Update on AIPL research since April 2009

Duane Norman

Animal Improvement Programs LaboratoryAgricultural Research Service, USDA, Beltsville, MD

[email protected] Board – 2009 (1)

Update on AIPL research since April 2009

What’s new!

NormanNDHIA Board – 2009 (2)

Genomic news from

the bovine g-nome



Calling genotypes

Genotypes called by Tad Sonstegard,BFGL, through April 2009

AIPL staff trained to run GenomeStudio

Cluster files shared with 4 commercial labs to allow call harmonization

Labs began providing genotypes in June

News from the bovine

g-nome


Commercial labs

GeneSeek (Lincoln, NE)

Genetics & IVF Institute (Fairfax, VA)

Genetic Visions (Middleton, WI)

DNA LandMarks(Saint-Jean-sur-Richelieu, QC, Canada)


g-nome


Managing sample ID

Web query established for nominations Indicates pedigree status Designates nominator Provides sample status, including rejection reasons

Query used by labs to convert sample ID to registration number and detect ID entry errors


g-nome


Genotype database

50,972 SNP called

Calling redone to provide additional genotypes

Many corrections required to make sample ID match

Genotypes from Illumina, University of Missouri, University of Alberta, and Switzerland also included


g-nome


SNP selection

Call rate of >90%

Not a duplicate

Parent-progeny conflicts of <2%

Minor allele frequency of >1%

Heterozygosity within 20% of expected

For bulls, X heterozygosity of <5%


g-nome


Evaluation preparation

Pedigree file created Checked for missing ancestors Pedigree requested for missing

ancestors

Canadian evaluations obtained for cows

Type evaluations obtained for Holsteins


g-nome


Genomic evaluations

Evaluations official Holstein and Jerseys (January 2009) Brown Swiss (August 2009)

June 2009 trait changes

Net merit calculated as sum of traits rather than as an individual trait

Holstein feet & legs and rear teat placement added

Current Interbull evaluation added at final selection-index step triannually


g-nome


Reliability calculation

Inversion and discounting

Gain in daughter equivalents times 0.6

Simple approximation

Could be adjusted for breed or number of close relatives

Used in April 2009 to beat deadline


g-nome


Interbull plans

Convert genomic PTAs (August 2009)

Young bulls from France, Netherlands, and New Zealand

EU requires reliability of ≥50% for marketing

Combine using G-MACE (2010)

Proven bulls next year (2010)

Domestic and genomic evaluations computed 1–2 weeks earlier to meet Interbull deadlines

Currently genomics and MACE at same time


g-nome


Evaluation options

National Include cows as predictors? Include polygenic effect in model?

International

Conversion formulas for young bulls

G-MACE to exchange genomic breeding values

Direct multicountry genomic evaluation


g-nome


Culling statistic

s



Culling status report

New annual AIPL Research Report by Norman, Wright, and Lombard available at AIPL web site (September 2009)

Based on destination (4) and termination (11) codes provided by DRPCs

Separate summaries by parity and breed 6 breeds 2 crossbred groups

− Heterosis of >90% (crossbred, CB)− Heterosis of 50 to 90% (backcross,

BC)


Destination codes

Frequency*, %

Code AY

BS

GU HO JE MS RW

CB

BC

Stayed in herd 70 68

63 67 71

68 68 74

72

Sold for dairy 7 6 6 3 7 7 4 4 5Sold for

slaughter19 2

124 24 1

722 22 1

820

Died 4 6 8 6 5 4 6 5 5

*Lactations completed between 1-1-07 and 12-31-08


Termination codes

Frequency*, %

Code AY BS GU

HO

JE MS RW CB

BC

Stayed in herd

Normal 69 67 63 66 71 67 68 73 71 Abortion <1 <1 <1 1 1 1 <1 1 1Sold Locomotion 1 1 1 1 <1 <1 1 1 1 Low yield 2 3 3 4 3 3 3 3 3

