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A population-wide linkage disequilibrium on bovine chromosome 14 between microsatellite ILSTS039 and DGAT1, a putative quantitative trait locus affecting milk production traits, was found in the Israeli Holstein population. A total of 394 bulls were genotyped for both DGAT1 and ILSTS039, and 1747 cows were genotyped for ILSTS039. The ILSTS039 allele termed "225," and the DGAT1 K allele (substitution of a lysine residue with alanine), were associated with decreased milk production, and increased fat production and fat and protein percent. The number of 225 ILSTS039 and K DGAT1 alleles per individual were the same for 80% of the bulls genotyped. From the effects associated with cows homozygous for the 225 allele, the effect of the quantitative trait locus appears to be approximately codominant. The substitution effect was 0.16% fat. Genotype probabilities for the quantitative gene were determined for the entire Israeli Holstein milk-recorded population, including 507,725 cows and 1442 bulls, using segregation analysis. Overall frequency of the allele that increased fat percent was 8.9% in cows and 15.5% in bulls. The frequency of this allele decreased from 1981 until 1990, from 15 to 5%, and since has increased to 10%. The effects estimated on the population-wide analyses of both cows and bulls were similar to the effect associated with DGAT1 in the daughters of genotyped bulls. Modified animal model evaluations were computed for the entire population with the effect of this gene included in the model. The correlations between the modified and standard animal model evaluations for all traits were > 0.99.
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J. Dairy Sci. 86:2219–2227
American Dairy Science Association, 2003.
Population-Wide Analysis of a QTL Affecting Milk-Fat Production
in the Israeli Holstein Population
J. I. Weller*, M. Golik*, E. Seroussi*, E. Ezra†, and M. Ron*
*Institute of Animal Sciences,
Agricultural Research Organization,
The Volcani Center, Bet Dagan, Israel 50250
†Israel Cattle Breeders Association
Caesaria Industrial Park, Caesaria, Israel 38900
A population-wide linkage disequilibrium on bovine
chromosome 14 between microsatellite ILSTS039 and
DGAT1, a putative quantitative trait locus affecting
milk production traits, was found in the Israeli Holstein
population. A total of 394 bulls were genotyped for both
DGAT1 and ILSTS039, and 1747 cows were genotyped
for ILSTS039. The ILSTS039 allele termed “225,” and
the DGAT1 K allele (substitution of a lysine residue
with alanine), were associated with decreased milk pro-
duction, and increased fat production and fat and pro-
tein percent. The number of 225 ILSTS039 and K
DGAT1 alleles per individual were the same for 80%
of the bulls genotyped. From the effects associated with
cows homozygous for the 225 allele, the effect of the
quantitative trait locus appears to be approximately
codominant. The substitution effect was 0.16% fat. Gen-
otype probabilities for the quantitative gene were deter-
mined for the entire Israeli Holstein milk-recorded pop-
ulation, including 507,725 cows and 1442 bulls, using
segregation analysis. Overall frequency of the allele
that increased fat percent was 8.9% in cows and 15.5%
in bulls. The frequency of this allele decreased from
1981 until 1990, from 15 to 5%, and since has increased
to 10%. The effects estimated on the population-wide
analyses of both cows and bulls were similar to the effect
associated with DGAT1 in the daughters of genotyped
bulls. Modified animal model evaluations were com-
puted for the entire population with the effect of this
gene included in the model. The correlations between
the modified and standard animal model evaluations
for all traits were > 0.99.
(Key words: cattle microsatellite, quantitative trait
loci, bovine chromosome 14, marker-assisted selection)
Abbreviation key: BV = breeding value, DYD =
daughter yield deviation, IBD = identical by descent,
LD = linkage disequilibrium.
Received May 22, 2002.
Accepted August 1, 2002.
Corresponding author: J. I. Weller; e-mail:
Many studies have shown that individual QTL can
be detected and mapped in commercial dairy cattle pop-
ulations with the aid of genetic markers by application
of daughter or granddaughter designs (Weller et al.,
1990). Several studies beginning with Ron et al. (1998)
found a major QTL associated with milk-fat concentra-
tion segregating in the Israeli and US Holstein dairy
cattle populations near the centromeric end of bovine
chromosome 14. The locus was also found to be segre-
gating in the Dutch Holstein population (Coppieters et
al., 1998) and German dairy cattle population (Looft et
al., 2001). Riquet et al. (1999) used identical by descent
(IBD) mapping to localize this QTL to a region near the
centromeric end of the chromosome, including CSSM66,
but excluding marker ILSTS039 at the extreme end
of the chromosome. Heyen et al. (1999) used interval
mapping to localize the QTL to the ILSTS039-CSSM66
interval, but the likelihood maximum was closer to
ILSTS039. Recently, Grisart et al. (2002) identified a
polymorphism in exon VIII of the gene acylCoA:diacy-
glycerol acyltransferase (DGAT1), which results in the
substitution of a lysine residue with alanine. DGAT1
is located in the confidence interval for the QTL on
BTA14, and a knockout mutation completely inhibited
lactation in mice. Grisart et al. (2002) genotyped 1818
Dutch Holstein sires and 529 New Zealand Holstein
cows for this polymorphism. In both populations the
DGAT1 allele with a lysine residue (denoted K), as op-
posed to alanine residue (denoted A), was associated
with increased fat yield and fat and protein percent,
and decreased milk and protein production. All these
effects correspond to the QTL effects observed in daugh-
ter and granddaughter designs. However, the magni-
tudes of effects were not similar in the two populations.
For the yield traits the absolute values of the substitu-
tion effects were greater in the Dutch population, while
the effects on the percent traits were similar.
Kinghorn and Kerr (1995) and Israel and Weller
(1998) proposed a method to obtain unbiased estimates
of QTL effects via a modified animal model, even though
only a small fraction of the population was genotyped,
provided that QTL genotype probabilities can be de-
rived for all animals. Kerr and Kinghorn (1996) derived
an algorithm to estimate genotype probabilities for all
animals in a population, based on a sample of individu-
als with known genotypes. Israel and Weller (2002)
applied this method on simulated data to obtain unbi-
ased estimates of QTL effects via a modified animal
model analysis.
Meuwissen and Goddard (2002) proposed that popu-
lation-wide linkage disequilibrium (LD) could be used
to fine map QTL. Looft et al. (2001) presented evidence
for population-wide LD in the German dairy cattle pop-
ulation between the QTL and a polymorphism in an
EST, KIEL_E8, which is very tightly linked to
This study reports on the effect of the QTL on BTA14
in the Israeli-Holstein population and the genetic trend
for the allelic frequencies. Various analysis methods
are compared, and genetic evaluations including the
QTL effect were computed based on the method of Israel
and Weller (2002). In addition we report on a popula-
tion-wide LD in the Israeli population between the QTL
on chromosome 14 and microsatellite ILSTS039. The
allele termed “225,” based on the length of the PCR
product, was associated with increased fat percent in
all heterozygous families in both the US and Israeli
Holstein populations. Allele 225 was the shortest of
eight alleles observed in the Israeli population. This
LD was verified by genotyping large samples of Israeli
cows and bulls. Partial LD was also found in the US pop-
Population Sample
Blood samples were collected from over 13,000 Is-
raeli-Holstein cows, daughters of 11 sires from 233
herds. Semen samples were collected from the 11 sires.
Cows (n = 6047) were genotyped for at least five
microsatellites to confirm paternity. Cows that did not
inherit either paternal allele for at least two loci were
considered to be not daughters of the sire listed, and
were therefore deleted from further analysis. Cows
without genetic evaluations for all five production
traits; milk, fat, and protein production, and fat and
protein percentage were also deleted from the analysis.
