current status of genomic evaluation for u.s. dairy cattle
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Wiggans, 2013China Emerging Markets Program Seminar
Dr. George R. WiggansAnimal Improvement Programs LaboratoryAgricultural Research Service, USDABeltsville, MD 20705-2350301-504-8407 (voice) 301-504-8092 (fax)george.wiggans@ars.usda.gov
Current statusof genomic evaluation forU.S. dairy cattle
Wiggans, 2013China Emerging Markets Program Seminar
Genotypes received (last 12 months)
Breed Female MaleAll
animalsFemale:
maleAyrshire 515 337 852 60:40Brown Swiss 701 606 1,307 54:46Holstein 149,712 28,191 177,903 84:16Jersey 18,600 3,059 21,659 86:14All 169,528 32,193 201,721 84:16
Wiggans, 2013China Emerging Markets Program Seminar
Genomic data flow
DNA samples
genotypes
genomic
evaluations
nominati
ons,
pedigr
ee dat
a
genotype
quality reportsge
nomic
evalu
ations
DNA sam
ples
genotypes
DNA samples
Dairy Herd Improvement (DHI) producer
Council on Dairy Cattle Breeding (CDCB)
DNA laboratory AI organization,breed association
Wiggans, 2013China Emerging Markets Program Seminar
Evaluation flow
Animal nominated for genomic evaluation by breed association or AI organization
Hair or other DNA source sent to genotyping lab
Source Samples (no.) Samples (%)Blood 27,043 14Hair 116,833 59Nasal swab 4,619 2Semen 4,119 2Tissue 45,018 23
Wiggans, 2013China Emerging Markets Program Seminar
Evaluation flow (continued)
DNA extracted and placed on chip for 3-day genotyping process
Genotypes sent fromgenotyping lab to CDCB for accuracy review
Wiggans, 2013China Emerging Markets Program Seminar
Laboratory quality control
Each SNP evaluated for Call rate Portion heterozygous Parent-progeny conflicts
Clustering investigated if SNP exceeds limits
Number of failing SNPs indicates genotype quality
Target of <10 SNPs in each category
Wiggans, 2013China Emerging Markets Program Seminar
Before clustering adjustment
86% call rate
Wiggans, 2013China Emerging Markets Program Seminar
After clustering adjustment
100% call rate
Wiggans, 2013China Emerging Markets Program Seminar
Evaluation flow (continued)
Genotype calls modified as necessary
Genotypes loaded into database
Nominators receive reports of parentage and other conflicts
Pedigree or animal assignments corrected
Genotypes extracted and imputed to 45K
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Imputation
Based on splitting genotype into individual chromosomes (maternal and paternal contributions)
Missing SNPs assigned by tracking inheritance from ancestors and descendants
Imputed dams increase predictor population
Genotypes from all chips merged by imputing SNPs not present
Wiggans, 2013China Emerging Markets Program Seminar
findhap
Developed by Dr. Paul VanRaden, ARS, USDA
Divides chromosomes into segments
Allows for successively shorter segments (usually 3 runs) Long segments lock in identical by descent Shorter segments fill in missing SNPs
Separates genotype into maternal and paternal contribution, haplotypes (phasing)
Builds haplotype library sequenced by frequency
Wiggans, 2013China Emerging Markets Program Seminar
Evaluation flow (continued)
SNP effects estimated
Final evaluations calculated
Evaluations released to dairy industry Download from CDCB FTP site with
separate files for each nominator Monthly release for new animals All genomic evaluations updated
3 times each year with traditional evaluations
Wiggans, 2013China Emerging Markets Program Seminar
Information sources for evaluations
Traditional evaluations of genotyped bulls and cows used to estimate SNP effects
Combined final evaluation Sum of SNP effects for an animal’s alleles Polygenetic effect Traditional evaluation
Pedigree data used and validated by genotypes
Wiggans, 2013China Emerging Markets Program Seminar
Genotypes evaluated
Jun A O Jan F A M J J A S O N D Jan F M A M J J A S O N D Jan F M A M J J A S O N D Jan F M A M J J A S0
50,000
100,000
150,000
200,000
250,000
300,000
350,000
400,000Young imputed
Old imputed
Female Young <50K
Male Young <50K
Female Old <50K
Male Old <50K
Female Young >=50K
Male Young >=50K
Female Old >=50K
Male Old >=50K
Evaluation date
Ani
mal
s ge
noty
ped
(no.
