 .91 .88
ITA .58 .59 .85 .60 .70 .61
NLD .89 .81 .79 .59 .89 .79
SWE .75 .82 .89 .78 .69 .86
USA .71 .78 .93 .76 .77 .87

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Stillbirth Genetic CorrelationsStillbirth Genetic Correlations
Service sire above diagonal, daughter belowService sire above diagonal, daughter below
Ctry DNK FIN ISR NLD SWE USA
DNK .85 .82 .67 .92 .70
FIN .82 .77 .64 .82 .65
ISR .67 .70 .73 .80 .66
NLD .82 .77 .60 .65 .63
SWE .88 .92 .65 .73 .64
USA .81 .87 .60 .71 .87

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Brown Swiss Calving EaseBrown Swiss Calving Ease
Service sire correlations above diagonal, daughter belowService sire correlations above diagonal, daughter below
Ctry CHE DEU NLD USA
CHE .83 .81 .68
DEU .61 .77 .67
NLD .89 .76 .79
USA .70 .61 .76

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Index ConclusionsIndex Conclusions
 A routine evaluation for stillbirth in US
Holsteins was implemented in August 2006
 Direct and maternal stillbirth were included in
NM$ for Holsteins starting in August 2006
 August 2006 data were included in the
September 2006 Interbull test run
 The US will participate in routine Interbull
evaluations beginning in November 2006

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Recent Calving Ease ResearchRecent Calving Ease Research

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Abnormal Herd-YearsAbnormal Herd-Years
 Many herd-years have abnormal
distributions of scores
 Two recent approaches to problem
• Eliminate HY based on GoF tests
• Collapse categories when mode > 1
 Both strategies improve prediction
of later evaluations by earlier

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An IllustrationAn Illustration
 Herds with unusual distributions of data affect evaluations of
bulls
 Worst case is when large share of records for a bull are in
one “bad” herd
 Herd reporting changes over time
0
20
40
60
80
100
1 2 3 4 5
Calving Ease Scores - Herd 1
ScorebyHerd(%)
Parity 1
Parity 2
0
20
40
60
80
100
1 2 3 4 5
Calving Ease Scores - Herd 2
ScorebyHerd(%)

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Test Edits -Test Edits - χχ22
GoF statisticsGoF statistics
 Based on multinomial distributions
 Independent of herd size
=
= ∑
2
i i,1 i,2 i,3 i,4 i,5
i 1 i
Log(Multi(N ,n ,n ,n ,n ,n ,P))
GoF
N

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Percentage of Score by Parity In AllPercentage of Score by Parity In All
(AN) and GoF Excluded (AG) Herds(AN) and GoF Excluded (AG) Herds
0
10
20
30
40
50
60
70
80
90
100
1 2 3 4 5
Calving Ease Score
CountsbyHerd-Parity(%)
Parity 1 - AN
Parity 2 - AN
Parity 1 - AG
Parity 2 - AG

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Collapse CategoriesCollapse Categories
 The mode for CE scores in a herd is
expected to be 1, but was higher for
nearly 10% of data
 Data from herd-years with a mode of 4
or 5 (1.2%) were deleted
 A mode of 3 is assumed to indicate that
the scorer normalized the data (middle
score of 3 for an 'average' birth)

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Collapse CategoriesCollapse Categories
 Herds with a mode of 2 or 3: scores up to the
mode were changed to 1, and scores greater
than the mode were decreased accordingly
 Herd-years with a mode of 3: scores 1-3 all
become 1, scores of 4 are changed to 2, and
scores of 5 are changed to 3
 Combining categories lowered the portion of
difficult calvings and increased the impact of
the subsequent goodness-of-fit test
 Overall, 6.4% of data were excluded

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ConclusionsConclusions
 Exclusion of herds with poor
distributions improves prediction of
future evaluations across birth years
• Correlations across all data increased from .
66 to .68
 Herds with poor score distributions
were excluded uniformly across herd
size
 Exclusion of herds results in loss of
evaluations for some bulls

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Separate Parity EffectsSeparate Parity Effects
 First and later parities currently
modelled as a single trait
 cblup90iod only accepts one
threshold trait
 Options for bivariate analysis
• Gibbs sampling (thrgibbs1)
• Linearization (airemlf90)
• RR on parity (cblup90iod)

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ResultsResults
 RR on a 0-1 parity effect does not
account for heterogeneous variances
 GS and AIREML solutions were similar
• GS required more processing time than is
desirable for routine national evaluations
• The impact of the approximation necessary
to linearize the scores is not known
 Implementation of a bivariate analysis is
desirable, but challenging

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AcknowledgmentsAcknowledgments
 Jeff Berger, Iowa State University
 John Clay, Dairy Records Management
Systems
 Ignacy Misztal and Shogo Tsuruta,
University of Georgia
 National Association of Animal Breeders

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Genetic Evaluation of Calving Traits in US Holsteins