The use of SNP chips for selection of dairy cattle

Curt Van TassellBovine Functional Genomics LaboratoryAgricultural Research Service, USDA Beltsville, [email protected]

Applied Genomics for Sustainable Livestock Breeding (1)

The use of SNP chips for selection of dairy cattle


A Little History…

1908

1936

1989

1997

2009

USDA organizes a national milk-recording program based on success in Michigan

The first national sire evaluations are calculated from daughter-dam comparisons

Animal model evaluations use the relationships among all cows and bulls

InterBULL evaluations introduced to incorporate foreign daughter information

First official genetic evaluations incorporating genomic data


History of genomic evaluations

Oct. 2007 BovineSNP50 BeadChip availableApr. 2008 First unofficial evaluation

releasedJan. 2009 Genomic evaluations official for

Holstein and JerseyAug. 2009 Official for Brown SwissSept. 2010 Unofficial evaluations from 3K

chipreleased

Dec. 2010 3K genomic evaluations official


Genome Selection

“Train” system using phenotypic and genotypic data

Large regression system

Predict genetic merit at birth by combining pedigree merit and merit predicted from SNP

Final genetic predictions are transparent to technology


Genomic Prediction


What’s a SNP genotype worth? Pedigree information ~7

daughters

SNP information ~34 daughters for protein yield (h2 = 0,30)

SNP information ~ 31 daugthers for fertility (h2 = 0,04)


Reliability Gain1 by Breed

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%

Yield traits and NM$ of young bulls


Genotyped Holsteins

DateAll

animalsBulls Cows Bulls Heifers

04-10 9,770 7,415 16,007 8,630 41,82208-10 10,430 9,372 18,652 11,021 49,47509-10 10,611 9,453 19,389 13,333 52,78610-10 10,616 9,787 20,184 15,288 55,87711-10 10,619 10,175 20,836 17,095 58,72712-10 11,293 12,825 21,161 18,336 63,61501-11 11,194 13,582 22,567 22,999 70,34202-11 11,196 13,935 23,330 26,270 74,73103-11 11,713 14,382 24,505 29,929 80,52904-11 12,152 11,224 25,202 36,545 85,123

Traditional evaluationNo traditional evaluation


Training Bulls

1950

1970

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

0200400600800

100012001400160018002000

Year of Birth


50K Genotypes

2009

-04

2009

-06

2009

-08

2009

-10

2010

-01

2010

-02

2010

-04

2010

-05

2010

-06

2010

-07

2010

-08

2010

-09

2010

-10

2010

-11

2010

-12

2011

-01

2011

-02

2011

-03

2011

-04

2011

-050

5000

10000

15000

20000

25000

F-Yng M-Yng F-Old M-Old


3K Genotypes

2010-09

2010-10

2010-11

2010-12

2011-01

2011-02

2011-03

2011-04

2011-05

0

1000

2000

3000

4000

5000

6000F-Young M-Young F-Old M-Old


April Genotypes – Holstein

0

500

1000

1500

2000

1998-2006 2007 2008 2009 2010 2011

Birth year

Num

ber

of G

enot

ypes

3K Females 3K Males 50K Females 50K Males


Holstein Bulls

0100020003000400050006000700080009000

10000

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Birth Year

Num

ber

of B

ulls

Total 10 Herds Genotyped Both


Reliabilities for young animals*

*Animals with no traditional PTA in March 2011

0

5

10

15

20

25

30

3K genotype50K genotype

Reliability for PTA protein (%)

Anim

als

(%)


Determination of Reliability Sum of genomic relationships with the

predictor animals weighted by reliability

Call rate Expected imputation error rate Reliability of parent average

Larger impact if dam not genotyped


Use of genomic evaluations

Determine which young bulls to bring into AI service

Use to select mating sires

Pick bull dams

Market semen from 2-year-old bulls


Use of 3K genomic evaluations

Sort heifers for breeding Flush Sexed semen Beef bull

Confirm parentage to avoid inbreeding

Predict inbreeding depression better

Precision mating considering genomics (future)


Results


2009 Genomic Milk

-1500 -1000 -500 0 500 1000 1500 2000 2500 3000 3500

-2000

-1500

-1000

-500

0

500

1000

1500

2000

2500

3000

f(x) = 0.854747985183735 x − 411.006010504377R² = 0.656057220000062f(x) = 0.803548436861551 x − 341.513603873803R² = 0.473797337393081

TraditionalLinear (Tradi-tional)GenomicLinear (Genomic)


2009 Traditional Milk

-1000 -500 0 500 1000 1500 2000 2500 3000

-2000

-1500

-1000

-500

0

500

1000

1500

2000

2500

3000

f(x) = 0.83221442474764 x − 495.740571838771R² = 0.36912984168143f(x) = 0.872532261521668 x − 533.610454732522R² = 0.331569529092576

TraditionalLinear (Tradi-tional)GenomicLinear (Genomic)


Response to Selection - Milk

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10

500

1000

1500

2000

2500

Gen 2009 Trad 2009

Fraction Selected


Response to Selection - Milk

0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04 0.045 0.050

500

1000

1500

2000

2500

Gen 2009 Trad 2009

Fraction Selected


Response to Selection – SCS

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 12.5

2.6

2.7

2.8

2.9

Gen 2009 Trad 2009

Fraction Selected


Response to Selection – SCS

0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.12.4

2.5

2.6

2.7

2.8

Gen 2009 Trad 2009

Fraction Selected


Future


Increase in accuracy

Genotyped bulls get traditional evaluation when 5 years old

Possible genotyping of 10,000 bulls with semen in CDDR

Collaboration with more countries

Use of more SNP from HD chips

Full sequencing


Application to more traits

Animal’s genotype is 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?


High density (HD) genotypes

Illumina Bovine HD BeadChip available 777,962 SNP Collaborations with GBR, ITA, & CAN to

provide genotypes Over 400 genotypes from research

projects in database Affymetrics HD

648,855 SNP Optimized for genetic coverage NAAB negotiating plan for use


Use of HD

Some increase in accuracy from better tracking of QTL

Potential for across breed evaluations

Requires few new HD genotypes once adequate base for imputation developed

Imputation improvements were particularly beneficial in imputing HD


Low-Plex Genotyping

Need cost-effective genotyping platform for application to commercial cows

<$5 / animal

Applications:

Parentage, traceability

Relatedness

Targetted panels


Genome Sequencing? Whole-genome sequences on

individuals will be available in the next few years How will we store and use those data?

Not feasible to calculate effects for 3,000,000,000 nucleotides or even 3,000,000 SNP

May be best to fine map then target genotype…


Exome Sequencing?

Capture and sequence coding part of genome and regulatory regions

~50-60 Mb

Higher likelihood of functional SNPs

Less data than complete sequence

Soon price difference irrelevant?


Summary

Extraordinarily rapid implementation of genomic evaluations

Young-bull acquisition and marketing now based on genomic evaluations

Genotyping of many females because of 3K chip


Documents

The use of SNP chips for selection of dairy cattle