Bastiaansen, J.

Berry, D.P.

Bovenhuis, H.

Calus, M.P.L.

Lunden, A.

Veerkamp, R.F.

Wall, E.

Wijga, S.

Name not available

GWAS for Robustness Traits

NARCIS 

Wageningen Yield 

INTERBULL BULLETIN NO. 44. Stavanger, Norway, August 26 - 29, 2011 
 
216 
 
GWAS for Robustness Traits 
H. Bovenhuis1, D. Berry2, A. Lunden3, E. Wall4, J. Bastiaansen1, S. Wijga1,  
M. Calus5 and R. Veerkamp5 
1 Animal Breeding and Genomics Centre, Wageningen University, The Netherlands 
2Animal & Grassland Research and Innovation Centre, Teagasc, Moorepark, Co. Cork, Ireland. 
3Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Sweden 
4Sustainable Livestock Systems Group, Scottish Agricultural College, United Kingdom  
5Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, Lelystad, The Netherlands 
  
 
Introduction 
 
Genomic information is expected to make an 
important contribution to selection for traits 
which are difficult to improve by means of 
traditional selection. These might be traits which 
are difficult or expensive to measure and 
therefore routine recordings are not available, or 
traits which are recorded routinely but the 
phenotypes are not very accurate in a sense that 
the genetics is masked by disturbing 
environmental factors. However, before genomic 
information can make a contribution to genetic 
improvement of these traits either genes need to 
be identified that affect these traits or a reference 
population for setting up genomic prediction 
equations is needed (genomic selection). This 
requires animals that have both genotypes and 
phenotypes available. For several traits 
populations of sufficient size might not be 
readily available.  
 
In the field of human genetics it has become 
increasingly common to form genome-wide 
association consortia (e.g. Bennett et al., 2011). 
These consortia are an effective way to increase 
sample size and therefore to increase the 
statistical power to detect loci. In livestock 
science genome-wide association consortia are 
less common, however, combining data from 
several sources offers excellent opportunities for 
association studies and for the development of 
genomic selection tools. 
 
Here we will present results of genome-wide 
association studies that have been conducted as 
part of the RobustMilk project, which is an 
initiative funded by the European Union in 
which data sets collected at experimental herds 
have been combined.  
 
 
 
Materials and Methods 
 
Genotypes 
 
Animals from experimental farms at WUR 
Livestock Research (LR, The Netherlands), 
Teagasc Moorepark (MPK, Ireland), Swedish 
University of Agricultural Sciences (SLU, 
Sweden) and Scottish Agricultural College 
(SAC, Scotland (UK)) were available. Animals 
included in the genotyping were selected based 
on availability of sufficient amounts of good 
quality DNA and the availability of phenotypes. 
Further, only animals of the Holstein Friesian 
breed were included.  
 
DNA was extracted from blood samples. 
Cows were subsequently genotyped for 54k SNP 
by a commercial genotyping company 
(ServiceXS, Leiden, the Netherlands) using the 
Illumina BovineSNP50 BeadChip (Illumina Inc., 
San Diego, CA). SNP genotypes were scored 
using Illumina BeadStudio software (v3.3.4). 
Quality control was performed on the genotypic 
data of the separate countries. SNP were 
included in the dataset when the following 
criteria were met: 1) the minor allele frequency 
(MAF) was > 1% in each country; 2) the 
percentage of missing genotypes for a SNP 
across all samples was <5%; 3) the Gen Train 
score (statistical score for accuracy of clustering) 
was > 0.55 and the Gen Call score (statistical 
score for genotyping accuracy) was > 0.20; and 
4) the SNP did not deviate from Hardy Weinberg 
equilibrium (Hardy Weinberg χ2 values < 600). 
A SNP that failed a criterion in at least one 
country was discarded from the GWAS. 
Furthermore, animals with SNP call-rates <95% 
were removed from the dataset (n=70). A total of 
37,590 SNP  were retained and used for analyses.  
  
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217 
 
Pedigree data and SNP information were 
compared to check for inconsistencies in 
pedigree of cows using the methodology outlined 
by Calus et al. (2011). 
 
In total 696 animals from LR, 577 from 
MPK, 243 from SLU and 452 from SAC were 
genotyped as part of the RobustMilk project. In 
addition SAC made available genotypes of 318 
animals that were genotyped as part of other 
projects. 
 
