Selection in Beef Cattle II. Selection Response

S E L E C T I O N IN B E E F C A T T L E
II. S E L E C T I O N RESPONSE 1,2
Robert M. Koch 3 , Keith E. Gregory4 and Larry V. Cundiff4
University of Nebraska and U.S. Department of Agriculture
Clay Center 68933
Summary
weaning gain or yearling weight may increase
weaning gain or weight more than direct
Selection response was studied in three lines
selection for these traits. Response in postof Hereford cattle selected for (1) weaning
weaning gain and yearling weight per unit of
weight (WWL), (2) yearling weight (YWL) or selection applied was relatively large (0.37 and
(3) index of yearling weight and muscling score 0.48). Correlated responses to selection in the
(IXL). Selection response was evaluated by
three lines suggest that a wide variety of
several measures of offspring regression on
selection patterns will lead to improvement in
selection in parents. Average estimated reall traits even though optimum selection
sponse, expressed in standard deviation units
indexes
may maximize improvement in particper generation, in the three lines, WWL, YWL
ular traits.
and IXL, were: birth weight, 0.22, 0.28 and
0.28; weaning daily gain, 0.20, 0.13 and 0.12;
Introduction
weaning weight, 0.23, 0.17 and 0.15; postweaning daily gain 0.28, 0.42 and 0.33; yearling
Breeding objectives involving single or
weight, 0.36, 0.43 and 0.33 and muscling score,
multiple
traits, stated in measurable aesthetic,
-.03, 0.01 and 0.24, respectively. Birth weight
response per unit of selection was 0.47 and economic or biological terms, form the basis of
appeared highly correlated genetically with all selection programs. Selection applied is usually
performance traits. Expected increase in birth measured by the observed selection differentials
weight could be reduced 30% if all emphasis on or by an index that expresses the average
growth was directed to postnatal growth rate relative weight given to observed selection
rather than weaning or yearling weight. differentials for each trait involved in multiple
Response per unit of selection applied was low trait selection. Individual sires and dams are the
for weaning gain or weight (0.10 or 0.12) units selected, but the effective selection units
relative to other traits. Selection for post- are the midparents, i.e., sire and dam pairs that
produce each subsequent generation. Natural
selection, unintended attention to traits or
chance may modify actual midparent selection
aPublished as Paper No. 3545, Journal Series, as compared with selection intentions. Genetic
Nebraska Agricultural Experiment Station. Contribu- changes from selection are reflected in phenotion from North Central Regional Project NC-1,
Improvement of Beef Cattle Through .Breeding typic values of offspring from selected parents
Methods.
and form a basis for evaluating selection
The authors gratefully acknowledge assistance of effectiveness.
the late J. E. Ingalls, W. W. Rowden, J. A.
This paper is an evaluation of offspring
Rothlisherger and R. D. Humphrey in collection of
data and supervision of livestock operations. Special response to intrayear differences in cumulative
recognition is given to G. E. Dickerson for assistance midparent selection for weaning weight, yearwith numeroustheoretical aspects of the study.
ling weight and muscling score in three lines of
~
of Animal Science, University of Hereford cattle. Offspring-parent regressions in
Nebraska, U.S. Meat Animal Research Center, Clay
selected vs. unselected parental populations are
Center, Nebraska 68933.
4 U.S. Meat Animal Research Center, North Central examined. Estimates of genetic change in
Region, A.R.S., Clay Center, Nebraska 68933.
various traits due to selection are presented.
459
JOURNAL OF ANIMAL SCIENCE, vol. 39, no. 3, 1974
460
KOCH, GREGORY AND CUNDIFF
Materials and Methods
Three 150-cow-6-sire selection lines were
established in 1960 at the Fort Robinson Beef
Cattle Research Station, Crawford, Nebraska.
In one fine the selection objective was weaning
weight (standardized to 200 days of age and
adjusted for age of dam). In a second line the
selection criterion was adjusted yearling weight
(252 or 350 days post-weaning gain of bulls or
heifers added to 200 day weight). An index
giving equal emphasis to standardized deviations of adjusted yearling weight and a
muscling score was the selection objective for
the third line. Details related to line formation,
measurement of performance traits, calculation
of selection differentials, selection indexes in
retrospect and generation interval were presented in the first paper of this series (Koch,
Gregory and Cundiff, 1974). Selection and
response were expressed in standard deviation
units for all traits.
The experimental design incorporated regular replacement of bulls and heifers, without
further selection based on progeny performance, to permit intrayear comparisons of
animals representing different generations and
differing in accumulated selection differential.
Analysis on an intrayear basis avoided year to
year fluctuations caused by environmental,
management or genetic causes.
Phenotypic time trends were examined but
selection response was estimated primarily
from: (1) sire and dam selection indexes
combined with estimates of genetic covariance
from paternal half-sibs; (2) regression of
offspring deviations on generation coefficients;
(3) simple regression of offspring deviations on
cumulative midparent selection differentials;
(4) partial regression of offspring deviations on
cumulative midparent selection differentials;
(5) and regression of offspring on midparent
averaged over lines and sexes used in conjunction with the midparent index in retrospect.
