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Arch. Anim. Breed., 60, 357–362, 2017
https://doi.org/10.5194/aab-60-357-2017
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the Creative Commons Attribution 3.0 License.
Open Access
Archives Animal Breeding
A combined genotype of three SNPs in the bovine PPARD
gene is related to growth performance in Chinese cattle
Jieping Huang1,2, Qiuzhi Zheng1, Shuzhe Wang1, Qiongqiong Zhang1, Lijun Jiang1,2, Ruijie Hao1,
Fen Li1,2, and Yun Ma1,2
1College of Life Sciences, Xinyang Normal University, Xinyang, Henan, China
2Institute for Conservation and Utilization of Agro-Bioresources in Dabie Mountains, Xinyang, Henan, China
Correspondence to: Yun Ma (mayun_666@126.com)
Received: 26 May 2017 – Accepted: 28 August 2017 – Published: 6 October 2017
Abstract. PPARD is involved in multiple biological processes, especially for those associated with energy
metabolism. PPARD regulates lipid metabolism through up-regulate expression of genes associating with adipo-
genesis. This makes PPARD a significant candidate gene for production traits of livestock animals. Association
studies between PPARD polymorphisms and production traits have been reported in pigs but are limited for other
animals, including cattle. Here, we investigated the expression profile and polymorphism of bovine PPARD as
well as their association with growth traits in Chinese cattle. Our results showed that the highest expression
of PPARD was detected in kidney, following by adipose, which is consistent with its involvement in energy
metabolism. Three SNPs of PPARD were detected and used to undergo selection pressure according the result
of Hardy–Weinberg equilibrium analysis (P< 0.05). Moreover, all of these SNPs showed moderate diversity
(0.25 <PIC <0.5), indicating their relatively high selection potential. Association analysis suggested that in-
dividuals with the GAAGTT combined genotype of three SNPs detected showed optimal values in all of the
growth traits analyzed. These results revealed that the GAAGTT combined genotype of three SNPs detected
in the bovine PPARD gene was a significant potential genetic marker for marker-assisted selection in Chinese
cattle. However, this should be further verified in larger populations before being applied to breeding.
1 Introduction
Peroxisome-proliferator-activated receptors (PPARs) are a
group of transcription factors belonging to the nuclear hor-
mone receptor superfamily (Evans et al., 2004). Many stud-
ies have revealed PPARs take part in numerous biological
processes, including lipid metabolism, the insulin signaling
pathway, glucose metabolism, and adipocyte differentiation
(Youssef and Badr, 2013). To date, three subtypes of PPARs
have been discovered: PPARA,PPARD, and PPARG. Among
these, PPARD is widely expressed in various tissues, includ-
ing kidney, liver, heart, intestine, and adipose (Abbott, 2009).
PPARD regulates lipid metabolism through up-regulate ex-
pression of genes involved in the adipogenesis process (Ved-
hachalam et al., 2007). Recently, studies have suggested that
PPARD is essential for adipogenesis as well (Garbacz et al.,
2015; Barroso et al., 2015; Palomer et al., 2016).
Genetic variation in PPARD is proved to be associated
with human diseases. The PPARD rs2016520 polymorphism
was reported to affect repaglinide response in Han Chinese
patients with type 2 diabetes mellitus (Song et al., 2015).
Furthermore, this mutation was shown to be associated with
brain diseases (Huang et al., 2015) and colorectal cancer
(Rosalesreynoso et al., 2017). For its vital role in various
biological processes, PPARD is a potential gene affecting
production traits of livestock animals. Polymorphisms of
PPARD were shown to affect ear size (Ren et al., 2011) and
litter size (Spötter et al., 2010) in pigs. Recently, functional
SNPs in the 50regulatory region of the porcine PPARD gene
have been reported to be significantly associated with fat
deposition traits (Zhang et al., 2015). However, association
studies between PPARD and production traits in other ani-
mals are limited, including cattle.
Published by Copernicus Publications on behalf of the Leibniz Institute for Farm Animal Biology.
358 J. Huang et al.: A combined genotype of three SNPs
Marker-assisted selection (MAS) has been widely used as
a breeding strategy in livestock (Margawati, 2012). To detect
functional SNPs of PPARD for MAS in cattle, we (i) ana-
lyzed the expression profile of PPARD in different tissues,
(ii) detected SNPs in the bovine PPARD gene by direct se-
quencing using 514 Chinese cattle, and (iii) assessed the re-
lationship between detected SNPs and growth traits in partial
cattle.
