# Presentation: 095292

## Research Plans for Genomics, Crossbreeding, Fertility, etc. 

## AIPL 5-Year Plan 2007-2012

**Objectives**
**Collect genotypes, new phenotypes**
**Document current status and effects of management on dairy traits**
**Improve accuracy of predictions by including SNP data, refining models **
**Estimate economic values of traits to maximize lifetime profit**

## Genomic Goals

**Predict young bulls and cows more accurately**
**Compare actual DNA inherited**
**Use exact relationship matrix G instead of expected values in A **
**Trace chromosome segments**
**Locate genes with large effects**

## How Related are Relatives?

**Example: Full sibs **
**are expected to share 50% of their DNA on average **
**may actually share 45% or 55% of their DNA because each inherits a different mixture of chromosome segments from the two parents.**
**Combine genotype and pedigree data to determine exact fractions**

## Genomic Relationships

**Measures of genetic similarity**
**A**** = Expected % genes identical by descent from pedigree (Wright, 1922)**
**G**** = Actual % of DNA shared (using genotype data)**
**T**** = % genes shared that affect a given trait (using genotype and phenotype)**
**Best measure depends on use**

## QTL Relationship Matrix (T)

**Three bulls each +50 PTA protein.**
**Are their QTL alleles the same?**
**Possibly, but probably not.**
**Bull A could have 10 positive genes.**
**Bull B could have 10 positive genes, not on same chromosomes as bull A.**
**Bull C could have 20 positive and 10 negative genes.**

## Genes in Common at One Locus

|  | If Full Sib 1 inherits: |  |  |  |  |
| --- | --- | --- | --- | --- | --- |
| If Full Sib 2 inherits: |  | w,y | w,z | x,y | x,z |
|  | w,y | 2 | 1 | 1 | 0 |
|  | w,z | 1 | 2 | 0 | 1 |
|  | x,y | 1 | 0 | 2 | 1 |
|  | x,z | 0 | 1 | 1 | 2 |

**w**** = gene from sire of sire**
**x**** = gene from dam of sire**
**y**** = gene from sire of dam**
**z**** = gene from dam of dam**

## Alleles Shared by Sibs

| Indep-endent Loci | Percentage of alleles shared |  |  |  |
| --- | --- | --- | --- | --- |
|  | Full sibs |  | Half sibs |  |
|  | Mean | SD | Mean | SD |
| 1 | 50 | 35.4 | 25 | 17.7 |
| 5 | 50 | 15.8 | 25 | 7.9 |
| 10 | 50 | 11.2 | 25 | 5.6 |
| 50 | 50 | 5.0 | 25 | 2.5 |
| 100 | 50 | 3.5 | 25 | 1.8 |
| Infinite | 50 | 0.0 | 25 | 0.0 |

## Unrelated Individuals?

**No known common ancestors**
**Many unknown common ancestors born before the known pedigree**
**G = Z Z’ / number of loci**
**Elements of Z are –p and (1 – p), where p is allele frequency**
**Relationships in base = 0 +/- LD**

**Notes:**
Yet all could have the same PTA.

## Traditional Pedigree

|  |  |  |
| --- | --- | --- |
|  |  | Sire of Sire |
|  |  Sire |  |
|  |  | Dam of Sire |
|   Animal |  |  |
|  |  | Sire of Dam |
|  |  Dam |  |
|  |  | Dam of Dam |
|  |  |  |

## Genomic Pedigree

**Notes:**
Here is a simple Genomic pedigree chart.  2 separate DNA segments are shown for each ancestor.  The earliest generation, are all one color for illustrative purposes.  Dairy cattle have 30 chromosomes, including the   X and Y.   On average each chromosome carries millions of base pairs, and thousands of genes.
For the first segment, the sire has inherited 1⁄2 from each piece.  In the second segment, the majority was inherited from one piece (an example of a crossover).   The individual has received portions of the first segment that are traced back to the grandparent generation.
2) The dam has inherited most of one segment from one portion of her sire’s piece, and a mixture (double crossover) from her dam’s piece.  The individual has segments that can be traced to all grandparents.

