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Current status of genomic evaluation for U.S. dairy cattle. Genotypes received (last 12 months). Genomic data flow. Dairy Herd Improvement (DHI) producer. DNA samples. DNA samples. genomic evaluations. DNA samples. DNA laboratory. AI organization, breed association. genotypes.

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Current status of genomic evaluation for u s dairy cattle

Current statusof genomic evaluation forU.S. dairy cattle


Genotypes received last 12 months
Genotypes received (last 12 months)


Genomic data flow
Genomic data flow

Dairy Herd Improvement (DHI) producer

DNA samples

DNA samples

genomic

evaluations

DNA samples

DNA laboratory

AI organization,

breed association

genotypes

nominations,

pedigree data

genotypes

genotype

quality reports

genomic

evaluations

Council on Dairy Cattle Breeding (CDCB)


Evaluation flow
Evaluation flow

  • Animal nominated for genomic evaluation by breed association or AI organization

  • Hair or other DNA source sent to genotyping lab


Evaluation flow continued
Evaluation flow (continued)

  • DNA extracted and placed on chip for 3-day genotyping process

  • Genotypes sent from

    genotyping lab to CDCB

    for accuracy review


Laboratory quality control
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




Evaluation flow continued1
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


Imputation
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


Findhap
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


Evaluation flow continued2
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


Information sources for evaluations
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



Holstein prediction accuracy
Holstein prediction accuracy

*2013 deregressed value – 2009 genomic evaluation


Holstein prediction accuracy1
Holstein prediction accuracy

*2013 deregressed value – 2009 genomic evaluation


Genotypes by animal age last 12 months
Genotypes by animal age (last 12 months)


Parent ages for marketed holstein bulls
Parent ages for marketed Holstein bulls

100

90

Sire

80

Dam

70

60

Parent age (mo)

50

40

30

20

10

0

2007

2008

2009

2010

2011

2012

Birth year



Genetic merit of marketed holstein bulls
Genetic merit of marketed Holstein bulls

Average gain:

$77.51/year

Average gain:

$43.76/year

Average gain:

$20.21/year


Genomic prediction of progeny test
Genomic prediction of progeny test

0

1

2

3

4

5

  • Select parents, transfer embryos to recipients

Calves born from DNA-selected parents

Bull receives progeny test

  • Calves born and DNA tested

Reduce generation interval from 5 to 2 years


Benefit of genomics
Benefit of genomics

  • Determine value of bull at birth

  • Increase accuracy of selection

  • Reduce generation interval

  • Increase selection intensity

  • Increase rate of genetic gain

Bovine G-Nome


Why genomics works for dairy cattle
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


Current organizational roles
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


Funding
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

$


Ways to increase accuracy
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)


Evaluation accuracy by included snps
Evaluation accuracy by included SNPs

Reliability

(%)*

Trait

45K

60K

75K

91K

Milk

69.2

69.3

(0.1)

68.9

(

0.3)

69.2

(0.0)

Fat

68.4

68.7

(0.3)

68.6

(0.2)

68.4

(0.0)

Protein

60.9

60.8

(

0.1)

60.6

(

0.3)

60.8

(

0.1)

Fat percentage

93.7

94.4

(0.7)

93.9

(0.2)

93.5

(

0.2)

Protein percentage

86.3

87.1

(0.8)

86.3

(0.0)

86.1

(

0.2)

Net merit

51.6

51.7

(0.1)

51.6

(0.0)

51.3

(

0.3)

Productive life

73.7

74.0

(0.3)

73.1

(

0.6)

73.8

(0.1)

Somatic cell score

64.9

65.8

(0.9)

65.6

(0.7)

65.6

(0.7)

Daughter pregnancy rate

53.4

54.1

(0.7)

53.6

(0.2)

53.8

(0.4)

Service

-

sire

calving ease

45.8

45.7

(

0.1)

45.1

(

0.7)

46.2

(0.4)

Daughter calving ease

44.2

45.8

(1.6)

44.9

(0.7)

44.9

(0.7)

Service

-

sire stillbirth rate

28.2

28.3

(0.1)

28.7

(0.5)

29.9

(1.7)

Daughter

stillbirth rate

37.6

37.8

(0.2)

37.1

(

0.5)

39.2

(1.6)

*Difference in reliability from 45K in parentheses


Evaluation accuracy continued
Evaluation accuracy (continued)

Reliability

(%)*

Trait

45K

60K

75K

91K

Final

score

58.8

58.7

(

0.1)

58.4

(

0.4)

58.7

(

0.1)

Stature

68.5

69.0

(0.5)

68.8

(0.3)

69.1

(0.6)

Dairy

form

71.8

72.2

(0.4)

71.9

(0.1)

72.0

(0.2)

Rump

angle

70.2

70.9

(0.7)

70.7

(0.5)

70.9

(0.7)

Rump

width

65.0

65.4

(0.4)

65.0

(0.0)

65.2

(0.2)

Feet and

legs

44.0

45.1

(1.1)

45.1

(1.1)

45.1

(1.1)

Fore

udder attachment

70.4

70.6

(0.2)

70.0

(

0.4)

70.4

(0.0)

Rear

udder height

59.4

59.9

(0.5)

59.6

(0.2)

59.8

(0.4)

Udder

depth

75.3

76.2

(0.9)

76.0

(0.7)

76.1

(0.8)

Udder

cleft

62.1

62.2

(0.1)

62.0

(

0.1)

62.2

(0.1)

Front

teat placement

69.9

70.1

(0.2)

70.2

(0.3)

70.4

(0.5)

Teat

length

66.7

67.2

(0.5)

66.6

(

0.1)

66.9

(0.2)

All production, type, and fitness

traits

(0.5)

(0.1)

(0.4)

*Difference in reliability from 45K in parentheses


Key issues for the dairy industry
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)


Application to more traits
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?


What s already planned
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


What s already planned continued
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


Parentage validation and discovery
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

Who’s your daddy?


Mgs detection hap method
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)


Mgs detection snp method
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)



Haplotypes affecting fertility
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


Haplotypes affecting fertility1
Haplotypes affecting fertility

*Causative mutation known


Haplotype tracking of known recessives
Haplotype tracking of known recessives

*Causative mutation known


Progression of chips
Progression of chips

BovineSNP50 BeadChip

(50K)

BovineHD BeadChip

(777K)

Bovine3K BeadChip

(3K)

Jan

Jan

Jul

2008

2009

2010

Apr

Jan

Aug

Sep

Dec

Unofficial 50K evaluations

Official 50K Holstein & Jersey evaluations

Official 50K Brown Swiss evaluations

Unofficial 3K

evaluations

Official 3K

evaluations

BovineLD BeadChip

(7K)

GeneSeek Genomic Profiler (GGP) BeadChip (8K)

GGP HD BeadChip

(77K)

GGP v2 BeadChip

(19K)

Zoetis LD BeadChip

(12K)

Affymetrix BOS 1 Plate Array

(648K)

Jan

Sep

Feb

Dec

May

Sep

2011

2012

2013

Aug

Dec

Mar

Jan

May

Oct

Official 777K evaluations

Official

7K & 648K evaluations

Official 8K evaluations

Official 77K evaluations

Official 19K evaluations

Official 12K evaluations


International dairy breeding
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)



Impact on breeders
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 genotyped

    directly by breeders since April 2013

  • Prices for top genomic heifers can be

    very high (e.g., $265,000 )


Impact on dairy producers
Impact on dairy producers

  • General

    • Reduced generation interval

    • Increased rate of genetic gain

    • More inbreeding/homozygosity?


Impact on dairy producers continued
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


Conclusions
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



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