genomic selection and reproductive efficiency in dairy cattle · genomic selection and reproductive...
TRANSCRIPT
Pablo Pinedo Texas A&M University
Genomic Selection and Reproductive Efficiency in Dairy Cattle
Salt Lake City, UTAH November 13, 2014
Joseph Dalton University of Idaho
o Context
o Genomic Selection for Improved Fertility of Dairy Cows
o Improving Fertility of Dairy Cattle Using Translational Genomics
Outline
Failure to achieve and maintain a timely pregnancy:
o Insemination costs
o Less cows at their peak of production
o Delayed genetic progress
o Increased risk for culling
Limited Fertility
Norman et al., 2009; Santos et al., 2010; Ribeiro et al., 2012
A historical trend for declining dairy fertility has been extensively reported:
o Anovulation
o Reduced fertilization
o Embryonic survival
Fertility in Time
Lucy, 2001; VanRaden et al., 2004;
Hare et al., 2006; Walsh et al., 2011
65 40
0
20
40
60
80
100
1951 1996
%
1st service P/AI (NY)
22 12
0
5
10
15
20
25
30
35
70's 2000's
%
21d Pregnancy Rate (FL, GA)
Butler, 1998 De Vries & Risco, 2005
-25 -10
o Cow physiology associated with greater milk production
o Nutritional imbalances
o Housing and increased herd size
o Reduced expression of estrus
o Current genetic makeup (inbreeding)
Contributing Factors
Lucy, 2001; Weigel, 2006; Royal et al., 2002
1920
1960
2014
Genetic Selection for Production
o Milk: 23,385 pounds/year
o Fat: 3.7% - Protein 3.1%
2011 average for U.S. Holsteins
Milk yield per cow
Lb/vaca/ano
The point?
What is the
inherited allelic combination?
Will take 2.5 years
(female)
Will take 5 - 10 years
What is the inherited allelic combination?
Will take 2 years (female)
Will take 5 - 10 years
A new player
Genomic Selection
• Official since 2009
• Based on linkage relationships between multiple DNA markers and the traits of interest
• Genomic estimated breeding values (GEBV)
• Early in life
Genomic Evaluations
Schefers & Weigel 2012, Eggen, 2012,
Soler, 1994
Genomic Evaluations
Norman, 2014
0
20,000
40,000
60,000
80,000
100,000
120,000
140,000
1 2 3 4 5 6 7
Females
Males
2007 2010 2013
Different density for genotyping platforms (Chips) # SNP: 3k, 6k, 50k, 70k, 777k
Any side effects?
A very successful process…
USDA, Animal Improvement Programs Laboratory, 2007
Milk yield (lb)
Daughter Pregnancy Rate
Milk yield vs. fertility
Effect in Other Traits?
Rauw et al., 1998 Norman et al., 2009; Bello et al.,
2012
Effect in Other Traits?
Unfavorable genetic correlations between production and other traits:
o Genetic correlations between production and fertility traits are generally negative
o If selection for reproduction is not included • Descending trend in fertility
Would genetic selection work?
o Strong environmental effects o Low heritability (but high variation)
Genetics & Fertility?
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4
Milk Yield
Milk fat
Protein
1/4
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4
Conception rate
Reproductive Efficiency
Mastitis resistance
Dairy character
1/20
Weigel 2006
Would genetic selection work?
oPolygenic traits
oPrecise estimations are difficult o Breeding policy o Voluntary waiting period o Natural service bulls o Long time periods to validate phenotypes o Lots of records are needed
o Epigenetics and other unknown factors (?)
Genetics & Fertility?
Would genetic selection work?
Recent Evolution of Reproductive Parameters in Holsteins:
Norman et al, 2009
Inclusion in Sire Proofs
Would genetic selection work?
