c. p. van tassell 1,2 and j. b. cole 2, * 1 bovine functional genomics and 2 animal improvement...

C. P. Van TassellC. P. Van Tassell1,21,2 and and J. B. ColeJ. B. Cole2,2,**

1Bovine Functional Genomics and 2Animal Improvement Programs LaboratoriesAgricultural Research Service, USDABeltsville, MD [email protected]

Walking the Cattle Continuum: Moving From the BovineSNP50 to Higher- and Lower-Density SNP Panels

9th WCGALP, August 2010 (2) Van Tassell and Cole

Introduction

• The Illumina Bovine SNP50 Bead Chip has been very successful

• A new high-density chip with 778K markers is now available

• A low-density chip with 3K markers will be available soon

• Other densities under development


Bovine SNP50 Bead Chip

• The Illumina Bovine SNP50 Bead Chip has been very successful

• 43,382 SNP used for genetic prediction

• 47,645 animals genotyped in the US, many more worldwide

• 2nd generation chip with a slightly different SNP set has been developed


Uses of the SNP50

• Genetic improvement•Genomic prediction•Parentage and breed confirmation

• Scientific research• Improving the assembly•QTL discovery (calving traits, SCS)

•Recessives and causative Recessives and causative mutationsmutations

•Phylogeny


Most Holstein genotypes Feb 2010

Country Reference bulls

Germany 17,000

Netherlands 16,000

France 16,000

Scandinavia (DFS) 16,000

United States 9,300

Canada 8,800


Genotyped Holsteins August 2010

*Traditional evaluation

**No traditional evaluation

Date

Young animals**All

animalsBulls* Cows* Bulls Heifers

04-09 7,600 2,711 9,690 1,943 21,94401-10 8,974 4,348 14,061 6,031 33,41402-10 9,378 5,086 15,328 7,620 37,41204-10 9,770 7,415 16,007 8,630 41,82205-10 9,958 7,940 16,594 9,772 44,26406-10 9,958 8,122 17,507 10,713 46,30007-10 9,963 8,186 18,187 11,309 47,64508-10 10,430 9,372 18,652 11,021 49,475


0500

100015002000250030003500400045005000

60616465666768697071727374757677787980

REL (%) for mlk yield

Bu

lls (

no.)

REL for young Holstein bulls July 2010


Bovine High-Density Bead Chip (HD)

• 778K SNP chosen to•Be evenly spaced• Include some Y-specific SNP• Include mitochondrial SNP

• Utilize across-breed information

• Fine mapping of QTL

• Enhanced performance in Zebu cattle


Collaboration was essential

• Illumina provided:• DNA sequence for

a range of breeds• Pfizer provided:

• DNA sequence of additional breeds

• SNP discovery expertise

• USDA-ARS provided:• DNA and library

construction• SNP discovery

expertise• Assay design

expertise

• University of Missouri• Roslin Institute• UNCEIA (France)• Sao Paulo State

University• University of Milan• Technische

Universitaet Muenchen

• Beef CRC• Embrapa• National University

(Korea)


• Enormous amount of DNA sequence data• ~180-200x genome equivalent coverage• ~600 BILLION base-pairs

• Represents: • ~120 libraries• >300 animals

• Animals from breeds representing:• European and Zebu cattle• Beef and dairy • Temperate and tropically adapted

Data highlights


BFGL-IlluminaDeep SNP Discovery

AngusHolsteinLimousin

JerseyNelore

BrahmanRomagnola

Gir

BFGLGenome Assemblies

NeloreWater Buffalo

PfizerLight SNP Discovery

AngusHolsteinJersey

HerefordCharolais

SimmentalBrahmanWaygu

PartnersDeep SNP Discovery

N’DamaSahiwal

SimmentalHanwoo

Blonde d’AquitaineMontbeliard


• >45 million SNPs discovered• ~6 million were used to design the

high density chip• ~800,000 new SNPs added• Kept almost all of the BovineSNP50 SNPs

• Breed groups included• Holstein, Angus, Nelore, Taurine dairy,

Taurine beef, Indicine, tropically adapted Taurine

• 852,645 total gaps• 850,816 (99.8%) < 20kb• 1,795 >20kb, < 100kb• 34 > 100 kb

High-density chip design


The HD chip in practice

• 777,962 available SNP

• 160 bulls genotyped

• 186,705 SNP edited-out• 1,269 unassigned chromosome• 3,197 low call rate• 1,804 Hardy-Weinberg failures• 115,850 MAF < 0.01• 64,585 uncertain location

• 591,258 useable SNP


Bovine Low-Density Bead Chip (3K)

• 2,900 SNP• Evenly spaced• 2,882 useable SNP• 14 Y-specific SNP• Includes 82 SNP for breed determination