## Example of a SNP haplotype

**caacg****t****at**** **

**caacg****g****at**** **

- SNP

**atccg****a****at**** **

**atccg****c****at**** **

- ...

- ...

- ...

- ...

- SNP

**tct****a****ggat**** **

**tct****c****ggat**** **

- SNP

- ...

- ...

- Chr1

- Chr2

- Haplotype is a set of single nucleotide polymorphisms (SNPs) associated on a single chromosome. Identification of a few alleles of a haplotype block can identify other polymorphic sites in the region.

- Haplotype 1

**tca**** **

**gac**** **

- Haplotype 2

## SNP Pedigree

- atagatcgatcg

- ctgtagcttagg

- agggcgcgcagt

- cgatctagatcg

- cggtagatcagt

- agagatcgatct

- atggcgcgaacg

- ctatcgctcagg

- ctgtagcgatcg

- agatctagatcg

- agagatcgcagt

- atgtcgctcacg

- ctgtctagatcg

- atgtcgcgcagt

## Haplotype Pedigree

- atagatcgatcg

- ctgtagcttagg

- agggcgcgcagt

- cgatctagatcg

- cggtagatcagt

- agagatcgatct

- atggcgcgaacg

- ctatcgctcagg

- ctgtagcgatcg

- agatctagatcg

- agagatcgcagt

- atgtcgctcacg

- ctgtctagatcg

- atgtcgcgcagt

## Genotype PedigreeCount number of copies of second allele

|  |  |  |
| --- | --- | --- |
|  |  | 121101011112 |
|  |  111011120202 |  |
|  |  | 101121121111 |
| 122021121111 |  |  |
|  |   | 101101111100 |
|  |  011111012011 |  |
|  |  | 121120011012
 |
|  |  |  |

**0 = ****homozygous for first allele**
**1 = ****heterozygous**
**2 = ****homozygous for second allele**

## Reliability from Full SibsMarker and QTL positions identical, sib REL = 99%

|  | Reliability Obtained From: |  |  |
| --- | --- | --- | --- |
| Full Sibs | 
A | 60 QTLs
G | 30,000 QTLs
G |
| 1 | .250 | .250 | .250 |
| 10 | .454 | .494 | .470 |
| 100 | .495 | .907 | .624 |
| Infinite | .500 | 1.000 | 1.000 |

**A**** = traditional additive relationships, ****G**** = genomic relationships**

## Bulls to Genotype58,533 SNP Project

**Choose HO bulls with semen at BFGL**
**Genotype 1777 proven bulls**
**Born 1994-1996 with >75% REL NM**
**Plus 172 ancestor bulls born 1952-1993**
**Predict 500 bulls sampled later**
**Born 2001 with >75% REL NM**
**Include other bulls in gap years?**
**Born 1997-2000 (proven) or >2002 (waiting)**

## Birth Years of Bulls to Genotype

**Data cutoff**

## Contributors of DNA500 CDDR bulls to predict, born in 2001

| AI Organization | Code | Number of bulls chosen |
| --- | --- | --- |
| CRI / Genex | 1 | 126 |
| Select Sires | 7 | 107 |
| Alta Genetics | 11 | 67 |
| Accelerated | 14 | 44 |
| ABS Global | 29 | 120 |
| Semex | 200 | 32 |

## Potential ResultsSimulation of 50,000 SNPs

**QTLs normally distributed, n = 100**
**Reliability vs parent average REL **
**58% vs 36% if QTLs are between SNPs**
**71% vs 36% if QTLs are located at SNPs (not likely)**
**Higher REL if major loci and Bayesian methods used, lower if many loci (>100) affect trait**

