Download Use Of Molecular Genetics In Poultry Breeding Programs: Short Vs

Use Of Molecular Genetics In Poultry Breeding Programs: Short Vs Long Term
Considerations
by
William Muir
1151 Lilly Hall, Department of Animal Sciences, Purdue University 47907.
INTRODUCTION
Advances in molecular genetics have raised the possibility of direct selection on the
genotype for genetic improvement of traits (See Muir 2002a, b for review). However, the
major question commercial breeders are asking is how much advantage will this new
technology offer over existing technology. Gibson (1994), conducting simulations using
an additive infinitesimal model plus a single bi-allelic locus, concluded that the answer
depended on the time horizon of interest. In the short term, greatest response resulted
from inclusion of molecular information while in the long term phenotypic selection gave
the greatest response. To address this issue, Dekkers (1998, 1999), Dekkers and van
Arendonk (1998) proposed dynamic allocation of weights, changing with time based on
Control Theory (See Dekkers and Hospital 2002 for review).
The objective of this research was to further examine these issues as particularly
impacted by a number of variable, including heritability and method of selection. These
issued were examined useing a Monte Carlo gene level simulation program. We limit
here examination of selecting directly on candidate genes to avoid the issue of
recombination with a lined marker, as such, these simulations should be viewed as the
upper limit of what is possible with MAS.
MATERIALS AND METHODS
A gene level simulation program was developed that included 500 quantitative trait loci
(QTL), each with two alleles, randomly distributed over 10 chromosome pairs, including
the sex chromosomes, with a total genomic size of 3500 centiMorgans. Recombination
was based on Haldane's (1919) formula as a function of map distance. Distribution of
gene effects (aij) was assumed normal, i.e. a large number ofloci with small effects and a
few with large effects (either plus or minus). Allele frequencies at each locus was
randomly set based on a uniform distribution. The base population was constructed such
that it was in both gametic and zygotic phase equilibrium. Environmental effects were
normally distributed with a variance set to give a desired heritability.
Three heritabilities were examined: .1, .25
numbers of each sex) was sampled from the
assumed to be measurable either sex-limited,
Phenotypic (P), and MAS, and 2 methods of
32
and .4. A population of size 2304 (equal
base population. The trait of selection was
or non-sex-limited. Two selection schemes,
evaluation, Best Linear Unbiased Prediction
(BLUP) and Individuals Own Performance (IOP) were examined. For each type of trait
(sex limited or not) and selection scheme, 192 males and 192 females were selected and
mated at random to produce the next generation. This process continued for 30
generations. The entire simulation was replicated 40 times, starting over each time with a
new sample of animals from the base population.
For Phenotypic selection, evaluation was based on the expected breeding value
determined from information only on the phenotype (Yp)
- EBV(Y)
Where EBV is the expected breeding value as determined by either IOP or BLUP
For MAS, evaluation was based on the phenotype adjusted for the candidate gene (Yp'),
and the candidate gene (Yc)
IMAS= EB V(Yp, ) + bcY
Where be is the weight places on the candidate gene, and EBV is the expected breeding
value as determined by either IOP or BLUP. Seven different weights were used in
combination with the index: 0, .1, .25, .4, .6, .8, 1.0, 1.5. The theoretical short term
weight is bc=l.
RESULTS
Non-Sex-Limited
Traits.
Figure 1 shows the classic results found by Gibson (1994) where MAS gives a short term
gain and long term disadvantage. However, when BLUP evaluation is used, there is a
short term advantage but no long term disadvantage. Examination of gene frequencies
shows that BLUP selection places less weight on the candidate gene than IOP, and is also
more efficient in changing the polygenic frequency. As a result there is less or no
polygenic drag. Sex-limited traits (Figure 3 and 4) showed as similar result but to a
greater degree, i.e. there was an advantage in both the short and long term, although the
advantage was greater in the short term.
Figure 1. Selection response for a non-sex-limited traitbased on IOP evaluation and
Phenotypicor MAS selection (bc=l).
H2:1.1 $(ILIH:O
ISEL=)O4 I[rlOO=lOP
IO
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Figure 2. Selection response for a non-sex-limited trait basedon BLUP evaluation and
Phenotypic or MAS selection (bc=l).