)
Imputed, youngImputed, old (young cows included before March 2012) <50K, young, female<50K, young, male<50K, old, female<50K, old, male ( 20 bulls)50K, young, female50K, young, male50K, old, female50K, old, male
2013201220112009 2010
Wiggans, 2013China Emerging Markets Program Seminar
Holstein prediction accuracy
*2013 deregressed value – 2009 genomic evaluation
Trait Bias* Reliability (%)Reliability gain
(% points)Milk (kg)
−80.369.2 30.3
Fat (kg)−1.4
68.4 29.5
Protein (kg)−0.9
60.9 22.6
Fat (%) 0.0 93.7 54.8Protein (%) 0.0 86.3 48.0Productive life (mo)
−0.773.7 41.6
Somatic cell score 0.0 64.9 29.3Daughter pregnancy rate (%) 0.2 53.5 20.9Sire calving ease 0.6 45.8 19.6Daughter calving ease
−1.844.2 22.4
Sire stillbirth rate 0.2 28.2 5.9Daughter stillbirth rate 0.1 37.6 17.9
Wiggans, 2013China Emerging Markets Program Seminar
Holstein prediction accuracy
*2013 deregressed value – 2009 genomic evaluation
Trait Bias* Reliability (%)Reliability gain
(% points)Final score 0.1 58.8 22.7Stature
−0.268.5 30.6
Dairy form−0.2
71.8 34.5
Rump angle 0.0 70.2 34.7Rump width
−0.265.0 28.1
Feed and legs 0.2 44.0 12.8Fore udder attachment
−0.270.4 33.1
Rear udder height −0.1
59.4 22.2
Udder depth −0.3
75.3 37.7
Udder cleft−0.2
62.1 25.1
Front teat placement −0.2
69.9 32.6
Teat length−0.1
66.7 29.4
Wiggans, 2013China Emerging Markets Program Seminar
Genotypes by animal age (last 12 months)
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24-35
36-47
48-59
60
0
5,000
10,000
15,000
20,000
25,000
30,000 Holstein male Holstein female Jersey male Jersey female
Age (mo)
Freq
uenc
y (n
o)
Wiggans, 2013China Emerging Markets Program Seminar
Parent ages for marketed Holstein bulls
Birth year
Dam
0
10
20
30
40
50
60
70
80
90
100
2007 2008 2009 2010 2011 2012
Pare
nt a
ge (m
o)
Sire
Wiggans, 2013China Emerging Markets Program Seminar
Marketed Holstein bulls
Year entered
AI
Traditional progeny-
testedYoung
genotypedAll
bulls2008 1,798 0 1,7982009 1,909 337 2,2462010 1,827 376 2,2032011 1,441 467 1,9082012 1,376 555 1,931
Wiggans, 2013China Emerging Markets Program Seminar
Genetic merit of marketed Holstein bulls
00 01 02 03 04 05 06 07 08 09 10 11 12-100
0
100
200
300
400
500
600
Year entered AI
Aver
age
net m
erit
($)
Average gain:$20.21/year
Average gain:$43.76/year
Average gain:$77.51/year
Wiggans, 2013China Emerging Markets Program Seminar
0 1 2 3 4 5
Genomic prediction of progeny test
Select parents, transfer embryos
to recipients
Calves born and
DNA tested
Calves born from DNA-selected
parents
Bull receives progeny test
Reduce generation interval from 5 to 2 years
Wiggans, 2013China Emerging Markets Program Seminar
Benefit of genomics
Determine value of bull at birth
Increase accuracy of selection
Reduce generation interval
Increase selection intensity
Increase rate of genetic gain
Wiggans, 2013China Emerging Markets Program Seminar
Why genomics works for dairy cattle
Extensive historical data available
Well-developed genetic evaluation program
Widespread use of AI sires
Progeny-test programs
High-value animals worth the cost of genotyping
Long generation interval that can be reduced substantially by genomics
Wiggans, 2013China Emerging Markets Program Seminar
Current organizational roles
Council on Dairy Cattle Breeding (CDCB) responsible for receiving data, computing, and delivering U.S. genetic evaluations for dairy cattle
Animal Improvement Programs Laboratory (AIPL) responsible for research and development to improve the evaluation system
CDCB and USDA employees co-located in Beltsville
Wiggans, 2013China Emerging Markets Program Seminar
Funding
CDCB evaluation calculation and dissemination funded by fee system Based on animals genotyped About 80% of revenue from bulls Higher fees for herds that
contribute less information
AIPL research on evaluation methodology funded by U.S. Federal government
$
Wiggans, 2013China Emerging Markets Program Seminar
Ways to increase accuracy
Automatic addition of traditional evaluations of genotyped bulls when bull is 5 years old
Possible genotyping of 10,000 bulls with semen in repository
Collaboration with other countries
Use of more SNPs from HD chips