Muscfing score was not obtained for most of
the dams in this study. However, muscling
scores were obtained on all heifers born since
1967. Muscling score response in these heifers
was analyzed on the 178, 175 and 179 heifers
born in 1967 to 1970 in the weaning weight,
yearling weight and index lines, respectively.
Abbreviations used are outlined below:
WWL - Weaning weight line
YWL - Yearling weight line
IXL - Index of yearling weight and muscling
score line
GC - Generation coefficient
A - Deviation from average as appropriate for
selection differentials or genetic change
I - Index of selection for sires, dams or
midparents
G - Average genetic value
/~ - Standard partial regression coefficients
BW - Birth weight
WDG - Weaning daily gain
WW - Weaning weight
PDG - Postweaning daily gain
YW - Yearling weight
MS - Muscling score
Results and Discussion
Phenotypic Time Trends. Trait means by
lines, years and sex are shown in table 1.
Regressions of trait means on years, shown in
table 1, include genetic and environmental
trends. Average values of the annual means over
all years, however, do provide estimates of
relative average genetic merit of calves in each
line. Division of cattle at the beginning of the
experiment was at random giving each line
similar expected genetic values. Birth weight
increased in all lines. Rate of change was
greatest in IXL. The average birth weight of
bulls and heifers over these years was greatest in
IXL and least in WWL, but average differences
were small.
The average regression of weaning weight on
years was larger in IXL and WWL than YWL.
However, the average regressions were similar to
t h e regressions on birth weight which suggests
most of the change could be accounted for by
increase in birth weight.
Yearling weight presents a confusing pattern.
In bulls the average weight over years was
highest in YWL and smallest in WWL, but the
regression on years was negative in all lines.
Because of the change in feeding program for
bulls and heifers in 1964, the annual means for
1963 were not used in calculating the
regressions of yearling weight, but are included
in the average value over all years. The low
performance in 1969 and 1970 were thought to
be due to severe weather and disease conditions. In any case, phenotypic regressions on
years were not considered good measures of
genetic change in bulls partly because ad
libitum feeding of a complete ration could not
be accommodated (hay was offered ad libitum
and concentrates were fed at 1.75 to 2.0% of
average body weight) and partly due to poor
feedlot conditions in 1969 and 1970. The
postweaning feeding and management program
used for bulls did permit assessment of genetic
461
SELECTION IN BEEF CATTLE
TABLE 1. ANNUAL TRAIT MEANS AND REGRESSION
OF MEANS ON YEARS a,b
Item
Line
BW(kg)
Bulls
Heif.
WW(kg)
Bulls
Heif.
YW(kg)
Bulls
Heif.
MS(units)
Bulls Heif.
1963
WWL
YWL
IXL
35.4
36.7
36.3
34.5
34.0
33.6
200.9
203.2
199.5
185.9
176.0
185.0
444.4
459.4
449.9
352.8
340.6
355.1
81
83
82
WWL
YWL
IXL
1965
WWL
YWL
IXL
1966
WWL
YWL
IXL
1967
WWL
YWL
IXL
1968
WWL
YWL
IXL
1969
WWL
YWL
IXL
1970
WWL
YWL
IXL
AVG
WWL
YWL
IXL
REGR c WWL
YWL
IXL
37,2
36.3
36.7
35.4
36.7
36.3
34.9
34.9
36.7
37.2
38.1
37.6
38.1
38.1
38.1
38.5
39.5
39.5
37.6
38.5
39.5
36.8
37.4
37.6
0.4
0.4
0.5
33.6
34.5
33.6
33.1
34.5
34.0
33.1
33.6
34.9
35.4
34.9
36.3
35.4
36.3
35.8
36.7
36.7
37.2
35.4
35.8
36.7
34.6
35.0
35.3
0.4
0.4
0.5
202.7
195.5
197.3
202.3
204.5
204.1
210.4
201.8
202.3
215.4'
215.9
209.5
211.3
198.6
208.6
203.2
199.1
195.0
201.4
202.3
205.9
206.0
202.6
202.8
0.5
0.1
0.6
185.0
185.5
182.3
192.7
184.1
191.4
192.7
185.9
191.4
205.4
197.3
195.5
195.0
186.4
194.6
190.5
183.2
187.3
185.5
182.8
184.6
191.6
185.2
189.0
0.5
0.7
0.4
431.7
434.5
434.9
423.6
444.9
439.5
451.7
449.9
446.7
437.2
449.4
429.9
470.3
461.2
470.3
416.8
415.9
409.5
415.0
420.9
427.2
436.3
442.0
438.5
-1.6
-3.1
-2.1
366.9
372.3
359.6
380.0
371.9
381.9
387.3
390.5
395.0
405.0
405.4
403.6
396.8
384.6
401.8
403.2
408.6
407.3
381.9
376.9
383.7
384.2
381.4
386.0
3.6
2.9
82
82
83
82
83
84
83
83
84
81
82
82
81
82
82
81
81
83
81
82
82
81.5
82.2
82.8
1964
81
81
82
81
80
81
81
81
83
80
81
81
80.8
80.8
81.8
4.6
a A p p r o x i m a t e standard errors for annual m e a n s for a line w e r e : BW, + .5 kg; WW, • 2.5 kg; YW, +- 4.6 kg; and
MS, -+ .3 units.
b B w and WW adjusted for age o f dam. WW standardized at 2 0 0 d a y s o f age, Y W at 4 5 2 d a y s o f age for bulls
a n d 5 5 0 d a y s for heifers.
