2007 Paul VanRaden 1, Jeff O’Connell 2, George Wiggans 1, Kent Weigel 3 1 Animal Improvement Programs Lab, USDA, Beltsville, MD, USA 2 University of Maryland.

Slides:



Advertisements
Similar presentations
2007 Paul VanRaden, Mel Tooker, and Nicolas Gengler Animal Improvement Programs Lab, Beltsville, MD, USA, and Gembloux Agricultural U., Belgium
Advertisements

Perspectives from Human Studies and Low Density Chip Jeffrey R. O’Connell University of Maryland School of Medicine October 28, 2008.
Genomic imputation and evaluation using 1074 high density Holstein genotypes P. M. VanRaden 1, D. J. Null 1 *, G.R. Wiggans 1, T.S. Sonstegard 2, E.E.
Wiggans, 2014CDCB meeting – August 5 (1) G.R. Wiggans Animal Genomics and Improvement Laboratory Agricultural Research Service, USDA Beltsville, MD
2007 Paul VanRaden and Jeff O’Connell Animal Improvement Programs Lab, Beltsville, MD U MD College of Medicine, Baltimore, MD
G.R. Wiggans Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville, MD G.R. WiggansAlta Genetics.
2007 Paul VanRaden, George Wiggans, Jeff O’Connell, John Cole, Animal Improvement Programs Laboratory Tad Sonstegard, and Curt Van Tassell Bovine Functional.
G.R. Wiggans 1, T.S. Sonstegard 1, P.M. VanRaden 1, L.K. Matukumalli 1,2, R.D. Schnabel 3, J.F. Taylor 3, J.P. Chesnais 4, F.S. Schenkel 5, and C.P. Van.
Wiggans, 2013RL meeting, Aug. 15 (1) Dr. George R. Wiggans, Acting Research Leader Bldg. 005, Room 306, BARC-West (main office);
2007 Paul VanRaden 1, Curt Van Tassell 2, George Wiggans 1, Tad Sonstegard 2, Jeff O’Connell 1, Bob Schnabel 3, Jerry Taylor 3, and Flavio Schenkel 4,
Mating Programs Including Genomic Relationships and Dominance Effects Chuanyu Sun 1, Paul M. VanRaden 2, Jeff R. O'Connell 3 1 National Association of.
2007 Paul VanRaden 1, George Wiggans 1, Curt Van Tassell 2, Tad Sonstegard 2, Jeff O’Connell 1, Bob Schnabel 3, Jerry Taylor 3, and Flavio Schenkel 4,
WiggansARS Big Data Workshop – July 16, 2015 (1) George R. Wiggans Animal Genomics and Improvement Laboratory Agricultural Research Service, USDA Beltsville,
Changes in the use of young bulls K. M. Olson* 1, J. L. Hutchison 2, P. M. VanRaden 2, and H. D. Norman 2 1 National Association of Animal Breeders, Columbia,
2007 J. B. Cole 1,*, P. M. VanRaden 1, J. R. O'Connell 3, C. P. Van Tassell 1,2, T. S. Sonstegard 2, R. D. Schnabel 4, J. F. Taylor 4, and G. R. Wiggans.
2007 Paul VanRaden Animal Improvement Programs Lab, Beltsville, MD 2011 Avoiding bias from genomic pre- selection in converting.
WiggansANSC UMD(1) 2013 George R. Wiggans Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville, MD , USA
Wiggans, 2013SRUC Imputation (1) Dr. George R. Wiggans Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville, MD ,
2007 Paul VanRaden, Curt Van Tassell, George Wiggans, Tad Sonstegard, and Jeff O’Connell Animal Improvement Programs Laboratory and Bovine Functional Genomics.
An Efficient Method of Generating Whole Genome Sequence for Thousands of Bulls Chuanyu Sun 1 and Paul M. VanRaden 2 1 National Association of Animal Breeders,
Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville, MD 2013 Paul VanRaden University.
Bovine Genomics The Technology and its Applications Gerrit Kistemaker Chief Geneticist, Canadian Dairy Network (CDN) Many slides were created by.
2003 G.R. Wiggans,* P.M. VanRaden, and J.L. Edwards Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD
2007 Paul VanRaden and Mel Tooker Animal Improvement Programs Laboratory, USDA Agricultural Research Service, Beltsville, MD, USA
2007 Paul VanRaden, George Wiggans, Jeff O’Connell, John Cole, Animal Improvement Programs Laboratory Tad Sonstegard, and Curt Van Tassell Bovine Functional.
John B. Cole 1, Daniel J. Null *1, Chuanyu Sun 2, and Paul M. VanRaden 1 1 Animal Genomics and Improvement 2 Sexing Technologies Laboratory Navasota, TX.
2007 Paul VanRaden, Mel Tooker, Jan Wright, Chuanyu Sun, and Jana Hutchison Animal Improvement Programs Lab, Beltsville, MD National Association of Animal.
2007 Paul VanRaden Animal Improvement Programs Lab, USDA, Beltsville, MD, USA 2009 Mixing Different SNP Densities Mixing Different.
2007 Melvin Tooker and Paul VanRaden Animal Improvement Programs Lab, USDA, Beltsville, MD, USA 2009 Happy Bulls, Happy Cows,
2007 Paul VanRaden, George Wiggans, Jeff O’Connell, John Cole, Animal Improvement Programs Laboratory Tad Sonstegard, and Curt Van Tassell Bovine Functional.
John B. Cole Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville, MD New Tools for.
T. A. Cooper and G.R. Wiggans Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville, MD Council.
Adjustment of selection index coefficients and polygenic variance to improve regressions and reliability of genomic evaluations P. M. VanRaden, J. R. Wright*,
Jeff O’ConnellInterbull annual meeting, Orlando, FL, July 2015 (1) J. R. O’Connell 1 and P. M. VanRaden 2 1 University of Maryland School of Medicine,
2007 Paul VanRaden Animal Improvement Programs Lab, USDA, Beltsville, MD, USA Pete Sullivan Canadian Dairy Network, Guelph, ON, Canada
Paul VanRaden, 1 Katie Olson, 2 Dan Null, 1 Mehdi Sargolzaei, 3 Marco Winters, 4 and Jan-Thijs van Kaam 5 1 Animal Improvement Programs Laboratory, ARS,
J. B. Cole * and P. M. VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville, MD
2007 Melvin Tooker Animal Improvement Programs Laboratory USDA Agricultural Research Service, Beltsville, MD, USA
G.R. Wiggans 1, T.S. Sonstegard 1, P.M. VanRaden 1, L.K. Matukumalli 1,2, R.D. Schnabel 3, J.F. Taylor 3, F.S. Schenkel 4, and C.P. Van Tassell 1 1 Agricultural.
G.R. Wiggans Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville, MD 2009 G.R. WiggansCouncil.
G.R. Wiggans* and P.M. VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville, MD
2007 Paul VanRaden Animal Improvement Programs Laboratory USDA Agricultural Research Service, Beltsville, MD, USA
Adjustment of breeding values for past and future inbreeding Paul VanRaden*, Lori Smith Animal Improvement Programs Laboratory Agricultural Research Service,
P. M. VanRaden and T. A. Cooper * Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD, USA
