Hugo H. Montaldo* Division of Animal Science, University of New England, Armidale, NSW. 2351. Australia. Tel : 61-2-6773-3004, Fax : 61-2-6773-3275 E-mail:hmontald@metz.une.edu.au. Cesar A. Meza-Herrera Unidad Regional Universitaria de Zonas Aridas. Universidad Autónoma Chapingo. A.P. No. 8. Bermejillo, Durango. México. 35230. E-mail:cmeza@chapingo.uruza.edu.mx *Corresponding author Keywords:
Livestock, Genetic improvement, Molecular markers, Marker assisted selection,
Quantitative trait loci, Major genes.
Recent developments in molecular biology and statistics have opened the possibility of identifying and using genomic variation and major genes for the genetic improvement of livestock. Information concerning the basis of these techniques and their applications to the genetic improvement of animals is reviewed. Main marker molecular marker systems in animals (RFPL and microsatellites), genome maps, methods for detecting marker major gene linkages and use of marker assisted selection, genetic fingerprinting and mixture models based on segregation analysis are analyzed. The characteristics where the application of marker assisted selection can be more effective are those that are expressed late in the life of the animal, or controlled by a few pairs of genes. The first example correspond to the longevity and carcass characteristics in meat producing animals, the second, to the resistance to certain diseases or defects of simple inheritance. The detection of major genes using mixture models with segregation analysis can direct the work of identification of DNA marker genotypes towards populations and characteristics with greater probability of detecting a major gene using molecular markers. The present trend indicates that molecular, pedigree and phenotypic information will be integrated in the future through mixture models of segregation analysis that might contain major gene effects through the markers, polygenic inheritance and uses powerful and flexible methods of estimation such as Gibbs Sampling.
During the last five decades, the application of methods based on population genetics and statistics allowed the development of animals with a high productive efficiency. These systems are based on simplified models of genic action that assume a large number of or genes with small individual effects in the expression of the phenotype (polygenes) and emphasizes the average genic effects (additive effects) over their interactions. The basis is predicting the breeding values of the animals using phenotypic and genealogical information. Properties of the predictions are equivalent to the levels of correlated random effects of a mixed linear model or best linear unbiased predictors (BLUP) which is based to a large extent on the work of C. Henderson (Henderson, 1984). Important advances to some of the economically important characters in several species of livestock has been a achieved based on phenotipic performance, how ever, several limitations of these methods of improvement based on population genetics alone are becoming evident with time. Their efficiency decreases when the characteristics are difficult to measure or have a low heritability. Additionally, selection has been generally limited to those characteristics that can properly be measured in large number of animals. Some characteristics such as the rate of survival are expressed very late in the life to serve as useful criteria of selection. Also, the traditional selection within populations has not been very efficient when the selection objective involves several characteristics with unfavorable genetic correlation, for example, milk production and protein content of milk (Schwerin et al., 1995). Additional terms which are biologically plausible could be added to the model, but seldom their effects can be estimated accurately with only phenotypic and genealogical information in outbreed animal populations. These complications might include interactions between genes in the same locus (dominance) or in different loci (epistasis) and between specific genes and the environment (genotype by environment interactions). The use of molecular techniques could help to solve some of the limitations of the current methods. The capacity to generate dense genetic maps in each species can in principle allow the complete genome to be evaluated for quantitative trait loci (QTL) with a major effect on the phenotype. This information can then be used in genetic programs (Kinghorn et al., 1994). Also, advances in the statistical and mathematical techniques applied to the modelling of the genetic processes are helping to make an optimal use of molecular and phenotypic information in the selection process.