CRegressions for yearling w e i g h t are for 1 9 6 4 t o 19"/0 due to change in feeding and m a n a g e m e n t in 1 9 6 4 ,
differences within years but was not conducive
to direct evaluation of genetic trends between
years. Beginning with 1964, heifers w~ere grown
out postweaning on winter range supplemented
with sufficient hay, protein and grain to achieve
an average weight approximating 275 kg just
prior to the breeding season and then carried
unsupplemented on summer pasture to the end
o f their performance period. Unrestricted
grazing o f winter and summer pasture would
more nearly approach ad libitum feeding
conditions for heifers than for bulls. Large
annual increases in yearling weight o f heifers,
actually 550-day weight, were noted in all lines.
The greatest rate o f change and the heaviest
yearling weights were in the IXL heifers and
least in the YWL heifers.
Averages for muscling score were highest in
IXL and lowest in WWL. Regressions were not
calculated because persons doing the scoring
each year a t t e m p t e d to give average animals a
score o f 80 with corresponding deviations
above and below average.
Evaluation o f phenotypic means b y a more
elaborate statistical model would be necessary
for further useful statements on genetic or
environmental trends.
Expected Genetic Change (Method One).
462
KOCH, GREGORY AND CUNDIFF
Expected genetic progress in each trait (AGi) covariance among heifers was used for estican be calculated from the selection applied in mating genetic change in dams. For example,
each trait (AI'/3tpk), the genetic correlation estimated genetic chang e in weaning weight of
(rGjk) and the square roots of heritability (h) as sires in WWL using 11 was [0.643 (0.160) +
0.415 (0.126) + 0.037 (-.063)1 1.582 = 0.24
AGi = .~(/3iPk'rGik'hihk)AI (Harvey and Bear- standard deviations for weaning weight. Simden, 1~62; Dickerson, 1969). Genetic change ilarly, expected change in other traits of sires
expected from sire selection and from dam and traits of dams were calculated. The
selection was evaluated. Sire and dam selection estimated genetic change from sires and from
indexes I1 and I2 reported in Koch et al. dams were averaged to give estimates of change
(1974) provided the appropriate AI and/3xp k expected in offspring per generation. The
terms, where AI is the selection differential of average values are shown as method 1 in table
the index in standard measure and /3ipk the 6.
Regression of Offspring on Generations of
standard partial regression of index on the k th Selection (Method 2). Sires of ages 3 to 5 years
trait. Estimates of heritability (h 2) and genetic and dams of ages 2 to 10 years and their
correlations (rGik) and genetic covariance in random mating provided considerable variation
standard measure (rGik'hihk) were obtained in generations of selection represented in lines
from paternal half-sib analysis within each line for any given year. Generation coefficients, GC
and sexbut pooled over the three lines as shown = (GCs + GCd)/2 + 1, where GCs and GCd are
the generation coefficients of sires and dams,
in table 2.
Except for birth weight, heritabilities in measure the average number of segregations
table 2 are slightly smaller than the average back to foundation animals. The intrayear
paternal half-sib estimates summarized by Petty standard deviation of generation coefficients
and Cartwright (1966), which were BW, 0.44; was 0.34 indicating an expected range of about
WDG, 0.34; WW, 0.32; PDG, d 0.54, 9 0.35; 1.7 generations. Regression of offspring deviYW, d 0.62, 9 0.41. Selection may have biased ations, expressed in standard measure, on
estimates in this study downward as suggested generation coefficients within year, line and sex
by the work of Ronningen (1972a). Estimated subclasses provide a direct estimate of genetic
genetic change for weaning weight, yearl!ng change per generation of selection. These
weight and muscling score utilized the Ii sire regression coefficients are shown for bulls and
and dam indexes. Estimated change in birth heifers of the three lines in the top part of table
weight, weaning daily gain, postweaning daily 3. There was no consistent difference between
gain, and muscling score utilized the I2 sire and bulls and heifers for preweaning traits. Heifers
dam indexes. Genetic covariance for bulls was generally exhibited a greater increase per
used for estimating genetic gain in sires. Genetic generation than bulls for postweaning gain and
TABLE 2. HERITABILITY, GENETIC CORRELATIONS AND GENETIC
COVARIANCE FROM PATERNAL HALF-SIB ANALYSIS OF
COVARIANCE POOLED OVER THE THREE LINES a
Trait
Sex
BW
WDG
WW
PDG
YW
MS
BW
Bull
Heif.
.51 + .09
.59 + .12
.19 -+ .19
.19 + .19
.50 + .15
.47 + .15
.58 + .12
.40 + .12
.70 + .11
.50 + .11
.24 +- .15
.07 +- .21
WDG
Bull
Heif.
.049
.058
.13 + .07
.16 +- .10
.94 + .02
.93 + .02
.09 -+ .22
.35 + .19
.56 + .15
.61 + .10
- . 4 7 + .33
.22 -+ .42
WW
Bull
Heif.
