genetic evaluation programs and future opportunities jueves ingles/james ro… · genetic...
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Genetic evaluation programs
and future opportunities
James Rowe (Sheep CRC, Australia)
Raul Ponzoni (Universidad de la República)
Daniel Brown (Sheep Genetics, Australia)
Julius van der Werf (UNE, Australia)
10th World Merino Conference 2018, Montevideo
Genetic evaluation
estimating genetic merit (breeding values)
NOT – what sort of sheep to breed
NOT – what sort of sheep to produce
Genetic gain determined by:
accuracy of estimating genetic merit
generation interval
0
0.2
0.4
0.6
0.8
1
0 0.5 1 1.5 2 2.5 3 3.5
Accura
cy
Age (years)
Assumedheritability=25%;Accuracyofgenomictest=50%
Performancerecord
Progeny
ParentEBVs
Noperformancerecords
ParentPerformance
Average fleece weights – Australia 1860-2010
0.0
1.0
2.0
3.0
4.0
5.0
6.0
1860 1910 1960 2010
Ave
rag
e fle
ece
we
igh
t (k
g/h
ea
d )
Trait trends in Australian Merinos (Swan et al. 2017)
Fining the clip FD
YWTIncreasing meat income
CFWFocus on fleece weight
MPP (Mer)
2000 2005 2010 2015
0
40
80
Year of birth
Contr
ibutio
n to in
dex
gain
(%
)
YWT
AWT
EMD
WEC
NLW
CFW
FD
SS
Estimating genetic merit (breeding values)
Pedigree
Performance
Genotype (DNA)
Estimated Breeding Values
(ASBV)
Indexes
Rate of Genetic Gain (index trends)
Maternal
1990 1995 2000 2005 2010 2015
0
1
2
3
4
5
Year of birth
Index tre
nd (
SD
)
MATDOL (BL) MATDOL (CM)
Merino
1990 1995 2000 2005 2010 2015
0
1
2
3
4
5
Year of birth
Index tre
nd (
SD
)
MPP (Mer)
Terminal
1990 1995 2000 2005 2010 2015
0
1
2
3
4
5
Year of birth
Index tre
nd (
SD
)CPLUS (Term)
Swan et al., 2017 AAABG
Maternal Merino Terminal
Ra
te o
f g
ain
–In
de
x tre
nd
(S
D)
2000 2005 2010 2015
0.0
40.0
80.0
120.0
160.0
200.0
1 2 3 4 5 6 7 8 9 10
Cum
ula
tive N
et
Pre
sent V
alu
e
($1000 u
nits)
Years
Faster genetic gain drives profit(Extra net income per 2,000 ewes) (Granleese 2018)
Stud gains(Index points/yr)
6
4
2
1
Genetic evaluation is a key tool
- helps achieve rapid genetic gain
- contributes to well-balanced genetic gain
- but…... expensive
Performance recording
Reference flocks
R&D of the genetic evaluation system
Database management and computing
Costly development of analytical tools
– Single step, MateSel, RamSelect, Flock profiling
Strong case for International collaboration
Competing against other breeds & species –
not against Merino breeders in other countries
Cloud computing makes data sharing easy
Compelling economies of scale in genomics
Standardised DNA testing in multiple countries
Good examples in dairy and beef breeding
G x E concerns increasingly well understood
Shared access to tools (Single Step, MateSel,
RamSelect, Flock Profiling …)
MERINOSELECT evaluation for
Australia and New Zealand (Brown & AGBU)
G x E interactions ?
13
Studied a range of traits – many environments
Accounted for sire by flock & year (SxF) interaction
Conclusions
All traits investigated had high genetic
correlations when Sire x Flock interaction
included
Breeders can select on MERINOSELECT
ASBVs regardless of the country of origin
MERINOSELECT is ‘open’ to concept of
hosting single international evaluation for
Merinos.✔ ? ? ? ?
Tools for improved genetic gain
MateSel available to Sheep Genetics client’s to
help with mate selection.
SingleStep evaluation analysis incorporating:
pedigree, performance & genomics
RamSelect.com.au a web-based app to help
identify rams for specific breeding objectives
Genomic Flock Profiling average flock breeding
values from DNA testing 20 latest drop progeny.