2 Material and methods
2.1 Samples
Samples used in this study were shown in a previous study
(Huang et al., 2017). Briefly, seven tissues were collected
at the slaughter house for reverse transcription polymerase
chain reaction (RT-PCR), including heart, liver, spleen, lung,
kidney, muscle, and adipose of three Jiaxian cattle (bullock,
30 months). A total of 514 individuals from six Chinese cat-
tle breeds – including 141 Jiaxian cattle, 139 Nanyang cat-
tle, 114 Luxi cattle, 30 Qinchuan cattle, 30 Bohai, cattle
and 60 Gaoyuan yak – were used for SNP genotyping. Birth
weight and six growth traits (body weight, body height, body
length, heart girth, hip width, and average daily gain) of Ji-
axian and Nanyang cattle at 6, 12, 18, and 24 months as well
as nine traits (body height, body length, heart girth, abdom-
inal circumference, hip width, sciatic width, height at hip
cross, body weight, and beef performance index) at around
28–30 months of age in 300 Henan cattle (100 Jiaxian, 100
Nanyang, and 100 Luxi) were recorded for association anal-
ysis.
2.2 Expression analysis of PPARD
In order to understand the potential biological effect of
PPARD on cattle, expression levels of PPARD in seven tis-
sues were investigated by RT-PCR. Details of the method are
shown in a previous study (Huang et al., 2017). Total RNA
was reversely transcribed into cDNA using a PrimeScript-
sRT reagent kit with gDNA Eraser (TaKaRa, Japan). RT-PCR
was performed using SYBR Green I with two-step reactions.
Primers of PPARD (NM_001083636.1) and reference genes
(TUBA1A, NM_001166505.1; β-actin, NM_173979.3) for
RT-PCR are shown in Table S1 (Supplement). The relative
expression level of each tissue was presented as mean ±SD.
2.3 SNP detection and genotyping
In order to investigate polymorphism of PPARD
(AC_000180.1) in Chinese cattle, nine pairs of primers
covering CDS and partial upstream regions were synthesized
(Table S1). The methods for SNP detection and genotyping
were as in a previous study (Huang et al., 2017). Pooled
DNA samples were used as a PCR template for SNP de-
tection. For SNPs detected (Table 1), three pairs of specific
Figure 1. Tissue distribution of bovine PPARD mRNA assessed by
RT-PCR. Values shown in this figure are averages of three indepen-
dent experiments. Error bars represent SD (n=3) of relative mRNA
levels. Expression data were normalized using geometric mean of
mRNA levels for two control genes (TUBA1A and β-actin).
Figure 2. Schematic characteristic of SNPs identified in bovine
PPARD and genotyping. From top to bottom: structure of bovine
PPARD, mutant peaks of sequencing, details of SNPs identified, and
electrophoretogram of genotyping.
primers were designed (Table 2). The traditional PCR-RFLP
method was used for SNP genotyping in 514 Chinese cattle
from six breeds. It should be noted that PCR production of
PPARD-MluI primers contained two recognition sites of
MluI, one of which was native and the other was introduced
from primers for genotyping.
2.4 Statistical analysis
The genetic characteristics of each mutation were investi-
gated after genotyping, including allele frequencies, Hardy–
Weinberg equilibrium (HWE), heterozygosity (He), effective
allele numbers (Ne), and polymorphism information con-
tent (PIC). To evaluate the potential relationship between the
PPARD gene and development of cattle, an association study
was performed based on the genotyping results and growth
traits in Nanyang, Jiaxian, and Luxi cattle. Significant analy-
sis was performed by SPSS 19.0 using general linear model.
Results were presented as means ±SE. Other details can be
found in a previous study (Huang et al., 2017).
Arch. Anim. Breed., 60, 357–362, 2017 www.arch-anim-breed.net/60/357/2017/
J. Huang et al.: A combined genotype of three SNPs 359
Table 1. Details of SNPs detected in the bovine PPARD gene.
Label Position Alleles rs number Functional consequence
SNP1 AC_000180.1: 9268142 G> A rs208371564 upstream variant 2KB
SNP2 AC_000180.1: 9341130 A> G rs470835077 intron 2
SNP3 AC_000180.1: 9352706 T> C rs207513597 intron 6
Table 2. Details of primers and restriction enzymes used for genotyping.