H2:0.i
$[ILIB:O
KS[L:304 H(rHOb=OLUP
tO0
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Figure 3. Selection response for a sex-limited trait based on IOP evaluationand
Phenotypic or MAS selection Coc=l).
H2-.0.1 SEILIH=I
HS(L-,']8¢ H[THOO:IOP
GO
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Figure 4. Selection response for a sex-limitedtrait based on BLUP evaluation and
Phenotypic or MAS selection (bc=l).
H2-0.1
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CONCLUSIONS
The concern of long term loss associated with marker assisted selection for either sex
limited or non sex limited traits is removed if BLUP (or other methods of combining
family information) is used to evaluate genetic merit. A short term gain and long term
' loss only occurs if individuals own performance is Used for non-sex-limited traits. The
differences in outcomes for BLUP vs.IOP is due to the relative weights the methods place
on the candidate genes.
Information from relatives used by BLUP to evaluate
performance automatically places less weight on the candidate gene and more weight on
the phenotype because the performance of relatives is adjusted for the candidate gene,
thereby increasing the accuracy on the genotype as determined by polygenes.
REFERENCES
Dekkers, J.C.M. and Hospital, F. (2002) Nature Reviews Genetics 3:22-32.
Gibson, J.P. (1994) Short-term gain at the expense of long-term response with selection
of identified loci. Proc. 5ta WCGALP. U. of Guelph, Guelph, Ontario CAN.
21:201-204.
Haidane, J.B.S. (1919) J. Genetics 8:299-309
Muir, W.M.. 2002.
Incorporating Molecular Information in Breeding Programs,
Applications and Limitations. In Poultry Breeding and Biotechnolog), Eds. WM
Muir and S Aggrey. CRC Press (in press).
Muir, W.M. 2002. Use of molecular genetics in poultry breeding.
Congress of Genetics Applied to Livestock Breeding. (In press)
Proc. 7_ World
52 Annual National Breeders Roundtable
St. Louis, Missouri
May 8-9, 2003
Questions and Answers
Speaker: Bill Muir
David Harry
Question:
Aside from allele frequency for candidate genes in populations, what other parameters
might you need to examine in your model? Specifically, I'm thinking about the number
of polygenes affecting a trait. What happens, qualitatively, if the number falls below the
threshold of 50?
ANSWER:
As the number of loci affecting a trait becomes small, the more rapid the genetic
parameter changes. Also the long-term response plateaus early as alleles at all loci
become fixed. This results becausethe per locus selection intensity increasesas the
number of loci decreases.
The most critical parameter that needs to be examined is the role of epistasis. As
molecular data increases on all species,almost all show epistasis.
Douglas Rhoads
QUESTION:
In your model how does the response compare between r4AS& phenotypic selection
when the candidate gene is actually 3 or 4 candidate genes with each having a minor
contribution (say 5%) to the variation in the trait?
ANSWER:
The trait is redefined as an index of the 3 or 4 candidates then the index behaves
similar to a single trait with the amount of genetic variation accounted for in the index.
Speaker: Bill Muir
Frank Siewerdt
QUESTION:
How likely is it to find a major gene in a very low frequency (e.g. P=.l) in a highly
selected population?
I believe that it would either through pleiotropy have an unfavorable effect on fitness or
that it should have a very high unfavorable correlation (rA) with the selection index in
use.
ANSWER:
There are four possibilities:
1. The trait has not been selected intensely, ie disease resistance or behavior
2. Antagonistic pleiotropy, the QTL has a favorable effect on one trait of economic
importance and an unfavorable effect on another with equal importance.
3. Genotypic environment interactions. The bird is grown in a new environment for
which a gene was previously disadvantageous, ie naked neck in cold vs hot
environment.
4. Epistasis(genotype x genotype interactions). On one genetic background the gene
is neutral or disadvantageous whereas on another it is advantageous (co-adapted
gene complexes)
Dominic Elfick
QUESTION:
In order to increase selection intensity, assuming program is running at maximum
efficiency, generation interval will increase, what effect will this have on the decision
whether to use MAS?
ANSWER:
Increasing generation interval as a result of increasing selection intensity (the
reproduction capacity must be increased) decreases the response per unit of time thus
further supporting an economic advantage of marker assisted selection which give a
response advantage without increasing generation interval.