Ten of the 11 sires were genotyped for ILSTS039,
and seven sires were heterozygous. The daughters of
the heterozygous sires were genotyped for this marker.
(The final sire did not have a sufficient sample of daugh-
ters at the time of the ILSTS039 genotyping.) There
were 1747 cows with genetic evaluations for production
traits, and valid genotypes for ILSTS039. Eighty-six
Journal of Dairy Science Vol. 86, No. 6, 2003
daughters of sire 3241, which was heterozygous for both
DGAT1 and the QTL affecting fat percent, as deter-
mined by the daughter design analysis, were also geno-
typed for DGAT1. Artificial insemination sires (n = 424)
with genetic evaluations were genotyped for the DGAT1
polymorphism. Of these, 394 were also genotyped for
ILSTS039. Genotypes were determined for most Israeli
AI sires born since 1982, and all but one of the sires
born since 1982 that were returned to general service.
Genotyping Methods
DNA from frozen blood or semen was extracted by
the salting out procedure (Ma et al., 1996). DNA was
diluted to 7 ng/µl, and 5 µl was aliquoted to 96-well and
384-well plates using Hydra robotic system (Robbins
Scientific, DNA in plates was dried
and stored at room temperature. The PCR protocols
for DNA isolated from semen and blood cells were as
described by Ron et al. (1995) using a DNA engine
thermocycler (MJ Research, Inc.,
The K (lysine) allele-specific primer (CAGCTTTGGC
AGGTAAGAA) for DGAT1 was labeled with FAM (blue)
fluorophore and the A (alanine) allele-specific primer
(yellow) fluorophore. These forward primers were used
in separate amplification reactions with one reverse
primer (TAGGTCAGGTTGTCGGGGTA). Ten-microli-
ter PCR reactions consisted of 1 µl of PCR Buffer (JMR-
435, JMR-Holdings, UK), 5 pmol of each primer, 1 µl
of dNTP, 0.24 U Taq polymerase (JMR-801, JMR-Hold-
ings), and 35 ng of whole genomic template DNA. Cy-
cling conditions were as follows: initial denaturation of
94°C for 3 min, followed by 30 cycles of 92°C for 40 s,
variable annealing (at 60°C for the K allele and at 66°C
for the A allele) for 40 s, 72°C for 1 min, and a final
single extension step of 72°C for 10 min. After PCR,
the two allele-specific reactions of each individual were
mixed and 0.6 µl were added to 0.6 µl of loading buffer
(75% formamide/dye, 25% MapMarker Low, BioVen-
tures, Murfreesboro, TN). These samples were dena-
tured at 92°C for 3 min and cooled on ice.
PCR reactions were run on the ABI 377 DNA se-
quencer (Applied Biosystems, Foster City, CA). Auto-
mated fragment analysis, size calling, and binning were
then used by GeneScan (Version 3.1) and Genotyper
(Version 2.0) genetic software (Applied Biosystems) to
identify the alleles of each locus.
Phenotypic Records and Statistical Methods
The official Israeli Holstein genetic evaluations are
computed twice yearly at the Agricultural Research Or-
ganization. Three hundred and five-day milk, fat, and
Table 1. Means and standard deviations for the genetic evaluations
of the 1747 cows genotyped.
Trait Mean deviation
Milk (kgs) 234 509
Fat (kgs) 7.4 14.5
Protein (kgs) 1.9 11.3
% fat 0.002 0.180
% protein 0.045 0.095
protein production, preadjusted for calving age and
month and days open, were analyzed by a repeatability
animal model (Weller et al., 1994). First through fifth
parity production records of all animals with valid rec-
ords for all three traits, and first-parity calving dates
since 1985 were included in the analysis. All known
relationships among animals were included via the nu-
merator relationship matrix. Later parity records were
included only if there were valid records for all previous
parities. The additive genetic and permanent environ-
mental variance components were each assumed to be
0.25 of the total variance for all three traits. The vari-
ance component values were verified by REML on a
subset of the data. The REML variance component esti-
mates were close to the values used in the animal model
analyses for all three traits. Genetic evaluations for fat
percentage for each cow were derived as follows:
= [(BV
+ M
+ M
)] M
where BV
are the cow’s estimated breeding
values for fat percentage, fat yield, and milk: and M
, and M
are mean adjusted first-parity fat yield,
milk, and fat percentage of cows born in 1995. Genetic
evaluations for protein percentage are computed simi-
larly, with protein yield and percentage, instead of fat
yield and percentage. The February, 2002, evaluations
were analyzed. Means, standard deviations, and mini-
mum and maximum values of genetic evaluations of
the cows genotyped for the five traits analyzed are given
in Table 1, and the correlations among the evaluations
are given in Table 2.
Preliminary QTL analysis for ILSTS039 was by the
following linear model for all five traits:
Table 2. Correlations among the genetic evaluations of the 1747 cows
Trait Milk Fat Protein % fat % protein
Milk (kgs) 1 0.21 0.72 0.68 0.66
Fat (kgs) 1 0.24 0.57 0.04
Protein (kgs) 1 0.43 0.04
% fat 1 0.52
% protein 1
Journal of Dairy Science Vol. 86, No. 6, 2003
= S
+ M
+ e
where BV
is the estimated cow breeding value of cow
k, daughter of sire i, that received paternal marker
allele j; S
is the effect of sire i on the trait; M
is the
effect of paternal allele j of sire i on the trait, and e
is the random residual associated with each record. If
the daughter had the same genotype as her sire, pater-
nal allele origin could not be determined, and these
cows were deleted from the analysis. A significant pa-
ternal allele effect is indicative of a segregating QTL
linked to the genetic marker. Significance of the pater-
nal allele contrast within each family was determined
by a t-test with residual variance computed across all
cows. A sire was considered heterozygous for the QTL
if the t probability was less than 0.01.
In addition the effect of marker ILSTS039 on the
cows’ breeding values was analyzed by the following
= S
+ M
+ e
where M
is the effect of the number of 225 alleles for
each cow, which could have values of zero, 1, or 2, and
the other terms are as defined previously. This model
was analyzed with M as a regression effect, and M as
a class effect (class effect, model 1). In addition the
model was also analyzed with M as a class effect, but
with the cows with one 225 allele divided into two
groups; those that were daughters of sires that had the
225 allele, and those cows that were daughters of sires
that did not have the 225 allele (class effect, model 2).
The sire breeding values for all five traits were ana-
lyzed by the following model:
= BY + BY
+ D + e
where BVS
is the breeding value of sire i, BY and BY
are the linear and quadratic regression effects of the
sires’ birth year, and D is the regression effect of the
number of DGAT1 K alleles for each sire. The BY and
effects were included to account for changes in the
frequency of the K allele over time. The sire breeding
values were also analyzed by the following model
= BY + BY
+ D + M + e
where M is the regression effect of the number of 225
alleles for ILSTS039, and the other terms are as de-
fined previously.
Only a small fraction of the cow population was geno-
typed for either ILSTS039 or DGAT1. Genotype proba-
bilities for the QTL were determined for the entire Is-
raeli Holstein milk-recorded population, including
Table 3. The allele substitution effects associated with ILSTS039, their standard errors, and the t-test
probabilities by the daughter design analysis.