Full sequencing (identify causative mutations)
Wiggans, 2013China Emerging Markets Program Seminar
Evaluation accuracy by included SNPs
*Difference in reliability from 45K in parentheses
Reliability (%)*Trait 45KMilk 69.2Fat 68.4
Protein 60.9Fat percentage 93.7Protein percentage 86.3Net merit 51.6Productive life 73.7Somatic cell score 64.9Daughter pregnancy rate 53.4Service-sire calving ease 45.8Daughter calving ease 44.2Service-sire stillbirth rate 28.2Daughter stillbirth rate 37.6
60K69.3 (0.1)68.7 (0.3)60.8 (–0.1)94.4 (0.7)87.1 (0.8)51.7 (0.1)74.0 (0.3)65.8 (0.9)54.1 (0.7)45.7 (–0.1)45.8 (1.6)28.3 (0.1)37.8 (0.2)
75K68.9 (–0.3)68.6 (0.2)60.6 (–0.3)93.9 (0.2)86.3 (0.0)51.6 (0.0)73.1 (–0.6)65.6 (0.7)53.6 (0.2)45.1 (–0.7)44.9 (0.7)28.7 (0.5)37.1 (–0.5)
91K69.2 (0.0)68.4 (0.0)60.8 (–0.1)93.5 (–0.2)86.1 (–0.2)51.3 (–0.3)73.8 (0.1)65.6 (0.7)53.8 (0.4)46.2 (0.4)44.9 (0.7)29.9 (1.7)39.2 (1.6)
Wiggans, 2013China Emerging Markets Program Seminar
Evaluation accuracy (continued)
*Difference in reliability from 45K in parentheses
Reliability (%)*Trait 45KFinal score 58.8Stature 68.5Dairy form 71.8Rump angle 70.2Rump width 65.0Feet and legs 44.0Fore udder attachment 70.4Rear udder height 59.4Udder depth 75.3Udder cleft 62.1Front teat placement 69.9Teat length 66.7
60K58.7 (–0.1)69.0 (0.5)72.2 (0.4)70.9 (0.7)65.4 (0.4)45.1 (1.1)70.6 (0.2)59.9 (0.5)76.2 (0.9)62.2 (0.1)70.1 (0.2)67.2 (0.5)
75K58.4 (–0.4)68.8 (0.3)71.9 (0.1)70.7 (0.5)65.0 (0.0)45.1 (1.1)70.0 (–0.4)59.6 (0.2)76.0 (0.7)62.0 (–0.1)70.2 (0.3)66.6 (–0.1)
91K58.7 (–0.1)69.1 (0.6)72.0 (0.2)70.9 (0.7)65.2 (0.2)45.1 (1.1)70.4 (0.0)59.8 (0.4)76.1 (0.8)62.2 (0.1)70.4 (0.5)66.9 (0.2)
All production, type, and fitness traits (0.5) (0.1) (0.4)
Wiggans, 2013China Emerging Markets Program Seminar
Key issues for the dairy industry
Inbreeding and genetic diversity(including across breeds)
Sequencing, new genes, and mutations
Novel traits, resource populations(feed efficiency, health, milk properties)
Wiggans, 2013China Emerging Markets Program Seminar
Application to more traits
Animal’s genotype good for all traits
Traditional evaluations required for accurate estimates of SNP effects
Traditional evaluations not currently available for heat tolerance or feed efficiency
Research populations could provide data for traits that are expensive to measure
Will resulting evaluations work in target population?
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What’s already planned
Genomic evaluations for new traits Health (e.g., resistance to heat stress) Feed efficiency
Genomic mating programs Selection of favorable minor alleles Reduction of genomic inbreeding
Genomic evaluations based on more SNPs (60K)
Adding SNPs for causative genetic variants
Wiggans, 2013China Emerging Markets Program Seminar
What’s already planned (continued)
BARD project (Volcani Center, Israel) A priori granddaughter design (APGD) Identification of causative variants for
economically important traits
International collaboration on sequencing United States, United Kingdom, Italy, Canada Bulls selected using APGD
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Parentage validation and discovery
Parent-progeny conflicts detected Animal checked against all other genotypes Reported to breeds and requesters Correct sire usually detected
Maternal grandsire (MGS) checking SNP at a time checking Haplotype checking more accurate
Breeds moving to accept SNPs in place of microsatellites
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MGS detection — HAP method
Based on common haplotypes
After imputation of all loci, determine maternal contribution by removing paternal haplotype
Count maternal haplotypes in common with MGS
Remove haplotypes from MGS and check remaining against maternal great-grandsire (MGGS)
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MGS detection — SNP method
Based on SNP conflicts
Check if animal and MGS have opposite homozygotes (duo test)
If sire is genotyped, some heterozygous SNPs can be checked (trio test)
Wiggans, 2013China Emerging Markets Program Seminar
MGS detection by breed
Ancestors confirmed (%)SNP method HAP method