(Bovenhuis et al., 1997; Hoeschele et al., 1997). Molecular techniques allow detecting variation or polymorphisms exists among individuals in the population for specific regions of the DNA. These polymorphisms can be used to build up genetic maps and to evaluate differences between markers in the expression of particular traits in a family that might indicate a direct effect of these differences in terms of genetic determination on the trait. More probably, the can prove some degree of linkage of the QTL effecting the trait and the marker (Albert et al., 1994; Lewin, 1994; Stein et al., 1996). Recently, methods have been developed to detect the presence of major genes from the analysis of pedigreed data in absence of molecular information (Bovenhuis et al., 1997). These methods, based on mixture models and segregation analysis, allow to direct the potentially expensive and time consuming genotyping activities towards populations and characteristics with a greater probability of being controlled by a QTL and to optimize the collection of molecular data (Kinghorn et al., 1994). The objective of this paper is to review some advances on molecular genetics and statistical methodology to identify and estimate the effects of major gene effects in animal populations, and its potential use in the genetic improvement of livestock. Restriction fragment length polymorphisms Sax (1923) showed that an observable gene with simple mendelian inheritance could act as a marker for the segregation of a gene involved in the expression of a quantitative trait. Early work on detection of genome variation of potential markers focused on the analysis of proteins and blood type variation, but this was found to be impractical to be used as genome markers. Protein systems lack adequate polymorphism, genome coverage was low and there was a requirement for the gene to be expressed at the phenotypic level to make detection possible (Drinkwater and Hetzel, 1991). Beginning in 1980, an accelerated understanding of the structure and function of the genome has been obtained as animals (Schimenti, 1998). At first, techniques were developed to visualize the differences at the level of the structure of the DNA based on the use of bacterial restriction enzymes that cut the DNA at sites with specific nucleotide sequences. With this basis, the technique denominated restriction fragment length polymorphisms (RFLPs) was developed. The identification of RFLPs requires the use of gel electrophoresis to separates the DNA fragments of differing sizes followed by transfer of the fragments to a nylon membrane (Southern blot) and visualization of specific DNA sequences using radioactive or chemiluminescent probes exposed to an X-ray film (Drinkwater and Hetzel, 1991). This methodology was the standard method
in the identification of RFLPs before 1986, situation that limited the
identification of the whole genome variation in animals. This technique
allowed the identification of only two alleles per locus and is slow compared
with large genome size in mammals of about 3 x109 individual nucleotides
in the total DNA content (Albert et al., 1994; Brash,
1994; Lewin, 1994; Wilmut et al.,
1992). The reduced variability observed in domestic animals by inbreeding
makes many RFLPs sites non-informative. Modification of the RFLPs technique
is possible to identify multiple alleles, but have still practical drawbacks
that make preferable the use of the PCR based microsatellite markers (Drinkwater
and Hazel, 1991). Polymerase Chain Reaction (PCR) Mullis et al. (1986) developed the
process known as polymerase chain reaction or PCR. This allows to the
amplification or reproduction in great amounts of particular regions
of the DNA. In order to initiate the process of replication of the DNA,
two informing sequence codes denominated primers are required which
promote the beginning and reversion of the reaction of the polymerase
(RNA-pol) at particular locations of the genome. A reproduction or amplification
of thousands of copies of a chromosomal region or gene of interest is
obtained by repeated cycles of synthesis and denaturalization (chain
separation) of the DNA using temperature changes. Since the primers
are specific sequences to bond to a determined region of the DNA, only
the specific amplification of the desired sequence of DNA instead of
amplifying the DNA in its totality is obtained (Buratowski,
1994; Koleske and Young, 1995; Stein
et al., 1996). Parallel to the development of the PCR, a new type
of polymorphism of DNA also known as hypervariable minisatellites were
discovered in the DNA structure. These minisatellites are defined regions
of DNA with polymorphisms in the number of repeated nucleotide sequences
of around 25 bp in length. These minisatellites can be used for search
for marker genes associations and as DNA fingerprints in paternity testing
(Albert et al., 1994; Lewin, 1994;
Bishop et al., 1995; Smith and Smith, 1993;
Stein et al., 1996). Microsatellites systems are composed of DNA repeats
in tandem at each locus. The tandem repeats are usually simple dinucleotides
(such as (TG) n ) with each dinucleotide repeated about ten
times. Its high degree of polymorphism in the number of repeats (n)
allow its use as location markers in genome mapping. The length of each
allele is determined by PCR using specific oligonucleotides primers
flanking the repeated sequence. The DNA products are visualized after
electrophoresis. PCR based Microsatellites techniques facilitated the
construction of genome maps in most livestock species because its abundance
in the genome, the specificity of the primers, its high degree of polymorphism
which several alleles and their easy detection (Albert et
al., 1994; Lewin, 1994; Bishop et al.,
1995; Smith and Smith, 1993; Stein et
al., 1996). Other types of DNA genetic markers used mainly in plant
breeding but with potential use in animals are randomly amplified polymorphic
DNA (RAPD), simple sequence repeats (SSR) and amplification fragment
length polymorphisms (AFLP) (Specht, J. personal comunication, 1996).
