Overview of the Dairy Genetic Evaluation System

1
Overview of the Dairy Genetic Evaluation System
2
AIPL Mission

• Conduct research to discover, test, and implement
  improved genetic evaluation techniques for
  economically important traits of dairy cattle and
  goats
• Genetically improve efficiency of dairy animals
  for yield and fitness

3
U.S. Dairy Population and Yield
4
Why genetic evaluations?

• A valuable tool for genetic selection
• Allows for comparison of animals in different
  environments
• Can include all of the information available for
  each animal
• Greatest impact on progress is from selection of
  males

5
What is an evaluation?
Phenotype Genotype Environment

• Phenotype is measurable
• Pounds of milk produced
• Stature
• An evaluation is an estimate of merit of the
  Genotype

6
Dairy Genetic Evaluation Program
PDCA
NAAB
DHI
AIPL
CDCB
Universities
AIPL Animal Improvement Programs Lab.,
USDA CDCB Council on Dairy Cattle
Breeding DHI Dairy Herd Information (milk
recording organizations) NAAB National
Association of Animal Breeders (AI) PDCA Purebred
Dairy Cattle Association (breed registries)
7
Genetic Evaluation Advances
Year Advance Gain
1926 Daughter-dam comparison 100
1962 Herdmate comparison 50
1973 Records in progress 10
1974 Modified cont. comparison 5
1977 Protein evaluated 4
1989 Animal model 4
1994 Net merit, PL, and SCS 50
2008 Genomic selection gt50
8
Traits Evaluated by AIPL
Trait Year Trait Year
Milk, fat yield 1926 Calving ease1 2000
Protein yield 1978 Dtr. preg. rate 2003
Conformation 1978 Stillbirth 2006
Productive life 1994 Bull CR2 2006
SCS (mastitis) 1994 Cow, heifer CR 2009
1Sire calving ease evaluated by Iowa State U.
1978-1999 2Estimated relative conception rate
evaluated by DRMS_at_Raleigh 1986-2005
9
Genetic Trend Milk
1000
500
Phenotypic base 11,638 kg
0
-500
-1000
Breeding value (kg)
-1500
sires
cows
-2000
-2500
-3000
-3500
1960
1970
1980
1990
2000
Holstein birth year
10
Genetic Trend Daughter preg. rate
cows
Phenotypic base 21.53
11
Economic Indexes

• An index combines evaluations for a group of
  traits based on their contribution to a selection
  goal
• Net Merit
• Cheese Merit
• Fluid Merit
• TPI Total production Index (Holstein)

12
Factors Affecting Value of Data

• Completeness of ID and parentage reporting
• Years herd has collected data
• Size of herd
• Frequency of testing and component determination

13
How Accurate are Evaluations?

• Reliability measures the amount of information
  contributing to an evaluation
• Increases at a decreasing rate as daughters are
  added
• Also affected by
• Number of contemporaries
• Reliability of parents evaluations
• Heritability of the trait

14
What do the Numbers Mean?

• Evaluations are predictions
• The true value is unknown
• The predictions rank animals relative to one
  another using a defined base
• The base is the zero- or center-point for
  evaluations
• For example the performance of animals born in a
  given year

15
Expressing Evaluations

• Estimated Breeding value (EBV)
• Animals own genetic value
• Predicted Transmitting ability (PTA)
• ½ EBV
• Expected contribution to progeny

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Factors in Genetic Improvement

• Heritability is the portion of total variation
  due to genetics
• Milk 30
• Daughter Pregnancy Rate 4
• Rate of genetic improvement is determined by
• Generation interval
• Selection intensity
• Heritability

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Bull Selection

• Purchase promising young bulls for progeny test
  (PT)
• Select only the best of the PT bulls for
  widespread use
• Only about 1 in 10 PT bulls enter active service
• Remove bulls from active service as better new
  bulls become available
• Bulls remain active only a few years

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Whole-genome Selection in Dairy Cattle
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What is Whole-Genome Selection

• Use many markers to track inheritance of
  chromosomal segments
• Estimate the impact of each segment on each trait
• Combine estimates with traditional evaluations to
  produce genomic evaluation (GPTA)
• Select animals shortly after birth using GPTA
• Replaces searching for individual genes of large
  effect (Major Genes)

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What is a SNP?