George R. Wiggans Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD Select Sires’
Council on Dairy Cattle Breeding April 27, 2010 Interpretation of genomic breeding values from a unified, one-step national evaluation Research project.
2007 Paul VanRaden and Melvin Tooker* Animal Improvement Programs Laboratory 2010 Gains in reliability from combining subsets.
2007 Paul VanRaden 1, Jeff O’Connell 2, George Wiggans 1, Kent Weigel 3 1 Animal Improvement Programs Lab, USDA, Beltsville, MD, USA 2 University of Maryland.
Paul VanRaden and Chuanyu Sun Animal Genomics and Improvement Lab USDA-ARS, Beltsville, MD, USA National Association of Animal Breeders Columbia, MO, USA.
2007 Paul VanRaden 1, Jeff O’Connell 2, George Wiggans 1, Kent Weigel 3 1 Animal Improvement Programs Lab, USDA, Beltsville, MD, USA 2 University of Maryland.
P.M. VanRaden and D.M. Bickhart Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD, USA
2007 Paul VanRaden Animal Improvement Programs Lab, Beltsville, MD Iterative combination of national phenotype, genotype, pedigree,
G.R. Wiggans* 1, P.M. VanRaden 1, L.R. Bacheller 1, F.A. Ross, Jr. 1, M.E. Tooker 1, J.L. Hutchison 1, T.S. Sonstegard 2, and C.P. Van Tassell 1,2 1 Animal.
H. D. Norman Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville, MD DRMS annual.
2007 John Cole, Paul VanRaden, George Wiggans, and Melvin Kuhn Animal Improvement Programs Laboratory USDA Agricultural Research Service, Beltsville, MD,
G.R. Wiggans Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville, MD G.R. WiggansADSA 18.
2007 Paul VanRaden, Dan Null, Katie Olson, Jana Hutchison Animal Improvement Programs Lab, Beltsville, MD National Association of Animal Breeders, Columbia,
G.R. Wiggans 1, T. A. Cooper 1 *, K.M. Olson 2 and P.M. VanRaden 1 1 Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville,
2007 Paul VanRaden Animal Improvement Programs Laboratory, USDA Agricultural Research Service, Beltsville, MD, USA 2008 New.
Multibreed Genomic Evaluations in Purebred Dairy Cattle K. M. Olson 1 and P. M. VanRaden 2 1 National Association of Animal Breeders 2 AIPL, ARS, USDA.
G.R. Wiggans Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville, MD Select Sires‘ Holstein.
G.R. Wiggans Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville, MD 2011 National Breeders.
G.R. Wiggans, T. A. Cooper* and P.M. VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville, MD
2007 Paul VanRaden 1, Curt Van Tassell 2, George Wiggans 1, Tad Sonstegard 2, Bob Schnabel 3, Jerry Taylor 3, and Flavio Schenkel 4, Paul VanRaden 1, Curt.
T. A. Cooper Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville, MD NAAB meeting April 2010.
My vision for dairy genomics
Methods to compute reliabilities for genomic predictions of feed intake Paul VanRaden, Jana Hutchison, Bingjie Li, Erin Connor, and John Cole USDA, Agricultural.
Genomic Evaluations.
Perspectives from Human Studies and Low Density Chip
Using Haplotypes in Breeding Programs
Presentation transcript:

