Download Genome-wide association study of superovulatory response traits in

Genome-wide association study of superovulatory response traits in
Canadian Holsteins (preliminary study)
C. Jaton12, M. Sargolzaei13, M.K. Abo-Ismail14, F. Miglior15, C. A. Price6, A. Koeck1 and F. S.
Schenkel1
1
Centre for Genetic Improvement of Livestock (CGIL), University of Guelph, Guelph, Ontario, Canada, N1G 2W1, 2Centre
d’insémination artificielle du Québec (Ciaq), Saint-Hyacinthe, Québec, Canada, J2S 7B8, 3Semex Alliance, Guelph, Ontario,
Canada, N1G 3Z2, 4Damanhour University, Egypt, 5Canadian Dairy Network (CDN), Guelph, Ontario, Canada, N1K 1E5,
6
Université de Montréal, Faculté de médecine vétérinaire, St-Hyacinthe, Québec, Canada, J2S 2M2
INTRODUCTION Superovulation and embryo transfer are frequently used in the Canadian dairy industry to produce
more offspring from elite donor cows. The technical aspect of superovulation in dairy cattle has been
described by many authors around the world, but the genetic and genomic aspect of this technique has
still to be discovered. Superovulatory response is moderately heritable in Holstein dairy cattle (Jaton
et al., 2015), so that it could be possible to genetically select donors that would produce more
embryos. Moreover, finding genes that impact the superovulatory response may also help with to
select of a donors that would respond well to superovulation.
To our knowledge, very few studies have performed a genome-wide association study (GWAS) in
dairy cattle for traits related to superovulatory response. One study performed a GWAS for fertility
traits such as fertilization and blastocyst rate of Holstein cows and found significant SNPs associated
with those traits (Huang et al., 2010). Another study done on Japanese black cattle identified a genetic
variant in the Glutamate Receptor AMPA 1 (GRIA1) gene that has an impact on the ovulation rate
(Sugimoto et al., 2010). This gene located on chromosome 7 of Bos Taurus. On the other hand, using
candidate gene approach, some studies looked at SNPs in specific genes and tried to find associations
with superovulatory response (Cory et al., 2012; Yang et al., 2010). One study performed in Canada
found a SNP in the Follicle-stimulating hormone receptor (FSHR) gene located on chromosome 11 to
identify good and bad donors (Cory et al., 2012). They concluded that this finding would need to be
confirmed in a larger population. Another study done in a Chinese Holstein population found similar
results for FSHR gene (Yang et al., 2010). This gene has been reported to play a role in the mediation
of FSH signal transduction and follicle maturation (Cory et al., 2012). Also, a study demonstrated that
the IGF1R (insulin-like growth factor 1 receptor) gene, which plays a role in ovulation, in the preimplantation embryo development and in pregnancy rate, could be a potential marker to select
superovulated donors (Yang et al., 2013).
The main objectives of this study were 1) to perform a genome-wide association study in order to find
SNPs associated with superovulatory response traits, and 2) to identify candidate genes corresponding
to these associations and retrieve the biological pathways and mechanisms linked to superovulation
and embryo transfer.
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MATERIAL AND METHODS Data Holstein Canada (www.holstein.ca) provided a data set containing records of all donors that had been
superovulated over the last 35 years. After editing, 137,446 records from 54,463 donors were
considered for the analysis, with one record corresponding to one superovulatory protocol (Jaton et al.,
2015).
Traits. The two superovulatory response traits that were analyzed from the data set provided were the
total number of embryos per flush and the number of viable embryos per flush. The difference
between them is that the number of viable embryos does not include degenerated or dead embryos
recovered from a flush.
Pedigree. An animal pedigree file containing 197,246 animals was generated by tracing the pedigrees
of the donors with records 7 generations back.
EBV. Genetic parameters and estimated breeding values (EBV) for both superovulatory response traits
were already estimated from univariate analyses (Jaton et al., 2015). Breeding values from logarithmic
transformation were considered for the GWAS. Overall, 57,976 donors and their sires had EBVs
available for both traits.
EBVs were de-regressed using VanRaden’s simplified method for de-regression (VanRaden and
Sullivan, 2010). Animals with a reliability of de-regressed EBV lower than 10% were not considered
for further analysis.
Genotypes and imputation. Genotypes were available for 7,925 donors and sires that had deregressed EBVs. Of that number, 5,582 animals were genotyped with at least a 50K SNP panel and all
those were imputed to high density genotypes using FImpute software (Sargolzaei et al., 2014). After
accounting for the reliability threshold, 4,589 (803 M, 3,486 F) and 4,172 (758 M, 3,414 F)
individuals were considered for further analyses of the total number of embryos and the number of
viable embryos, respectively.
Genome-­‐wide association study Quality control. The quality control measures that were applied included the exclusion of SNPs
having a minor allele frequency lower than 1%, a call rate lower than 90%, an excess of
heterozygosity higher than 15% and a Mendelian error larger than 5%. The SNPs that were out of
Hardy-Weinberg equilibrium with very low probability (1 x 10-8) and the individuals with a call rate
lower than 90% were also excluded. Parentage verification was performed in snp1101. Overall,
657,932 SNPs on 29 autosomal chromosomes were considered for the association analysis.