Breed MGS MGS MGGSBrown Swiss 94 97 85Holstein 95 97 92Jersey 91 95 95
Wiggans, 2013China Emerging Markets Program Seminar
Haplotypes affecting fertility
Rapid discovery of new recessive defects Large numbers of genotyped animals Affordable DNA sequencing
Determination of haplotype location Significant number of homozygous animals
expected, but none observed Narrow suspect region with fine mapping Use sequence data to find causative mutation
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Haplotypes affecting fertility
*Causative mutation known
Name
BTAchromo-
someLocation*
(Mbp)
Carrierfrequency
(%) Earliest known ancestorHH1 5 63.2* 4.5 Pawnee Farm Arlinda ChiefHH2 1 94.9–96.6 4.6 Willowholme Mark AnthonyHH3 8 95.4* 4.7 Glendell Arlinda Chief,
Gray View SkylinerHH4 1 1.3* 0.7 Besne BuckHH5 9 92.4–93.9 4.4 Thornlea Texal SupremeJH1 15 15.7* 23.4 Observer Chocolate SoldierBH1 7 42.8–47.0 14.0 West Lawn Stretch ImproverBH2 19 10.6–11.7 15.4 Rancho Rustic My DesignAH1 17 65.9–66.2 23.6 Selwood Betty’s Commander
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Haplotype tracking of known recessives
*Causative mutation known
Recessive Haplotype
BTAchromo-
some
Testedanimals
(no.)Concord-ance (%)
New carriers
(no.)BLAD HHB 1* 11,782 99.9 314CVM HHC 3* 13,226 — 2,716DUMPS HHD 1* 3,242 100.0 3Mule foot HHM 15* 87 97.7 120Polled HHP 1 345 — 2,050Red coat color HHR 18* 4,137 — 5,927SDM BHD 11* 108 94.4 108SMA BHM 24* 568 98.1 111Weaver BHW 4 163 96.3 32
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Progression of chips
2008 2009 2010
Official 3Kevaluations
DecUnofficial 3K
evaluations
Sep
Bovine3K BeadChip
(3K)Jul
BovineHD BeadChip
(777K)Jan
Official 50K Brown Swiss evaluations
AugOfficial 50K
Holstein & Jersey evaluations
JanUnofficial 50K
evaluations
Apr
BovineSNP50 BeadChip
(50K)Jan
2011 2012 2013
Official 12K evaluations
Oct
Zoetis LD BeadChip (12K)Sep
GGP v2 BeadChip
(19K)May
Official 19K evaluations
MayOfficial 77K evaluations
Jan
GGP HD BeadChip
(77K)Dec
Official 8K evaluations
Mar
GeneSeek Genomic Profiler (GGP) BeadChip (8K)Feb
Official7K & 648K
evaluations
Dec
BovineLD BeadChip
(7K)Sep
Official 777K evaluations
Aug
Affymetrix BOS 1 Plate Array
(648K)Jan
Wiggans, 2013China Emerging Markets Program Seminar
International dairy breeding
Genotype alliances North America (US, Canada, UK, Italy) Ireland, New Zealand Netherlands, Australia Eurogenomics (Denmark/Sweden/Finland, France,
Germany, Netherlands/Belgium, Spain, Poland)
Interbull genomic multitrait across-country evaluation (GMACE)
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GMACE reference populations (August)
Country Animals (no.)Australia 5,314Denmark/Finland/Sweden 23,961France 24,313Germany 25,624Italy 21,041Netherlands 23,047Poland 3,174Switzerland (Red Holstein) 4,194
Wiggans, 2013China Emerging Markets Program Seminar
Impact on breeders
Haplotype and gene tests in selection and mating programs
Trend towards a small number of elite breeders that are investing heavily in genomics
About 30% of young males genotypeddirectly by breeders since April 2013
Prices for top genomic heifers can bevery high (e.g., $265,000 )
Wiggans, 2013China Emerging Markets Program Seminar
Impact on dairy producers
General
Reduced generation interval
Increased rate of genetic gain
More inbreeding/homozygosity?
Wiggans, 2013China Emerging Markets Program Seminar
Impact on dairy producers (continued)
Sires
Higher average genetic merit of available bulls
More rapid increase in genetic merit for all traits
Larger choice of bulls in terms of traits and semen price
Greater use of young bulls
Wiggans, 2013China Emerging Markets Program Seminar
Conclusions
Genomic evaluation has dramatically changed dairy cattle breeding
Rate of gain is increasing primarily because of a large reduction in generation interval
Genomic research is ongoing Detect causative genetic variants Find more haplotypes affecting fertility Improve accuracy through more SNPs, more
predictor animals, and more traits
Wiggans, 2013China Emerging Markets Program Seminar
U.S. genomic evaluation team
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