Trait 2283 3241
Milk (kgs) 193 ± 54*** 106 ± 48*
Fat (kgs) 4.5 ± 1.9* 7.1 ± 1.7****
Protein (kgs) 0.6 ± 1.4 1.1 ± 1.2
% fat 0.102 ± 0.017**** 0.100 ± 0.015****
% protein 0.048 ± 0.009**** 0.019 ± 0.008*
Number of informative daughters 202 261
*P 0.05.
***P 0.001.
****P 0.0001.
507,725 cows and 1442 bulls, using the segregation
analysis algorithm of Kerr and Kinghorn (1996). In this
analysis complete linkage was assumed between the
QTL allele that increased fat concentration and the K
allele of DGAT1 for bulls, and between the QTL and
the 225 allele of ILSTS039 for cows that were genotyped
for this marker. The number of animals analyzed by
the segregation analysis algorithm was reduced to
33,292 by four “pruning” steps. At each step, cows that
were not genotyped, and were not listed as dams of cows
remaining in the data file were deleted. The pruning did
not affect the segregating analysis, because these cows
by definition include no information with respect to the
allelic frequencies. The algorithm requires an estimate
of the allelic frequencies in the base population. The
initial estimate was derived from the frequencies of the
genotyped bulls. After application of the algorithm this
estimate was revised, based on the allelic frequencies
of all animals with unknown parents. The segregation
analysis algorithm was rerun with the updated base
population allelic frequencies until convergence for the
base population allelic frequencies was obtained. The
genotype probabilities for the “pruned” cows were then
regenerated from the genotype probabilities of their
parents, assuming random distribution of alleles. For
cows with either one or two unknown parents, the allelic
frequencies of the base population were used for the
unknown parent.
The estimated allelic frequencies as a function of
birth year were computed for the entire population of
bulls and cows. Modified animal model evaluations
were computed for the entire population for milk, fat,
and protein production including the QTL as a fixed
effect as described by Israel and Weller (2002). The
QTL effect was assumed to be additive. Therefore only
the frequency of rare QTL allele was included in the
model. Modified genetic evaluations, consisting of the
sum of the polygenic and QTL effects for each individual
were compared to the standard genetic evaluations de-
Journal of Dairy Science Vol. 86, No. 6, 2003
rived from a standard animal model. In addition, the
QTL effect was estimated separately for all bulls and
cows with evaluations by the following model:
= BY + BY
+ Q + e
where Q is the regression effect of the expected number
of DGAT1 K alleles for animal i, and the other terms
are as defined previously. Cows born before 1981 and
bulls born before 1961 were deleted. Bulls with reliabili-
ties for production traits less than 0.5 were also deleted
from this analysis.
Table 3 includes the effects of ILSTS093 from the
daughter design on production traits for the two fami-
lies with significant effects. Significant effects were
found for milk and fat production, and fat and protein
percent for both sires. The effect on fat percent was
highly significant (P < 0.0001) for both sires. Significant
effects were not found for protein production. In both
sires, allele 225 was associated with increased fat and
decreased milk production. None of the other sires ana-
lyzed had allele 225. Both of the sires that were hetero-
zygous for the QTL were also heterozygous for DGAT1.
The five other sires analyzed in the daughter design
were all homozygous for the A allele of DGAT1.
Effects of allele 225 on the cows’ genetic evaluations
from all seven families analyzed and the standard er-
rors for all five traits for all three-analysis models are
given in Table 4. The frequency of the 225 allele in the
sample of cows genotyped was 12%. The effect of allele
225 was significant for all five traits in the regression
model analysis of cow breeding values, supporting the
hypothesis of population-wide LD between the 225 al-
lele and the QTL. Except for the effect on protein, the
effects of allele 225 were slightly less than the mean of
the effects found in the daughter design analysis for
Table 4. Effects of allele 225 on the cows’ genetic evaluations and standard errors for all five traits for all three analysis models
Class effect, Model 1 Class effect, Model 2
No. 225 alleles Regression 1 2 1
Milk (kgs) 127 ± 23**** 127 ± 24**** 302 ± 91**** 127 ± 32*** 302 ± 91** 127 ± 38***
Fat (kgs) 3.4 ± 0.78**** 3.4 ± 0.8**** 6.4 ± 3.2* 4.5 ± 1.1**** 7.0 ± 3.2* 1.9 ± 1.3
Protein (kgs) 2.0 ± 0.57*** 2.0 ± 0.6** 4.0 ± 2.3 1.4 ± 0.8 3.7 ± 2.3 2.9 ± 1.0**
% fat 0.072 ± 0.007**** 0.070 ± 0.008**** 0.153 ± 0.029**** 0.082 ± 0.10**** 0.159 ± 0.029**** 0.054 ± 0.012****
% protein 0.018 ± 0.004**** 0.017 ± 0.004**** 0.047 ± 0.016** 0.023 ± 0.006**** 0.050 ± 0.016** 0.008 ± 0.007
Number of cows 1749 384 18 276 18 108
Effects in the class effect models, significance levels, and standard errors are given relative to cows with zero 225 alleles. There were
1347 cows with zero 225 alleles.
Cows with one 225 allele, and daughters of the two sires heterozygous for this allele.
Cows with one 225 allele, but not daughters of the two sires heterozygous for this allele.
*P 0.05.
**P 0.01.
***P 0.001.
****P 0.0001.
the two families with significant contrasts. However,
from the standard errors it is clear that differences were
not significant.
Effects in the class effect models are given relative
to the class with zero 225 alleles. In the class effect
models, the effect of a single 225 allele was generally
similar to the effects in the regression model, and the
effects of two 225 alleles were approximately equal to
twice the effect of a single 225 allele. The latter results
give further support to population-wide LD, because
one of the 225 alleles of these cows must have come
from the cows’ dams, and is not due to the specific
linkage phase relationships in the two heterozygous
sires. These results also indicate that the effect of the
QTL is approximately additive, as also determined by
Grisart et al. (2002). However, there were only 18 cows
that were homozygous for the 225 allele. Furthermore,
if LD is incomplete, then the effect associated with the
225 allele homozygotes will be greater than heterozy-
gotes, even if there is complete dominance at the QTL.
Thus, the conclusion of additivity must still be consid-
ered tentative. Further support for population-wide LD
is presented by the results of class effect model 2. The
effects obtained for cows that received a 225 allele, but
were not daughters of either sire 2283 or 3241, were
similar to the effects obtained for those cows that were
daughters of these two sires and received a single 225
allele. The effects obtained for the cows that were not
daughters of the heterozygous sires were equal for milk,
slightly greater for protein, but less for the other traits.
None of the differences between the effects for cows
with one 225 allele that were daughters of the two sires
segregating for the QTL, and cows with one 225 allele
that were daughters of the other sires were significant,
except for the effect on fat yield.
Journal of Dairy Science Vol. 86, No. 6, 2003
Of 86 daughters of sire 3241 that were genotyped for
both loci, there were only seven cows for which the
number of K alleles for DGAT1 was not equal to the
number of ILSTS039 225 alleles, 8.1%. However, since
the dams were not genotyped, paternal allele origin can
only be determined if the daughter genotype is different
from her sire. There were 39 cows that met this require-
ment for both loci. Of these, only one cow was a recombi-
nant. This corresponds to a recombination frequency of
2.5% between ILSTS039 and DGAT1.
The joint frequencies of the DGAT1 and ILSTS039
genotypes for the genotyped bulls are given in Table 5.
Again, with respect to ILSTS039, only the number of
225 alleles is considered. Although all nine possible
genotypes were found, the allelic frequencies for the two
loci were highly correlated. Of the 394 bulls genotyped
there were only 81 in which the number of 225
ILSTS039 alleles was not equal to the number of
DGAT1 K alleles (20%). The χ
value for the test of
independent assortment was 159. With four degrees of
freedom this value is highly significant by any criterion.