,143
,157
.136
.162
.16 + .07
.19 + .10
.27 + ,20
.44 + ,17
.72 -+ .11
.70 -+ .08
- . 3 2 + .29
.18 +- .33
PDG
Bull
Heif.
,194
.246
.015
.112
.051
.153
.22 + ,08
.64 + ,12
.86 + .05
.96 + .04
- . 2 9 + .22
.11 + ,21
YW
Bull
,218
.088
.126
.176
.19 + .08
- . 5 0 + .26
MS
Heif.
Bull
Heif.
.260
.084
.029
.166
-.083
.048
.207
-.063
.043
.521
-.067
.048
.46 + .11
-.107
.045
.12 + .23
.24 + .08
.30 + .14
aHeritability values and standard errors are along diagonal, g e n e t i c c o r r e l a t i o n s and t h e i r standard errors are
t o t h e right o f diagonal, and genetic covariance is to the left of diagonal.
SELECTION IN BEEF CATTLE
463
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464
KOCH, GREGORY AND CUNDIFF
yearling weight. Genetic values of parents of
bulls and heifers have the same expected value.
Therefore, differences observed in response
measured in bulls and heifers may be due to
chance, differential expression of genetic
differences or differences in the feeding and
management conditions for the two sexes.
Differences in the feeding and management of
the two sexes and chance likely account for
differences observed in these data. Average
response for the two sexes are shown in table 6
as method 2.
Regression of Offspring on Midparent
Cumulative Selection Differentials (Method 3).
In an unselected population regression of
offspring deviation, expressed in standard
measure, on midparent selection differential
would be an estimate of total correlation and is
a measure of direct or correlated response to
selection. The regression includes genetic and
phenotypic contributions from maternal influence if these are important sources of variation
(Koch, 1972). Intrayear regressions of offspring
deviation on midparent cumulative selection
differentials were calculated and are presented
in the lower portion of table 3. These are
similar to the more frequently used offspringparent regressions except that the cumulative
parental differentials include average deviations
of ancestors back to foundation animals. Use of
cumulative selection differentials permits evaluation of intrayear differences among offspring
from parental groups that differ more widely in
selection applied than would be possible among
contemporary parental groups.
Regression coefficients along the diagonal
can be considered as selection specific estimates
of heritability and off-diagonal regressions as
change expected in correlated traits in each
line. The expected value of the regression
coefficient can be expressed as a function of
the index of selection and genetic and
phenotypic covariances in an unselected population (Magee, 1965; Dickerson, 1969, p. 61).
In standard measure, the expected selection
differential per generation for any trait, Pi is
E ~ i = [~ip~'rjk]AI/oi, where A"~j is the
k
"
average observed midparent selection differential,/3xp k is the standard partial regression of
index on the kth trait, rjk is the phenotypic
correlation between j and k in an unselected
population, AI is the average selection differential of the index and oi is the standard
deviation of the index. Expected genetic gain
per generation is EzSG~= ~ (/3iv. rG..
9
k
K
JK
hjhk] Al/al, where hj and hk are the square
roots of heritability of j and k, rGj k their
genetic correlation, AI and oi as explained
before. The regression of offspring on midparent has the same expectation as the ratio,
~-(]j/z~j, which is specific to each population
of index /3's even when underlying genetic
parameters are similar between populations.
Response of offspring per generation of
selection is predicted by multiplying appropriate regression coefficients in table 3 by
observed selection differentials for midparents
as reported earlier in Koch et al. (1974). For
example, estimated change of weaning weight
in the WWL is 0.35(0.958)= 0.335 for bulls
and 0.22(0.958)= 0.211 for heifers and their
average of 0.27 standard deviations per
generation. Average response of bulls and
heifers per generation estimated as outlined
above is shown as method 3 in table 6.
Regression as obtained among unselected
parents and unselected offspring would be more
useful for generalizing prediction of expected
selection response than the selection specific
regressions shown in table 3. Extent of
selection bias and alternative methods of
expressing covariation between parent and
offspring in terms of an unselected population
were examined. VanVleck (1968) and Ronningen (1970) used Monte Carlo simulation to
evaluate selection bias in estimates of genetic
correlations between two traits with various
selection weightings, heritability levels and true
genetic correlations between the two traits.
They noted that bias increased as selection
intensity increased, but for practical selection
levels encountered in milk production situations they concluded the bias was likely small
relative to the sampling errors of estimated
genetic correlations. In Monte Carlo studies of
selection effects on heritability estimated by
parent-offspring regression, Ronningen (1972b)
noted that when selection was on parents but
not on offspring the regression gave unbiased
estimates of heritability for the case of single
trait selection. The effects of multiple trait
selection seem to have received less attention in
studies of bias than single or two trait selection.
To evaluate the bias encountered here Alan
Robertson (personal communication) suggested
using the following formulation. For traits
linearly related, say i, j and k with selection on
i, COVikt = COVjk
[1 _ srij rikl
ri k j where COVikt is
the covariance between two traits j and k in the
selected population and COVjk the covariance in
SELECTION IN BEEF CATTLE
the unselected population; s = (oi 2 -oi2t)/ai 2,
is the fraction that variance in i is reduced by
selection and the r's are correlations in an
unselected population. The formula given above
derives from formulas first developed by
Pearson (1903).