## Reliability from Genotyping

**Daughter equivalents**
**DE****Total**** = DE****PA**** + DE****Prog**** + DE****Y**** + DE****G**
**DE****G**** is additional DE from genotype**
**REL = DE****total**** / (DE****Total**** + k)**
**Gains in reliability**
**DE****G**** could be about 15 for Net Merit**
**More for traits with low heritability**
**Less for traits with high heritability**

## Genomic Computer Programs

**Simulate SNPs and QTLs**
**Compare SNP numbers, size of QTLs**
**Calculate genomic EBVs **
**Use selection index, G instead of A**
**Use iteration on data for SNP effects**
**Form haplotypes from genotypes**
**Not programmed yet**

## Computing Times

**Inversion including G matrix**
**Animals****2**** x markers to form G matrix**
**Animals****3**** to invert selection index**
**10 hours for 3000 bulls, 50,000 SNPs**
**Iteration on genotype data**
**Markers ****x ****animals x iterations**
**16 hours for 1000 iterations**

## Distribution of Marker Effects

## Linear vs Non-linear Models

## All-Breed Model: Goals

**Evaluate crossbred animals without biasing purebred evaluations**
**Accurately estimate breed differences**
**Compare crossbreeding strategies**
**Compute national evaluations and examine changes**
**Display results without confusion**

## Methods

**All-breed animal model**
**Purebreds and crossbreds together**
**Relationship matrix among all**
**Unknown parents grouped by breed**
**Variance adjustments by breed**
**Age adjust to 36 months, not mature**
**Within-breed-of-sire model examined but not used**

## Data

**Numbers of cows of all breeds**
**22.6 million**** for milk and fat **
**16.1 million**** for protein**
**22.5 million**** for productive life**
**19.9 million**** for daughter pregnancy rate**
**10.5 million**** for somatic cell score**
**Type traits are still collected and evaluated in separate breed files **

## Purebred and Crossbred DataUSA milk yield records

| Breed | % of total | Cows born 2003 |
| --- | --- | --- |
| Holstein | 90.5 | 642,354 |
| Jersey | 6.4 | 45,151 |
| Brown Swiss | .8 | 5,960 |
| Guernsey | .4 | 2,563 |
| Ayrshire | .3 | 1,926 |
| F1 Crossbred | 1.2 | 8,647 |

## Crossbred Cowswith 1st parity records

| Fresh year | F1    (%) | F1 cows | Back-cross | Het   > 0 | XX cows |
| --- | --- | --- | --- | --- | --- |
| 2006 | 1.4 | 10153 | 3422 | 15365 | 6099 |
| 2005 | 1.2 | 8647 | 2495 | 12621 | 4465 |
| 2004 | 1.1 | 7863 | 1983 | 11191 | 3947 |
| 2003 | .9 | 6248 | 1492 | 9051 | 3111 |
| 2002 | .7 | 4689 | 1467 | 7338 | 2564 |

## Number of Cows with Records (with > 50% heterosis; March 2007)

| Dam |  |  |  | Sire Breed |  |  |  |  |  |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Breed |  | AY |  | BS | GU | JE | MS | XX | HO |
| AY |  | — |  | 29 | 29 | 221 | 48 | 43 | 1796 |
| BS |  | 20 |  | — | 50 | 294 | 42 | 13 | 2619 |
| GU |  | 46 |  | 96 | — | 288 | 32 | 16 | 3256 |
| JE |  | 181 |  | 357 | 155 | — | 116 | 56 | 3718 |
| MS |  | 281 |  | 52 | 10 | 71 | — | 5 | 965 |
| XX |  | 489 |  | 1544 | 308 | 3568 | 323 | — | 8859 |
| HO |  | 1843 |  | 13993 | 1721 | 35193 | 1858 | 675 | — |

