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Genetic Evaluations: Past, Present, and Future. Curt Van Tassell USDA Agricultural Research Service AIPL – Animal Improvement Programs Laboratory BFGL – Bovine Functional Genomics Laboratory. [email protected] 301-504-6501. Background. Bovine Functional Genomics Laboratory (BFGL)

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genetic evaluations past present and future

Genetic Evaluations: Past, Present, and Future

Curt Van Tassell

USDA

Agricultural Research Service

AIPL – Animal Improvement Programs Laboratory

BFGL – Bovine Functional Genomics Laboratory

[email protected]

301-504-6501

background
Background
  • Bovine Functional Genomics Laboratory (BFGL)
    • Structural and functional genomics of cattle
    • Emphasis on health and productivity
    • Bioinformatics (storage and use of genomic data)
  • Animal Improvement Programs Laboratory (AIPL)
    • “Traditional” genetic improvement of dairy cattle
    • Increasing emphasis on animal health and reproduction
definitions
Definitions
  • Phenotype – actual measurements from the cow, affected by genotype, environment, and errors

P = G + E + 

  • Predicted breeding value (PBV) – the expected (average) deviation of offspring
  • Predicted transmitting ability (PTA) – half the PBV – is our best guess of what deviation from an average would result in offspring from a parent
  • Pedigree index or parent average – estimated genetics of an animal, based solely on its sire and dam
definitions more
Definitions – More…
  • Heritability – how much of the phenotype is controlled by genetics – do children resemble their parents?
  • Reliability – a measure of accuracy of prediction of genetic merit (specifically, the fraction of genetic variation captured in the predicted merit)
  • Repeatability – how much of the phenotype is controlled by the cow across records (as opposed to random noise and environment)
traditional selection programs
Traditional Selection Programs
  • Estimate genetic merit for animals in a population
  • Select superior animals as parents of future generations
genetic evaluation system
Genetic Evaluation System
  • Traditional selection has been very effective for many economically important traits
  • Example: Milk yield
    • Moderately heritable
    • ~30 million animals evaluated 4x/yr
    • Uses ~70 million lactation records
    • Includes ~300 million test-day records
    • Genetic improvement is near theoretical expectation
dairy cattle genetics success

2000

Cows

Bulls

0

-2000

BV Milk

-4000

-6000

1960

1970

1980

1990

2000

Year of Birth

Dairy Cattle Genetics Success
revised productive life
Revised productive life
  • DIM > 305 credited
    • Differential weighting by DIM gives some advantage to cows that calve more often
  • Heritability reduced from 8.5 to 8%
  • Implementation planned for August 2006 along with revised net merit index
productive life credits current
Productive life credits - current

140

120

100

80

Credit (%)

60

40

1

2

3

20

0

0

1

2

3

4

5

Years

productive life credits revised
Productive life credits – revised

140

120

100

80

Credit (%)

60

40

1

2

3

20

0

0

1

2

3

4

5

Years

evaluation for stillbirth
Evaluation for stillbirth
  • Stillbirth – born dead or died within 48 hours
  • Reported for about half of calving-ease records
  • Evaluation and reporting similar to calving ease
  • To be included in Net Merit index
  • Implementation planned for August 2006
stillbirth data
Stillbirth Data

Stillbirth Score

animal model genetic evaluation
Animal Model Genetic Evaluation
  • Includes an animal (genetic) effect for all animals with data or in the pedigree
  • That genetic prediction is a complex combination of information from
    • Animal’s own performance
    • Sire and dam predicted genetic merit
    • Progeny predicted merit
  • All these genetic effects are inter-related
    • e.g., granddaughter performance trickles up to a sire through the dam
slide20
Animal model describes a cow\'s lactation

record as the sum of the effects

  • management group, m
  • genetic merit (animal effect), a
  • permanent environment, p
  • interaction of her herd and sire, c
  • unexplained residual, e

For:

  • herd i
  • year-season, parity, and registry group j
  • sire k
  • daughter l
calculation of pta
Calculation of PTA

w values depend on relative amounts of information: w1 + w2 + w3 = 1

predicting genetic merit of a cow
Predicting Genetic Merit of a Cow
  • Just use pedigree prediction
    • Sire
    • Dam?
  • Just use phenotype –milk
  • Use a mixture of both!!
pedigree based prediction
Pedigree-Based Prediction

