Genotype by Environment Interactions for Hereford BW
L. Leachman
ABSTRACT: The objectives of this study were to determine regional environment
effects on Birth Weights (BW) of Hereford bull progeny born in Canada and the United
States. From this genetic variances and heritabilities of BW were also to be calculated
utilizing data from the different regions. The study was also used to determine if rank of
most highly utilized sires varied by region. Information was gathered from the American
and Canadian Hereford Associations to carry out the evaluation. BW EPD’s were
calculated at the Agriculture Business Research Institute in Armidale, Australia. They
were provided as part of a performance file from the American Hereford Association and
the Canadian Hereford Association.
Introduction
Birth Weight in Hereford cattle is a very important trait for seedstock producers to focus
on in trying to meet the demands of commercial cattleman. The purpose of this study
was to determine how Hereford birth weights changed across three geographical regions
due to genotype by environment interactions. The study showed how highly utilized sires
with progeny in all regions ranked for the birth weight trait. The goal was to see how
significantly the genetic and environmental components of birth weight EPD’s varied
across by region. The study also determined if re-ranking occurred among bulls with
highly accurate EPD’s used in each area. The study will hopefully help producers
understand what impact different climates and topography have on BW performance.
Interesting interactions among genetics and environment can then be utilized to make the
best management decisions possible.
Materials and methods
The American and Canadian Hereford Associations provided a pedigree file and
birth weight performance file for use in the analysis. Contemporary groups were created
for the project and were broken down in very specific criteria to increase the accuracy of
the evaluation. Groups were broken down based on origin herd, year, season, sex and
management group. The actual recorded birth weight data was already adjusted for age
of dam by the breed associations.
The actual birth weight data was analyzed with the SAS statistical program to
calculate the mean weight and standard deviation for all three regions and overall. This
was expressed in pounds of calf at birth (Table 1).
The three regions were selected using latitude. Region1 included Canada having
ten provinces and three territories. Region 2 included thirty-four states. The southern
border of this region included Nevada, Utah, Colorado, Kansas, Missouri, Kentucky, and
Virginia. Region 3 included thirteen states. The northern border of this region included
Arizona, New Mexico, Oklahoma, Arkansas, Tennessee, and North Carolina. Alaska and
Hawaii were omitted because of their isolated locations. California was omitted because
it is divided by both regions.
The data set was also analyzed with the MTDFREML software package and the
animal model. Fixed effects included the temporary group and the random effects
included the animals. The software ran the three regions as different traits in theory so
that genetic and environmental variances could be calculated (Table 2). Furthermore, this
allowed heritability and genetic correlations to be calculated for and among these regions
(Table 3).
Results and Discussion
The number of records analyzed for birth weight along with means and associated
standard deviations are shown in Table 1. The northern US had the greatest number of
records followed by Canada and the southern US. Actual birth weight was heaviest in
Canada and eventually decreased moving to the south. Standard deviation for birth
weight was highest in Canada followed by the southern US and northern US.
With the contemporary group characteristics outlined, the study utilized 3,760
groups. The minimum number of head was 20 for increased accuracy and connectedness.
This contributed to the 42.5 head average contemporary group size.
MTDF REML provided both genetic and environmental variances that were
combined into total phenotypical variance shown in Table 2. Each of these values were
highest in Canada, then the north US and south US. Finally heritability and genetic
correlations results are illustrated in Table 3. Heritability for birth weight in Canada and
the north were in the upper area of moderately heritable. Heritability for birth weight in
the south was lower, but still moderate. The genetic correlations were also stronger
between the regions that border one another versus totally disconnected areas.
Table 4 also designated highly utilized sires with significant accuracy for all
regions and showed how there BW EPD ranked by region. Some bulls EPD remained
relatively constant over all regions. Others were significantly higher in one area and
lower in another. The bottom line is that there was a re-ranking of sires based on
circumstances that we really can’t explain.
Implications
The study showed that variability in both the genetic and environmental aspects of
birth weight is highest in Canada and decreases traveling South. The study showed that
there is a strong, positive correlation in BW across regions. Analysis of heavily used
sires shows a fairly consistent BW EPD across regions for the older, higher accuracy
sires. However, younger sires did re-rank as far as BW across the three regions which are
difficult to explain.
The study suggests three ways that genetic evaluations could be carried from this
point on. First, would be to leave the genetic evaluations untouched and continue as
normal. Second, three different regional BW EPD’s could be published based on the data
that comes into the breed associations. Finally, the EPD’s could be scaled in a manner to
reduce variability and tighten the range of numbers, although not affecting sire rank for
the trait.
Table 1.
Actual Birth Weight Statistics
N
Mean
SD
Overall
157,883
87.19
10.57
Canada (R1)
33.267
92.91
11.24
North (R2)
107,573
86.13
9.57
South (R3)
17,043
82.74
10.95
Table 2.
Birth Weight Analysis
Genetic Variance
Environment
Variance
Phenotypic Variance
Canada
(R1)
43.97
49.66
93.63
North
(R2)
33.81
34.26
68.07
South
(R3)
24.88
36.15
61.03
Table 3.
Birth Weight Analysis
Canada
(R1)
0.47
(Heritability)
North
(R2)
0.65
(Correlation)
0.50
(Heritability)
South
(R3)
0.54
(Correlation)
0.63
(Correlation)
0.41
(Heritability)
Table 4. Ten Highly Utilized Sires
BW
EPD
ACC
R1
EPD
ACC
R2
EPD
ACC
R3
EPD
ACC
Bull 1
6.0
0.93
7.5
0.80
5.3
0.80
7.2
0.56
Bull 2
4.9
0.92
5.0
0.76
6.2
0.76
5.6
0.59
Bull 3
8.8
0.92
9.5
0.72
8.6
0.80
10.2
0.53
Bull 4
3.8
0.91
3.3
0.72
4.3
0.72
4.8
0.56
Bull 5
6.3
0.88
3.6
0.69
8.7
0.69
4.8
0.59
Bull6
6.3
0.90
5.0
0.76
6.5
0.80
8.6
0.39
Bull 7
7.7
0.87
10.9
0.54
4.1
0.66
8.1
0.51
Bull 8
5.3
0.88
2.0
0.69
6.0
0.63
5.1
0.40
Bull 9
5.6
0.83
6.7
0.72
6.3
0.53
4.1
0.44
Bull
10
7.0
0.80
8.8
0.63
5.7
0.40
3.3
0.46