From Contemporary Comparison to Genomic selection; trends in the principles for genetic evaluations Raphael Mrode

Raphael Mrode

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SRUC

• Former Scottish Agricultural College (SAC)

• SRUC formed last October

• SAC , Barony, Elmwood and Oatridge Colleges

• 1500 staff in 6 campuses

• Three major area of interest

• Research

• Education

• SAC Consultancy

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SRUC Research

• Animal & Veterinary Science

– Edinburgh Genetic evaluation services (EGENES)

• Crop and Soil Systems

• Land Economy and Environment

• Future Farming system

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Outline of presentation

• Importance of genetic evaluations

• Trends in national genetic evaluation systems in dairy and beef cattle until 2005

• Trends in international genetic evaluation systems

• Trends in evaluation in the last five years or so

• Possible future trend – National evaluations

– International evaluations

• Conclusions

• Some views on genomic selection in African context

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Importance of genetic evaluations

• Genetic improvements have resulted in huge economic returns

- Meat and Livestock Australia reported from 1963-2001, investment in genetic selection and crossbreeding resulted in net gain about $861 million

– Amer, et al., 2007 in the United Kingdom estimated that genetic progress in growth and carcass traits in dual-purpose beef breeds over a 10 year period is worth £18.2 million over a 20 year time frame

• Undergirding these improvements is the accurate evaluation of animals on which selection is based

• Thus genetic evaluation is an important component of any breed improvement programme

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Trends in national evaluation systems in Dairy and Beef cattle

• Up to 1960’s dairy sires were evaluated using contemporary comparison or herd-mate comparison

– CC = Weight (bulls daughters - contemporary daughters of other bulls)

– Weight = effective number of daughter

– Limitations:

– Dams were assumed to be of same genetic merit

– Genetic merit of sires of herd mates not accounted for

– Assume there is no genetic trend

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Trends in national genetic evaluation systems-MCC

• This lead to the development of Modified Contemporary comparison to address these limitations of CC

– Incorporate bull pedigree : sire and grand maternal sire

• In beef cattle, performance testing has been the main method of evaluation.

– Individual performance and use of selection index to incorporate information from relatives were the main tools of evaluation and selection

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Trends in national genetic evaluation systems - BLUP

• BLUP (Best Linear Unbiased Prediction) was

introduced by Henderson in about 1950

• BLUP involves the simultaneous estimation of fixed

effects and prediction of animal breeding values

• Main advantages include: – Avoid the need to pre-correct data for fixed effects

– Ability to use all pedigree information

– More accurate evaluations

– Account for selection if all relevant data is included

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Trends in national genetic evaluation systems - BLUP

• Early years: Sire models and sire and grand maternal sire models

• In the 1990s, animal model evaluations - univariate and

multi-variate models were used at national levels

• Models for beef cattle include effects for the genetic maternal effects (Maternal trait model)

• Advances in computing methods and in computing enhanced this development

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Impact of Genetics on dairy cattle

• Tremendous progress in last 20 years

– Increase of Milk genetics of 100+ kg/year

– Increase of actual yield close to 150 kg/yr

Milk EBV by Year of Birth

-1750

-1500

-1250

-1000

-750

-500

-250

0

250

500

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

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Genetic trend for protein in the USA

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Impact of BLUP on Beef value in the UK

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Major Beef Breeds Evaluated

Breeds No. with observations

Limousin 176,647

Blonde D’aquitaine 18,629

Sussex 18,543

Welsh Black 16,236

Lincoln Red 14,086

Devon 9,847

Stabilisers 4,615

Other less numerable breeds evaluated include:

Red Poll, Galloway, Salers, Highland

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Summary of Traits and Models FOR Beef evaluations at EGENES

• Animal models evaluations implemented for growth and

carcass quality related traits:

400 d weight, Muscle Score, Fat Depth, Muscle Depth

• Animal model with maternal effects fitted for :

Birth weight, 200d weight, Gestation length and Calving

Ease

• Both sets of traits are combined in a multivariate

analyses

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• In the mid-1990’s, covariance functions and random regression models were introduced

