VoIP Service and Marketing using Odoo and Asterisk PBX
From contemporary comparison to genomic selection: Trends in the principles for genetic evaluations
1. From Contemporary Comparison to
Genomic selection; trends in the
principles for genetic evaluationsRaphael Mrode
Raphael Mrode
2. 22
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
3. 33
SRUC Research
• Animal & Veterinary Science
– Edinburgh Genetic evaluation services (EGENES)
• Crop and Soil Systems
• Land Economy and Environment
• Future Farming system
4. 444
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
5. 555
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
6. 666
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
7. 777
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
8. 88
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
9. 999
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
10. 1010
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
13. 13
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
14. 14
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
15. 1515
• 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
16. 1616
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
16
17. 1717 17
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
18. 1818 18
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
19. 1919
Genomic Era
• However over the last 7 years developments in molecular
biology meant genotyping technology for single nucleotide
polymorphism (SNP) has become available.
20. 202020
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
21. 212121
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
22. 222222
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
23. 232323
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
24. 242424
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
26. 26
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
27. 2727
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
28. 2828
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
29. 2929
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)
30. 3030
Marketed HOL bulls in USA
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2007 2008 2009 2010 2011
%oftotalbreedings
Breeding year
Old non-G
Old G
First crop non-G
First crop G
Young Non-G
Young G
31. 313131
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
32. 323232
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
33. 333333
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)
34. 343434
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
35. 3535
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
36. 3636
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
37. 3737
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.
38. 3838
Genomics in African context
• Since cross breeding is very important,
identification and use of haplotypes with specific
combining abilities has huge potential ( under
study)