Advanced genetics

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This is the 5th and final presentation in a 5-part webinar series on Breeding Better Sheep & Goats. The presenter is Susan Schoenian, University of Maryland Extension Sheep & Goat Specialist.

Transcript of Advanced genetics

Advanced Genetic Improvement

SUSAN SCHOENIANSheep & Goat Specialist

University of Maryland Extensionsschoen@umd.edu - www.sheepandgoat.com

2013 Winter Webinar Series: Breeding Better Sheep & Goats

Advanced genetic improvement1. Across-flock genetic evaluation

National performance record keeping programsa) NSIP/LambPlan (meat and fiber animals)b) AIPL/DHI/AGDA (dairy animals)

2. Genomics - marker-assisted selection (MAS)a) Single and lowly complex quantitative traitsb) Complex quantitative traits

National Sheep Improvement Program (NSIP)

• Established in 1986 to assist producers in compiling records into a usable form.

• Spreadsheet data was sent to a breed coordinator who compiled data and sent it to Virginia Tech for processing.

• Geneticists used complex software and mainframe computers to calculate flock and across-flock EPDs.

National Sheep Improvement Program (NSIP)

• In 2010, a cooperative agreement was reached between NSIP and Meat and Livestock Australia (MLA).

• Genetic evaluations are now performed by LambPlan, Australia’s national sheep performance program.

• LambPlan calculates flock and across-flock EBVs (NSIP calculated EPDs).

www.sheepgenetics.org.au

Terminology

• EPD: Expected Progeny DifferenceEstimates the genetic value of an animal as a parent. Predict differences in performance between future offspring.(½ x EBV)

• EBV - Estimated Breeding Value A value that expresses the difference between an individual animal and the benchmark to which the animal is being compared (2x EPD).

• Accuracy Reliability of EPD / EBV. The higher the accuracy is the closer the EBV is to the animal’s true breeding value.

Information used to calculate EPDs/EBVs

+ Animal’s own performance for a particular trait• Data is adjusted for known environmental effects, e.g. type of birth and rearing, age of dam.

+ Animal’s own performance for genetically-related traits.+ The performance of relatives for those traits.

Across-flock EPDs/EBVsComparing animals in different flocks regardless of location or management.

Flocks must be genetically linked/connected. Most effective way to create linkage is to have progeny from a

sire in different flocks. Should use rams from other NSIP flocks to establish linkages.

EBVs for weight traits

1) Birth weight [BWT]Direct genetic effects

2) Maternal birth weight [MBWT]Ewe effects (uterine environment)

3) Weaning weight [WWT]Pre-weaning growth potential

4) Maternal weaning weight [MWWT]Maternal milk (mothering ability)

5) Total Maternal Weaning weightMilk + growth (calculated)

EBVs for weight traits

6) Post-weaning weight [PWWT] (120-d)

7) Yearling weight @ 12 mos. [YWT]

8) “Hogget” weight @ 18 mos. [HWT]

9) Adult body weights

EBV for wool traits

1) Fleece weight [GFW]% of mean grease fleece weight

2) Fiber diameter [FD] (microns)3) Staple length [SL] (mm)4) Fiber diameter coefficient

of variation [FDCV] (%)Fleece uniformity

5) Fiber curvature [CURV] (°)Crimp frequency

6) Clean fleece weight7) Staple strength

EBVs for body composition traits determined via ultrasound (certified technician)

1) Fat depth [CF] (mm)Adj. to 110-lb. post-weaning weightAdj. to 187-lb. yearling weight

2) Loin eye muscle depth [EMD] (mm)Adj. to 110-lb. post-weaning weightAdj. to 187-lb. yearling weight

EBVs for reproductive traits

1) Number of lambs born [NLB]2) Number of lambs weaned [NLW]3) Scrotal circumference [SC] (cm)

EBVs for parasite resistance

1) Worm egg count [WEC] (%)At weaning or at early or late post-weaning ages

Interpreting data

Trait abbreviation NLB, % NLW,% PSC, cm

EBV 2 3 1.2

Accuracy 42 43 55Compared to a ram with an EBV of 0, this ram’s progeny will:

Produce 1% more lambs

Wean 1.5% more lambs

Have 0.6 cm greater scrotal circumference

Trait abbreviation PWEC, %

EBV -20

Accuracy 60Compared to a ram with an EBV of 0, this ram’s progeny will be: 10% more resistant at weaning

Trait abbreviation BWT, kg MWWT (mm) WWT, kg PWT, kg YWT, kg

EBV 0.28 1.4 6.4 9.8 6

Accuracy 65 55 72 76 68Compared to a ram with an EBV of 0, this ram’s progeny will be:

0.14 kg heavier at birth

Produce daughters who wean 0.7 kg heavier

3.2 kg heavier at weaning

4.9 kg heavier at post weaning

3 kg heavier at yearling

Breed sire summaries

Speciesbreed Trait Annual

progress

Holstein cattle

Milk production + 0.8 %

Angus cattle

Yearling weight + 0.5 %

Suffolk sheep

120-d weight + 0.3%

Impacts

Selecting sheep (or goats) using EBVs

I = (V1 x EBV1) + (V2 x EBV2) + (V3 x EBV3) + …

My index = (0.33 x NLW EBV) + (0.33 X WWT EBV) + (0.33 WEC EBV)

• Never select for only one trait: there may be undesirable consequences.

• Used balanced selection– Use a selection index• NSIP/LambPlan• Make your own index.• Selecting on the basis of two or

more EBVs is similar to selecting on the basis of an index.

