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Improving Fertility of Dairy
Cattle Using Translational
Genomics
AFRI 2013-68004-20365
Tom Spencer, Holly Neibergs, Joe Dalton,
Mirielle Chahine, Dale Moore, Pete
Hansen, John Cole, & Albert De Vries
Historical Changes in Estimated
Breeding Value for DPR and Milk
Production
-8000
-6000
-4000
-2000
0
2000
4000
-2
-1
0
1
2
3
4
5
6
7
8
1957
1960
1963
1966
1969
1972
1975
1978
1981
1984
1987
1990
1993
1996
1999
2002
2005
2008
2011
Milk
DaughterPregnancyRate(DPR)
Holstein year of birth
DPR Milk
DPR h2=0.04 DPR is the percentage of a bull’s daughter’s eligible for breeding that
become pregnant during each 21-day period
Genetics 101
 What is a gene?
 What is a mutation?
 What are SNPs (single nucleotide
polymorphisms)?
 Genes are the blueprints that tell cells how to
make individual proteins – workhorse
molecules of the body (muscle, enzymes,
signaling molecules, etc.)
 There are about 20,000 genes in cattle
 Mutations are a change in the blueprint –
usually bad but sometimes good
Double-muscled Piedmontese bull
caused by a single nucleotide
polymorphism mutation in a gene
called myostatin (abbreviated MSTN)
limits muscle growth in fetal life
MSTN
gene
Myostatin
inhibits muscle growth
Normal
muscling
Excessive muscling
Daughter Pregnancy Rate
Number of cows that became pregnant during a given 21-day period
Number of cows that were eligible for breeding
A 1% increase in DPR =
~ -4 days open
1% PR=400 lb milk
Welcome Super Petrone-ET
PR =
National average for PR ~16%
DPR = PR of a bull’s daughters
PR (DPR) = 21/(days open – voluntary waiting period + 11)
(Dec 2014)
+3.7 (-15 days open)
Many Factors Determine When a Cow Gets
Pregnant – Low Heritability and Many
Genes
Walsh et al., Animal Reproduction Science, Volume 123, Issues 3–4, 2011, 127 - 138
Genetic Control of Reproduction
The heritability for reproduction is low (days open=0.04)
 which means lots of variation in reproduction
due to environment
 which means identifying genetically-superior
animals is difficult and progress is slow
 which does not mean that it is futile to select
for reproduction
Differences in fertility between high and low
DPR groups
Trait N
LSMEANS (%) (SEM)
P value
High DPR Low DPR
Preg. Rate, first service (Lact1) 2213 53.1 (1.69) 28.6 (2.32) <0.0001
Preg. Rate, first service (Lact2) 1969 43.9 (1.77) 23.0 (2.38) <0.0001
Preg. Rate, first service (Lact3) 1321 41.0 (1.88) 25.0 (2.53) <0.0001
Trait N
LSMEANS (SEM)
P value
High DPR Low DPR
Services /conception (Lact1) 2213 1.93 (0.06) 3.26 (0.07) <0.0001
Services /conception (Lact2) 1969 2.09 (0.07) 3.30 (0.07) <0.0001
Services /conception (Lact3) 1321 2.20 (0.08) 3.20 (0.10) <0.0001
Days open (Lact 1) 2213 98 (2.59) 163 (2.94) <0.0001
Days open (Lact 2) 1969 112 (2.80) 167 (3.13) <0.0001
Days open (Lact 3) 1321 110 (3.24) 158 (3.81) <0.0001
There is a negative genetic correlation
between fertility and milk production
Trait Correlation with DPR
Cow conception rate 0.61
Productive life 0.81
Net merit 0.49
Milk yield -0.45
Fat yield -0.35
Protein yield -0.34
Somatic cell score -0.55
Trait
Milk yield Fertility Milk yield
Fertility
Daughter Pregnancy Rate
Number of cows that became pregnant during a given 21-day period
Number of cows that were eligible for breeding
A 1% increase in DPR =
~ -4 days open
1% PR=400 lb milk
PR =
National average for PR ~16%
DPR = PR of a bull’s daughters
PR (DPR) = 21/(days open – voluntary waiting period + 11)
Welcome Super Petrone-ET
(Dec 2014)
+3.7 (-15 days open)
Milk +624 lb
Milk yield Fertility Milk yield
Fertility
Petrone
Four obstacles to achieving optimal
results for genetic selection for
reproduction
