Use of Genome-wide Association Mapping to Identify Chromosomal Regions
Associated with Rectal Temperature During Heat Stress in Holstein Cattle
John B. Cole*,1, Serdal Dikmen2, Daniel J. Null1, and Peter J. Hansen3
1Animal
Improvement Programs Laboratory, Agricultural Research Service, USDA, Beltsville, MD; 2Department of Animal Science, Faculty of Veterinary Medicine, Uludag University, Bursa, Turkey; and
3Department of Animal Sciences, D.H. Barron Reproductive and Perinatal Biology Research Program, and Genetics Institute, University of Florida, Gainesville, FL 32611
Summary
Dairy cattle experiencing heat stress have
reduced production, fertility, and health
compared to non-heat stressed animals, and
dairy cattle in the southern US commonly are
heat-stressed for at least some of the year. The
objective of this study was to perform a genomewide association study (GWAS) for rectal
temperature (RT) during heat stress in lactating
Holstein cows to identify single nucleotide
polymorphisms (SNP) associated with genes
that have large effects on RT. The largest
proportion of SNP variance (0.07 to 0.44%) was
explained by markers flanking the region
between 28,877,547 and 28,907,154 bp on Bos
taurus autosome (BTA) 24. That region is flanked
by U1 (28,822,883 to 28,823,043 bp) and NCAD
(28,992,666 to 29,241,119 bp). In addition, the
SNP at 58,500,249 bp on BTA 16 explained 0.08%
and 0.11% of the SNP variance for 2- and 3-SNP
analyses, respectively. That contig includes
SNORA19, RFWD2, and SCARNA3. Other SNP
associaed with RT were located on BTA 16 (close
to CEP170 and PLD5), BTA 5 (near SLCO1C1 and
PDE3A), BTA 4 (near KBTBD2 and LSM5), and
BTA 26 (located in GOT1, a gene implicated in
protection from cellular stress). There do appear
to be QTL associated with RT in heat-stressed
dairy cattle, but the QTL explain relatively small
proportions of overall additive genetic variance.
These SNP could prove useful in genetic
selection and for identification of genes involved
in physiological responses to heat stress.
Materials and Methods
• Phenotypes collected on 9 Florida dairies:
• 1500 to 1700 h from June to September 2007
• 1400 to 1600 h from June to September in
2010, 2011 and 2012
• RT measured under shade and, generally,
cows were in head locks (free-stall barns) or
resting (tunnel-ventilation barns)
• Data collected from days in which the THI at
the time of collection was > 78.2
• This indicates that heat stress was sufficient
to cause hyperthermia
Materials and Methods (cont’d)
Table 1. The 20 loci with the largest
proportion of SNP variance explained
using 3-SNP sliding windows.
• 1,451 animals (107 cows and 1,344 bulls) had
available genotypes using the Illumina
BovineSNP50 BeadChip (Illumina, Inc., San
Diego, CA, USA).
SNP name
BTB-01646599
ARS-BFGL-NGS-41140
Hapmap58887-rs29013502
BTB-00638221
BTB-01485274
ARS-BFGL-NGS-71584
ARS-BFGL-NGS-23064
BTB-01267098
ARS-BFGL-NGS-89847
BTA-26221-no-rs
Hapmap46698-BTA-38760
ARS-BFGL-NGS-108847
ARS-BFGL-NGS-29516
ARS-BFGL-NGS-35716
ARS-BFGL-NGS-95833
ARS-BFGL-NGS-16848
BTA-27496-no-rs
BTB-01267080
ARS-BFGL-NGS-107395
ARS-BFGL-NGS-100006
• Animals and SNP with call rates < 0.90, SNP
with minor allele frequencies < 0.05,
monomorphic SNP, and animals with parentprogeny conflicts were dropped
• The final dataset included 39,759 SNP from
1,440 individuals
• A pedigree including 12,346 ancestors was
obtained from the National Dairy Database
(Beltsville, MD, USA)
• Single-step genomic BLUP (ssGBLUP) was
used to simultaneously estimate genomic
breeding values and allele substitution effects
•
•
•
•
Fixed effects were parity, year, stage of
lactation, location of cows, farm type,
technician, and farm. THI and milk yield
were included as covariates
Random effects were additive animal,
permanent environment, and random
residual error
Results were calculated using a Bayes A
model as implemented in the BLUPF90
program modified for genomic analyses.