Method. Univariate single SNP generalized mixed linear model (SSR) was used to perform the
GWAS using snp1101 software (Mehdi Sargolzaei, personal communication). Considering that there
was a large variation in the reliabilities of the de-regressed EBVs, SSR method was chosen because it
weights the reliabilities. In order to account for population structure, the genomic relationship matrix
was built in snp1101 using VanRaden’s method.
Correction for multiple-­‐testing. The false discovery rate (FDR) at genome-wise level was used to
correct for multiple testing. SNPs were considered to be significantly associated with the traits if they
were above the 5% FDR significance level.
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Enrichment analysis Significant SNP at 5% FDR were mapped to the nearby genes using NGS-SNP (Grant et al., 2011).
Genes located in a distance of 100,000 base pairs (bp) on each side of the SNPs were considered for
the enrichment analysis. Then, the gene list was submitted to the Database for Annotation,
Visualization, and Integrated Discovery (DAVID) 6.7 tool to perform the enrichment analysis
(Huang et al., 2009a, 2009b). Biological processes and pathways were retrieved for both
superovulatory response traits.
RESULTS AND DISCUSSION Genome-­‐wide association study After accounting for quality control criteria, 595,074 and 594,955 SNPs were considered for the total
number of embryos and the number of viable embryos, respectively. The Quantile-Quantile (QQ) plots
are presented for both traits in figure 1 a and b.
After accounting for multiple comparisons, a total of 57 and 47 SNPs were significantly associated at
5% FDR with the total number of embryos and the number of viable embryos, respectively. Figures 2
and 3 show the distribution of the significant SNPs for superovulatory response traits across the 29
chromosomes. For both traits there was a major peak on chromosome 11 and the majority of the
significant SNPs were located on that chromosome. For the total number of embryos, 81% of the
significant SNPs (46/57) were located on chromosome 11. The other significant SNPs were located
on chromosomes 2 (4/57), 22 (2/57), 25 (1/57) and 29 (4/57). For the number of viable embryos, 46
out of 47 significant SNPs were located on chromosome 11 whereas the other significant SNP was
located on chromosome 9.
Thirty-three significant SNPs on chromosome 11 were having pleotropic effect on the total number of
embryos and the number of viable embryos. This makes sense considering that the two superovulatory
response traits considered in this study are very similar.
Gene Identification and Enrichment analysis Total number of embryos. Table 1 lists the identified genes within 100k base of the 10 most
significant SNPs for the total number of embryos. The most significant SNP (BovineHD1100027188)
was located nearby (60,957 bases) prostaglandin-endoperoxide synthase 1 (PTGS1) gene. The PTGS1
protein coding gene is responsible for the conversion of arachidonic acid into PGH2, which is a
precursor of different form of prostaglandins such as PGE2 and PGF2α (Arosh, 2002). Prostaglandins
are, among other things, responsible for the ovulation of oocyte (Ball and Peters, 2004). All the other
genes nearby this SNP were referenced as olfactory factor 1L8 protein coding gene (NCBI). We don’t
know yet how this gene could be linked to superovulatory response.
Also, several potential genes were found nearby significant SNPs. For example, NADH
dehydrogenase (ubiquinone) 1 alpha subcomplex (NDUAF8) was reported to transfer electrons with a
high redox potential from NADH to ubiquinone and its RNA being mostly expressed in human heart,
skeletal muscle, and fetal heart (Triepels et al., 1998). The study identified tubulin tyrosine ligase-like
family, member 11 (TTLL11) gene that is involved in the polyglutamylation of microtubules, which
“are major constituents of the cytoskeleton” (van Dijk et al., 2007). Furthermore, this study identified
LIM homeobox protein 6 (LHX6). A study performed on mouse demonstrated that LHX6 plays “an
important role in the maturation of cortical interneurons and the formation of inhibitory circuits in the
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mammalian cortex” (Neves et al., 2013). RNA binding motif protein 18 (RMB18) is a protein coding
gene. RNA-binding proteins have been reported to be associated with the building of the cerebral
cortex during the embryonic development (Pilaz and Silver, 2015). The DENN/MADD domain
containing 1A (DENND1A) regulates Rab GTPases, which is, among other things, required for
GnRH-induced gonadotropin release (Welt et al., 2012). This protein was reported to be highly present
in human brain and testis (Eriksen et al., 2013). In humans, mitochondrial ribosome recycling factor
(MRRF) is important for cell viability. A study confirmed that the depletion of MRRF in human cell
resulted in reduced growth rate and cell death (Rorbach et al., 2008). The biological functions of
MORN repeat containing 5 (MORN5) are still unclear.
