Genomic Selection and Reproductive Efficiency in Dairy Cattle · Genomic Selection and Reproductive...
Transcript of Genomic Selection and Reproductive Efficiency in Dairy Cattle · Genomic Selection and Reproductive...
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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
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o Context
o Genomic Selection for Improved Fertility of Dairy Cows
o Improving Fertility of Dairy Cattle Using Translational Genomics
Outline
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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
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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
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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
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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
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Milk yield per cow
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Lb/vaca/ano
The point?
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What is the
inherited allelic combination?
Will take 2.5 years
(female)
Will take 5 - 10 years
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What is the inherited allelic combination?
Will take 2 years (female)
Will take 5 - 10 years
A new player
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Genomic Selection
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• 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
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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
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Any side effects?
A very successful process…
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USDA, Animal Improvement Programs Laboratory, 2007
Milk yield (lb)
Daughter Pregnancy Rate
Milk yield vs. fertility
Effect in Other Traits?
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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
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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
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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?
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Would genetic selection work?
Recent Evolution of Reproductive Parameters in Holsteins:
Norman et al, 2009
Inclusion in Sire Proofs
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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
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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
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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
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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/
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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
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To make use of advanced molecular technologies to improve fertility traits through genomic selection
Overall Objective
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1. Develop a fertility database with genotypes and phenotypes based on direct measures of fertility in Holstein cows
Specific Objectives
Research:
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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:
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Approach
Phenotypes:
12,000 cows
2,000 cows/state
2 - 4 farms/state
Cool / hot season
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Approach
• Uterine health – Metritis (d7)
– Clinical Endometritis (d28)
• Resumption of postpartum ovulation – CL d35 – d49
• Subclinical ketosis (d7)
• Detection of estrus
Phenotypes:
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Approach
• BCS (d7 & d35) & lameness score (d35)
• Pregnancy per artificial insemination (d32)
• Maintenance of pregnancy (d60)
Plus: – Production data
– Health events
– Management
Phenotypes:
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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)
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Results
Phenotypes:
0%
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A B C D E F G H I J K L
SUM
WIN
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A B C D E F G H I J K L
SUM
WIN
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Results
Phenotypes:
0%
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A B C D E F G H I J K L
SUM
WIN
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A B C D D E E F F G K L
SUM
WIN
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Results
Phenotypes:
0%
10%
20%
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A B C D E F G H I J K L
SUM
WIN
0%
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18%
20%
A B C D E F G H I J K L
SUM
WIN
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• 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
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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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1.00
A B C D E F G H I J K L
High
Low
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A high-density DNA analysis platform (777k) will be used to interrogate SNPs across our study population
Approach
Genotyping:
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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
High
Low
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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:
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• 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:
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Fertility Phenotypes
High-Low fertility cows
Genotyping GWAS
GEBV
SNP-GSEA Genomic selection model for
fertility
Outline
Extension
Education