Assessing genomic diversity and signatures of selection in ...
An Overview of Genomic Selection and Fertility
Transcript of An Overview of Genomic Selection and Fertility
Improving Fertility of Dairy Cattle Using Translational
GenomicsAFRI 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
1957
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Holstein year of birth
Dau
ghte
r Pr
egna
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Rate
(D
PR)
Milk
DPR h2=0.04 DPR is the percentage of a bull’s daughter’s eligible for breeding thatbecome 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 A SNP is a specific type of mutation
caused by a single change in the DNA code – one base pair
Double-muscled Piedmontese bull caused by a single nucleotide
polymorphism mutation in a gene called myostatin (abbreviated MSTN)
limits muscle growth in fetal life
MSTNgene
Myostatininhibits muscle growth
Normal muscling Excessive muscling
Daughter Pregnancy Rate
Number of cows that became pregnant during a given 21-day periodNumber 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 selectfor reproduction
Differences in fertility between high and low DPR groups
Trait NLSMEANS (%) (SEM)
P valueHigh 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 valueHigh DPR Low DPRServices /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 0.81Net merit 0.49Milk yield -0.45Fat yield -0.35Protein yield -0.34Somatic cell score -0.55
Trait
Milk yield Fertility Milk yieldFertility
Daughter Pregnancy Rate
Number of cows that became pregnant during a given 21-day periodNumber 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 yieldFertility
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 Complicates the use of genomics
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 yieldFertility
causativeSNP
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 SNPs550 bulls
40 SNPs associated with DPR12 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 DPRare 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 Reproduction
More Reliable Estimates of Breeding Values for Reproductive Traits
More Rapid Progress in Improving Dairy Cow Fertility
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
ShenandoahDairy