Multiple trait selection can be accommodated by considering the index as a single
trait with truncation selection on the index (7).
Since unselected offspring are a reflection of
the genetic values of parents the problem can
be treated as bias affecting the regression of
average genetic value (G) on phenotype (P)in
the parents with selection on I. The expected
value for the regression in the selected
population is
b~v = bGp
rrGP s (riG rip) 7
Gp-S (rGp r2ip)_J
and as rlGrIp --> rGpr2ip, the bias ~ 0. Thus,
regression on the index or when I = P is
unbiased by selection. Brown and Turner
(1968) used a similar approach in evaluating
selection effects on parameter estimates in
Merino sheep. Evaluation of selection bias by
this formula requires accurate estimates of
genetic and phenotypic parameters. "Alternatively, a method estimating response free of
bias was pursued.
465
contained the variables birth weight, weaning
daily gain, postweaning daily gain and muscling
score. Traits affecting fitness or fertility were
left unmeasured but may have affected
selection. The correlated portion of ignored
effects could bias the partial regressions of
variables included in the index in a manner
similar to the bias discussed earlier. However,
these biased partial regressions pick up the
correlated part of the predicted value of any
traits ignored in the index.
Partial regression coefficients for combinations one and two are shown in table 4. Change
in unselected offspring is a reflection of change
in genetic value of parents, plus any direct
maternal affects. Response per generation__may
be estimated by Z(APk 9 b*jfi-k), where API~ is
the average midparent select16a] differential and
b*j~k is the partial regression of j in offspring
on k in midparents. Average selection differentials of selected midparents were given in
table 5, Koch et al. (1974). Response in WW,
YW and MS were estimated from partial
regression coefficients in combination one,
while coefficients in combination two were
used to estimate BW, WDG, PDG and MS. For
example, estimated response for WW of bulls in
the WWL was 0.1356(0.958) + 0.2555(0.886) .1015(0.257)= 0.33 and for heifers was
-.0006(0.958)
+
0.2395(0.886) +
0.1480(0.257) = 0.250 and their average is 0.29
standard deviations per generation. Average
estimated response of bulls and heifers per
generation calculated as described above is
shown in table 6 as method 4. Response in
muscling score is the average of estimates from
combinations one and two.
Partial Regression of Offspring Deviations on
Midparent Cumulative Selection Differentials
(Method 4). In a system of linearly related
variables, such as genetic and phenotypic values
of various performance traits, the multiple
regression of offspring on parent should provide
a more accurate evaluation or prediction of
Regression of Offspring on Midparent in an
offspring response or average genetic value than Unselected Population (Method 5). Partial
single trait regression. Further, a theorem given regressions in table 4 can be used to estimate
by Pearson (1903) states that if a trait was simple offspring-midparent regression coeffiaffected only by indirect selection (as in the cients in an unselected population. The partial
case of genetic values here), then its partial regression coefficients, bojp-k, have an expected
regression coefficients on any complex of other
traits, provided it includes all the directly value of /~oi~k "Oo,/Off,. and the correlation
selected traits, will remain unchanged by the between j in offspring and k in midparents is
selection.
k~(/~ojFk -r~iFk ), where rFj~k is the phenotypic
Multiple regression of standardized offspring correlation between midparent values. In these
deviations on cumulative midparent selection data the phenotypic correlations between j and
differentials for two alternative combinations k of unselected bull and heifer offspring (Koch
of traits thought to include those performance et al., 1974) were averaged to estimate the
traits that contributed significantly to selection correlations between midparent values for all
in the parents were obtained on an intrayear, traits except MS where correlations among bull
line and sex subclass basis. Combination one offspring were used. The simple regression of j
was comprised of cumulative midparent selec- in offspring on k in midparents is rojffk ~
tion differentials for weaning weight, yearling
weight, and muscling score. Alternatively, Ooj/O~k = k~(~]oj-15k ~ r~j~k)Ooj/O~k = k~(bo*j~k ~
performance measured in combination two r~j~k ). For example, the regression of BW of
466
KOCH, GREGORY
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SELECTION IN BEEF CATTLE
467
TABLE 5. ESTIMATED REGRESSION OF OFFSPRING ON MIDPARENT
IN AN UNSELECTED POPULATION
Offspring:
Midparent
BW
WDG
WW
PDG
YW
MS
BW
WDG
WW
PDG
YW
MW
Line
Bulls Heif. Bulls Heif. Bulls Heif. Bulls Heif. Bulls Heif.
Bulls Heif.