## Number of Cows with Records (with > 50% heterosis; March 2007)

| Sire Breed |  | Dam Breed | # | Sire Breed |  | Dam Breed | # |
| --- | --- | --- | --- | --- | --- | --- | --- |
| BS |  | SM | 25 | HO |  | DL | 47 |
| DL |  | HO | 109 | HO |  | LD | 195 |
| MO |  | HO | 73 | HO |  | MI | 60 |
| NO |  | HO | 38 | HO |  | NR | 21 |
| NR |  | HO | 23 | HO |  | RE | 22 |
| SR |  | HO | 118 | HO |  | SM | 16 |

**Notes:**
MI = Mueserhineissel  RE = European Red Dairy  SM = Simmental   LD = American Lineback   DL = Dutch Belted   MO = Montbeliarde NO = Normande

## Crossbred Daughters Addedfor sires in top 10 NM$ within breed

|  | Sire
breed | Daughters |  |
| --- | --- | --- | --- |
| Sire Name |  | Feb ‘07 | Added |
| Legacy | AY | 157 | 33 |
| Agenda | BS | 35 | 21 |
| Excite | BS | 144 | 57 |
| Q Impuls | JE | 241 | 20 |
| Stetson | MS | 36 | 31 |

## Heterosis for Yield Traits Percent of Parent Breed Average

|  |  | Milk |  |  |  | Fat |  | Protein |  |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Breed |  |  | HO Sire |  | HO Dam | HO Sire | HO Dam | HO Sire | HO Dam |
| Ayrshire |  |  |  | 2.4 | -2.0 | 2.7 | -1.8 | 2.9 | -2.4 |
| Brown Swiss |  |  |  | 5.6 |   3.2 | 4.8 |   4.5 | 4.7 |   3.8 |
| Guernsey |  |  |  | 5.2 |   2.4 | 7.1 |   4.4 | 5.5 |   4.0 |
| Jersey |  |  |  | 7.5 |   1.6 | 6.6 |   4.5 | 7.2 |   4.1 |
| M. Shorthrn  |  |  |  | 2.8 |   0.3 | 3.2 |   1.3 | 3.6 |   1.2 |
| Heterosis |  |  |  | 3.4 |  | 4.4 |  | 4.1 |  |

## All-Breed Analyses

**Crossbred animals**
**Now have PTAs, only ****3%**** did before if in breed association grading-up programs**
**Reliable PTAs from both parents**
**Purebred animals**
**Information from crossbred relatives**
**More herdmates (other breeds, crossbreds)**
**Routinely used in other populations**
**New Zealand ****(1994),**** Netherlands ****(1997)**
**USA goats ****(1989),**** calving ease ****(2005)**

## Unknown Parent Groups

**Look up PTAs of known parents**
**Estimate averages for unknowns **
**Group unknown parents by**
**Birth year  **
**Breed **
**Path (dams of cows, sires of cows, parents of bulls)**
**Origin (domestic vs other countries)**

## All- vs Within-Breed EvaluationsCorrelations of PTA Milk

| Breed | 99% REL bulls | Recent bulls | Recent cows |
| --- | --- | --- | --- |
| Holstein | >.999 | .994 | .989 |
| Jersey |   .997 | .988 | .972 |
| Brown Swiss |   .990 | .960 | .942 |
| Guernsey |   .991 | .988 | .969 |
| Ayrshire |   .990 | .963 | .943 |
| Milking Shorthorn |   .997 | .986 | .947 |

## Display of PTAs

**Genetic base**
**Convert all-breed base to within-breed bases (or vice versa)**
**PTA****brd**** = (PTA****all**** – mean****brd****) SD****brd****/SD****HO**
**PTA****all**** = PTA****brd**** (SD****HO****/SD****brd****) + mean****brd**
**Heterosis and inbreeding**
**Both effects removed in the animal model**
**Heterosis added to crossbred animal PTA**
**Expected Future Inbreeding (EFI) and merit differ with mate breed **