PTA of a cow is average of the sire and dam PTA. So…

Cow PTA = ½ [Sire PTA + Dam PTA]

Cow PBV = [Sire PTA + Dam PTA]

Dam PTA = ½ [MGS PTA + MGD PTA]

This prediction has a maximum reliability of 50%

pedigree based prediction1
Pedigree-Based Prediction

Cow PTA = ½ [Sire PTA + ½ MGS PTA]

This prediction has a maximum reliability of 37%

phenotype based prediction
Phenotype-Based Prediction

Cow PTA = ½ Cow PBV

= ½ heritability * deviation from herd

Deviation accounts for environmental effects (herd, year, season), age and parity, stage of lactation, registry status, and other effects

milk 30 heritabilty
Milk – 30% Heritabilty

25,000 Cow production

20,000 Herd Average

5,000 Deviation

1,500 PBV: predicted breeding value

30% * (+5000)

750 PTA: predicted transmitting ability

50% of breeding value

scc 12 heritabilty
SCC – 12%Heritabilty

3.00 Cow phenotype

3.70 Herd Average

-.70 Deviation

-0.084 PBV: predicted breeding value

12% * (-0.70)

-0.042 PTA: predicted transmitting ability

50% of breeding value

reliability accuracy
Reliability (Accuracy)
  • A measure of how confident we are about the PTA.
  • It ranges from 0 to .99, and increases with the added information.
  • Reliability depends on:
    • Number of information (reported as daughters equivalents)
    • Heritability
daughter equivalents de
Daughter Equivalents (DE)
  • A measure to standardize value of information
  • Parents with accurate PTA are valuable
  • A phenotypic record is valuable
  • Daughters in many herds are most valuable.
heritability h 2 and repeatability r
Heritability (h2) and Repeatability (r)

h2 r k Trait

.30 .55 11.3 Milk

.25 .40 14 Udder

.15 .25 24.7 Feet

.12 .25 31.3 SCS

.08 .135 48 Productive life

.04 .13 98 DPR

k = (4 - 2*herit) / herit

female selection
Female Selection
  • DHIA, animal ID, pedigree
    • Get optimal PTA from AIPL
  • Non-DHIA
    • Pedigree index derived PTA
    • Simple production derived PTA
    • Blended PTA
fundamental principal
Fundamental Principal
  • Zero is defined arbitrarily in evaluation system!
  • Absolute values of PTA are meaningless
  • Example:
    • O Man PTA NM$ is 706
      • This does NOT mean that a daughter of O Man will earn you $706 more than her dam
    • Sharky has PTA NM$ of 599
  • What you can say is that ON AVERAGE an O Man daughter will earn 706-599 = $107 MORE than a Sharky daughter from the same cow
genome project objectives
Genome Project Objectives
  • PHASE I - 8X Genome Sequence
    • Line 1 Hereford cow and her sire
    • 6 genome equivalents in fragments from Dominette (the cow)
    • 2 genome equivalents

in fragments from

Domino (sire) based on

physical location

L1 Dominette 01449

shotgun genome sequence
Shotgun Genome Sequence

AGCTTTAAGCCATACCTTAG . . . GACATTACCTAGGAGCTTTAAGCCATAC

AATGTACACACACACACAC . . . ACGTGCGTCGT

AACTGGTCTACAG . . . GTTCAACGTCCTTGAC

ATCGTTCAAGTATGCGTAAATCGTTGT . . . ACGTAATAGTACGT

GTCGTAACCTGA . . . TCAACTGGTACA

GTCGTACATGT . . . TGACGTAACTGA

TCAACTGGTACGT . . . ACTTCCAGGAGACCTGTATC

GCCACATGTAGCGT . . . TATGCGTATGTGTAAACGTGGGTACTA

GTGCAACCACTGTATGCGA . . . AGTTGTGCCACGT

AAACTACGTTGTTTACCAG . . . GTGGGACACTAGTGATCG

TTAGACGATATCG . . . TATGACACGTACGT

shotgun assembly
Shotgun Assembly

...AGCTTTAAGCCATACCTTAGGACATTACCTAGGAGCTTTAAGCCATAC...

...AGCTTTAAGCCATACCTTAGGACATTACCTAGG

...AGCTTTAAGCCATACCTTAGGACATTACCTAGGAGCTTTAAGCCATAC...