Trait
 Reproductive traits routinely measured on cows
are not very accurate
 Heritability is low
 so we are not that good at identifying genetically-
superior bulls
 In general, animals that are genetically superior
for reproduction are genetically inferior for
production
 Selection for fertility could reduce production
 Reproductive traits are controlled by many
genes and effects of one gene may depend on
others
Approaches for overcoming obstacles to
achieving optimal results for genetic selection
for reproduction
Trait
 Find genetic mutations controlling reproduction
 Using routinely measured traits and those not routinely
measured
 In genes that control reproduction
 In parts of the DNA physically close to genes that control
reproduction (GWAS)
 Find how genes interact with each other to affect reproduction
(networks)
 Genes that have been copied where number of copies are
related to reproduction (copy number variants)
 Find genes related to reproduction that are
either not deleterious to production or are
positively related to production
Fertility Milk yield
Fertility
causative
SNP
Genetic
Marker
(GWAS)
Gene networksCopy number variants
 Research:
• Develop novel genetic markers of fertility in replacement heifers and
lactating cows, determine effects of specific single nucleotide
polymorphisms (SNPs) on DPR and embryo development, and
understand gene networks associated with DPR, fertilization and
embryo development.
 Extension:
• Develop a sustained effort to disseminate, demonstrate, evaluate
and document the impact of using genetic selection tools to
increase fertility on herd management and profitability to producers
and personnel involved in dairy cattle enterprises.
Agriculture and Food Research Initiative
Grant 2013-68004-20365
Improving Fertility of
Dairy Cattle Using
Translational Genomics
OBJECTIVES
Research Objectives and Goal
• Develop novel genetic markers of fertility in replacement heifers and
lactating cows
• Understand genetic variants that control fertility
– Identify causative SNPs in genes known to be involved in
reproduction that are related to daughter pregnancy rate (DPR)
– Identify genetic markers for embryo cleavage rate and blastocyst
development
– Identify genetic markers for uterine receptivity and capacity for early
pregnancy
• Provide novel markers useful in genomic selection of sires and
dams to improve fertility in dairy cattle
• Approach: Breeding records will be used to fertility classify
replacement Holstein heifers and primiparous lactating cows based
on pregnancy outcome to AI.
o Heifers must have a normal reproductive tract by palpation,
no record of diseases, and display standing estrus before AI.
• Cows must have a normal reproductive tract, uncomplicated
pregnancy, no records of diseases (mastitis, retained
placenta, metritis or uterine infection, milk fever, displaced
abomasum, clinical lameness) preceding or after AI, display
standing estrus before AI, and average to high milk yields
(>53 lb milk per day).
• Fertility phenotypes:
o Highly fertile (pregnant on first AI)
o Subfertile (pregnant after 4th AI)
o Infertile (never pregnant to AI and culled)
Objective 1: Develop novel genetic markers of
fertility in replacement heifers & lactating cows
Genome-wide Association Study (GWAS)
of Fertility in Holstein Heifers
• Fertility phenotyped by artificial insemination (AI) breeding record analysis
• 470 High Fertile (pregnant upon first AI)
• 189 Infertile (never pregnant with no obvious physiological problems)
• Animals were genotyped using the Illumina BovineHD 777K BeadChip
• The blue line represents the Wellcome Trust threshold for moderate significance.