WWL
YWL
IXL
Avg
WWL
YWL
IXL
Avg
WWL
YWL
IXL
Avg
WWL
YWL
IXL
Avg
WWL
YWL
IXL
Avg
WWL
YWL
IXL
Avg
.41
.52
.44
.46
.35
.10
.04
.16
.55
.06
.09
.23
.31
.25
.17
.24
.62
.20
.22
.35
.57
.06
.15
.26
-.01
-.24
.06
-.06
-.03
-.08
.17
.02
-.03
-.06
.17
.03
.04
-.08
.12
.02
.01
-.10
.18
.03
.35
.24
.32
.30
.44 .09 .01 .16 .09
.53 .01 .14 .11 .23
.47 .12 --.01 .20 .08
.48 .08 .05 .16 .13
.23 .26 .25 .30 .26
.13 - . 0 6
.01 - . 0 4
.03
.17 .14 .04 .15 .06
.18 .11 .10 .14 .12
.46 .22 .13 .30 .20
.16 - . 0 6
.17 - . 0 5
.05
.21 .16 .04 .17 .07
.28 .11 .11 .14 .11
.40 .14 .23 .19 .28
.28 .11 .17 .15 .21
.30 .26 .41 .28 .43
.33 .17 .27 .21 .31
.66 .22 .19 .32 .30
.25 .06 .14 .10 .18
.40 .31 .30 .34 .35
.44 .20 .21 .25 .27
.47 - . 0 8
.23 .03 .30
.01 .09 - . 0 7
.10 - . 0 7
.39 .00 .23 .03 .28
.29 .00 .13 .05 .17
bull offspring on BW o f midparents in WWL is
0.2920 + 0.2142(0.2250) + 0.0694(0.3265) +
0.3100(0.138) = 0.41. Similarly, the regression
o f WW o f bull offspring on WW of midparents
in WWL is 0.1356 + 0 . 2 5 5 5 ( 0 . 7 3 4 5 ) 0.I015(0.203) = 0.30. A summary o f these
calculations is given in table 5. The difference
between individual regressions in table 5 a n d
corresponding regressions in table 3 estimate
bias associated with selection. Although a few
regressions appear biased to a sizeable extent,
most estimates o f bias were small. Comparison
of coefficients averaged over the three lines
provides some idea of bias that may be
encountered when pooling data from herds
with different selection objectives. The average
bias without regard to sign for the six offspring
traits regressed on birth weight o f parents was
0.02 and similarly, average bias for regressions
on weaning daily gain was 0.04, on weaning
weight was 0.02, on postweaning daily gain was
0.03, on yearling weight was 0.04, and on
muscling score was 0.05 with standard devia-
.08
.21
.27
.19
.12
.23
.07
.14
.09
.24
.10
.14
.29
.32
.30
.30
.26
.36
.29
.30
.50
.07
.08
.22
.27
.29
.49
.35
.55
.41
.25
.40
.54
.43
.29
.42
.41
.55
.36
.44
.60
.66
.49
.58
.45
.14
.16
.25
.17
.20
.33
.24
.31
.14
.47
.31
.30
.14
.18
.21
.33
.31
.41
.35
.41
.30
.43
.38
.41
.10
.09
.20
.27
.40
.31
.33
.53
.33
.20
.35
.50
.37
.22
.36
.50
.48
.50
.49
.63
.56
.52
.57
.52
.11
.23
.29
-.03
-.10
.07
-.02
-.01
.17
.15
.10
--.05
.14
.16
.08
.12
.06
-.05
.04
.04
.17
.08
.10
.51
.22
.22
.32
tions of these differences approximating the
magnitude of the average difference. If these
differences are indicative of other selection
situations it offers some hope that pooling data
from many sources with varied selection
objectives will provide parent-offspring regressions that may not be seriously biased, at least
by selection, from those observed in unselected
populations. Differences observed in the regression coefficients for the three lines may be due
to sampling error, real differences in average
maternal effects of the lines or possible bias
from not including all important variables. In
any case, the average regression over the three
lines should be a better estimate o f the
offspring-midparent regression in an unselected
population than that o f any single line.
Regressions averaged over lines were similar for
preweaning traits o f bulls and heifers, but in
postweaning traits regressions were consistently
higher in heifers. Whether the difference in
response is due to differential genetic expression for the two sexes, sampling error or
468
KOCH, GREGORY AND CUNDIFF
postweaning management conditions of the two
sexes is not known. In application it seems best
to average the coefficients of bulls and heifers
and use these to predict expected change in
total calf crop even through it may understate
or overstate change in either sex. One expects
change in average genetic values over generations to be similar in the two sexes even though
expression within a generation is related to
phenotypic variation for each sex.
Regression coefficients in table 5 averaged
over lines and sexes and multiplied by
appropriate terms o f the midparent._selection
index (Koch et al., 1974) as ~(13i~k -bOj~k)Al
is an estimate of response expected if selection
in each line followed its index in retrospect but
offspring response per unit o f selection was
similar in all lines. For example, WW response
in WWL is estimated by 89
+ 0.11) +
0.415(0.25 + 0.27) - 0.034(0.05 + 0.17)]
0.995 = 0.19. Response estimated in this
manner is summarized as method 5 in table 6.
It should be noted that regressions in table 5
are not symmetric about the diagonal as
expected if maternal influence was present to a
different extent in the two relationships
between traits of parent and offspring, i.e.,
boj~ k and bok~j. Also, genetic correlations
estimated from these regressions were generally
large or over 1.0 suggesting significant maternal
effects may be present.
TABLE 6. AVERAGE OFFSPRING RESPONSE
PER GENERATION EXPRESSED IN
STANDARD DEVIATION UNITS
Trait
Birth
wt
Wean.