The study identified several prospective biological mechanisms associated with total number of
embryos including one significant: G-protein coupled receptor protein signaling pathway
(GO:0007186). Some of the other mechanisms found were: in utero embryonic development
(GO:0001701), ovulation cycle process (GO:0022602), embryonic development (GO:0009790),
blastocyst development (GO:0001824), blastocyst growth (GO:0001832), prostaglandin
biosynthetic process (GO:0001516), embryonic development ending in birth or egg hatching
(GO:0009792), prostaglandin metabolic process (GO:0006693), luteinisation (GO:0001553) and
ovulation cycle (GO:0042698).
For total number of embryos, a total of 55 genes were within or nearby 100K base from the significant
SNPs. Only 49 of those genes were submitted to DAVID software for the enrichment analysis,
because 6 of them were novel genes for which no information was available. Table 2 lists all
biological pathways that were found through Kyoto Encyclopedia of Genes and Genomes (KEGG).
Only the olfactory transduction pathway was significantly enriched with 7 genes. For now, we don’t
know how this pathway is related to superovulatory response, more research is needed. The other
pathways that were found for the genes associated with the total number of embryos were not
significantly enriched. Wnt signaling pathway was reported to regulate “crucial aspects of cell fate
determination, cell migration, cell polarity, neural patterning and organogenesis during embryonic
development” (Komiya and Habas, 2008). Parkinson’s disease and Huntington’s disease pathway
are both related to a neurodegenerative disorder that affects dopaminergic and medium spiny striatal
neurons, respectively (KEGG database). Alzheimer’s disease pathway corresponds to a chronic
disorder that also affects neurons (KEGG database). We haven’t been able to understand the how
those three pathways relate to superovulatory response yet. The Oxidative phosphorylation pathway
is involved in the energy metabolism. Basically, the oxidation of NADH liberates energy that can then
be used to produce ATP (Nath and Villadsen, 2015). Finally, Arachidonic acid metabolism pathway
plays a role in the lipid metabolism. As stated earlier, the arachidonic acid is transformed into many
different products such as prostaglandins, which are hormones that play a role in ovulation (Arosh,
2002).
Thus, the study provided a list of potential genes that are involved in biological pathways related to the
total number of embryos.
CONCLUSION This first genome-wide association study for superovulatory response in Canadian Holstein cattle
found significant SNPs associated with the traits of interest. The SNPs were mainly located on
chromosome 11 for both the total number of embryos and the number of viable embryos. These
results will need to be validated in an independent population to be confirmed.
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For now, we haven’t identified a candidate gene for superovulatory response that has already been
reported in another study; maybe the next steps will be more conclusive.
NEXT STEPS The next steps will be to continue the enrichment analysis for the total number of embryos and to
perform the same analysis for the number of viable embryos. More research is needed to understand
how the different pathways that were found are related to superovulatory response. We will then try to
see if the significant genes for the total number of embryos are the same as for the number of viable
embryos. We can then also consider SNPs that are above the 10% FDR significant threshold instead of
5% to see what this would add to results.
ACKNOWLEDGMENTS The authors are thankful to Holstein Canada for its contribution in providing the data. This study was
funded by CIAQ (St-Hyacinthe, Québec, Canada), the Canadian Dairy Network (Guelph, Ontario,
Canada) and the Natural Sciences and Engineering Research Council of Canada (Ottawa, Ontario,
Canada).
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TABLES Table 1 –The Most significant SNP and their nearby genes for the total of embryos
BTA
SNP
Location
(bp)
P-Value
11
BovineHD1100027188
93306002
2.92E-08
11
11
11
11
11
11
BovineHD1100027045
BovineHD1100027046
BovineHD1100027047
BovineHD1100027048
BovineHD1100027049
BovineHD1100027627
92945507
92946989
92950202
92950950
92952140
94849392
5.16E-08
5.16E-08
5.16E-08
5.16E-08
5.16E-08
5.44E-08
11
BovineHD1100027073
93034168
1.01E-07
11
11
BovineHD4100009144
BovineHD1100027064
92991291
92993865
2.99E-07
2.99E-07
Entrez gene name
LOC100301469, LOC515482, LOC787071,
LOC509073, LOC508785, LOC787415,
PTGS1, LOC615170
TTLL11, NDUFA8, MORN5
TTLL11, NDUFA8, MORN5
TTLL11, NDUFA8, MORN5
TTLL11, NDUFA8, MORN5
TTLL11, NDUFA8, MORN5
DENND1A
NDUFA8, LHX6, RBM18, MRRF,
MORN5
NDUFA8, MORN5, LHX6, TTLL11
NDUFA8, MORN5, LHX6, TTLL11
Table 2 – Biological pathways associated with the total number of embryos in Holstein Cattle
Pathway
Olfactory transduction
Wnt signaling pathway
Parkinson's disease
Alzheimer's disease
Oxidative phosphorylation
Arachidonic acid metabolism
Huntington's disease
*
Count of Genes
P-value
7
1
1
1
1
1
1
1.12E-04*
1
1
1
1
1
1
The pathway significantly enriched at 6% FDR
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FIGURES Figure 1 - QQ plot for a) total number of embryos and b) number of viable embryos
a)
b)
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Figure 2 – Manhattan plot for total number of embryos
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Figure 3 – Manhattan plot for total number of embryos
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