• Expected to ship very soon• Allflex tissue-collection tags to be

released• Canada will use DNA Genotek nasal

swabs

• Large initial use anticipated


• Producing AI sires• Accuracy adequate for initial screening • 50K or HD genotyping for bulls acquired

• Confirm IDConfirm ID• Second-stage selectionSecond-stage selection

• Genotype more candidates for less money

• Parentage verification and pedigree discovery

• Traceability for disease outbreaks

Applications of the 3K chip


Other chips

• 96 SNP parentage chip• Use to identify and correct pedigree

errors• Very low cost

• 384 SNP chip• Use for initial screening of cows• 70 to 80% of benefit of 50K for 10% of

cost with haplotyping and parental genotypes

• 700K SNP Affymetrix chip• Will be cheaper than Illumina HD chip


Illumina chips are [mostly] nested

Bovine HD (700K)

Bovine SNP50 (50K)

Bovine LD (3K)

Missing 5,264 V2 markers

Missing 76 3K markers

SNP50 v 2 (V2)

Missing 7,352 SNP50 markers

50K is missing 14 3K markers


• Impute to highest density

• Calculate SNP effects for all HD SNP

• Account for loss in accuracy due to imputation error

• Store only observed genotypes

• Label evaluations with source of genotype

How do we deal with other chips?


• Predict unknown SNP from known• Measure 3,000, predict 50,000 SNP• Measure 50,000, predict 500,000• Measure each haplotype at highest

density only a few times

• Predict dam from progeny SNP

• Increase reliabilities for less cost

Why impute haplotypes?


• Identify haplotypes in population using many markers

• Track haplotypes with fewer markers

• e.g., use 5 SNP to track 25 SNP • 5 SNP: 22020

• 25 SNP: 2022020002002002000202200

How does imputation work?


Example bull haplotypes chromosome 15


Expected REL with haplotyping

• Actual 3K subset of 50K genotypes• Correlation (50K, 3K) was .95 to .97

• REL PA = 35% , 3K = 63% , 50K = 70%

• Simulated 500K genotypes• REL, all animals 50K = 82.6%, 500K = 84%• REL improved only if >1,000 had 500K

• Gains in reliability above PA• 3K chip gives >80% of 50K REL gain• 50K chip gives >96% of 500K REL gain


0

20

40

60

80

100

PA only 2,500 10,000 25,000 100,000

Number of Bulls

Re

lia

bil

ity 3K

50K

500K

3K to 500K

REL Using 3K, 50K, or 500K SNP


• Whole-genome sequences on individuals will be available in the next 5 years

•How will we store and use those data?

• Not feasible to calculate SNP effects for 3,000,000,000 SNP

• Best application may be SNP identification

Whole-genome sequencing


• Collection of genotypes from universities and public research organization

• 3K genotypes from cooperator herds need to enter the national dataset for reliable imputation

• Encourage even more widespread sharing of genotypes across countries

• Funding of genotyping necessary to predict SNP effects for future chips

• Intellectual property issues

Other genotyping issues


• The 50K chip has been very successful, but other densities are coming

• We are collaboratively developing tools to increase the ability to characterize cattle with both lower and higher density SNP chips

• This technology has the potential to impact the developing world

Conclusions

9th WCGALP, August 2010 (28) Van Tassell and Cole28

iBMAC Consortium

Funding

• USDA/NRI/CSREES• 2006-35616-16697• 2006-35205-16888• 2006-35205-16701• 2008-35205-04687 • 2009-65205-05635

• USDA/ARS• 1265-31000-081D• 1265-31000-090D• 5438-31000-073D

• Merial• Stewart Bauck

• NAAB• Gordon Doak• Accelerated Genetics• ABS Global• Alta Genetics• CRI/Genex• Select Sires• Semex Alliance• Taurus Service

• Illumina (industry)• Marylinn Munson• Cindy Lawley• Diane Lince• LuAnn Glaser• Christian Haudenschild

• Beltsville (USDA-ARS) • Curt Van Tassell• Lakshmi Matukumalli• Steve Schroeder• Tad Sonstegard

• Univ Missouri (Land-Grant)• Jerry Taylor• Bob Schnabel• Stephanie McKay

• Univ Alberta (University)• Steve Moore

• Clay Center, NE (USDA-ARS)• Tim Smith• Mark Allan

• AIPL• Paul VanRaden• George Wiggans• John Cole• Leigh Walton• Duane Norman

• BFGL• Marcos de Silva• Tad Sonstegard• Curt Van Tassell

• University of Wisconsin• Kent Weigel

• University of Maryland School of Medicine

• Jeff O’Connell• Partners

• GeneSeek• DNA Landmarks• Expression Analysis• Genetic Visions

Implementation Team


Questions about different chips?

c. p. van tassell 1,2 and j. b. cole 2, * 1 bovine functional genomics and 2 animal improvement...

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