Objective 2: Identify SNPs in genes known
to be involved in reproduction that are
related to daughter pregnancy rate
Importance:
 Identification of mutations in genes
controlling fertility (causative mutations)
rather than genetic markers near mutation
Genes associated with DPR in a population
of 550 bulls
Cochran et al. 2013
434 SNPs
550 bulls
40 SNPs associated with DPR
12 SNPs associated with blastocyst development
Fat yield - 19
Milk yield - 23
Net merit - 34
Productive life -36
Cow conception rate - 33
Heifer conception rate - 22
Protein yield -19
Protein percent - 22
Fat percent - 13
Somatic cell score - 13
• Obtained semen from 550 bulls born between 1962 and 2010
• High DPR Bulls (>1.7) (n=288)
• Low DPR Bulls (<-2) (n=262)
• Varying reliabilities (46-99%)
29 of 40 genes associated with DPR
are not associated with production
 Objective 3: Evaluate the efficiency and profitability of
increasing fertility in dairy cattle using genetic selection tools.
Studies will evaluate their added value in terms of efficiency
of food production and profitability for dairy farmers through
computer modeling. A Web-based decision support tool will
be developed for producers.
 Objective 4: Conduct a national effort to transfer science-
based information to dairy producers, managers, and allied
industry personnel, complete with strategies to improve
fertility using novel genomic information and tools from the
first three parts.
Expected Outcomes of the Grant
Better Genomic Tools for Predicting Reproducti
More Reliable Estimates of Breeding Values for
Reproductive Traits
More Rapid Progress in Improving Dairy Cow Fe
20
24
28
32
10,000
15,000
20,000
25,000
30,000
1950 1960 1970 1980 1990 2000 2010
DaughterPregnancyRate(%)
MilkProduction(lbs)
Year
Milk Production Rate (lbs) Daughter Pregnancy Rate (%)
Hearty Thanks!
• M/M Feedlot (Idaho)
o Darin Mann
• Ag Health Laboratories (Sunnyside, WA)
o Fred Mueller
• Cow Palace Dairy (Washington)
o Levi Gassaway
• DeRuyter Brothers Dairy (Washington)
o Kelly Reed
• J&K Dairy (Washington)
o Jason Sheehan
• George DeRuyter & Son Dairy
o Dan DeRuyter
• Kevin Gavin & Joao Moraes (WSU)
Genasci Dairy
Shenandoah
Dairy

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An Overview of Genomic Selection and Fertility

  • 1. Improving Fertility of Dairy Cattle Using Translational Genomics AFRI 2013-68004-20365 Tom Spencer, Holly Neibergs, Joe Dalton, Mirielle Chahine, Dale Moore, Pete Hansen, John Cole, & Albert De Vries
  • 2. Historical Changes in Estimated Breeding Value for DPR and Milk Production -8000 -6000 -4000 -2000 0 2000 4000 -2 -1 0 1 2 3 4 5 6 7 8 1957 1960 1963 1966 1969 1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005 2008 2011 Milk DaughterPregnancyRate(DPR) Holstein year of birth DPR Milk DPR h2=0.04 DPR is the percentage of a bull’s daughter’s eligible for breeding that become pregnant during each 21-day period
  • 3. Genetics 101  What is a gene?  What is a mutation?  What are SNPs (single nucleotide polymorphisms)?  Genes are the blueprints that tell cells how to make individual proteins – workhorse molecules of the body (muscle, enzymes, signaling molecules, etc.)  There are about 20,000 genes in cattle  Mutations are a change in the blueprint – usually bad but sometimes good
  • 4. Double-muscled Piedmontese bull caused by a single nucleotide polymorphism mutation in a gene called myostatin (abbreviated MSTN) limits muscle growth in fetal life
  • 6. Daughter Pregnancy Rate Number of cows that became pregnant during a given 21-day period Number of cows that were eligible for breeding A 1% increase in DPR = ~ -4 days open 1% PR=400 lb milk Welcome Super Petrone-ET PR = National average for PR ~16% DPR = PR of a bull’s daughters PR (DPR) = 21/(days open – voluntary waiting period + 11) (Dec 2014) +3.7 (-15 days open)