NSIP/LambPlan Selection Indexes

1) Western Range Index(PWWT EBV) + (0.26 x MWWT EBV) – (0.26 YWT EBV) + (1.92 x YFW EBV) - (0.47 x YFD EBV) + (0.36 x NLB EBV)

2) Ewe productivity index1) Katahdin (hair sheep)

(0.246 x WWT EBV) + (2.226 x MWWT EBV) + (0.406 x NLW EBV ) – (0.035 x NLB EBV)

2) Polypay (maternal breeds)(0.265 x WWT EBV) + (1.200 x MWWT EBV ) + (0.406 x NLW EBV) – (0.035 x NLB EBV)

3) Carcass plus (for terminal sire breeds)(5.06 x PWWT EBV) – (13.36 x CF EBV) + (7.83 x EMD EBV)

4) Lamb 2020(0.32 x WWT EBV) + (0.47 x PWWT EBV) – (0.21 x BWT EBV) – (55 x CV EBV) + (1.54 x EMD EBV) – (0.04 x PWEC EBV)

What about meat goats?

• Previously, some Boer goat breeders participated in NSIP via B-GIN (Boer Goat Improvement Network).

• NSIP/LambPlan could be used by meat goat producers who are interested in making genetic improvements in their herd and breed.– Kiko data from NSIP has already been

migrated to LambPlan

• Several states operate meat goat buck performance tests.

Participating in NSIP/LambPlan

• Send enrollment form and check to NSIP.

• Install Pedigree Wizard software on your computer.

• Enter your data.• You will receive data back 3-4 days

after the 15th or end of the month.• NSIP publishes trait leader

summaries.

CostsEnrollment fee ($50-$350)$25 for additional breed(s)Database fee ($2/animal lifetime)

Genetic evaluation of dairy goats

• Genetic evaluation of dairy goats (and cows) is done by the Animal Improvement Programs Laboratory (AIPL) in partnership with industry organizations.

• As of 1/1/13, enrollment in DHI was 15,357 does from 446 herds in 41 states. http://aipl.arsusda.gov/

Production evaluationDHI records• Milk yield• Fat yield• Fat percentage• Protein yield• Protein percentage

Type evaluationLinear appraisal1. Stature 2. Strength3. Dairyness4. Rear legs5. Rump angle6. Rump width7. Fore udder attachment8. Rear udder height9. Rear udder arch10. Udder depth11. Medial ligament12. Teat placement13. Teat diameter

Final score

Genetic evaluation of dairy goats incorporates production records from DHI and linear appraisal and pedigree records from ADGA.

Different terminology – same technology

1. Predicted transmitting ability (PTA) Average genetic value for a certain trait that an animal transmits to its offspring.

Performance of animal + genetic merit of parents and relatives + progeny

2. Estimated transmitting ability (ETA)Artificial index based on PTAs of sire and dam.An estimate of transmission of genetic merit to offspring.

3. Production type index (PTI)Artificial index calculated from production and type evaluations.– PTA of fat corrected milk [FCM] + PTA of linear appraisal final score– PTA 2:1 or 1:2 production: type

4. Reliability

www.adgagenetics.org

Genomics• The genome is an organisms complete

genetic make-up.

• The sheep genome is more than 90 percent mapped and has ~90% homology with the cattle sequence, leaving few gaps.– Ovine SNP50 BeadChip (~$200) is a

cutting-edge genetic tool that allows researchers to characterize the genetic variation at more than 50,000 SNPs in the sheep genome.

• Gene mapping in goats is much less advanced, containing only half the number of markers as sheep.

Detection of genetic markersQUALITATIVE TRAITS

Single gene effects

Examples1) Spider lamb disease2) Hairy lamb syndrome3) Polled intersex4) Horns5) Callipyge6) Muscular hypertrophy

QUANTITATIVE TRAITS1. Major genes with

large effects on trait.

Examples1) Booroola fecundity2) Inverdale fecundity3) Myostatin4) Footrot 5) Cold tolerance 6) Scrapie resistance7) OPP resistance

2. Many genes with small individual effects.

ExamplesMost traits of economic importance1) Reproduction2) Growth 3) Milk production4) Carcass5) Disease resistance

Genetic linkage analysis Genome-wide association studiesSNP50 Chip

What’s available now? Several genomic-based diagnostic tests

SHEEP GOATS1) Parentage2) Alpha S1 Casein

1) Parentage2) Scrapie resistance3) Spider lamb syndrome4) Hairy lamb syndrome5) OPP susceptibility

Scrapie resistance• In the PRNP gene, three

codons affect scrapie susceptibility: 171, 154, and 136.

• Codon 171 is the major determinant of scrapie susceptibility in the U.S.

Alpha s1 Casein• Alpha s1 Casein is one of the four casein

proteins found in goat's milk and is the most important of the four for cheese making.

• The Alpha s1 Casein gene (CSN1S1) that produces the protein shows polymorphisms which affect the amount of protein and fat produced.

Genotype Scrapie susceptibility

RR Resistant

QR Rarely susceptible

QQ Susceptible

Variant Production levels

A High content of alpha s1 casein in milkB

ELow amount of alpha s1 casein in milk

F

N

Genomics in the U.S. sheep and goat industry

Limitations• Mapping is less advanced in sheep

and goats.• There is less investment in sheep

and goat research.• Most sheep and goat farms are small

and many are limited resource.• Lack of large number of performance

tested animals• Genomic selection criteria

developed in other countries may not be accurate in the U.S.

• Will most likely focus on single and major gene traits.

The application of genetic markers for selection of quantitative traits is still in the distant future.

Most producers don’t use the tools we already have.

1. On-farm performance evaluation

2. Central performance testing3. Across-flock genetic

evaluationa) NSIP/LambPlan (EBVs)b) AGIL/DHI/ADGA

Thank you for participating in the UME 2013 webinar series.

All recordings and PowerPoint presentations are available at http://www.sheepandgoat.com/recordings.html

Is she finally done? She

talks too much!