Reproduction

5 6 6 5 3 6 6 3 4

Mastitis 2 3 3 4 3 3 4 4 4 Other 8 8 11 10 7 9 8 6 7



Left herd but not sold for dairy

Frequency*, %

Termination code

AY

BS

GU HO JE MS RW

CB

BC

Sold Locomotion 4 5 3 4 2 1 4 4 3 Low yield 11 1

29 15 1

412 10 1

415

Reproduction 22 21

18 16 14

23 22 15

16

Mastitis 10 10

11 12 13

13 13 17

16

Other 35 29

35 33 32

36 29 28

29

Died 19 23

24 21 25

16 21 22

21


NormanNDHIA Board – 2009 (18) NormanNDHIA Board – 2009 (18)

AM-PM factors


Cooperative research

Purdue University (Mike Schutz)

Objectives

Derive factors to estimate daily yields from 1 record for 2X milking and 1 or 2 records for 3X milking

Compare factors derived by several methods for their accuracy in predicting true daily yield or somatic cell score (SCS)

AM-PM factors


Progress to date

Adjustment factors developed for Holstein and Jersey milk yield from 2X and 3X milkings

Preliminary Holstein and Jersey 2X AM-PM factors developed for fat, protein, and SCS

AM-PM factors


Plans

Verification of 2X AM-PM factors for fat and protein

Development and verification of 3X factors for fat and protein

Determination of whether effect of milking interval on somatic cell count is consistent enough to allow adjustment

All breeds combined for final estimation of adjustment factors

AM-PM factors

NormanNDHIA Board – 2009 (22) NormanNDHIA Board – 2009 (22)

Genetic resistance to

Johne’s disease


Cooperative studies

Characteristics of milk ELISA scores and factors affecting scores Antel BioSystems (Byrem, Norman)

Estimation of genetic parameters and transmitting ability for milk ELISA scores University of Minnesota (Attala ... Cole)

Johne’s disease


Milk ELISA characteristics

Average score of 0.04 (±0.18) for 196,412 tests from 696 herds in 16 States from 2002 through 2008 3.2 and 6.1% positives based oncutoffs of 0.40 and 0.10

Same average and SD for 42,778 scores from 25 more comprehensively tested herds in Michigan and Wisconsin 3.0 and 5.6% positives

Johne’s disease


Milk ELISA (cont.)

Cows with multiple tests within parity (10%) 95% negative for last test if 1st test negative

52% positive for last test if 1st test positive

Cows with multiple tests across parities (27%) 91% negative for last test if 1st test negative

51% positive for last test if 1st test positive

Johne’s disease


Milk ELISA (cont.)

Unusually high percentage (44%) of untested cows removed from herd by end of current lactation likely indicates selection of which cows to test for Johne’s

Tested cows removed from herd 15% of positive cows 12% of negative cows

Further analysis needed to optimize usefulness of DHI records in evaluation of milk testing for Johne's

Johne’s disease


Factors affecting scores

Cow distributionby parity

Score distribution by days from calving to test

Birth and test seasons (four 3-mo seasons starting in January) normally distributed

Score distribution by year

Parity 1 2 3 ≥4Cows (%) 45 26 15 14

Test stage (d)

1–60

61–120

121–180

181–240

241–300 301–360

≥361

Scores (%) 12 9 8 11 23 18 20

Year2002 2003 2004 2005 2006 2007

2008*

Scores (%) 4 8 12 14 20 25 16

*partial year

Johne’s disease


Score factors (cont.)

Scores generally increased with year, parity, and test stage

Birth and test seasons nonsignificant

Low heritability (4%)

Moderate repeatability (26%)

Johne’s disease


Correlations

185 Holstein AI sires with ≥50 daughters

PTA correlation with breeding value for ELISA score Milk (0.08) Fat (–0.06) Protein (0.03)

Selection based on SCS, productive life, DPR, and net merit could improve resistance to Johne’s

SCS (-0.01) Productive life (–

0.19) DPR (–0.15) Net merit (–0.16)

Johne’s disease

Documents

Update on AIPL research since April 2009