New types of markers are single nucleotide polymorphic
markers (SNP) based on high density DNA arrays (Chee et
al., 1996 ). In this technique of "gene chips", DNA corresponding
to thousand of genes are arranged on small matrices ("chips")
and probed with labeled cDNA from a tissue of choice. The information
is then read by a device to be downloaded to a computer (Schimenti,
1998). Highest resolution of DNA variation can be obtained
using sequence analysis. Sequence analysis provides the fundamental
structure of gene systems. DNA sequencing is generally not practical
to identify variation between animals for the whole genome, but is a
vital tool in the analysis of gene structure and expression (Drinkwater
and Hazel, 1991). A step towards the use of genomic information in livestock
improvement is the location of all markers and protein coding genes
in the chromosomes. Thus the development of genetic maps of the species
of interest is required for detecting QTL using genetic markers (Bovenhuis
et al., 1997). Mapping based on recombination frequencies could
be built up on the basis of genetic marker genotyping from DNA obtained
from populations of reference, with several collaborating laboratories
worldwide (Beattie, 1994). Development of PCR based techniques
and microsatellite markers, increased the efficiency of the mapping
processes in all living organisms. An aid in the development of livestock genome maps,
has been the high level of conservation of gene sequences between humans,
cattle, sheep, goat, pig and mice. By such reason, once loci of particular
DNA sequences has been mapped in one species, the information is frequently
of help in the genome mapping in another. Livestock species mapping
had been greatly facilitated by the increasing availability of human
and murine sequences (Beattie, 1994; Schimenti,
1998). Additionally, the construction of physical maps has
been favored by means of the development of techniques like the hybrids
of somatic cells and fluorescence in situ hybridization (FISH)
(Beattie, 1994). With the development and use of these
techniques, genome mapping has had a spectacular advance in the last
years. Whereas in 1990 150 positions in the bovine genome had been identified,
for 1998 this number surpasses 1,500 positions. Examples of current genome mapping information available
in the Internet for several mammal species are: http://sol.marc.usda.gov/genome/cattle/cattle.html http://sol.marc.usda.gov/genome/swine/swine.html http://ws4.niai.affrc.go.jp/dbsearch2/mmap/ There are two main categories of genomic information
that can be used in genetic improvement of livestock: :
Examples of the first type (1) in livestock are: 1.1 The gene associated with porcine malignant hyperthermia.
In this case, a (C® T) mutation at position
1843 of the gene calcium release channel ryanodyne receptor locus (Ryr1)
in recessive condition have a high probability of being the cause of
the susceptibility to this disease (Huges and Lowden, 1998). 1.2 The myostatin (MH) locus which contains
a series of mutations which disrupt the myostatin function, detected
in several European cattle breeds causing muscular hypertrophy (Georges
et al., 1998). 1.3 A promising candidate gene for litter size in pigs
is the estrogen receptor gene. Independent confirmation of such an effect
in several populations might help to confirm the suspected QTL effect
of this gene (Rothschild et al., 1996). The approach for search genes of type (1), known as
candidate gene, based on the physiological or biochemical affinity of
gene with the nature of the characteristic, has not yet been useful
in the identification of an important number of genes in quantitative
traits. Its use has been considered with some skepticism in the case
of diseases of the mouse. (Frankel, 1995). In the mouse, the number of identified potential markers
type (1) is greater than in other species of mammals. In this species,
the presence of inbred lines, short generation intervals and reduced
costs by individual allow good conditions for detection. Part of the limitations of the candidate gene approach
seems to be the polygenic nature of most traits in animals, the appearance
of mutations and the possibility that the supposed QTL is in fact a
marker type (2) very next to gene, which allows some probability of
recombination. Another possibility is the presence of interactions between
genes in different loci (epistasis). These can modify the expression
of genes in populations with different genotypes (races or crosses).
As an illustration of these difficulties, there are animals detected
as free of the porcine malignant hyperthermia mutation with the PCR
based test that show the disease (Huges and Lowden, 1998).
The second type (2), corresponds to genes linked to
the QTL with detectable variation by means of RFLP, microsatellites
or other similar molecular systems (Beattie, 1994). Several
studies have demonstrated relationships between molecular variants and
the phenotypic expression in several characteristics in several animal
species (Andersson et al., 1994; Ashwell et
al., 1997; Beever et al., 1990; Georges
et al., 1995; Haley, 1995). This has stimulated
the idea to add the genomic to the phenotypic information to increase
or speed up the selection response to the "traditional methods"
in which it is known as marker-assisted selection or MAS. In laboratory species, crosses between full inbred
lines allow to produce F2 of segregating backcrosses suitable for efficient
detection of QTL-marker linkages. In normal outbreed livestock populations
the linkage between the markers and the QTL (linkage disequilibrium)
will disappear when is evaluated across families. This makes pointless
to compare the average performance of animals with different molecular
variants from the whole population to infer marker-QTL associations.