GWAS for RT were conducted with
individual SNP effects, as well as moving
averages of 2, 3, 4, 5, and 10 consecutive
SNP, using the POSTGSF90 package
Key Results
• The 20 largest explanatory SNP for RT are
shown in Table 1. Allele substitution effects
are plotted in Figure 1 as the proportion of
variance explained.
• The largest proportion of variance was
explained by a region on BTA 24:
• The region is flanked by a U1 spliceosomal
RNA (U1) and a cadherin-2 (NCAD).
• U1 is involved in postranscriptional
modification and regulation of mRNA
length, which could be related to changes
in gene expression in cells exposed to
elevated temperature.
Chromosome
24
24
24
16
24
26
26
5
7
28
16
16
23
24
26
28
12
5
29
23
Location (bp) Variance explained (%)
28941584
0.284289
28975828
0.258319
28907154
0.244098
35272426
0.169289
28877547
0.153510
20290497
0.150088
20365711
0.145223
89545151
0.118979
2457750
0.115361
35345760
0.109708
35317388
0.107123
58500249
0.106275
14246801
0.103440
29013292
0.100621
37797893
0.098292
2924302
0.094916
2500836
0.092552
89512928
0.090345
47527067
0.089550
14215024
0.082668
1
• A SNP at 58,500,249 bp on BTA 16 is near
Conclusions
•
The QTL identified in this study may be
useful for genetic selection for
thermotolerance, although additional data
are needed to compute high-reliability
genetic predictions.
•
Several candidate genes for regulation of RT
were identified, and one or more of them
may play an important role in physiological
adaptation to heat stress.
•
One candidate gene, SLC01C1, which is
involved in regulation of metabolic rate
through transport of thyroxine, may play a
regulatory role in RT.
•
More commonly, candidate genes play roles
important for stabilizing cellular function
during stress. Among these are GOT1,
which synthesizes the cytorotective
compound sulphur dioxide, genes involved
in protein ubiquitination (KBTBD2 and
RFWD12), and genes involved in RNA
metabolism (LSM5, SCARNA3, SNORA19,
and U1).
SNORA19, RFWD2, and SCARNA3.
• SNORA19 is involved in initiation of translation.
• SCARNA3 encodes a small nucleolar RNA
similar to SNORA19.
• RFWD12 encodes a protein ligase, that selects
proteins for proteasomal degradation.
• A consensus region of BTA 5 at ~89,500,000 bp is
flanked by solute carrier organic anion
transporter family member 1C1 (SLCO1C1) and a
phosphodiesterase (PDE3A).
Acknowledgments
•
• Human SLCO1C1 mediates the Na+independent high-affinity transport of thyroxine
and reverse triiodothyronine, and may be
involved in the mechanism which depresses
plasma thyroxine concentrations in heatstressed dairy cows.
Figure 1. Proportion of marker variance •
explained (%) by 3-SNP sliding windows
The authors thank the following dairies for
providing access to cows and records:
Alliance Dairy (Trenton, Florida), Hilltop
Dairy (Trenton, Florida), Larson Dairy
(Okeechobee, Florida), McArthur Dairy
(Okeechobee, Florida), North Florida
Holsteins (Bell, Florida) and the University
of Florida Dairy Unit (Hague, Florida).
J.B. Cole and D.J. Null were supported by
appropriated project 1265-31000-096-00.
References
Dikmen, S., J.B. Cole, D.J. Null, and P.J.
Hansen. 2013. Genome-wide association
mapping for identification of quantitative trait
loci for rectal temperature during heat stress
in Holstein cattle. PLoS ONE. 8(7):e69202.