DG
Wean.
wt
Post.
DG
Yrlg
wt
Combined Estimates of Offspring Response.
None o f the methods used to evaluate selection
response shown in table 6 seems satisfactory,
yet each provides useful evidence on change
due to selection. Method 1 uses sire and dam
indexes and paternal half sib estimates of
covariance for each sex pooled over the three
lines. Paternal half sib covariances do not
include maternal effects and estimates have
large sampling errors. Method 2 is the intrayear
regression of offspring on generation coefficient
and is a direct estimate of response per
generation that is independent of maternal
effects or selection bias. The method is subject
to sampling error due to the rather small
variation (approximately 1.7 generations) present within a given year and to sampling
variation in rate of increase in cumulative
selection per generation for selected sires and
dams. Method 3, the intrayear linear regression
of offspring on cumulative midparent selection
differential, measures response specific to each
sex and line including maternal effects.
Information on only one of the observed
selection differentials is utilized in the prediction. Method 4 uses the partial regression of
Musc.
score
Method
1
2
3
4
5
Avg
1
2
3
4
5
Avg
1
2
3
4
5
Avg
1
2
3
4
5
Avg
1
2
3
4
5
Avg
1
2
3
4
5
Avg
WWL
.17
.11
.16
.39
.28
.22
.13
.22
.23
.28
.16
.20
.16
.22
.27
.29
.19
.23
.13
.36
.13
.41
.36
.28
.18
.37
.41
.46
.38
.36
-.06
-.20
.10
-.02
.05
-.03
YWL
.21
.34
.20
.27
.36
.28
.07
.29
-.02
.09
.24
.13
.10
.34
.01
.15
.27
.17
.20
.54
.36
.52
.47
.42
.18
.60
.45
.43
.50
.43
-.03
-.25
.14
.06
.11
.01
IXL
.24
.10
.20
.41
.45
.28
-.01
.18
.04
.24
.17
.12
.02
.18
.05
.29
.22
.15
.11
.48
.28
.32
.45
.33
.04
.42
.38
.36
.44
.33
.21
.10
.29
.30
.31
.24
offspring on all midparent traits thought to be
important in selection and the average midparent selection differentials. The method
utilizes multiple trait information but is
restricted to an evaluation of offspring response
in each line. Method 5 uses the estimates of
offspring-midparent regression expected in an
unselected population with response averaged
over all lines in conjunction with the midparent
index for each line. If midparent indexes are
used with regressions shown for each line
instead o f the average regression over all lines,
the results are identical with method 4.
Methods 3, 4 and 5 include maternal effects
SELECTION IN BEEF CATTLE
which, to the extent they are genetically
determined, form a valid part of estimated
response to selection.
The best combination of all methods is not
clear as methods are related in different ways.
Only methods 2 and 3 have straight forward
estimates of sampling error. The simple average
of all methods at least affords comparisons of
lines which differed in selection applied but
were evaluated by the same methods. Response
per generation in table 6 is expressed in
phenotypic standard deviation units of an
unselected population and can be converted to
actual units by multiplying by the phenotypic
standard deviation of bulls and heifers. In these
data the standard deviations of bulls and heifers
were BW = 3.9 and 3.6 kg; WDG = 103 and 92
g; WW = 21.7 and 19.7 kg;PDG ---97 and 56g;
YW --- 35.8 and 29.5; and MS = 2.6 and 2.5
units, respectively.
Birth weight would be expected to change as
a direct component of weaning and yearling
weight and to the extent it is correlated with
weaning or postweaning gain. Birth weight
response averaged somewhat higher in the YWL
(0.28) and IXL (0.28) than in WWL (0.22) and
is similar to the 0.25 a reported by Brinks,
Clark. and Kieffer (1965). Average regression of
birth weight response (table 5 ) o n parental
weaning daily gain is lower than the regression
on postweaning daily gain or muscling score
which received greater relative emphasis in
YWL and IXL. Expected increase in birth
weight could be reduced by 30% if all emphasis
on growth were directed to postnatal growth
instead of weaning or yearling weight. Avoiding
direct selection for birth weight and even giving
it negative attention sufficient to partially
offset correlated response from weaning or
postweaning gain may be advisable to avoid
possible increase in death loss associated with
relatively large birth weights.
Weaning gain and weaning weight response
was greater in the WWL (0.20 and 0.23) than in
the YWL (0.13 and 0.17) or IXL (0.12 and
0.15). Response in these lines was lower than
the estimated genetic response in weaning gain
(0.250) and weight (0.280) reported by Brinks
et aL (1965) whose average midparent index
selection differential for performance traits was
similar (0.93) to that reported in this study
even though individual weighting of traits
differed. Heritability for weaning gain (0.10)
and weaning weight (0.12) found in this study
is lower than the average of offspring-sire and
offspring-dam regressions for weaning gain
(0.12) or weaning weight (0.23) summarized in
469
Petty and Cartwright (1966). Average regression of weaning gain or weight on postweaning
gain or yearling weight in table 5 was higher
than the heritability of weaning gain or weight.