Information from crosses of within family analysis is therefore required
to detect associations or linkage disequilibrium between the marker
and the QTL (Weller et al., 1990). In livestock, there are basically four design possibilities
for marker QTL linkage analysis.
Method 1 allows detecting QTL already fixed in one
breed. Methods 2 and 3 are more suitable for prediction of QTL effects
for within-population selection.
In outbred populations, only heterozygous sires or
grandsires will be informative for the segregation of the marker for
the marker and the QTL. In a family, where the marker and the QTL allele
are in coupling phase, the effect detected for the substitution of allele
A1 of the marker by allele A2 can be of for example -500 kg of milk.
In another family, where the marker and the QTL allele are in repulsion,
the result will be of +500 kg. Marker assisted selection (MAS) It is currently possible to incorporate this information
in the present systems of selection with BLUP, that is to say, to add
the information corresponding to the markers to the systems of equations
of the mixed model (Goddard, 1992; Kinghorn
and Clarke, 1997). The identification of the precise position of the QTL
in the chromosome, avoids the ambiguity caused by the possibility of
recombination between the marker and the QTL. In the later case we should
strictly define this kind of selection as QTL assisted selection. For
simplicity we treat this option as a special case of MAS without recombination
among the marker and the QTL. Current marker use in MAS with the availability
of relatively dense genome maps and multiple microsatellite markers
available, will be more probably groups of allelic configurations of
haplotypes, usually flanking the QTL, than a single marker. These haplotypes
could in some cases have very low recombination rates with the QTL.
Several studies of simulation have evaluated the consequences
of MAS in populations with a QTL segregating by comparing the use of
a purely polygenic animal-BLUP model with a mixed model that incorporates
both the polygenic effects and the haplotype identities. An extreme
case is the result of Meuwissen and Goddard (1996).
They found possible increases of 30 to 64% in the genetic response to
selection of different characteristics in the first five generations
from selection when the QTL explains a 33% of the genetic variation
in the base population. However, Ruane and Colleau (1995)
found possible increases in selection response of only 0.2 to 1% in
six generations using a single marker. Pongpisantham (1994) found that the
inclusion of markers could increase up to 15% the genetic response to
selection for growth rate in a population of chickens, compared with
selection based on family selection. Ruane and Colleau (1996)
found an increase of 6 to 15% from MAS in the selection response for
milk production in cattle nucleus that used multiple ovulation and embryo
transfer (MOET) in the first six generations of selection. In a review, Clarke (1997) concluded
that substantial increases to the selection response are possible using
MAS in several species. The range of the estimates of increase in selection
response for all studies with parameters combinations giving the maximum
responses were 2 to 38%. Similar range for parameters combinations giving
minimum responses were –0.7 to 22.4%. She concluded that the increases
in selection response from MAS could be overestimated by an inadequate
modeling of the reduction in the QTL variance by selection. The variation in the results are a consequence of differences
in the assumed sizes of the QTL effects, allelic frequencies, recombination
rates between the marker and the QTL, type of marker (single or haplotype),
residual polygenic variances, environmental variances, number of generations
of selection, population structures and selection procedures. This suggests
to maintain an attitude of caution in absence of greater experimental
evidence and a greater amount of simulation studies covering more specific
situations, that allow to reach certain consensus on the value of the
MAS in diverse characters and species. Meuwissen and Goddard (1996) concluded
the following from their study on the use of the MAS:
Some studies have shown possible economic advantages
of the use of the MAS in dairy cattle (Meuwissen and van
Arendonk, 1992; Ruane and Colleau, 1996;
Spelman and Garrick, 1997) when the benefits are evaluated for the
industry as a whole. It is applied with progeny testing or multiple
ovulation and embryo transfer (MOET) nuclei improvement schemes. The increase of the density of genome maps can have
other potential beneficial effects in the genetic improvement. Through
the identification of paternity in production systems, without controlled
mating by means of the use of "genetic fingerprinting" or in the most
precise estimation of the genetic relations between the animals, to
calculate the additive numerator relationship matrix among animals (A),
used in the mixed model equations for the genetic evaluations with BLUP
(Nejati-Javaremi et al., 1997). Mayo (1996) analyzed the possible application
of QTL technology to Merino sheep breeding in Australia. He concluded
that introduction of new technology will be slow and suggests that the
first technology to be used is cost-effective DNA parentage, due to
the lack of pedigree information, which hinders the utilization of BLUP
techniques. Another application of genetic fingerprinting is the
search of the maximization of dominance effects in crosses (to maximize
heterosis) (Godshalk et al., 1990) and their use to control inbreeding.