## All-Breed PTAs – March Test Run

**Genetic correlations mostly same**
**JE increase .02 for PL and .01 for SCS**
**BS decrease .01 for fat and SCS**
**AY increase .01 for PL**
**USA bulls in top 100 differ little**
**Numbers are averages across all scales**
**JE improve for SCS, fat (26 vs 25)**
**JE decline for milk, protein (59 vs 62)**
**BS decline for yield (10 vs 15)**
**HO improve for yield (17 vs 16)**

## Jersey and Swiss PTAs

**Base cow means changed little**
**Base cow SD changed little**
**Top bulls for protein dropped by ~9 lbs, bottom bulls dropped by ~4 lbs in both breeds**
**Unknown parent grouping, heterosis may be responsible**

## All-breed Trend Validation

**85 tests, 6 were significant (.05)**
**None significant for milk or SCS**
**1 of 15 for fat and for protein**
**2 of 15 for PL and for DPR**
**Increase in DPR repeatability made trend more negative, helped tests**

## Daughter Pregnancy RateGenetic trend on all-breed base

## Assumed Effects – Other TraitsTransmitting ability differences from Holstein

|  | Size | Udder | F&L | Calving Difficulty |  | Still-birth |
| --- | --- | --- | --- | --- | --- | --- |
| Jersey | −10.4 | −1.4 | −2.1 | −7.1 | −1.5 |  |
| B. Swiss | 0.0 | 0.7 | 0.3 | −3.2 | −0.7 |  |
| Guernsey | −7.3 | −0.5 | −1.3 | −4.6 | 1.1 |  |
| Ayrshire | −5.8 | −1.6 | −0.9 | −3.5 | −1.2 |  |
| M. Short. | −4.2 | 0.1 | −0.6 | −0.1 | −2.4 |  |
| Heterosis | 0.9 | 0.0 | 0.0 | 0.0 | 0.0 |  |

**Notes:**
Udder and F & L were calculated from regressions using the correlations on the previous slide.
Calving Ease and stillbirths are breed means from June 2006.
Heterosis value for size is from New Zealand. 
Calving Ease heterosis was calculated in a crossbreeding presentation 2 years ago.  Slight positive CE heterosis for 1st lactation , and slight negative for 2nd and later lactations. 
Other heterosis values assumed to be zero.

## Merit of F1 Holstein Crossbreds2006 Merit Indexes

| Second Breed |  | NM$ |  | CM$ |  | FM$ |
| --- | --- | --- | --- | --- | --- | --- |
| Ayrshire |  −304 |  |  −261 |  | −364 |  |
| Brown Swiss |  55 |  |  139 |  | −78 |  |
| Guernsey | −408 |  | −405 |  | −503 |  |
| Jersey |  31 |  | 153 |  | −158 |  |
| M. Shorthorn | −498 |  | −461 |  | −547 |  |

**Compared to 2005 genetic base for Holstein**

**Notes:**
Jersey x Brown Swiss F1 were +76 CM$  better than purebred Holsteins.

## Later Generation Crosses

| Holstein backcross or multi-breed |  | NM$ |  | CM$ |  |     FM$ |
| --- | --- | --- | --- | --- | --- | --- |
| HO x (BS x HO) | +28 |  | +70 |  | −39 |  |
| HO x (JE x HO) | +16 |  | +77 |  | −79 |  |
| BS x (JE x HO) | −32  |  | +109 |  | −251 |  |
| JE x (BS x HO) | −44 |  | +116 |  | −292 |  |
| HO x (BS x JE) | +44 |  | +147 |  | −118 |  |

**Compared to 2005 genetic base for Holstein**

**Notes:**
Three way cross on the bottom line +147 CM$, is similar to F1 JE x HO.

## Butterfat yield of three breed crosses was greater than from their F1 crossbred dams.
Three breed crosses averaged 14,927 pounds of milk and 641 pounds of butterfat as 2-year-olds in 1947. 