Thus there is strong LD between these two loci. The
frequency of the 225 allele among the bulls genotyped
was 17.1%, which is somewhat higher than among the
Table 5. Frequency table of bull genotypes for DGAT1 and ILSTS039.
Number of Number of “K” alleles for DGAT1
“225” alleles
for ILSTS039 0 1 2 Total
0 248 22 1 271
1 45 62 4 111
Total 295 91 8 394
Table 6. QTL substitution effects and their standard errors on the bull’s genetic evaluations for bulls that
were genotyped for DGAT1, and for all bulls and cows based on the algorithm of Kerr and Kinghorn (1996).
Dependent variable
Trait Bulls with genotypes All bulls
All cows
Milk (kgs) 306 ± 62**** 258 ± 48**** 443 ± 3
Fat (kgs) 7.4 ± 2.1*** 8.7 ± 1.6**** 2.8 ± 0.1****
Protein (kgs) 3.1 ± 1.5* 0.8 ± 1.2 7.4 ± 0.1****
% fat 0.164 ± 0.021**** 0.162 ± 0.016**** 0.0160 ± 0.001****
% protein 0.057 ± 0.012**** 0.081 ± 0.009**** 0.054 ± 0.001****
Number of animals 416 1038 491,613
Born since 1961 with reliability greater than 0.5.
Born since 1981.
*P 0.05.
***P 0.001.
****P 0.0001.
cows. The frequency of the K allele of DGAT1 was
The effects of DGAT1 genotype in the analyses of the
sire evaluations are given in Table 6. A total of 416
bulls born since 1960 were genotyped, and the effects
on these bulls are given in the first column of the table.
The effects were significant for all five traits. In the
model that included both the effects of DGAT1 and
ILSTS039, only the effect of DGAT1 was significant by
the type III sum of squares (SAS, 1988), which corrects
for all other effects in the model. This gives further
confirmation that DGAT1 is in fact the QTL. It is ex-
pected that the QTL effects in the sire analyses should
be greater than the effects obtained in the cow analyses,
because DGAT1, the actual QTL, was genotyped for the
bulls, while ILSTS039 was genotyped for the cows; and
the cow evaluations are more highly regressed (Israel
and Weller, 1998). The difference should be greater for
the production traits, which have lower heritabilities
than the concentration traits, and this was generally
the case.
Similar results for the effect of the DGAT1 polymor-
phism were obtained for the regression on the expected
sire genotypes, including bulls that were not genotyped
with reliability greater than 0.5. The regression effects
for all cows included in the animal model analysis born
since 1981 are also listed. Effects for cows were greater
for milk, protein, and protein percent, but less for fat
yield. The effect on fat percent, 0.16%, was nearly the
same for all three analyses.
Expected allelic frequencies for the QTL for the entire
cow and bull populations by birth year are given in
Table 7. Overall, the frequency of the rare QTL allele
was nearly double in the bull population as compared
to the cows. The frequency for the allele that increases
fat percent was lowest for cows born in 1991, and has
since then increased from 0.053 to 0.095. Similar trends
Journal of Dairy Science Vol. 86, No. 6, 2003
are evident in the sire population. The frequency means
of cows by birth year are plotted in Figure 1. For com-
parison, the estimated animal model BV means for fat
and protein percent are also plotted. As can be seen,
Table 7. Estimated frequencies for the K allele of DGAT1 in the
total population of bulls and cows by birth year.
Cows Bulls
Allele Allele
Birth year Number frequency Number frequency
1968 7 0.147
1969 8 0.084
1970 7 0.198
1971 10 0.165
1972 15 0.110
1973 8 0.287
1974 15 0.214
1975 14 0.120
1976 23 0.116
1977 32 0.153
1978 34 0.193
1979 50 0.156
1980 42 0.164
1981 9621 0.152 38 0.150
1982 12,571 0.125 65 0.133
1983 16,060 0.091 24 0.081
1984 20,098 0.095 45 0.084
1985 22,471 0.127 44 0.188
1986 26,165 0.118 43 0.200
1987 26,394 0.104 44 0.195
1988 27,245 0.072 53 0.085
1989 27,526 0.067 41 0.105
1990 28,812 0.054 39 0.197
1991 30,277 0.053 48 0.197
1992 30,896 0.073 45 0.142
1993 33,546 0.074 57 0.115
1994 31,402 0.086 47 0.189
1995 31,428 0.099 38 0.163
1996 30,149 0.100 55 0.208
1997 30,244 0.097 26 0.188
1998 30,482 0.092
1999 26,090 0.095
Total 491,638 0.089 1038 0.155
Figure 1. Mean frequencies of the K allele of DGAT1 in the cow
population by birth year, and mean estimated breeding values for
fat and protein percent. —, mean frequency for the K allele; ,
mean estimated breeding value, fat percent; , mean estimated
breeding value, protein percent.
all three graphs show a general decrease until 1990,
and then increase until 1999. These trends correspond
to the change in the Israeli breeding index, which was
based chiefly on milk production until 1990. Since then
the index has been based chiefly on protein with a nega-
tive weight for milk yield.
The substitution effects of the QTL derived from the
modified animal model analysis after 1000 iterations
are given in Table 8. Effects are smaller than those
obtained in the regression models in Table 6, except
for the effect of fat in the analysis of all cows. The
progression of the estimates of the QTL effect as a func-
tion of iteration number up to 500 iterations are given
in Figure 2. In the first iterations, the effect for milk was
200 kg, and then became positive before converging to
the relatively small negative value of 28. The effect
for fat increased to about 8 kg, before converging to 3.4
kg. Correlations for genetic evaluations of cows derived
by the standard and modified animal models including
the QTL effect were all greater than 0.99 for all five
milk production traits, and are therefore not presented.
The effects obtained for the QTL on BTA14 for fat
and protein percent were similar to those obtained by
Table 8. Substitution effects for the K allele of DGAT1 from the
animal model evaluations.
Trait effects
Milk (kgs) 28
Fat (kgs) 3.4
Protein (kgs) 0.2
% fat 0.040
% protein 0.006
Journal of Dairy Science Vol. 86, No. 6, 2003
Figure 2. Trends of the estimates for the DGAT1 substitution
effect by iteration. —, milk; – – –, fat; — —, protein.
Heyen et al. (1999) in the granddaughter design analy-
sis of the US population. In the current study, the effect
observed for milk production was greater, while the
effect on fat production was lower. The effect on milk
production was only marginally significant in the previ-
ous study. In the US population, the two sires heterozy-
gous for this QTL were also heterozygous for allele 225,
and this allele was associated with increased fat per-
centage. However, two other US sires included in the
granddaughter analysis were also heterozygous for the
225 allele, even though they were apparently homozy-
gous for the QTL. Thus within the US population LD
is much lower. Frequency of the 225 allele in the US
Holstein population is also much higher than the Israeli
population. Based on the genotypes of a sample of 90
sons from two US families (Heyen et al., 1999), the
frequency of the 225 allele among the maternal alleles
was 48%.
The pedigrees of the two heterozygous Israeli bulls
analyzed that were heterozygous for the QTL were
traced back three generations for all ancestors, and
no common ancestors were found. Similarly neither of
these bulls is known to be related to the two US bulls
that were heterozygous for this QTL. Thus, if these four
bulls received an IBD segment from a common ancestor,
this ancestor must be several generations removed, and
the common IBD segment is probably quite small.