  • 7. Many Factors Determine When a Cow Gets Pregnant – Low Heritability and Many Genes Walsh et al., Animal Reproduction Science, Volume 123, Issues 3–4, 2011, 127 - 138
  • 8. Genetic Control of Reproduction The heritability for reproduction is low (days open=0.04)  which means lots of variation in reproduction due to environment  which means identifying genetically-superior animals is difficult and progress is slow  which does not mean that it is futile to select for reproduction
  • 9. Differences in fertility between high and low DPR groups Trait N LSMEANS (%) (SEM) P value High DPR Low DPR Preg. Rate, first service (Lact1) 2213 53.1 (1.69) 28.6 (2.32) <0.0001 Preg. Rate, first service (Lact2) 1969 43.9 (1.77) 23.0 (2.38) <0.0001 Preg. Rate, first service (Lact3) 1321 41.0 (1.88) 25.0 (2.53) <0.0001 Trait N LSMEANS (SEM) P value High DPR Low DPR Services /conception (Lact1) 2213 1.93 (0.06) 3.26 (0.07) <0.0001 Services /conception (Lact2) 1969 2.09 (0.07) 3.30 (0.07) <0.0001 Services /conception (Lact3) 1321 2.20 (0.08) 3.20 (0.10) <0.0001 Days open (Lact 1) 2213 98 (2.59) 163 (2.94) <0.0001 Days open (Lact 2) 1969 112 (2.80) 167 (3.13) <0.0001 Days open (Lact 3) 1321 110 (3.24) 158 (3.81) <0.0001
  • 10. There is a negative genetic correlation between fertility and milk production Trait Correlation with DPR Cow conception rate 0.61 Productive life 0.81 Net merit 0.49 Milk yield -0.45 Fat yield -0.35 Protein yield -0.34 Somatic cell score -0.55 Trait
  • 11. Milk yield Fertility Milk yield Fertility
  • 12. Daughter Pregnancy Rate Number of cows that became pregnant during a given 21-day period Number of cows that were eligible for breeding A 1% increase in DPR = ~ -4 days open 1% PR=400 lb milk PR = National average for PR ~16% DPR = PR of a bull’s daughters PR (DPR) = 21/(days open – voluntary waiting period + 11) Welcome Super Petrone-ET (Dec 2014) +3.7 (-15 days open) Milk +624 lb
  • 13. Milk yield Fertility Milk yield Fertility Petrone
  • 14. Four obstacles to achieving optimal results for genetic selection for reproduction Trait  Reproductive traits routinely measured on cows are not very accurate  Heritability is low  so we are not that good at identifying genetically- superior bulls  In general, animals that are genetically superior for reproduction are genetically inferior for production  Selection for fertility could reduce production  Reproductive traits are controlled by many genes and effects of one gene may depend on others
  • 15. Approaches for overcoming obstacles to achieving optimal results for genetic selection for reproduction Trait  Find genetic mutations controlling reproduction  Using routinely measured traits and those not routinely measured  In genes that control reproduction  In parts of the DNA physically close to genes that control reproduction (GWAS)  Find how genes interact with each other to affect reproduction (networks)  Genes that have been copied where number of copies are related to reproduction (copy number variants)  Find genes related to reproduction that are either not deleterious to production or are positively related to production
  • 17.  Research: • Develop novel genetic markers of fertility in replacement heifers and lactating cows, determine effects of specific single nucleotide polymorphisms (SNPs) on DPR and embryo development, and understand gene networks associated with DPR, fertilization and embryo development.  Extension: • Develop a sustained effort to disseminate, demonstrate, evaluate and document the impact of using genetic selection tools to increase fertility on herd management and profitability to producers and personnel involved in dairy cattle enterprises. Agriculture and Food Research Initiative Grant 2013-68004-20365 Improving Fertility of Dairy Cattle Using Translational Genomics OBJECTIVES