This suggests that selection for postweaning
gain or yearling weight would lead to more
improvement in weaning traits than direct
selection for these traits. The lower average
estimate of response for weaning gain or weight
in YWL, however, does not support this
expectation. Differences in direct maternal
effects related to pre- and postweaning growth
in WWL and YWL could account for differences
observed early in the experiment that may not
be sustained in future generations. Bias in age
of dam correction factors could also affect the
intrayear regression, particularly for birth
weight and weaning gain. Intra age of dam
analyses of these data suggest the age of dam
factors did not seriously bias the regressions
reported here.
Response for postweaning gain and yearling
weight was greater in the YWL (0A2 and 0.43)
than in the WWL (0.28 and 0.36) or the IXL
(0.33 and 0.33). The response observed here is
intermediate to those reported in other
selection experiments with beef cattle. Bailey et
al. (1971) reported increases of 0.28a and
0.750 in postweaning gain per generation at
two locations. Brinks et al. (1965) estimated a
genetic increase of 0.380 for final weight off
test for bulls and 0.400 for 18 months weight
of heifers. Nelms and Stratton (1967)observed
an increase of 0.340 in yeading weight.
Newman, Rahnefeld and Fredeen (1973)
reported yearling weight increased 4.4 kg per
year in bulls and 2.8 kg per year in females
which corresponds to an estimated 3.3 kg per
year in bulls and 2.8 kg per year in heifers in
these data. Thus, most selection experiments
with beef cattle have reported relatively large
estimated response in postweaning or yearling
growth.
Muscling score response increased only in
the IXL where it received major selection
pressure. Selection for muscling score in parents
was associated with sizeable correlated response
in birth weight, postweaning gain and yearling
weight and to a lesser extent weaning gain or
weight.
The similarity of response in birth weight,
weaning weight and yearling weight in the three
lines which differed markedly in the relative
selection applied is evidence of strong genetic
correlations between the traits under selection.
This situation is fortunate in that improvement
programs can utilize a wide variety of
470
KOCH, GREGORY AND CUNDIFF
p e r f o r m a n c e e v a l u a t i o n p a t t e r n s as d i c t a t e d b y
various m a n a g e m e n t c o n s i d e r a t i o n s t o a t t a i n
improved growth performance.
Literature Cited
Bailey, C. M., W. R. Harvey, J. E. Hunter and C. R.
Torell. 1971. Estimated direct and correlated
response to selection for performance traits in
closed Hereford lines under different types of
environment. J. Anim. Sei. 33:541.
Brinks, J. S., R. T. Clark and N. M. Kieffer. 1965.
Evaluation of response to selection and inbreeding
in a closed line of Hereford cattle. U.S.D.A.,
A.R.S. Tech. Bull. 1323.
Brown, G. H. and H. N. Turner. 1968. Response to
selection in Australian Merino sheep. II. Estimates
of phenotypic and genetic parameters for some
production traits in Merino ewes and an analysis of
the possible effects of selection on them.
Australian J. Agr. Res. 19:303.
Dickerson, G. E. 1969. Techniques for research in
quantitative animal genetics. In Techniques and
Procedures in Animal Science Research. Amer.
Soc. Anim. Sci.
Harvey, W. R., and G. D. Bearden. 1962. Tables of
expected genetic progress in each of two traits.
U.S.D.A. ARS 20-12.
Koch, R. M. 1972. The role of maternal effects in
animal breeding: VI. Maternal effects in beef
cattle. J. Anim. Sci. 35:1316.
Koch, R. M., K. E. Gregory and L, V. Cundfff. 1974.
Selection effects in beef cattle. I. Selection applied
and generation interval. J. Anita. Sci: 39:449.
Magee, W. T. 1965. Estimating response to selection.
J. Anita. Sci. 24:242.
Nelms, G. E. and P. O. Stratton. 1967. Sdection
practiced and phenotypic change in a closed line of
beef cattle. J. Anim. Sei. 26:274.
Newman, J. A., G. W. Rahnefeld and H. T. Fredeen.
1973. Selection intensity and response to selection
for yearling weight in beef cattle. Can. J. Anim.
Sci. 53:1.
Pearson, K. 1903. I. Mathematical contributions to the
theory of evolution. XI. On the influence of
natural selection on the variability and correlation
of organs. Roy. Soc. (London) Phil. Trans., A.
200:1.
Petty, R. R., Jr. and T. C. Cartwright. 1966. A
summary of genetic and environmental statistics
for growth and conformation traits of young beef
cattle. Texas Agr. Exp. Sta. Dept. Anim. Sei.
Tech. Rep. 5.
Ronningen, K. 1970. Studies on selection in animal
breeding. V. Bias in the estimates of the genetic
correlation due to selection according to an
unrestricted selection index. Acta Agr. Stand.
20:143.
Ronningen, K. 1972a. The effect of selection of
progeny performance on the heritability estimated
by half-fib correlation. Acta Agr. Scand. 22:90.
Ronningen, K. 1972b. The effect of selection on
hefitabilities estimated by twice the parentoffspring regressions or twice the parent-offspring
correlation. Acta Agr. Scand. 22:200.
VanVleck, L. D. 1968. Selection bias in estimation of
the genetic correlation. Biometrics 24:951.

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