The SNP ARS-BFGL-NGS-109285 at 57,589,121 bp (rs109478645; UMD 3.1 assembly) has been reported to have large effects on body shape & size, dystocia, longevity, and lifetime economic merit (Cole et al., 2009). This region is similar to the human sialic acid binding Ig-like lectin 6-like (Siglec-6) gene, which may be involved in leptin signaling. Sequence data from 11 US Holstein bulls were used to identify putative causal mutations associated with calving and conformation traits on Bos taurus autosome (BTA) 18.

1. P1097: Candidate causative mutation on BTA18 associated with
calving and conformation traits in Holstein bulls
J.B. Cole,1 J.L. Hutchison,1 D.J. Null,1 P.M. VanRaden,1 G. Liu,2 S.G. Schroeder,2 T.S. Sonstegard,2
C.P. Van Tassell,2 and D.M. Bickhart1
1Animal Improvement Programs and 2Bovine Functional Genomics Laboratories, Agricultural Research
Service, USDA, Beltsville, MD
Introduction
The SNP ARS-BFGL-NGS-109285 at
57,589,121 bp (rs109478645; UMD
3.1 assembly) has been reported to
have large effects on body shape &
size, dystocia, longevity, and lifetime
economic merit (Cole et al., 2009).
This region is similar to the human
sialic acid binding Ig-like lectin 6-like
(Siglec-6) gene, which may be
involved in leptin signaling. Sequence
data from 11 US Holstein bulls were
used to identify putative causal
mutations associated with calving and
conformation traits on Bos taurus
autosome (BTA) 18.
References
Cole et al. 2009. Distribution and location
of genetic effects for dairy traits. J Dairy
Sci. 92:2931–2946.
Hach et al. 2010. mrsFAST: a cache-
oblivious algorithm for short-read
mapping. Nat Meth. 7:576–577.
Hahne et al. 2013. Gviz: Plotting data
and annotation information along
genomic coordinates. R package version
1.6.0.
Hormozdiari et al. 2010. Next-generation
VariationHunter: combinatorial algorithms
for transposon insertion discovery.
Bioinformatics 26:i350–i357.
Sequence coverage on the Illumina
HiSeq2000 (Illumina, Inc., San Diego,
CA) for all bulls ranged from
approximately 7X to 35X coverage
(Table 1). Tandem duplications,
insertions and deletions were detected
using paired-end read alignments and
split-read mapping.
One duplication CNV and two different
tandem duplication events were
detected within the gene (Figure 2).
Predicted tandem duplications present
in the carrier animals suggest that the
portions of two exons and a connecting
intron within the Ig-like protein domains
of the Siglec-6 gene may have been
duplicated. Some heterozygotes with
desirable SCE also have deletions near
the N-terminal end of the protein.
Results & Discussion
Willow-Farm
Rockman Ivanhoe
Aa, SCE: 6
Cass-River Select
Delegate
Aa, SCE: 15
Wedgwood Laramie
aa, SCE: 15
Unrelated carriers
of largest haplotype
affecting SCE:
Related carriers and non-carriers of the
haplotype with the largest effect on SCE:
Pawnee Farm Arlinda Chief
AA, SCE: 7MGS
Glendell Arlinda
Chief
AA, SCE: 8
Arlinda Rotate
AA, SCE: 8
Sweet-Haven Tradition
Aa, SCE: 10
MGS
Arlinda Melwood
Aa, SCE: 8
Juniper Rotate Jed
Aa, SCE: 15
CMV Mica
Aa, SCE: 14
Lystel Leduc
Aa, SCE: 18
Figure 1. Sequencing design.
MGS = maternal grandsire.
SCE = sire calving ease, a measure of dystocia
(calving difficulty). Lower values are desirable.
A pedigree- and haplotype-based
scheme was used to select 5 carrier
and 3 non-carrier bulls from the same
family, as well as 3 additional, unrelated
carrier bulls (Figure 1). Animals were
selected based on their predicted
transmitting ability for sire calving ease,
a trait of economic importance
associated with dystocia (difficult
births).
Genomic DNA was extracted from
frozen semen purchased commercially
or obtained from the Cooperative Dairy
DNA Repository (Beltsville, MD).
Paired-end libraries were created using
the recommended protocol for the
Illumina Tru-seq DNA sample prep kit.
Samples were sequenced to 20X target
coverage in 100 x 100 SBS reactions
on the HiSeq 2000 HiSeq2000
(Illumina, Inc., San Diego, CA).
Sequence reads were aligned to the
UMD3.1 reference genome using
MrsFAST (Hach et al., 2010) and
discordantly mapping reads were
identified with custom Java programs. A
heavily modified version of
VariationHunter (Hormozdiari et al.,
2010) was used to identify variants
based on read orientation and
alignment distance within clusters of
read pairs that aligned in the same
location. Figures 1 and 2 were
constructed using the Bioconductor
package Gviz 1.60 (Hahne et al.,
2013).
Materials and Methods
Acknowledgments
Bickhart, Cole, Hutchison, Null,
VanRaden, and Wiggans were supported
by appropriated project 1265-31000-096-
00. Liu, Schroeder, Sonstegard, and Van
Tassell were supported by appropriated
project 1245-31000-104-00.
Figure 2. Structural variations on
BTA 18 for Arlinda Chief (top) and
Rockman Ivanhoe (bottom).
57.49 mb
57.5 mb
57.51 mb
57.52 mb
57.53 mb
57.54 mb
57.55 mb
57.56 mb
57.57 mb
57.58 mb
57.59 mb
ensGene
ENSBTAT00000006050
ENSBTAT00000012346
ENSBTAT00000016644 ENSBTAT00000031802
ENSBTAT00000052760ENSBTAT00000055031
refGene
NM_001077954 NM_001191347
DiscordantReads
500
1000
1500
2000
ReadDepth
57.49 mb
57.5 mb
57.51 mb
57.52 mb
57.53 mb
57.54 mb
57.55 mb
57.56 mb
57.57 mb
57.58 mb
57.59 mb
ensGene
ENSBTAT00000006050ENSBTAT00000012346
ENSBTAT00000016644
ENSBTAT00000031802
ENSBTAT00000052760
ENSBTAT00000055031
refGene
NM_001077954 NM_001191347
DiscordantReads
500
1000
1500
2000
2500
ReadDepth
Structural variants in and around the
Siglec-6 gene are associated with
differences in SCE. These results
demonstrate that sequence data can be
used to generate novel hypotheses
from quantitative studies. However,
higher-quality assemblies and improved
annotations are necessary in order to
better understand the functional basis
for observed QTL effects, particularly
those associated with complex
phenotypes.
Conclusions
Bull name Total reads Coverage
Chief 333,628,731 12.03
Arlinda Chief 981,726,824 35.41
Tradition 390,387,538 14.01
Rotate ~476,000,000 17.00
Melwood ~448,000,000 16.00
Jed 656,190,604 23.66
Mica 433,353,161 15.63
Leduc 767,440,677 27.68
Rockman Ivanhoe 195,769,690 7.06
Delegate 377,380,110 13.61
Laramie 371,477,172 13.39
Table 1. Sequencing metrics.