Selection for High Net Merit, PTA Milk, Bull Fertility, and Daughter Fertility can be achieved
High NM
High DPR
High PTA Milk
High DPR
Already Here
• DPR
• Calving easy traits – Sire calving easy
– Daughter calving easy
– Sire stillbirth
– Daughter stillbirth
• Sire Conception Rate (SCR)
• PTA Productive Life
Selection for Fertility
1. Candidate gene approach
• Markers on biologically plausible genes
2. Whole genome scan
• Simultaneous discovery of multiple markers
o Reported QTL:
• Ovulation rate
• DPR
• Intensity of estrus
• Stillbirth…
Research Today
Fortes et al, 2013
Genomic Selection for Improved
Fertility of Dairy Cows with
Emphasis on Cyclicity and
Pregnancy
Award # 2012-02115
NIFA AFRI Translational Genomics for Improved Fertility of Animals
http://agrilife.org/afridairycowfertility/
Cornell University, U. of Florida, U. of Minnesota, U. of Wisconsin, U. of Illinois at Urbana-Champaign, Texas A&M AgriLife Research, Texas A&M University, The Ohio State University
Pinedo P J, Santos J E, Galvao K, Seabury C, Rosa J M, Bicalho R C, Gilbert R O, Schuenemann G, Chebel R, Thatcher W, Rodriguez-Zas S, Fetrow J
Award # 2012-02115
NIFA AFRI Translational Genomics for Improved Fertility of Animals
To make use of advanced molecular technologies to improve fertility traits through genomic selection
Overall Objective
1. Develop a fertility database with genotypes and phenotypes based on direct measures of fertility in Holstein cows
Specific Objectives
Research:
2. Identify SNPs associated with fertility traits by use of genome-wide analyses (GWAS)
3. To obtain genomic-estimated breeding values (GEBV) that can be applied in selection for improved fertility
Specific Objectives
Research:
Approach
Phenotypes:
12,000 cows
2,000 cows/state
2 - 4 farms/state
Cool / hot season
Approach
• Uterine health – Metritis (d7)
– Clinical Endometritis (d28)
• Resumption of postpartum ovulation – CL d35 – d49
• Subclinical ketosis (d7)
• Detection of estrus
Phenotypes:
Approach
• BCS (d7 & d35) & lameness score (d35)
• Pregnancy per artificial insemination (d32)
• Maintenance of pregnancy (d60)
Plus: – Production data
– Health events
– Management
Phenotypes:
Approach
Phenotypes:
Calving date and related problems
7 ± 3 DIM
BCS + BHBA Metritis
Clinical endometritis
28 DIM 35 DIM
BCS and Lameness score
US (CL)
Pregnancy Check Re-Check
12 to 14 d
32d post AI
60d post AI
49 DIM
US (CL)
Results
Phenotypes:
0%
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60%
A B C D E F G H I J K L
SUM
WIN
0%
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45%
A B C D E F G H I J K L
SUM
WIN
Results
Phenotypes:
0%
10%
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90%
A B C D E F G H I J K L
SUM
WIN
0%
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A B C D D E E F F G K L
SUM
WIN
Results
Phenotypes:
0%
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A B C D E F G H I J K L
SUM
WIN
0%
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20%
A B C D E F G H I J K L
SUM
WIN
• Reproductive Index (RI):
Predicted probability that a cow will become pregnant after 2 AI as a function of the explanatory variables used in the logistic model
Approach
Ranking:
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A B C D E F G H I J K L
RI
Subpopulations for extreme high and low fertility:
• High-fertility cows (n=850): Pregnant cows on d 60 after first AI
with the highest RI
• Low-fertility cows (n=1750): Non-pregnant cows on d 60 after
two postpartum AI with the lowest RI
Approach
Genotyping:
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A B C D E F G H I J K L
High
Low
A high-density DNA analysis platform (777k) will be used to interrogate SNPs across our study population
Approach
Genotyping:
A GWAS will be conducted to detect genomic regions contributing to the variation of each phenotypic trait and the RI
Approach
Bioinformatics:
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A B C D E F G H I J K L
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Low
New pool of 1,000 cows based on high and low RI and a group
of 200 AI sires with extreme values for daughter fertility (high
DPR > +15 - low DPR < -15)
Approach
Validation:
• A SNP-based gene-set enrichment analysis will be applied for the identification of candidate genes
• Genomic-estimated breeding values (GEBV) will be developed for RI and other available phenotypes
Approach
Bioinformatics:
Fertility Phenotypes
High-Low fertility cows
Genotyping GWAS
GEBV
SNP-GSEA Genomic selection model for
fertility
Outline
Extension
Education