  • 18. Research Objectives and Goal • Develop novel genetic markers of fertility in replacement heifers and lactating cows • Understand genetic variants that control fertility – Identify causative SNPs in genes known to be involved in reproduction that are related to daughter pregnancy rate (DPR) – Identify genetic markers for embryo cleavage rate and blastocyst development – Identify genetic markers for uterine receptivity and capacity for early pregnancy • Provide novel markers useful in genomic selection of sires and dams to improve fertility in dairy cattle
  • 19. • Approach: Breeding records will be used to fertility classify replacement Holstein heifers and primiparous lactating cows based on pregnancy outcome to AI. o Heifers must have a normal reproductive tract by palpation, no record of diseases, and display standing estrus before AI. • Cows must have a normal reproductive tract, uncomplicated pregnancy, no records of diseases (mastitis, retained placenta, metritis or uterine infection, milk fever, displaced abomasum, clinical lameness) preceding or after AI, display standing estrus before AI, and average to high milk yields (>53 lb milk per day). • Fertility phenotypes: o Highly fertile (pregnant on first AI) o Subfertile (pregnant after 4th AI) o Infertile (never pregnant to AI and culled) Objective 1: Develop novel genetic markers of fertility in replacement heifers & lactating cows
  • 20. Genome-wide Association Study (GWAS) of Fertility in Holstein Heifers • Fertility phenotyped by artificial insemination (AI) breeding record analysis • 470 High Fertile (pregnant upon first AI) • 189 Infertile (never pregnant with no obvious physiological problems) • Animals were genotyped using the Illumina BovineHD 777K BeadChip • The blue line represents the Wellcome Trust threshold for moderate significance.
  • 21. Objective 2: Identify SNPs in genes known to be involved in reproduction that are related to daughter pregnancy rate Importance:  Identification of mutations in genes controlling fertility (causative mutations) rather than genetic markers near mutation
  • 22. Genes associated with DPR in a population of 550 bulls Cochran et al. 2013 434 SNPs 550 bulls 40 SNPs associated with DPR 12 SNPs associated with blastocyst development Fat yield - 19 Milk yield - 23 Net merit - 34 Productive life -36 Cow conception rate - 33 Heifer conception rate - 22 Protein yield -19 Protein percent - 22 Fat percent - 13 Somatic cell score - 13 • Obtained semen from 550 bulls born between 1962 and 2010 • High DPR Bulls (>1.7) (n=288) • Low DPR Bulls (<-2) (n=262) • Varying reliabilities (46-99%) 29 of 40 genes associated with DPR are not associated with production
  • 23.  Objective 3: Evaluate the efficiency and profitability of increasing fertility in dairy cattle using genetic selection tools. Studies will evaluate their added value in terms of efficiency of food production and profitability for dairy farmers through computer modeling. A Web-based decision support tool will be developed for producers.  Objective 4: Conduct a national effort to transfer science- based information to dairy producers, managers, and allied industry personnel, complete with strategies to improve fertility using novel genomic information and tools from the first three parts.
  • 24.
  • 25. Expected Outcomes of the Grant Better Genomic Tools for Predicting Reproducti More Reliable Estimates of Breeding Values for Reproductive Traits More Rapid Progress in Improving Dairy Cow Fe 20 24 28 32 10,000 15,000 20,000 25,000 30,000 1950 1960 1970 1980 1990 2000 2010 DaughterPregnancyRate(%) MilkProduction(lbs) Year Milk Production Rate (lbs) Daughter Pregnancy Rate (%)
  • 26. Hearty Thanks! • M/M Feedlot (Idaho) o Darin Mann • Ag Health Laboratories (Sunnyside, WA) o Fred Mueller • Cow Palace Dairy (Washington) o Levi Gassaway • DeRuyter Brothers Dairy (Washington) o Kelly Reed • J&K Dairy (Washington) o Jason Sheehan • George DeRuyter & Son Dairy o Dan DeRuyter • Kevin Gavin & Joao Moraes (WSU)