These possible applications are still preliminary ideas that require
further evaluation. Current estimation methods of heterosis from crossing
experiments are very expensive, thus, indirect prediction of heterosis
from genetic diversity at the molecular level may be advantageous. An application that has been mentioned in the literature
is the introgression a major gene in another population by means of
backcrosses assisted by molecular markers. In this case, it does not
seem to exist advantage in using a single genetic marker information,
in comparison with the use of only phenotypic information when the characteristic
is continuous and the considered genetic effects are additives (Groen
and Smith, 1995). Nevertheless, it seems feasible that using a dense
map that involves many chromosomal regions and with more than one allele
of interest, the time for fixation of the major genes can be reduced.
Detection and use of major genes In the last ten years statistical methodologies of
detection of major genes based on pedigree and phenotypic information
on populations have been developed for animal populations. These methods
are based on the use of mixed models and segregation analysis to fit
the data to a mixture genetic model that includes in addition to the
polygenic effects, those of a biallelic major gene. Calculation is performed
in two stages; firstly genotype probabilities are obtained, then major
gene, fixed effects and polygenic effects are fitted and used to recalculate
new parameters by regressing phenotypes on estimated probabilities.
Calculation is iterated upon convergence (Kinghorn et al.,
1993). Segregation analysis allows inferring the unknown genotypes
from the probabilities of transmission of the gene given the phenotype
of the individual and their relatives. In mixture models, regression and Gibbs sampling estimation
approaches have been implemented to obtain estimates of the major gene
effects and allelic frequency (Bovenhuis et al., 1997).
Meuwissen and Goddard (1997) evaluated
the effect of including different proportions of individuals genotyped
for a QTL in a mixture model that is based on the analysis of segregation
of Kerr and Kinghorn (1996) and a regression approach
which uses the estimated genotype probabilities as weights in the estimation
process. Unbiased estimates of QTL effect and frequency were obtained
in absence of information on the genotype of the QTL, but some improvement
in the precision of the estimates were observed as the proportion of
genotyped individuals increased. The main limitation of this method
is that the genetic hypothesis is generally limited (one biallelic locus),
thus, the presence of more alleles could not be detected. Also, the
location of the locus in the genome, in absence of markers, remains
unknown. Mixture models can be modified to include markers associated
with the QTL, instead of the direct effect of the QTL in addition to
the information of the pedigree and the phenotype. This is achieved
by modifying the additive numerator relationship matrix (A),
according to the conditional probabilities of transmission of the given
QTL the information of the markers (Kinghorn and Clarke,
1997). These developments can make possible to evaluate the
likelihood of the model or another fitting criterion, to prove the relation
between the markers and the QTL in populations animals with outbreed
mating structures. They also may increase the possibilities of making
MAS in animal populations when incomplete information exists on the
genotypes of the animals for the QTL or markers so that the use of the
genomic information is optimized. Kinghorn (1997a) developed
a method to evaluate the amount of genomic information that it allows
maximizing a function of economic utility for the analysis of QTL with
mixture models. Major genes have been detected using these methods
for carcass characteristics in pigs based on a mixture model of inheritance
and Gibbs Sampling (Janss et al., 1995). Also, important effects of
major genes have been detected using Findgene software (Kinghorn,
1997b) for several carcass characteristics in cattle (Woodward
et al., 1998) and for parasite resistance in sheep (McEwan
and Kerr, 1998). This methods that make use of information currently
available in many animal populations, are an option for a preliminary
screening for major genes that can contribute to rationalize the use
of expensive QTL-marker linkage estimation experiments. A fundamental aspect for the efficient use of the markers
for the MAS resides in the right detection of the location of the QTL
in the chromosomes, as well as of the magnitude of its allelic effect
and its allelic frequency. Most of the available studies for detection
of QTL have limitations of power related to the design, structures of
the pedigree and number of animals evaluated for the molecular variants.