Farnir et al. (2002) found extensive genome-wide link-
age disequilibrium in cattle for genetic markers. Thus,
it is not surprising that this should be the case for the
approximately 1 cM interval between ILSTS039 and
DGAT1 in the Israeli Holstein population.
Nearly all previous published QTL analyses in dairy
cattle have been based on either daughter or grand-
daughter designs. In either case only the additive QTL
effect can be detected. This is the first dairy cattle QTL
for which it was also possible to estimate dominance.
The results from the analysis of the cow breeding values
indicate that the QTL effect is in fact approximately
codominant, similar to the results of Grisart et al.
(2002). In plants, QTL with codominance, partial domi-
nance, complete dominance, and overdominance have
all been reported (e.g., Weller et al., 1988).
Two out of seven sires analyzed were segregating for
this QTL in the Israeli population. This corresponds to
an allelic frequency of 0.17 for the rare allele, which is
close to the observed frequency of 0.15 in the entire sire
population. Assuming that only two QTL alleles are
segregating in the population, the variance associated
with this QTL in the population can be estimated as
, where p is the frequency of one of the alleles,
and a is the additive effect (Weller, 2001). Using the
allelic frequency estimate from the sample of genotyped
cows of 10%, and the estimate of the additive effect of
0.16% fat from Tables 4, 5, and 6 gives a variance esti-
mate of 0.0046 for this trait. The genetic variance for
fat percent in the Israeli Holstein population, as deter-
mined by a REML analysis of first parity lactations,
was approximately equal to 0.056. Thus, even though
the additive effect of this QTL is equal to 0.68 genetic
standard deviations, the QTL accounts for only about
8% of the genetic variance for fat percent.
It is therefore possible that other QTL of similar mag-
nitude are also segregating in commercial populations.
In fact, a QTL of similar effect on percent fat was also
found on chromosome 6 (Ron et al., 2001). The effects
observed for this locus in a daughter design were ap-
proximately 0.08% fat, and 0.065% protein. Thus this
locus has a slightly smaller effect on percent fat, but a
much greater effect on percent protein, relative to the
genetic standard deviations for each trait.
As demonstrated by the genetic trend for this locus,
selection for the current Israeli breeding index will
probably continue to increase the rare allele, and there-
fore increase the genetic variance due to this locus.
Thus, contrary to the prediction of the infinitesimal
model, with segregating QTL, selection can sometimes
lead to an increase in the genetic variance of the popula-
tion. de Koning and Weller (1994) observed this result
on simulated data.
The small effects for the QTL obtained by the modi-
fied animal model analyses were somewhat surprising.
Similar results were obtained in an analysis that as-
sumed a smaller polygenic variance, and in an analysis
that did not assume additivity (data not shown). Israel
and Weller (1998, 2002) found on simulated data that
results obtained by this method were unbiased, while
estimates derived from daughter yield deviations
(DYD) or genetic evaluations underestimated the simu-
lated effects. However, in their simulations, at least
25% of the population was actually genotyped, and the
Journal of Dairy Science Vol. 86, No. 6, 2003
frequency of the rare allele was no less than 0.2. Fur-
thermore, only two or three generations were simu-
lated, while the current analysis included close to eight
generations. Finally, in the modified animal model
analysis, complete linkage was assumed between the
QTL and ILSTS039 for cows that were genotyped, even
though this is not the case. Kinghorn and Kerr (1995)
also obtained unbiased estimates of the QTL effect on
simulated data, but did not include a polygenic effect
in either the simulation or analysis models.
The regression models did not include the effect of
relationships, which might upwardly bias the esti-
mates. In any event, the effect of the QTL and the
relationship matrix would be highly confounded in the
current analysis. These two factors can only be distin-
guished by animals with similar pedigree but with dif-
ferent genotypes. This was the case for some of the cows
genotyped, but was rarely the case for the bulls. In the
relatively small Israeli Holstein population, there are
no large half-sib families of bulls with genetic evalua-
tions. Grisart et al. (2002) analyzed the bull DYD by a
regression model that included the relationships among
these animals. However, they assume equal residual
variance among DYD, which is clearly not the case.
Furthermore, properties of statistical models based on
analysis of DYD, which are derived from animal model
analyses, have not been investigated in detail. Israel
and Weller (1998) found that QTL estimates derived
from analysis of DYD are biased.
Mackinnon and Georges (1998) proposed marker-as-
sisted selection based on preselection of young sires
based on their genotypes for QTL. The disadvantage of
this method is that individuals with superior overall
genetic value are culled if they do not have the desired
genotype for specific QTL under control. Israel and Wel-
ler (1998, 2002) proposed that QTL effects could be
incorporated into animal model analyses even if only a
small fraction of the population is actually genotyped.
Using this method it should be possible to correctly
rank all animal, including information on known QTL.
This is the first application of their method to an actual
QTL. Genetic evaluations derived by this method were
nearly identical to the standard animal model evalua-
tions. Thus, in this specific example, the gain obtained
by marker-assisted selection would be minimal. How-
ever, there is also no potential loss that could be ob-
tained by alternate MAS proposals (Weller, 2001).
This research was supported by a grant from the
Israel Milk Marketing Board and the US-Israel Bina-
tional Agricultural Research and Development fund
(BARD). The authors thank B. Kinghorn for use of the
Geneprob program.
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... These results are consistent for the 3 breeds but the magnitude of substitution effects varied. These estimated average allelic substitution effects were in agreement with previous studies (Grisart et al., 2002;Spelman et al., 2002;Thaller et al., 2003;Weller et al., 2003). ...
... All sires heterozygous at the K232A polymorphism were also heterozygous at the QTL. The frequency of the K allele estimated in our Holstein population is in the range reported in other studies: 0.40 in New Zealand , 0.35 (Winter et al., 2002) or 0.55 (Thaller et al., 2003) in Germany, 0.16 in Israel (Weller et al., 2003), and 0.27 in Brazil (Lacorte et al., 2006). ...
... In addition, using a variance component approach on a larger sample of the French Holstein population, the proportion of genetic variance explained by the QTL traced by closely linked markers has recently been found to be very similar (Druet et al., 2006). Nevertheless, because of a lower frequency of the K allele in the Israeli Holstein population, lower values have been observed (Weller et al., 2003). Interestingly, the estimated variance for protein yield was relatively small, indicating that the use of DGAT1 to improve this The number of reconstructed haplotypes containing information for both markers in the considered population. ...
... Several studies have targeted the bovine quantitative trait loci (QTLs) on chromosome 14 for their association with milk production traits (12)(13)(14)(15)(16)(17)(18)(19)(20). Acyl CoA:diacylglycerol acyltransferase (DGAT1) gene at chromosome 14 has been documented as a candidate marker for the QTLs associated with milk production traits through cattle genome and linkage mapping studies (21,22). ...
... The allelic frequency and the influence of the DGAT1 K232A polymorphism have been illustrated in dairy cattle populations in different countries including New Zealand (12,19,21,50), Israel (13), the Netherlands (51, 52), Germany (53,54), Poland (55,56), China (57)(58)(59), France (60), India (45), and Sweden (47). ...