GCCATACCTTAGGACATTACCTAGGAGCTTTAAGCCATAC...

...AGCTTTAAGCCATACCTTAGGACATTACCTAGGAGCTTTAAGCCATAC...

...AGCTTTAAGCCATACCTTAGGACATTACCTAGGAGCTTTAAGCCATAC...

Consensus

...AGCTTTAAGCCATACCTTAGGACATTACCTAGGAGCTTTAAGCCATAC...

genetic markers

Polymorphism

“poly”= many“morph”= form

General

population

94%

Single nucleotide

polymorphism

(SNP)

6%

Genetic Markers
  • Allow inheritance to be followed in a region across generations
  • Single nucleotide polymorphisms (SNiP) are the markers of the future!
  • Need lots!
    • 3 million in the genome
    • 10,000 initial goal
snp discovery
SNP Discovery

Brahman

Holstein

Jersey

Limousin

Hereford

Angus

Norwegian Red

snp discovery1
SNP Discovery
  • Dominette data:
  • Consensus:
  • Martha:

...AGCTTTAAGCCATACCTTAGGACATTACCTAGG

GCCATACCTTAGGACATTACCTAGGAGCTTTAAGCCATAC...

...AGCTTTAAGCCATACCTTAGGACATTACCTAGGAGCTTTAAGCCATAC...

...AGCTTTAAGCCATACCTTAGGACATTACCTAGGAGCTTTAAGCCATAC...

...AGCTTTAAGCCATACCTTAGGACATTACCTAGGAGCTTTAAGCCATAC...

...AGCTTTAAGCCATACCTTAGGACATTACCTAGGAGCTTTAAGCCATAC...

...AGCTTTAAGCCATACCTTAGGACATTACCTAGGAGCTTTAAGCCATAC...

...AGCTTTAAGCCATACCTTAGGATATTACCTAGGAGCTTTAAGCCATAC...

SNP

validate and genotype snp
Validate and Genotype SNP
  • Characterize potential SNP across ~25 breeds
  • Preliminary goal was to characterize at least 20,000 SNP
  • Industry assisting in the funding of the validation through genotyping cost
snp project outcomes
SNP Project Outcomes
  • Parentage verification & traceability panels
  • Enhanced quantitative trait locus mapping
  • Genome-wide selection
haplotype
Haplotype
  • From “haploid genotype.” A set of closely linked alleles (genes or DNA polymorphisms) inherited as a unit. Different combinations of polymorphisms are known as haplotypes.
linkage disequilibrium ld
Linkage disequilibrium (LD)
  • The non-random association of alleles at two or more loci, not necessarily on the same chromosome.
  • It is not the same as linkage, which describes the association of two or more loci on a chromosome with limited recombination between them.
  • LD describes a situation in which some combinations of alleles or genetic markers occur more or less frequently in a population than would be expected from a random formation of haplotypes from alleles based on their frequencies.
ld example bta14
LD Example – BTA14

Holstein

DGAT1

TG

Limousin

so what
So What?!
  • Estimate effect of each block
  • All intervals estimated simultaneously
  • Based on the concept proposed by Meuwissen, Hayes, and Goddard (Genetics, 2001)
whole genome selection
Whole Genome Selection
  • Fit haplotype block into a statistical model:

Effect

A

B

C

D

E

F

G

H

I

J

K

L

M

1

1

1

1

1

1

1

1

1

1

1

1

1

1

Levels

2

2

2

2

2

2

2

2

2

2

2

2

2

2

3

3

3

3

3

3

3

3

3

3

4

4

4

4

so what does this mean
So What Does This Mean?
  • Animals can be genotyped at birth
  • GEPBV available at birth for many traits
    • Even those not typically recorded (eg, semen quality)
  • Accuracy is predicted to be similar to progeny test evaluation
  • Generation intervals can be reduced
  • Costs of progeny testing can be decreased
  • Our group is conducting a pilot study
  • The future is almost here!
parentage verification and discovery
Parentage Verification and Discovery
  • Genotype a LARGE number of animals
    • Variety of herd types
      • Size
      • Housing
      • Registry status
    • Large number of SNP (200-400)
    • Acquire DNA?
  • Proof of concept that it can be done computationally
  • Characterize ID errors
  • Develop validated panel of SNP
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