Further, 58 bulls, which were sires of the 
cows in our data, were genotyped. MPK made 
available genotypes of an additional 154 bulls. In 
total genotypes of 2286 cows and 212 bulls were 
used for analyses in the RobustMilk project. 
 
 
Phenotypes 
 
The present studies used phenotypic data of first 
lactation Holstein cows. Many phenotypes are 
available and were analysed. In the present paper 
we will describe the GWAS for a limited number 
of traits typical for the RobustMilk project. The 
three examples chosen are somatic cell count, 
start of luteal activity based on hormonal profiles 
and feed intake.  
 
Somatic Cell Count. Wijga et al. (2011) 
analysed lactation-average SCC and test-day 
SCC standard deviation which were calculated 
for each cow based on test-day records. The 
standard deviation of test-day SCC aims to 
capture fluctuations in SCC associated with 
infection. The number of test-day records per 
cow on the experimental herds ranged between 
ten and 52 with an average of 31 test-days.  
 
Fertility Berry et al. (2011) analysed fertility 
traits. The traditional fertility traits were days 
from calving to first observed heat, days from 
calving to first service, calving interval, number 
of services, and pregnancy rate to first service. 
Besides traditional fertility traits information on 
the interval from calving to first luteal activity 
(CLA) based on hormonal profiles was available. 
CLA was defined as the number of days from 
calving to the first occurrence of two consecutive 
test-day records with a milk progesterone 
concentration of ≥3 ng/ml. 
 
 
Feed utilisation Veerkamp et al. (2011) 
analyzed several traits related to feed utilization. 
Records were available for live weight, body 
condition score and dry matter intake. The 
averages for the predicted values for week 3 – 15 
in lactation were used in the GWAS. Only 
animals with ten or more observations in this 
period were included in the analysis. 
 
 
Results and Discussion 
 
We will briefly highlight the main results of the 
genome-wide association studies that were 
conducted. A detailed description of the results 
can be found in Wijga et al. (2011) on somatic 
cell count traits, Berry et al. (2011) on fertility 
traits and Veerkamp et al. (2011) on feed 
utilization traits.  
 
Somatic Cell Count Two SNP were found to be 
significantly associated with lactation-average 
SCC and one SNP with the standard deviation of 
SCC. One SNP on BTA18 was associated with 
both lactation-average SCC and the standard 
deviation of SCC. A SNP on BTA4 was uniquely 
associated with the lactation-average SCC. In 
total 98 cows in the data set had a case of clinical 
mastitis during their first lactation. The SNP with 
significant effects on the lactation-average SCC 
or the standard deviation of SCC were not 
significantly associated with clinical mastitis. 
 
Relatively few significantly associated SNP 
were detected, suggesting that both somatic cell 
count traits are controlled by many loci, each 
with a relatively small effect. Different SNP 
contributing to lactation-average SCC and the 
standard deviation of SCC could reflect 
differences in genetic regulation of both traits 
where lactation-average SCC may refer to base-
line somatic cell count during lactation and 
standard deviation of SCC may reflect immune 
reactivity to infection. 
 
The number of test-day records per cow on 
the experimental herds ranged between ten and 
52 with an average of 31 test-days. These 
numbers are much higher as compared to 
routinely collected data on commercial herds 
where SCC usually are recorded monthly. 
Monthly SCC  recordings have lower probability  
 
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218 
 
of detecting infections of short duration than 
intensive recording as practiced on experimental 
herds.  
 
Fertility For traditional fertility traits (days from 
calving to first observed heat, days from calving 
to first service, calving interval, number of 
services, and pregnancy rate to first service) only 
weakly significant SNP were detected. Much 
stronger evidence for the presence of QTL was 
detected for CLA: a SNP on BTA 2 explained 
0.51% of the genetic variance in CLA while a 
SNP on BTA 21 explained 0.35% of the genetic 
variance in CLA. 
 