Full-text available
Milk fatty acids are essential for many dairy product productions, while intramuscular fat (IMF) is associated with the quality of meat. The triacylglycerols (TAGs) are the major components of IMF and milk fat. Therefore, understanding the polymorphisms and genes linked to fat synthesis is important for animal production. Identifying quantitative trait loci (QTLs) and genes associated with milk and meat production traits has been the objective of various mapping studies in the last decade. Consistently, the QTLs on chromosomes 14, 15, and 9 have been found to be associated with milk and meat production traits in cattle, goat, and buffalo and sheep, respectively. Diacylglycerol O -acyltransferase 1 (DGAT1) gene has been reported on chromosomes 14, 15, and 9 in cattle, goat, and buffalo and sheep, respectively. Being a key role in fat metabolism and TAG synthesis, the DGAT1 has obtained considerable attention especially in animal milk production. In addition to milk production, DGAT1 has also been a subject of interest in animal meat production. Several polymorphisms have been documented in DGAT1 in various animal species including cattle, buffalo, goat, and sheep for their association with milk production traits. In addition, the DGAT1 has also been studied for their role in meat production traits in cattle, sheep, and goat. However, very limited studies have been conducted in cattle for association of DGAT1 with meat production traits in cattle. Moreover, not a single study reported the association of DGAT1 with meat production traits in buffalo; thus, further studies are warranted to fulfill this huge gap. Keeping in view the important role of DGAT1 in animal production, the current review article was designed to highlight the major development and new insights on DGAT1 effect on milk and meat production traits in cattle, buffalo, sheep, and goat. Moreover, we have also highlighted the possible future contributions of DGAT1 for the studied species.
... In cattle, some studies showed that SNPs were associated with increased milk fat content in Holstein cows (Spelman, Ford, McElhinney, Gregory, & Snell, 2002) and decreased protein content and milk yield in Jersey cows (Weller, Golik, Seroussi, Ezra, & Ron, 2003). Cardoso et al. (2015) found a variable nucleotide repeat (VNRT) in the promoter region of DGAT1 that explains 32% of additive genetic variance of fat percentage. ...
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Background The triacylglycerols in milk fat determine the physical and functional properties of dairy products rich in milk fat. Therefore, understanding the variability of genes related to fat synthesis is important for food production. We investigated the effect of diacylglycerol O-acyltransferase 1 (DGAT1) gene polymorphism on milk production parameters of the Zaraibi goat. Milk components were estimated by infrared spectroscopy. Moreover, Restriction Fragment Length Polymorphisms (RFLP) were used to detect genetic variants in DGAT1 genes. The amplified products were sequenced and aligned to the caprine reference sequence of this gene. Results Two alleles (T and C) were identified in Zaraibi goats. The T allele resulted in one silent mutation while the C allele specified two-point mutations: one was located within a non-coding region (T703C) and the other (T713C) causing a Ile → Thr substitution in the deduced amino acid sequence. Moreover, the DGAT1 polymorphism significantly ( p < 0.05) affected total solid content of milk, wherein harboring CC genotype had significantly higher amount of total solid than those with TC genotype. Milk contents and yields did not differ significantly between goats with CC and TC genotype. Conclusion These results advance our understanding of the genetic architecture of Zaraibi milk composition and will help to improve the management and breeding program of the Egyptian dairy goat. Graphical Abstract
... The diacylglycerol o-acyltransferase 1 (DGAT1) gene encodes for one of the enzymes that covalently attaches diacylglycerol to long-chain fatty acyl-CoAs to form triglycerides [96], which are the major fat type present in milk. Genetic variations in DGAT1 were highly associated with fat content in dairy animals [89,[96][97][98][99][100][101][102][103]. Additionally, these alterations were also associated with milk protein content and milk volume in some species [98,99]. ...
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Human milk is considered the optimal nutrition for infants as it provides additional attributes other than nutritional support for the infant and contributes to the mother’s health as well. Although breastfeeding is the most natural modality to feed infants, nowadays, many mothers complain about breastfeeding difficulties. In addition to environmental factors that may influence lactation outcomes including maternal nutrition status, partner’s support, stress, and latching ability of the infant, intrinsic factors such as maternal genetics may also affect the quantitative production and qualitative content of human milk. These genetic factors, which may largely affect the infant’s growth and development, as well as the mother’s breastfeeding experience, are the subject of the present review. We specifically describe genetic variations that were shown to affect quantitative human milk supply and/or its qualitative content. We further discuss possible implications and methods for diagnosis as well as treatment modalities. Although cases of nutrient-deficient human milk are considered rare, in some ethnic groups, genetic variations that affect human milk content are more abundant, and they should receive greater attention for diagnosis and treatment when necessary. From a future perspective, early genetic diagnosis should be directed to target and treat breastfeeding difficulties in real time.
... [30] reported that DGTA1-K, which is the ancestral allele, caused a 0.34%, 0.08% and 10.46kg increase in milk fat, milk protein, and fat yield respectively, and a reduction of 316kg and 10.46kg in milk yield and protein yield respectively, when compared to the DGTA1-A allele. It is generally believed that the K-variant is associated with increased milk fat content while the A-variant lowers fat content of milk but increases milk protein and milk yield [31]- [33]. Cattle with K-allele synthesized over 1.5x triglyceride than those with K-allele [34]. ...
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Constant improvement of desirable traits is the key to a sustainable animal production and marker-assisted selection is pivotal to achieving this aim. Marker-assisted selection guides farmers by taking advantage of genetic variations within candidate genes that influence production traits in the animals. One of such desirable traits is milk production. ATP-binding cassette sub-family G member 2 (ABCG2) protein is involved in the transport of xenobiotics and other nutrients such as cholesterol from the blood into the milk. Diacylglycerol acyltransferase (DGAT1) plays a crucial role in regulating the rate of synthesis of triacylglycerides in fat cells such as those in the mammary gland. Previous researches have reported association between these genes and milk production traits in cattle. In this study, we examined polymorphisms in the variable regions of these candidate genes in Africa's White Fulani and Muturu cattle breeds. The results revealed three variants, KK, AK and AA for DGAT1 exon 8. The KK genotype predominates in both breeds with a frequency of 83% and 60% in White Fulani and Muturu, respectively. All sampled animals in both breeds were monomorphic at the ABCG2 exon 14.
... DGAT1 enzyme acts an important role in lipogenesis pathway in many tissues (Cases et al 1998) so the DGAT1 gene, encoding this enyzme has been found relevant in milk production. In many of the studies, associations between DGAT1 gene polymorphism and milk composition and production traits have been investigated Weller et al 2002;Thaller et al 2003;Gautier et al 2007). Fat is an important component of mammalian milk. ...
... Hence, wholegenome/specific chromosome scans were carried out to identify the QTL. In dairy cattle, several QTL associated with protein and fat percentage and milk, protein, and fat yield have been identified on bovine chromosome 6-BTA6 ( Freyer et al. 2003;Ashwell et al. 2004;Olsen et al. 2004;Szyda et al. 2005;Chen et al. 2006; Kucerová et al. 2006), BTA7 ( Ron et al. 2004;Weller et al. 2008), BTA11 ( Ashwell et al. 2004;Kucerová et al. 2006), BTA14 ( Weller et al. 2003;Ashwell et al. 2004;Schrooten et al. 2004;Kučerová et al. 2006), and BTA23 ( Mosig et al. 2001;Schrooten et al. 2004). Similarly, existence of QTL for resistance to mastitis in cattle has been reported on almost all chromosomes (Rupp and Foucras 2010). ...