**Three breed crosses averaged ****14,927**** pounds of milk and ****641**** pounds of butterfat as 2-year-olds in 1947. **

***USDA Yearbook of Agriculture 1947***

**Three-Breed Crosses**

**Notes:**
6660kg milk
290kg fat

No predictions based on f1 daus:dam so don’t know whether this can be attributed to ‘hybrid vigor’
This group was heavy on the Red Dane sire
These were 3 breed crosses, so more hybrid vigor should be maintained (~85% in 3 breed rotations), 
as opposed to rotating only 2 breeds (~65% in 2 breed rotations)

## Crossbreeding Conclusions

**All-breed model accounts for:**
**Breed effects and general heterosis**
**Unequal variances within breed**
**Implemented in May 2007**
**PTA converted back to within-breed bases, crossbreds to breed of sire**
**PTA changes larger in breeds with fewer animals**

## Cow Fertility Research

**Daughter Pregnancy Rate works well, except that**
**Other traits are evaluated by Interbull**
**Other countries don’t use DPR in their indexes, and their calving interval data comes too late**
**Synchronization changes traits**

## Emphasis on Fertility, Longevity(% of total merit)

| Ctry | Fert | Long |  |  | Ctry | Fert | Long |
| --- | --- | --- | --- | --- | --- | --- | --- |
| USA | 9 | 17 |  |  | DNK | 8 | 6 |
| DEU | 1 | 25 |  |  | AUS | 9 | 8 |
| NLD | 8 | 16 |  |  | NZL | 7 | 6 |
| FRA | 13 | 13 |  |  | GBR | 7 | 15 |
| CAN | 5 | 7 |  |  | SWE | 15 | 5 |
| ITA |  | 8 |  |  | IRL | 22 | 18 |

## Days Open Genetic Correlations Jorjani, 2005 Interbull Bulletin

|  | DFS | ESP | GBR | IRL | NLD | NZL | USA |
| --- | --- | --- | --- | --- | --- | --- | --- |
| DFS |  | .91 | .91 | .75 | .93 | .76 | .91 |
| ESP | .91 |  | .89 | .82 | .90 | .83 | .93 |
| GBR | .91 | .89 |  | .84 | .96 | .84 | .85 |
| IRL | .75 | .82 | .84 |  | .80 | .70 | .80 |
| NLD | .93 | .90 | .96 | .80 |  | .83 | .88 |
| NZL | .76 | .83 | .84 | .85 | .83 |  | .73 |
| USA | .91 | .93 | .85 | .80 | .88 | .73 |  |

**DFS**** = Denmark-Finland-Sweden**

## DPR Results – March Test Run Holstein genetic correlations

| Eval | Model | BEL | DFS | ESP | GBR | IRL | ITA | NLD | NZL |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Mar | All breed | 86 | 89 | 93 | 83 | 76 | 90 | 86 | 62 |
| Feb | Within breed | 85 | ... | 93 | 83 | 72 | 86 | 85 | 60 |
| Diff |  | +1 | ... | 0 | 0 | +4 | +4 | +1 | +2 |

**March model also included an increase in repeatability**

## Daughter Conception Rate Genetic CorrelationsJorjani, 2005 Interbull Bulletin

|  | CAN | DEU | DFS | FRA | ISR | NLD |
| --- | --- | --- | --- | --- | --- | --- |
| CAN |  | .90 | .80 | .78 | .72 | .70 |
| DEU | .90 |  | .72 | .92 | .65 | .47 |
| DFS | .80 | .72 |  | .75 | .96 | .62 |
| FRA | .78 | .92 | .75 |  | .70 | .42 |
| ISR | .72 | .65 | .96 | .70 |  | .64 |
| NLD | .70 | .47 | .62 | .42 | .64 |  |