2007 Paul VanRaden 1, Jeff O’Connell 2, George Wiggans 1, Kent Weigel 3 1 Animal Improvement Programs Lab, USDA, Beltsville, MD, USA 2 University of Maryland School of Medicine, Baltimore, MD, USA 3 University of Wisconsin Dept. Dairy Science, Madison, WI, USA 2010 Fill ing Missing Genotypes Using Haplotypes Fill ing Missing Genotypes Using Haplotypes

ADSA / ASAS annual meeting, Denver, July 2010 (2)Paul VanRaden 2010 Genotypes / Haplotypes  Genotypes indicate how many copies of each allele were inherited  Haplotypes indicate which alleles are on which chromosome  Observed genotypes partitioned into the two unknown haplotypes Pedigree haplotyping uses relatives Population haplotyping finds matching allele patterns

ADSA / ASAS annual meeting, Denver, July 2010 (3)Paul VanRaden 2010 Filling missing genotypes  Predict unknown SNP from known Measure 3,000, predict 43,000 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

ADSA / ASAS annual meeting, Denver, July 2010 (4)Paul VanRaden 2010 Haplotyping Program findhap.f90  Begin with population haplotyping Divide chromosomes into segments, ~250 SNP / segment List haplotypes by genotype match Similar to fastPhase, IMPUTE  End with pedigree haplotyping Detect crossover, fix noninheritance Impute nongenotyped ancestors

ADSA / ASAS annual meeting, Denver, July 2010 (5)Paul VanRaden 2010 Computer Requirements 500,000 markers, 33,414 animals StepGbytesCPU hours Simulate genotypes391.8 Pop’n haplotypes21.2 Pedigree haplotypes31.8 Store genotypes13- Store haplotypes3- Iterate allele effects (for 5 traits) 830

ADSA / ASAS annual meeting, Denver, July 2010 (6)Paul VanRaden 2010 Recent Program Revisions  Improved imputation and GEBV reliability since 9WCGALP paper  Changes since January 2010 Use known haplotype if second is unknown Use current instead of base frequency Combine parent haplotypes if crossover is detected Begin search with parent or grandparent haplotypes Store 2 most popular progeny haplotypes

ADSA / ASAS annual meeting, Denver, July 2010 (7)Paul VanRaden 2010 Example Bull: O-Style USA , Sire = O-Man  Read genotypes and pedigrees  Write haplotype segments found List paternal / maternal inheritance List crossover locations

ADSA / ASAS annual meeting, Denver, July 2010 (8)Paul VanRaden 2010 O-Style Haplotypes Chromosome 15

ADSA / ASAS annual meeting, Denver, July 2010 (9)Paul VanRaden 2010 Pedigree Haplotyping AB allele coding Genotypes: OMan BB,AA,AA,AB,AA,AB,AB,AA,AA,AB Ostyle BB,AA,AA,AB,AB,AA,AA,AA,AA,AB Haplotypes: OStyle (pat) B A A _ A A A A A _ OStyle (mat) B A A _ B A A A A _

ADSA / ASAS annual meeting, Denver, July 2010 (10)Paul VanRaden 2010 Allele and Segment Coding  Genotypes 0 = BB, 1 = AB or BA, 2 = AA 5 = missing  Haplotypes 0 = B, 1 = not known, 2 = A  Segment storage (example) O-Style has haplotype numbers 5 and 8 O-Man has haplotype numbers 8 and 21 O-Style got haplotype number 5 from dam

ADSA / ASAS annual meeting, Denver, July 2010 (11)Paul VanRaden 2010 Most Frequent Haplotypes Most Frequent Haplotypes 1st segment of chromosome % % % % % % % % % % Most frequent haplotype in Holsteins had 4,316 copies =.0516 * 41,822 animals * 2 chromosomes each

ADSA / ASAS annual meeting, Denver, July 2010 (12)Paul VanRaden 2010 Population Haplotyping Steps  Put first genotype into haplotype list  Check next genotype against list Do any homozygous loci conflict? – If haplotype conflicts, continue search – If match, fill any unknown SNP with homozygote – 2 nd haplotype = genotype minus 1 st haplotype – Search for 2 nd haplotype in rest of list If no match in list, add to end of list  Sort list to put frequent haplotypes 1st

ADSA / ASAS annual meeting, Denver, July 2010 (13)Paul VanRaden 2010 Check New Genotype Against List Check New Genotype Against List 1st segment of chromosome % % % % % % % % % % Subtract 1 st haplotype from genotype to get 2 nd : Check genotype:

ADSA / ASAS annual meeting, Denver, July 2010 (14)Paul VanRaden 2010 Conclusions  Missing genotypes can be filled easily Population and pedigree haplotyping can both process long segments efficiently Imputing 500,000 SNP for 33,414 Holsteins required 3 Gbyte memory, 3 CPU hours  Program findhap.f90 implemented for April 2010 routine evaluation Several recent improvements to accuracy Ready to include lower or higher density genotypes in evaluations