• Used for traits measured along a trajectory such as age or time (longitudinal data)

• Continuous function to give variance and covariance of traits measured at different points along the trajectory – Better correction for fixed effects at the time of test

– Avoid extension of records and higher accuracy

– Opportunity for evaluations for persistency for dairy cattle

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RRM model in the UK

• Across breed single trait multi-lactation animal RRM

• Milk, fat and protein yields ~ 6 hours per trait

• SUMMARY STATISTICS

• Cows with yield = 8,300,526 ; Dams without yield = 1,474,952;

Number of bulls = 133,210

• Lact # Cows # Cows

• 305d TD TD records

• 1 3,247,660 4,526,940 40,665,679

• 2 2,560,259 3,741,445 33,170,977

• 3 1,951,366 2,9186,09 25,632,025

• 4 835,558 2,003,375 17,252,464

• 5 582,347 1,388,110 11,834,430

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Trends in International genetic evaluations

• International evaluations became necessary as a result of increased international trade in frozen semen, embryos and young animals

• Carried out by Interbull in Uppsala, Sweden and was formed in 1983

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Trends in international genetic evaluations

• 1994- till date: Multiple Across Country Evaluations

(MACE)

• Linear model but genetic correlations were

estimated and used among countries.

– These correlation reflect GXE interaction

– Usually higher for production traits (0.85 to 0.95) and

lower for functional traits (0.6 – 0.8)

– Input variable became de-regressed national EBVs

• Current size of operation

– About 30 countries with 38 traits evaluated for 6 dairy

breeds

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Genomic Era

• However over the last 7 years developments in molecular biology meant genotyping technology for single nucleotide polymorphism (SNP) has become available.

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Recent trends in national genetic evaluation system

• In the initial stages, 50K SNP chip by Illumina and 10K by Affymetrix were used mostly to genotype dairy sires.

• There was quickly followed by the HD chips ~ 800K by Illumina and 700k by Affymetrix

• Lower density chips 3k, 7k, 9k are now available

• Using the linkage disequilibrium between SNP and QTL for economic traits, breeding values (termed genomic breeding values ) can be computed directly for animals from SNP effects

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Recent trends in national genetic evaluation system

• Procedure involves genotyping bulls (with daughters records) in a reference population and estimating SNP effects.

– Currently most countries fit a linear model (GBLUP) with fixed mean effect and random SNP effects

- Current about 15 countries have implemented genomic evaluations which have been validated by Interbull

• SNP effects are validated in a validation data set of young bulls with no observations

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Recent trends in national genetic evaluation system

• Main advantages:

• Young bulls can be genotyped early in life and breeding values computed

• Can be used to select young bulls to be progeny tested, thereby reducing cost

• Young bulls with GEBV sold as a team of young bulls to farmers

• Higher accuracy of about 20-30% for young bulls above parent average

• Reduction in generation interval

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UK Dairy cattle situation Data

• Data consisted of ~ 20000 Holstein-Friesian bulls with 50K genotype

• About 600 were genotyped with the HD chip but corresponding 50K SNPs were extracted

• Genotypes are a combination of the North American Cooperative Dairy DNA Repository (CDDR), UK AI industry , ITALY and SRUC genotypes.

• 41703 SNPs were analysed after edits

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Model and Analysis

• Linear model consisting of – mean effect

– random residual polygenic effect (10 or 20%)

– random SNP effects

– error

• Model with no polygenic effect was also analysed and results compared

• Evaluations for genotyped animals with A was also implemented to enable gains due to genomics to be computed

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Accuracy of evaluations

Trait No polygenic effect 10% polygenic effect

Corr Reg MD Corr Reg MD

Milk yield 0.68 0.83 -11 0.66 0.99 25

Fat yield 0.68 0.87 -0.22 0.67 1.03 1.1

Protein yield 0.65 0.82 0.21 0.64 0.98 1.1

SCC 0.69 0.91 0.56 0.69 1.10 -1.0

Longevity 0.45 0.63 0.02 0.49 1.14 0.05

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Gains in reliability

Trait Pedigree

Index

Genomic

prediction

Gain

Milk yield 31 63 32

Fat yield 31 64 33

Protein yield 31 63 32

SCC 31 51 20

Longevity 30 45 15

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Gain in reliability for protein yield