**DFS**** = Denmark-Finland-Sweden**

## Days to 1st Insemination Genetic CorrelationsInterbull, May 2007

|  | CHE | DFS | ITA | NLD | NZL |
| --- | --- | --- | --- | --- | --- |
| CHE |  | .95 | .87 | .90 | .61 |
| DFS | .95 |  | .90 | .91 | .57 |
| ITA | .87 | .90 |  | .86 | .70 |
| NLD | .90 | .91 | .86 |  | .55 |
| NZL | .61 | .57 | .70 | .55 |  |

**DFS**** = Denmark-Finland-Sweden**

## Fertility Trait Indexes% relative emphasis

| Trait | USA | NLD | ITA | CAN | DNK1 | DEU | FRA |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Days 1st Insem. | 69 | 33 | 19 | 25 | 15 |  |  |
| Non− Return | 31 | 41 | 20 | 65 | 70 | 100 | 100 |
| Days Open | 100 | 26 | 61 |  |  |  |  |
| Heifer fertility |  |  |  | 10 | 15 |  |  |

**1****Time from first to last insemination replaces non−return rate**

## Predict Longevity from Fertility

**Which cow fertility trait contributes most to longevity?**
**Days to first insemination (DFI), or**
**Non−return rate (NR)**
**Combined longevity includes**
**23% DFI and 12% NR in ****CAN**
**Only DFI in ****NLD**
**Correlations = .33 DFI, .11 NR in ****USA**

## DPR - Top 100 bullsBorn in last 12 years, March 2007 test run

|  | Country with most daughters |  |  |  |  |  |  |  |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Scale | DFS | ESP | GBR | IRL | ITA | NLD | NZL | USA |
| BEL | 14 | 4 | 10 | 6 | 1 | 6 | 54 | 4 |
| DFS | 29 | 3 | 11 | 6 | 3 | 17 | 27 | 3 |
| ESP | 15 | 5 | 10 | 4 | 1 | 5 | 52 | 8 |
| GBR | 18 | 7 | 13 | 7 | 4 | 11 | 30 | 7 |
| IRL | 12 | 3 | 10 | 10 | 1 | 5 | 58 | 0 |
| ITA | 18 | 3 | 8 | 3 | 3 | 8 | 55 | 2 |
| NLD | 18 | 4 | 10 | 4 | 1 | 22 | 38 | 3 |
| NZL | 1 | 0 | 0 | 1 | 0 | 0 | 97 | 0 |
| USA | 17 | 4 | 8 | 3 | 2 | 6 | 53 | 7 |
| Total | 142 | 33 | 80 | 44 | 16 | 80 | 464 | 34 |

## Calving Interval Correlationswith other traits in the same country

| Ctry | Birth | Milk | Fat | Prot | Long | SCS |
| --- | --- | --- | --- | --- | --- | --- |
| DNK | −.40 | −.31 | −.28 | −.32 | .34 | −.18 |
| ESP | −.08 | −.38 | −.29 | −.35 | .38 | −.16 |
| GBR | −.27 | −.36 | −.36 | −.42 | .30 | −.13 |
| IRL | −.20 | −.40 | −.35 | −.37 | .49 |  |
| NLD | −.41 | −.52 | −.43 | −.50 | .06 | −.13 |
| NZL | −.11 | −.32 | −.05 | −.21 | .59 | −.10 |
| USA | −.04 | −.21 | −.21 | −.17 | .48 | −.12 |

## Conception Rate(Trait 4 correlations with other traits)

| Ctry | Birth | Milk | Fat | Prot | Long | SCS |
| --- | --- | --- | --- | --- | --- | --- |
| CAN | −.06 | −.07 | −.09 | −.09 | .09 | −.04 |
| DEU |   .06 | −.01 | −.03 | −.02 | .17 | −.04 |
| DNK | −.41 | −.43 | −.37 | −.47 | .23 | −.17 |
| FRA |   .09 |   .00 | −.02 |   .00 | .28 | −.08 |
| ISR | −.06 | −.07 | −.16 | −.27 | .38 | −.15 |
| NLD | −.41 | −.39 | −.37 | −.48 | .08 | −.04 |

