Current status of genomic evaluation for u s dairy cattle
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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

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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


Before clustering adjustment

Before clustering adjustment

86% call rate


After clustering adjustment

After clustering adjustment

100% call rate


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


Genotypes evaluated

Genotypes evaluated

2009

2010


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


Marketed holstein bulls

Marketed Holstein bulls


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)


Mgs detection by breed

MGS detection by breed


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)


Gmace reference populations august

GMACE reference populations (August)


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


U s genomic evaluation team

U.S. genomic evaluation team


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