This causes that, in most of the cases, the estimations have relatively
high statistical error. On the other hand, considering that in any study
is necessary to accept a value for the error type I (it is to say to
reject the hypothesis of existence of the QTL, when this really it does
not exist), it is possible that an important fraction of the QTL reported
in the literature are a product of the expected number of null hypotheses
incorrectly rejected. Low experimental power will reduce the detection
rate of true QTL The accumulation of studies within the same chromosomal
region can help to distinguish between the cases of real or false QTL
detection. Meuwissen and Goddard (1996) demonstrated
that the incorporation of a false QTL to MAS, can reduce the genetic
gain to 14% in comparison with a usual polygenic BLUP model. An alternative to determine the value of the MAS, is
to use deterministic models of the selection response (Luo
et al., 1997). The development of deterministic models that accurately
predict the selection response using MAS, could simultaneously optimize
selection schemes that involve the selection with BLUP, the use of reproductive
techniques like the multiple ovulation and the production in vitro of
embryos and the MAS in livestock populations. The use of stochastic
simulation, although having advantages, presents as a main difficulty,
the required time to obtain a suitable number of replicates. It is also
difficult to maximize the response functions due to the number of combinations
to study. Most studies so far have dealt with the effect of MAS
using rather simplified assumptions and a single trait affected by one
QTL and polygenes. Studies using more realistic models such as multiple
estimated QTL effects and multiple trait selection could help to make
better decisions regarding the use of MAS in animal improvement. While molecular techniques offer important options
for the genetic improvement of livestock, the materialization of these
expectations requires of the solution of a number important of technical
problems to take advantage of all the information available an efficient
way, to reduce the costs of generating genomic information and to obtain
reliable estimations of the effects of the QTL and the application of
the MAS and the genomic information in general for the improvement animal.
A common problem related with QTL estimates is inconsistency, which
means that a QTL effect is not expressed similarly in several years,
or when is used in a different population (Mayo and Franklin,
1998). Many epistatic effects have been found associated to
QTL effects. In order to use molecular information in selection, reliable
QTL effects should be incorporated in the models of analysis from population
genetics in a way, which is consistent with observed variation. Evidences
of widespread epistasis affecting QTL effects may restrict use and prediction
of QTL effects outside the populations used for detection. This is particularly
important when breed crosses instead of sire families in outbreed populations
are used as design to detecting the QTL effects (Mayo and
Franklin, 1998). A rational use of the molecular methodologies requires
the simultaneous optimization of selection on all the genes affecting
important traits in the population. The maximum benefit can be obtained
when these techniques are used in conjunction with reproductive technologies
like the artificial insemination, and collection and production in
vitro of embryos to accelerate the genetic change (Bishop
et al., 1995; Montaldo, 1993). There is a danger
associated with a potentially inadequate use of QTL information, giving
an excessively high emphasis to simple molecular information in detriment
of the overall economic gain through all traits and their polygenic
effects in the population. Dissemination of the information to the industry
is therefore a complex issue concerning QTL effects and molecular markers.
The characteristics on which the application of the
MAS can be effective are those that are expressed late in the life of
the animal, or those that are controlled by a few pairs of alleles.
The first example corresponds to the longevity and carcass characteristics
in meat producing animals; the second, to the resistance to certain
diseases or defects of simple inheritance. Because of its high cost,
the use of MAS could be justified, in animal nuclei that allow dilution
of the costs when germplasm is extensively used towards the commercial
population. Also in those characteristics in which the procedures of
conventional selection have reached their limits in efficiency or the
results have been not satisfactory. The main advantage of including molecular information
over pure mixture model and segregation analysis, is the possibility
of evaluating the simultaneous effect of several QTL on the characteristics
of economic importance, and in the future increasing its precision and
the complexity of the involved models of genic action, for example QTL
with multiple alleles. The present trend indicates that molecular, pedigree
and phenotypic information will be integrated in the future through
mixture models of segregation analysis that might contain QTL effects
through the markers, polygenic inheritance and the use of powerful and
flexible methods of estimation such as Gibbs Sampling. Before the molecular information on the QTL which control
the characteristics of economic interest is generated, the detection
of major genes using segregation analysis could direct the work of identification
of genotypes towards populations and characteristics with greater probability
of detecting a QTL using molecular markers. Many questions remain on the nature and action of the
QTL involved on the variation of complex traits and about the nature
and definition of QTL effects. The use of molecular techniques offers
new opportunities and challenges for building and using more predictive
and efficient statistical models for livestock improvement. The authors wish to thank Professor Brian Kinghorn
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