## Calving to First Insemination(Trait 2 correlations with other traits)

| Ctry | Birth | Milk | Fat | Prot | Long | SCS |
| --- | --- | --- | --- | --- | --- | --- |
| CAN | −.01 | −.26 | −.16 | −.21 | .32 | −.12 |
| DNK | −.34 | −.42 | −.36 | −.40 | .25 | −.22 |
| NLD | −.33 | −.49 | −.46 | −.50 | .04 | −.15 |
| NZL | −.08 | −.29 | −.05 | −.19 | .49 | −.10 |

## Heifer Fertility(Trait 1 correlations with other traits)

| Ctry | Birth | Milk | Fat | Prot | Long | SCS |
| --- | --- | --- | --- | --- | --- | --- |
| CAN | −.09 | −.11 | −.09 | −.14 | .14 | −.10 |
| DNK | −.27 | −.23 | −.19 | −.27 | .03 | −.05 |
| GBR | −.43 | −.48 | −.22 | −.44 | .13 | −.12 |

## Cow Fertility Conclusions

**Fertility and longevity receive a total of 8% to 40% of selection**
**Fertility definitions not uniform**
**Days to 1****st**** insemination is more important than conception rate?**
**Selection for fertility reduces costs and increases longevity **

## Bull Fertility ResearchDr. Melvin Kuhn

**Multiple services and an expanded service sire (SSR) term**
**“*****Type*****” of model: Linear, Threshold**
**Unconfirmed breedings: outcome not known with certainty**
**Edits and Modeling of nuisance variables**

## Service Sire Effects

**SSR inbreeding**
**Inbreeding of the Mating**
**SSR age at mating**
**Stud and Stud*year**
**Additive genetic effect (very low heritability)**

## Results: Correlations

- 						_    __Services__	_
- _	__	__Method__	__Predictor__	__All__	__1__st__ only__	_
- 		Simulation	Expanded	**87.2****	****   81.0**
- 				SSR only	**83.0****	****   71.4**
- 		Split-herd	Expanded	**56.1****	****   45.5**
- 				SSR only	**44.0****	****   37.5**
- 		Future yr	Expanded	**32.1****	****   29.4**
- _	__	__	__	__SSR only__	__**29.3**__**	**__**   23.6**__	__	_

- Expd Stud*yr: **38.1** 	Expd, no Stud*yr: **31.6**

## Linear/Threshold ModelConclusions to date:

**Little, if any, difference in predictions between the 2 models**
**Use of a good estimate of std. dev. of the predictor in thr model probability calculations may improve thr model evaluations**
**Threshold/Linear model is, at most and if anything at all, only a minor issue**
**Linear model will likely be implemented because it is computationally faster, more reliable, and simpler**

## Sexed Semen (S) Matings

**22,843 S-matings reported as of April 2007**
**92% are Holstein, most of remainder are Jersey**
**61% are on heifers (not eligible for ERCR)**
**69% are 1****st**** services**
**4,040 ERCR-eligible Holstein S-matings**
**398 bulls**
**Only 2 bulls with at least 300 ERCR-eligible S-matings**

## Bull Fertility Summary

**Research on use of multiple services and an expanded service sire term is complete**
**Linear/Thr model is, at most, of minor importance only for this trait; will likely implement linear model**
***Expect***** to delete unconfirmed matings and treat those with positive preg ck as successes but impact will be evaluated**
**Implementation expected January 2008**

## Test Day Model - Potential Benefits

**Increased accuracy of evaluations **
**Account for lactation curve differences**
**Account for genetic differences by parity**
**Evaluate persistency, rate of maturity**
**Include milk-only records if multi-trait**
**Possible earlier selection of bull dams**
**Promote as state-of-the-art system **
**Management effects more accurate**
**Could provide to DRPCs and herd owners**