• In addition heifer has a reliability at birth equivalent

to a cow with several lactations

Trait Pedigree

Index

Genomic

prediction

Gain

UK 31 63 32

USA 34 74 40

Ireland 30 56 26

Germany 31 73 42

Italy 35 75 40

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Amount of information from a genotype

Pedigree is equivalent to information on about 7 daughters

For protein yield

(h2=0.30), the SNP

genotype provides

information

equivalent to an

additional 34

daughters

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Does it work?

• 1814 bulls had only young sire genomic proofs in

April 2012, but now have official evaluations based

on daughter data

• Average genomic PLI prediction in April 2012 was

£94.0 (68.6% reliability)

• Average official PLI based on dtrs in April 2013 is

£94.7 (80.5% reliability)

• Protein: 12.5kg . vs. 12.4kg (r=0.862)

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Marketed HOL bulls in USA

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2007 2008 2009 2010 2011

% o

f to

tal b

reed

ing

s

Breeding year

Old non-G

Old G

First crop non-G

First crop G

Young Non-G

Young G

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Possible future trend

• Developments in molecular biology seem set to transform genetic evaluation methods

• The genome of some popular sire have been sequenced and it is likely more key sires will be fully sequenced

• 1000 bull genome project hosted by Scientists in Australia

• Genome Canada- Mostly on beef breeds

– Aim to sequence 30 bulls per breed/population

– Collaborating with several countries for further contribution of sequences

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Possible future trend

• Utilisation of full sequences

– Provide possibility of imputation of bulls genotyped with HD up to full sequences

– Poses challenges in terms of breeding value estimation

– May need development of new algorithms or methodologies

– Possible specialised chip panels for various traits of interest

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Possible future trend

• The release of lower density chips (3k ,7k , etc) implies – Farmers can genotype cows at a cheaper rate

– Imputation of then be used to infer genotype to a higher resolution and therefore providing more accurate cow evaluations

• More collaboration among countries and breeding companies to increase the size of the reference population. We already have – North American Consortium (USA & Canada) + UK &

Italy

– EuroGenetics ( Several European countries with 20,000 bulls in their reference population)

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Conclusions

• Genetic evaluations will continue to be important as it provides the basis for the accurate selection of animals

• SNP based methodologies are becoming the norm and are likely to be further refined in the next few years

• In this era of genomics, recording and storage of accurate phenotypic records will be key as these are the basis for estimating SNP effects

• International evaluations might likely focus on SNP models rather than on bulls if the political barriers can be overcome

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Genomics in African context

• Sires (Males) play the most significant role in

genomic selection.

• EBVS are more accurately estimated and therefore

more accurate estimates of SNP effects

• Have wider impact in terms of dissemination across

the breed

• Therefore any strategy should involve

– Genotyping all sires or males

– If no resources available, store DNA samples for all

males

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Genomics in African context

• Regional application most likely to be more

effective

– Collaboration among countries in the region for breeds

used across these countries

– Genotyping with HD will be necessary to allow for multi-

breed reference population (still under study)

– I guess that most of the foreign bulls used in cross

breeding have been sequenced in their countries of

origin. Some sort of collaboration to get the information

might be necessary

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Genomics in African context

• Some sort of region genetic evaluation (across the

countries) will be needed to implement genomics

on regional basis

– There is SRUC PhD studentship commencing this

October to examine such across country genetic

evaluations in four sub-Sahara countries

– This project is in collaboration with colleagues here at

ILRI, Kenya; ARC in South Africa, University of

Zimbabwe, and University of Agriculture and Natural

Resources in Malawi.

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Genomics in African context

• Since cross breeding is very important,

identification and use of haplotypes with specific

combining abilities has huge potential ( under

study)

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Questions?