• Single-nucleotide polymorphism
• Place on the chromosome where animals differ in
  the nucleotides (A, C, T, or G) they have
• Usually not part of the gene that controls a
  trait quantitative trait locus (QTL)
• With enough SNPs, association between SNP alleles
  and QTL alleles gives useful evaluations
• SNPs chosen to be distributed evenly and have
  both alleles well represented in population

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Source of Genomic Evaluations

• DNA extracted from blood, hair, or semen
• 43,400 genetic markers (SNPs) evaluated
• Genotypes represented as 0, 1, 2 number of A
  alleles (5 indicates missing)
• Genomic evaluation combines SNP effect estimates
  with existing PA or PTA
• Genomic data contribute 11 daughter equivalents
  to reliability

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Genotype Data for Elevation
Chromosome 1
10001112200200121110111121111011110011211000201220
02220111 1202101200211122110021112001111001011011
010220011002201101 120020110102022212112210201001
1100011220221222112021120120 20100202202000021100
01120201122111211102201111000021220200
0221012020002211220111012100111211102112110020102
100022000 220100020110000220221102211210112111012
2220012112122200200 02002020201222110022222220022
12111121002111120011011101120 0202220001112011010
211121211102022100211201211001111102111
2110211122000101101110202200221110102011121111011
202102102 121101102212200121101121101202201100222
0021002110001110021 10211011100022200202212121100
02220102002222121221121112002 0110202001222222112
212021211210110012110110200220002001002
0001111011001211021212111201010121202210101011111
021102112 211111121211121011012001111102111101111
1220121012121101022 20202121122212022200212121012
1210201100111222121101
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Genotype Data from Inbred Bull
Chromosome 24 of Megaster
10212221010210210111021101121122112110022020002220
20002020220 0000220020222202202000020020222222000
020222200000220200002002 200200000022220002222000
0000000020222022002000222020222220002
2022222222200002002202022202000200022000000002202
220000002200 202000222200202002002020222022222222
0222020002022022022220202 22020202022000220022202
20022200000220200002002002000200222220
0022220202002220022202000020200000022222020200002
002002222000 202202222002200022220220022220202000
2202202222002220022000200 22020000022002202220000
22000022000222202002222000220020020202
2020002220002220022202202200000220220020020020220
002000222202 200222002022020022220222000002022000
2020020202000220022000002 20222002022202000220020
00200022002002000200220222220022022000
2000020002000020220020220200200002220000222002000
200222000022 022002002200220220202020202020002220
2000220200202202220220000 20202000020202000222222
00222200020022022220000020220020200202
022022020200002000200220220002200
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What Can Go Wrong

• Sample doesnt provide adequate DNA quality or
  quantity
• Genotype has many SNPs that cant be determined
  (90 call rate required)
• Parent-Progeny conflicts
• Pedigree error
• Sample ID error
• Laboratory error
• Unrelated animal qualifies as parent or progeny

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Parent-Progeny Verification

• Parent
• 10212002101201211001020120100
• Progeny
• 10202010100200221001120120220

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X Chromosome

• Bull
• 202220200002022220002020222020202
• Cow
• 1201201212222010111022210210212022

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Genomic vs. Traditional PTA

• Genotype can be thought of as source of
  information like parents, progeny, and records
• Indicator added to official PTA that include a
  genomic contribution
• An animals one genotype can be used to calculate
  its genomic evaluations for all 29 traits
• Genomic evaluations used the same as traditional
  PTA
• Expected to increase rate of genetic improvement
  because of a large decrease in generation interval

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Data Evaluation Flow
AI organizations, breed associations
samples
nominations
evaluations
Animal Improvement Programs Laboratory, USDA
Dairy producers
samples
samples
genotypes
DNA laboratories
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Impact on Producers

• Young-bull evaluations with accuracy of early
  1st-crop evaluations
• AI organizations marketing genomically evaluated
  2-year-olds
• Bull dams likely to be required to be genotyped
• Rate of genetic improvement likely to increase by
  up to 50
• Progeny-test programs changing

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International Implications

• All major dairy countries investigating genomic
  selection
• Interbull meeting January 2009 discussed how
  genomic evaluations should be integrated
• AI organizations may see benefits in wider
  sharing of genotypes
• Importing countries must change rules to allow
  for genomically evaluated young bulls

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World Market Competitiveness

• US bulls recognized as siring high yield
• Genetic evaluation system perceived as unbiased
• Large program offers bulls with a wide range of
  strengths
• Effective international marketing effort
• Leader in genomic selection
• Large population of high producing cows offers
  many selection candidates
• Intense competition among bull studs yields good
  value for customer

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Summary

• Evaluation procedures have improved
• Selection is the basis of genetic improvement
• Effective selection has produced substantial
  annual genetic improvement
• Indexes enable selection for overall economic
  merit
• Increased weight on fertility necessary to
  prevent continued decline
• Genomic evaluations are rapid and allow the use
  of young bulls
• AIPL serves the dairy industry with reliable
  evaluations and research to improve procedures
• Competitive in the world market

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Financial Support

• National Research Initiative grants, USDA
• NAAB (Columbia, MO)
• ABS Global (DeForest, WI)
• Accelerated Genetics (Baraboo, WI)
• Alta (Balzac, AB)
• Genex (Shawano, WI)
• New Generation Genetics (Fort Atkinson, WI)
• Select Sires (Plain City, OH)
• Semex Alliance (Guelph, ON)
• Taurus-Service (Mehoopany, PA)
• Holstein Association USA (Brattleboro, VT)
• American Jersey Cattle Association (Reynoldsburg,
  OH)
• American Brown Swiss Association (Beloit, WI)
• Agricultural Research Service, USDA