Traditional fertility measures based on 
calving and insemination dates are heavily 
affected by decisions made by the farmer and 
therefore are not very accurate indicators for 
fertility. The interval from calving to first luteal 
activity (CLA) based on hormonal profiles has 
been suggested as a more accurate and therefore 
preferable measure for fertility. However, routine 
measures of CLA based on hormonal profiles are 
usually not available for reasons of cost and 
labour but were available on data collected on 
experimental herds. The GWAS results clearly 
illustrate the benefits of having an accurately 
measured phenotype and the potential benefits of 
physiological traits whose genetic control may be 
less complex than high level phenotypes.  
 
Feed utilisation The GWAS for feed utilization 
traits revealed several significant chromosomal 
regions. Highly significant effects were found on 
BTA4 for body condition scores, on BTA7, 
BTA13 and BTA18 for live weight and on 
BTA27 for dry matter intake. The percentage of 
the total genetic variance of most significant 
SNPs ranged from 0.5 to 0.6% indicating that the 
magnitudes of the effects were relatively small. 
Costs of feed are a major component of the 
variable costs of milk production. Feed intake 
and feed efficiency are therefore traits which 
should be taken into account in breeding 
decisions. Recently, the importance of feed 
efficiency has received renewed interest in order 
to reduce the environmental impact of dairy 
production. However, in practical dairy cattle 
breeding there is no direct selection for feed 
intake or feed efficiency. This is a consequence 
of the practical difficulties of measuring 
individual feed intake in dairy cows. The 
detection of genes regulating feed intake or the 
development of genomic selection tools could 
bring selection for feed intake based on genomic 
information within reach.  
 
 
Conclusion 
 
The success of genome-wide association studies 
is a function of, amongst others, the heritability 
of the trait under investigation and the number of 
phenotypic records on that trait. For traits which 
are expensive and difficult to measure the 
number of available records is a limiting factor. 
The present study is one of the first studies to 
show the potential of combining detailed 
phenotypic and genotypic data from research 
herds located in different countries, thereby 
increasing the power of the study.  
 
 
Acknowledgments 
 
This research receives a financial support from 
the European Commission, Directorate-General 
for Agriculture and Rural Development, under 
Grand Agreement 211708 and form the 
Commission of the European Communities, FP7, 
KBBE-2007-1. This paper does not necessarily 
reflect the view of these institutions and in no 
way anticipates the Commission’s future policy 
in this area. 
 
 
References 
 
Calus, M.P.L., Mulder, H.A. & Bastiaansen, 
J.W.M. 2011 Identification of Mendelian 
inconsistencies between SNP and pedigree 
information of sibs. Genetics Selection 
Evolution In press. 
Berry, D.P., Bastiaansen, J.W.M., Veerkamp, 
R.F., Wijga, S., Wall, E., Strandberg, E. & 
Calus, M.P.L. 2011 Genome-wide 
associations for fertility traits in Holstein-
Friesian dairy cows using data from 
experimental research herds in four European 
countries. Submitted to Animal. 
Bennett, S.N., Caporaso, N., Fitzpatrick, A.L., 
Agrawal, A., Barnes, K., Boyd, H.A., 
Cornelis, M.C., Hansel, N.N., Heiss, G., Heit, 
J.A., Kang, J.H., Kittner, S.J., Kraft, P., 
Lowe, W., Marazita, M.L., Monroe, K.R., 
Pasquale, L.R., Ramos, E.M., van Dam, 
R.M., Udren, J. & Williams, K. 2011. 
GENEVA Consortium. Phenotype 
INTERBULL BULLETIN NO. 44. Stavanger, Norway, August 26 - 29, 2011 
 
219 
 
harmonization and cross-study collaboration 
in GWAS consortia: the GENEVA 
experience, 2011. Genet Epidemiol. 35, 159-
73. 
Veerkamp, R.F., Coffey, M., Berry, D.P., de 
Haas, Y., Strandberg, E., Bovenhuis, H., 
Calus, M.P.L. & Wall, E. 2011. Genome-
wide associations for feed utilisation complex 
in Holstein-Friesian dairy cows using data 
from experimental research herds in four 
European countries. In preparation. 
Wijga, S.J., Bastiaansen, W.M., Wall, E., 
Strandberg, E., de Haas, Y., Giblin, L. & 
Bovenhuis, H. 2011 Genomic Associations 
with Somatic Cell Score in First Lactation 
Holstein Cows. Submitted to JDS 
 
 
 
 


GWAS for Robustness Traits

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