A benchmark to guide ram purchases.
Analysing genetic gain (From Swan et al 2017)
How does actual gain for Merinos
compare to potential gain?
How do individual ram breeders
compare?
Actual gain as % of potential gain(Swan et al. 2017)
Maternal
2000 2005 2010 2015
25
50
75
100
Year of birth
% p
ote
ntial gain
MATDOL (BL) MATDOL (CM)
Merino
2000 2005 2010 2015
25
50
75
100
Year of birth
% p
ote
ntial gain
MPP (Mer)
Terminal
2000 2005 2010 2015
25
50
75
100
Year of birth
% p
ote
ntial gain
CPLUS (Term)
Maternal Merino Terminal
100
75
50
25
2000 2005 2010 2015 2000 2005 2010 2015 2000 2005 2010 2015
Comparing gains for individual breeders)
-20
0
20
40
60
80
100
120
140
MPP (Mer) CPLUS (Term)
Top
20%
Bottom
20%
Top
20%
Bottom
20%
Merino Terminals
(From Stephen et al 2018)
Full pedigree data is one problem
0
20
40
60
80
100
Merino Terminal
(From Stephen et al 2018)
Top
20%
Bottom
20%
Top
20% Bottom
20%
Merino Terminals%
of a
nim
als
with
fu
ll p
ed
igre
e
Information Nucleus – innovation platform
Information
Nucleus
DNA
MeatWoolSheep
Phenotype data
1. Understanding complex phenotypes
2. Quantifying G x E
3. Genomic prediction of breeding values
4. Bio-bank (DNA and database)
Genomics
207Blending GBLUP EBVs with
ASBVs (2012)
Single Step Carcase Analysis
(2016)
Full Single step in Main Analyses
(2017)
Impact on industry through genomics (genetic gain - index points/year)
2000-2010 2011-2017 Difference
Merinos (MP+) 1.57 2.19 +39%
Terminals (C+) 3.85 4.29 +11%
Terminals (LEQ) 1.36 2.00 +47%
Some Confounding factors
e.g. Index development &
Reference population(Brown et al 2018)
Prediction accuracy: Meat Traits in Merino
0.0
0.1
0.2
0.3
0.4
0.5
0.6
ccfat cemd imf pemd sf5 pwt
Pre
dic
tio
n A
ccu
racy
50K 50K+Top Seq (2)
Value of genomicsearly information and difficult to measure traits
0
0.2
0.4
0.6
0.8
1
0 0.5 1 1.5 2 2.5 3 3.5
Accura
cy
Age (years)
Assumedheritability=25%;Accuracyofgenomictest=50%
Performancerecord
Progeny
ParentEBVs
Noperformancerecords
ParentPerformance
Genomic
Conventional
DNA tests getting cheaper and predictions more accurate
y=34.45x-69117
-
50
100
150
200
250
300
350
400
2004 2006 2008 2010 2012 2014 2016 2018
Numberofstudsregisteredin
MER
INOSELCT
Increase in membership of MERINOSELECT
Rapid increase in poll ram semen sales(Note: DNA test developed 2009)
0
4000
8000
12000
16000
2005 2007 2009 2011 2013 2015
Dose
s s
old
(N
SW
AA
SM
B)
Increase in poll ram sales (‘Top 20’ NSW studs)
(Note: DNA test developed 2009)R
am
s s
old
(N
SW
AA
SM
B top
20)
0
2000
4000
6000
8000
10000
2005 2007 2009 2011 2013 2015 2017
Poll
Horn
-
20,000
40,000
60,000
80,000
2010 2012 2014 2016 2018
(a) DNA parentage test numbers
(per year)
-
5,000
10,000
15,000
20,000
2010 2012 2014 2016 2018
(b) Genomic test numbers (per year)
Increasing use of DNA (Genomic) testing
Concluding comments
• Genetic evaluation programs are crucial for rapid and well-
balanced genetic gain
• Many Merino breeders can achieve much faster genetic gain for
a range of traits required by their clients
• Genomics offers huge potential for Merinos
• New tools and services (Single Step, MateSel, RamSelect, Flock
Profiling) assist in making best use of genetically superior sheep
• International collaboration – a strong case a single evaluation
program based on MERINOSELECT
? ? ? ?