AIPL Update

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AIPL Update
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Genotyped animals (October 2008)
Breed Bulls Cows Predictors
Holstein 12,275 2,445 7,821
Jersey 1,205 369 1,428
Brown Swiss 365 3 359
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Experimental DesignHolstein, Jersey, and Brown
Swiss breeds
HO JE BS
Predictor
Bulls born lt1999 3,576 743 225
Cows with data 202

Predictee
Bulls born gt1999 1,759 425 118
Data from 2003 used to predict independent data
from 2008
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Reliability Gain1 by BreedYield traits and NM
Trait HO JE BS
Net merit 23 9 3
Milk 23 11 0
Fat 33 15 5
Protein 22 4 1
Fat 43 41 10
Protein 34 29 5
1Gain above parent average reliability 35
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Reliability Gain by BreedHealth and type traits
Trait HO JE BS
Productive life 18 12 2
Somatic cell score 21 1 16
Dtr pregnancy rate 16 5 -
Final score 18 6 -
Udder depth 35 13 3
Foot angle 14 10 -
Stature 26 9 3
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New Genetic Terms

• Actual vs. expected genetic similarity
• Genomic relationships and inbreeding
• Genomic future inbreeding (GFI) vs. EFI
• Daughter merit vs. son merit
• Haplotyping and imputation
• Which allele is from sire vs. dam?
• Which alleles are linked together?
• Can missing genotypes be predicted?

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Genomic vs. PedigreeInbreeding
Bull Pedigree F Genomic F
O Man 4.5 15.8
Ramos 2.3 11.5
Shottle 5.6 11.9
Planet 6.7 18.8
Earnit 6.2 12.8
Nifty 3.1 11.7
Correlation .68
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Genomic vs. Expected Future Inbreeding
Bull EFI GFI
Blackstar 7.9 7.9
Elevation 7.6 7.4
Chief 7.1 6.8
Emory 7.0 6.9
RC Matt 7.0 6.7
Juror 7.0 6.7
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Net Merit by ChromosomePlanet - high Net Merit
bull
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Schedule

• Calculate SNP effects with each of 3 annual
  traditional evaluations
• Calculate genomic evaluations once or more
  between traditional evaluations, monthly?
• Recalculate SNP effects if significant number of
  predictor animals added
• Use existing SNP effects if only young animals
  added

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Official release in 2009

• Information from genomic evaluations propagated
  to evaluations of descendents without genotypes
• NAAB to manage bull-owner notification and
  sharing among AI organizations
• Public release of genomic evaluations
• Cows soon after calculated
• Bulls when enrolled with NAAB or Canadian AI
  organization
• Shared by agreement with owner

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Low cost genotyping research

• Develop a genetic test that is cheap enough to
  enable use on most animals
• Provide parentage verification/discovery
• Provide a genetic estimate useful for first stage
  screening
• 384 SNP proposed for first test
• High throughput procedures being developed

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Reliability of evaluations

• Reliability from inverse of a matrix with order
  the number of genotyped animals
• Approximation necessary as number of genotyped
  animals increases
• Daughter equivalents discounted by 0.6 to
  represent better the reliability of 2003 data in
  predicting bulls first evaluated in 2008

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Plans to increase accuracy

• Genotype more predictor bulls
• Reach 1,500 Brown Swiss, possibly through foreign
  collaboration
• Increase genotyped Jerseys from both domestic
  animals and possible foreign collaboration
• Investigate across-breed analysis so Holstein
  data can improve accuracy for Jerseys and Brown
  Swiss

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Haplotyping

• Haplotyping may increase accuracy
• Even a SNP very close to a QTL may have a
  different allele frequency
• Haplotype allele may have higher correlation with
  the QTL
• May assist in imputation of genotypes of missing
  SNP and perhaps whole animals

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International implications

• All major dairy countries are investigating
  genomic selection
• Interbull meeting in January on integration of
  genomic evaluations
• Studs must balance competitive benefit from
  treating genotypes as proprietary with benefits
  from sharing

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Interbull

• Genomics contribution to accuracy should be
  reported
• Avoid double counting when submitted by multiple
  countries
• Could be processed similar to parent contribution
• Change in 10-herd requirement needed to allow
  marketing bulls with only genomic information in
  countries without genomic evaluations

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Query example
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Dystocia Complex

• Markers on BTA 18 had the largest effects for
  several traits
• Dystocia Sire and daughter calving ease
• Conformation rump width, stature, strength, and
  body depth
• Efficiency longevity and net merit
• Large calves contribute to shorter PL and
  decreased NM

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(No Transcript)
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Markers on BTA18 with large effects
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SIGLEC proteins

• Human Siglec-9 highly expressed in the placenta
  (Foussias, 2000).
• Human Siglec-6 may be involved in initiation of
  parturition (Brinkman-Van der Linden et al.,
  2007).
• Siglec-6 binds and sequesters leptin
  (Brinkman-Van der Linden et al., 2007).

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Proposed mode of action

• Leptin-deficient mice delay parturition (Mounzih
  et al., 1998).
• Homozygotes may express high levels of Siglec-6,
  resulting in leptin deficiency and delayed
  parturition.
• ss86324977 may result in increased calf size
  associated with longer gestation lengths.

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Interbull fertility traits

• Heifer conception as a rate (heifer conception
  rate)?.
• Ability to recycle after calving (days to first
  breeding)?.
• Cow conception as a rate (cow conception rate)
  and interval (first breeding to conception)?.
• Calving to conception (days open)?.

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Status of fertility traits

• Traits 1 and 3 (heifer and cow conception rates)
  submitted to Sept. 2008 test run.
• Work on Trait 2 (days to first breeding) is
  underway.
• Trait 4 (ability to conceive as an interval) is
  now required.
• We already report Trait 5 (DPR).

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Heifer and cow conception rate

• Heifer conception rate (HCR) is the percentage of
  inseminated heifers that become pregnant at each
  service.
• Cow conception rate (CCR) is defined as the
  percentage of inseminated cows that become
  pregnant at each service.

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Conception rate variance components
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Correlations among fertility PTA
Correlations among PTA for bulls with at least100
CR daughters.
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Distribution of Heifer CR PTA
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Distribution of Cow CR PTA
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Top bulls