Selective breeding is a traditional method of improving livestock, but molecular genetic revolution in the last decade of the twentieth century has initiated the modern era of genomics. Molecular genetics has influenced the breeding strategies in a big way by providing genetic maps, individual genes, and quantitative trait loci (QTL) related to performance traits in livestock species. QTL detection in animals led the shift from conventional selective breeding to marker-assisted selection (MAS) and SNPs related to performance traits. Advancements in genomics have motivated animal breeder to formulate high-density SNP chips comprising of lakhs of SNPs covering the whole genome of a species. Selection on the basis of whole-genome markers could make selection of genetically superior animals at very early age and at the same time with the accuracy of 0.8 in predicting their breeding value. The SNP chip analysis has been very popular in livestock in predicting breeding potential at early age, but some traits, i.e., traits involving nonadditive effects and epigenetic effects, are still out of the reach of genomic selection.
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The literature review presents the current understanding of cholesterol metabolism occurring under physiological conditions. The homeostasis of cholesterol in the body is determined by its endogenous synthesis, the transition to the cell from plasma as part of low-densitylipoproteins( LDL), the release of their cells as part of high-density lipoproteins (HDL). The molecular-genetic mechanisms of regulation of cholesterol homeostasis are described in detail. The genes for cholesterol biosynthesis in major multicellular animals were inherited from their last common eukaryotic ancestor and are evolutionarily conserved for cholesterol biosynthesis. Non-coding variants of singlenucleotide polymorphisms can significantly contribute to the phenotypic variability of cholesterol, and missense variants that lead to the replacement of amino acids in proteins can have a significant effect on the phenotypic variability. The modern aspects of cholesterol homeostasis in cattle are formed and sufficiently fully presented. During absence of exogenous intake, the balance of cholesterol in cattle is maintained by endogenous synthesis, occurring mainly in the liver, the intake of lipoproteins, as well as reverse transport mechanisms. This review gives an idea that the stability of homeostasis can be achieved only with the complex interaction of all systems (transport, enzyme, receptor) involved in this process. The analysis of the latest scientific works concerning the problem of the content and regulation of cholesterol in cow’s milk is presented. Significant single-nucleotide polymorphisms localized in the ACAT2, LDLR, DGAT, and AGPAT1 genes involved in the exchange of cholesterol in the liver or its transport and associated with the level of cholesterol in milk are described. Part of the review is devoted to cholesterol deficiency syndrome in Holstein cattle (HCD). Modern data on the prevalence, molecular and genetic basis, clinical and laboratory manifestations of the syndrome are presented.
Objective: The aim of the study was to evaluate the influence of polymorphic loci and other factors on milk performance and the technological properties of milk. Methods: The analysis was performed on Simmental and Holstein cows in field conditions. Milk yield in kg, fat and protein percentage and yield were evaluated. Technological properties were evaluated by milk fermentation ability, renneting, and an alcohol test. Polymorphisms in the DGAT1, LEP, FASN, SCD1, CSN2, CSN3 and LGB genes were genotyped, and association analysis was performed. Results: The DGAT1 AA genotype was associated with higher milk, protein and fat yields (p0.05). The MM genotype in the LEP gene was associated with a lower protein percentage and the W allele with a higher protein percentage (p0.05). In cows with the FASN GG genotype, the protein percentage was higher, but the A allele was associated with higher milk, protein and fat yields than the G allele. The TT genotype in SCD1 was associated with the lowest milk, protein and fat yields and with the highest milk protein percentage (p0.01). The T allele had higher values than the C allele (p0.05) except for fat percentage. The genotype CSN3 AA was associated with a significantly heightened milk yield; BB was associated with a high protein percentage. The effect of the alleles on the technological properties was not significant. The CSN2 BB genotype was associated with the best alcohol test (p0.01), and the renneting order was inverse. Milk from cows with the CSN2 A1A1 genotype was best in the milk fermentation ability. CSN3 significantly affected the technological properties. Conclusion: The findings revealed the potential of some polymorphic loci for use in dairy cattle breeding and for the management of milk quality. In field research, the pivotal role of farms in milk yield, composition and technological properties was confirmed.
Background Diacylglycerol O-acyltransferase 1 (DGAT1) plays a key role in the synthesis of triglycerides. Recent studies have shown that a transition mutation resulting in substitutions of guanine by adenine in the DGAT1 gene in cattle has considerable effects on milk yield and composition. Currently, there is no systematic research reporting on the utilization of this gene segment in Iranian buffalo (Bubalus bubalis). Objective In this study, the genetic differentiation of three indigenous Iranian buffalo populations was investigated in the region spanning exon 3 to exon 17 of the DGAT1 gene. Methods A total of 200 buffaloes were genotyped, all the samples were sequenced directly in both directions with forward and reverse sequencing primers. Results Sequence analysis showed novel SNPs compared to the reference GenBank sequence (DQ886485) at nucleotide positions g.6097A>G, g.7036C>T, g.7338G>A, g.7710C>T, g.8087C>T, g.8259G>A, g.8275G>A, g.8367C>T, and g.8426C>T. No polymorphisms were found within exon 8. Therefore, the K232A position was thought to be a conserved and fixed region for high milk fat content (K allele) in Bos indicus and all buffalo breeds. Comparison with Indian buffalo revealed three exonic SNPs, one of which was nonsynonymous. A unique 22 bp insertion was observed in intron 10 of DGAT1. Linkage disequilibrium analysis allowed the identification of nine haplotypes among the sampled animals. To our knowledge, this is the first report of sequencing analysis of the DGAT1 gene in Iranian buffalo. Conclusion Our results suggest that genetic diversity exists and could be useful in examining the association between the DGAT1 gene and milk production traits in buffalo.
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DNA microsatellites were used to detect individual loci affecting economically important quantitative traits in dairy cattle via the granddaughter design. Eighteen US Holstein grandsires and 1555 of their sons were genotyped for 30 genetic markers located on 19 of the 29 bovine autosomes. From 16 to 205 sons were genotyped per family. Of 14,650 son genotypes determined, 77% were informative. The genotype data was matched to the bulls' daughter yield deviations for milk, fat, and protein production, fat and protein percentage, productive life, and somatic cell score. The within-family allele effect was significant at p<0.01 for TGLA263 on chromosome 3, CSRM60 on chromosome 10, and CSSM66 on chromosome 14. TGLA263 and CSSM66 had significant effects on more than one trait, but the effects on fat percent were greatest for both loci. The effect of CSSM66 on fat percent was significant at p<10 . CSSM66 also had a significant -7 effect on fat percent in the Israel Holstein population (p<0.001), which was analyzed by a daughter design of seven families. By maximum likelihood, it was determined that the QTL has a substitution effect of about 0.28% fat, and is probably located 10 to 20 cM from CSSM66 proximal to the centromere. INTRODUCTION Many studies have shown that individual quantitative trait loci (QTL) affecting economic traits can be detected and mapped via linkage to genetic markers (reviewed by Weller, 1996). Weller et al. (1990) showed that, assuming an appropriate population structure, power per individual genotyped can be increased if sons of sires heterozygous for the genetic marker are genotyped, and the records of their daughters, the granddaughters of the original heterozygous sires, are analyzed. It is still necessary to genotype hundreds of sons for power to detect a QTL accounting for less than 10% of the additive genetic variance.
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A computationally tractable approach to complex segregation analysis for large data sets is described. This is then used to extend the value of DNA tests for major locus genotype, by calculating probabilities of belonging to each genotype class for all animals not DNA tested. Under the conditions simulated, this approach led to an approximate doubling of the number of animals genotyped with 100% confidence, the ability to exclude many more animals from one genotype class, plus a high probability (> 90%) of belonging to a given genotype class for many other animals. Verwendung von Spaltungsanalyse für rationelle Anwendung von DNA Tests für Hauptgene Ein rechnermäßig traktabler Ansatz zu komplexer Spaltungsanalyse großer Datenmengen wird beschrieben. Dieser wird verwendet, um den Wert der DNA Tests für Hauptgene zu erweitern und zwar dadurch, daß die Wahrscheinlichkeiten der Zugehörigkeit zu jeder Genotypenklasse für Tiere ohne DNA Diagnose berechnet wird. Die Simulation ergab eine Verdopplung der Zahl der Tiere, die mit 100% Sicherheit genotypisiert werden konnten sowie Ausschluß von mehr Tieren aus einer gegebenen Genotypenklasse und schließlich eine hohe Wahrscheinlichkeit (> 90%) der Zuweisung vieler Tiere zu gegebenen Genotypenklassen.
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A whole genome scan was undertaken in a granddaughter design comprising 1158 progeny-tested bulls in order to map QTL influencing milk yield and composition. In this paper we report the identification of a locus on the centromeric end of bovine Chromosome (Chr) 14, with major effect on fat and protein percentage as well as milk yield. The genuine nature of this QTL was verified using the grand2-daughter design, that is, by tracing the segregating QTL alleles from heterozygous grandsires to their maternal grandsons and confirming the predicted QTL allele substitution effect.
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A genome-wide linkage disequilibrium (LD) map was generated using microsatellite genotypes (284 autosomal microsatellite loci) of 581 gametes sampled from the dutch black-and-white dairy cattle population. LD was measured between all marker pairs, both syntenic and nonsyntenic. Analysis of syntenic pairs revealed surprisingly high levels of LD that, although more pronounced for closely linked marker pairs, extended over several tens of centimorgan. In addition, significant gametic associations were also shown to be very common between nonsyntenic loci. Simulations using the known genealogies of the studied sample indicate that random drift alone is likely to account for most of the observed disequilibrium. No clear evidence was obtained for a direct effect of selection ("Bulmer effect"). The observation of long range disequilibrium between syntenic loci using low-density marker maps indicates that LD mapping has the potential to be very effective in livestock populations. The frequent occurrence of gametic associations between nonsyntenic loci, however, encourages the combined use of linkage and linkage disequilibrium methods to avoid false positive results when mapping genes in livestock.
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There is considerable interest in bovine DNA-level polymorphic marker loci as a means of mapping quantitative trait loci (QTL) of economic importance in cattle. Progeny of a sire heterozygous for both a marker locus and a linked QTL, which inherit different alleles for the marker, will have different trait means. Based on this, power to detect QTL, as a function of QTL effect, heritability of the trait, and number of animals tested was determined for 1) daughter design, marker genotype and quantitative trait values assessed on daughters of sires heterozygous for the markers; and 2) granddaughter design, a newly devised alternative design in which marker genotype is determined on sons of heterozygous sires and quantitative trait value measured on daughters of the sons. For equal numbers of assays, power increased with the number of daughters per sire (design 1) and sons per grandsire (design 2). For equal power and heritability less than or equal to .2, design 2 required half as many marker assays as design 1, e.g., with heritability of .2, QTL effect of .2 SD units, and type 1 error of .01, power was .70 if 400 daughters of each of 10 sires were assayed for the markers and .95 if markers were assayed on 100 sons of each of 20 sires with 50 granddaughters per son.
QTL analyses have been performed in three guava mapping populations ('Enana' × 'N6'; MP1, 'Enana' × 'Suprema Roja'; MP2 and 'Enana' × 'Belic L-207'; MP3) based on the interval mapping method. Sixteen different traits related to leaf and fruit morphology, fruit characteristics, fruit quality, plant height and yield were recorded in the parents and progeny genotypes of the three mapping progenies. Sufficient variation was available for all characters allowing an efficient QTL analysis. The coefficients of variation (CV) depended strongly on the particular trait under evaluation and ranged from 5.7 to 65.2%. Several significant correlations were detected within leaf, fruit and yield traits which were generally similar in the different progenies. QTLs were detected for all traits under study. A total of 75, 56 and 59 QTLs were detected in populations MP1, MP2 and MP3, respectively. QTL numbers per trait varied between two and seven. Individual QTLs explained between 2.6 and 31.6% of the variance. Total variance explained by the sum of all detected QTLs varied between 6.6 for only one detected QTL and 68.3% between traits and populations. QTLs were integrated in the corresponding linkage maps. QTLs for different traits are co-located in these maps, reflecting the observed correlations between characters. Some of the QTLs are also co-located or closely linked to SSR markers, which will allow an efficient selection for marker assisted breeding in different genetic backgrounds.
Selection on known loci affecting quantitative traits (DSQ) was compared to phenotypic selection index for a single and a two-trait selection objective. Two situations were simulated; a single known quantitative locus, and ten identified loci accounting for all the additive genetic variance. Selection efficiency of DSQ relative to traitbased selection was higher for two-trait selection, than was selection on a single trait with the same heritability. The advantage of DSQ was greater when the traits were negatively correlated. Relative selection efficiency (RSE) for a single locus responsible for 0.1 of the genetic variance was 1.11 with heritabilities of 0.45 and 0.2 and zero genetic and phenotypic correlations between the traits. RSE of DSQ for ten known loci was 1.5 to 1.8 in the first 3 generations of selection, but declined in each subsequent generation. With DSQ most loci reached fixation after 7 generations. Response to trait-based selection continued through generation 15 and approached the response obtained with DSQ after 10 generations. The cumulative genetic response after 10 generations of DSQ was only 93% to 97% of the economically optimum genotype because the less favorable allele reached fixation for some loci, generally those with effects in opposite directions on the two traits.
Twenty pairs of cattle twins were genotyped for 3 to 12 microsatellites each using semen, blood, milk and hair roots. Chimaerism was recognized in 19 pairs by discrepancies in microsatellite analysis from milk and blood as opposed to semen and hair, or by detection of more than 2 alleles per genotype from milk and blood. Chimaerism of 2, 3 or 4 alleles was demonstrated in genotypes of twins from blood as compared to 1 or 2 alleles only from hair. The appearance of predominant bands in genotypes from blood or milk representing alleles of only one of the co‐twins was not consistent among the different microsatellites for the same twins. No evidence for germ cell chimaerism was found in semen of dizygotic male twins although our PCR system could detect cell mixes as small as a 1:100 ratio. Genotyping from either hair or semen for 4 microsatellites are sufficient to confirm zygotic origin of twins at .98 accuracy. Researchers should be aware of the possibility of erroneous genotyping when analyzing DNA from twins derived from blood or milk and the potential of chimaerism as an experimental model to study different immunological characteristics of cattle co‐twins.
This study investigates the value of a `bottom-up' approach to marker-assisted selection in a conventional progeny-testing dairy-breeding programme. By marker genotyping the daughters in the progeny test for markers known to be closely linked to a quantitative trait locus (QTL), it can be decided whether their sire is heterozygous for the QTL. If the sire is heterozygous with allelic contrast greater than some threshold, c, then only those bull-sons which inherited the favourable QTL allele are retained for subsequent progeny testing. In this way, posterior information on a sire's genotype from his daughters is used to preselect his sons and thereby increase the selection differential in the new generation of bulls. Simulations were used to predict the genetic gains and costs of using the bottom-up approach in a national dairy breeding scheme in which 500 young bulls were progeny-tested each generation. It was found that rates of genetic gains could be increased by 8%, 14% and 23% compared with conventional progeny testing if selection was based on 1, 2 and 5 QTL, respectively, and that this would cost less than US$100,000 per locus. A `top-down' approach selecting QTL alleles inherited from the grandsires was also evaluated and shown to be highly profitable, though less so than for the bottom-up scheme.