Name Primer sequence (50-30)Tm(◦) Size (bp) Used for Restriction Main
enzyme fragments
PPARD
-Hha I
F:GCAGGATATAGTTCCCAGC
R:GACTTGTCATCCCAACCTT
55 137 SNP1 Hha I GG: 117
bp
GA: 137
bp, 117
bp
AA: 137
bp
PPARD
-Pvu II
F:TCCTTCCAGCAGCTACACAG
CT
R:GGGAGACAACTCGCCCAAG
A
57.5 195 SNP2 Pvu II GG: 147
bp
AG: 167
bp, 147
bp
PPARD
-Mlu I
F:ATGGCAGTGGGACACGCG
R:CCACCAGAAATAACCCCCAT
C
63 121 SNP3 Mlu I TT: 107
bp
TC: 121
bp, 107
bp
CC: 121
bp
Note: letters underlined in the primer sequence are the introduced mutant for genotyping.
3 Results and discussion
3.1 Expression profile of PPARD
The expression profile of PPARD has been widely investi-
gated in rodent and human development, but it is limited in
cattle. In order to understand the potential biological effect
of PPARD on cattle, expression levels of PPARD were in-
vestigated (Fig. 1). Consistent with previous studies, PPARD
was widely expressed in main tissues, suggesting that it was
involved in multiple biological processes. The highest level
of expression was detected in kidney, followed by adipose
tissue (Fig. 1), indicating its significant biological role in
kidney and adipose tissues. Expression levels of the PPARD
gene in the other six tissues were nearly the same, with rel-
atively low values. In fact, the expression pattern of PPARD
was found to be variable in different studies. PPARD was
expressed in kidney with a high level in adult rats (Brais-
sant and Wahli, 1996), adult mice (Girroir et al., 2008), and
adult human (Auboeuf et al., 1997). PPARs were identified as
the genetic sensor responsive to fatty acid ligands (Feige et
al., 2006) and involved in lipid metabolism and the insulin
signaling pathway (Youssef and Badr, 2013). In addition,
chronic kidney disease was attributed to metabolic disorders
mainly through the mechanisms of insulin resistance and re-
sultant hyperinsulinemia (Perlstein et al., 2007). In fat tissue,
only a moderate level was detected in adult rats and humans
(Braissant and Wahli, 1996; Auboeuf et al., 1997). These re-
sults were consistent with our study. However, a moderate to
high level of expression in liver, heart, and lung was detected
in adult rodents and humans (Girroir et al., 2008; Tugwood
et al., 1996; Mukherjee et al., 1997), which was nearly con-
tradictory with our result. Regardless, all of these results un-
derline multiple functions of PPARD in the development of
mammals. Thus, PPARD should be necessary for cattle de-
velopment.
3.2 SNP detection and genetic characteristics of
PPARD in Chinese cattle
In total, three SNPs were detected (Table 1 and Fig. 2),
including AC_000180.1:g.9268142 G > A in the upstream
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360 J. Huang et al.: A combined genotype of three SNPs
Table 3. Association analysis between combined genotypes of three SNPs in PPARD and growth traits of 300 adult cattle.
Growth
traits
Combined genotypes
GAAGCC
(10)
GAAGTC
(66)
GAAGTT
(35)
GAGGTC
(45)
GAGGTT
(21)
GGAGTC
(29)
GGAGTT
(14)
GGGGTC
(41)
GGGGTT
(20)
BH
(cm)
129.450 ±
3.028
129.106 ±
1.179
130.843 ±
1.618
130.033 ±
1.427
129.286 ±
2.089
129.448 ±
1.778
127.286 ±
2.559
131.598 ±
1.495
127.450 ±
2.141
BL
(cm)
145.900 ±
4.034
144.068 ±
1.570
147.743 ±
2.156
143.500 ±
1.901
143.619 ±
2.783
143.017 ±
2.369
146.643 ±
3.409
145.415 ±
1.992
141.750 ±
2.852
HG
(cm)
171.400 ±
5.195
174.538 ±
2.022
176.414 ±
2.777
174.156 ±
2.449
168.214 ±
3.585
169.414 ±
3.051
171.357 ±
4.391
175.634 ±
2.566
168.750 ±
3.673
AC
(cm)
200.100 ±
6.774
203.008 ±
2.637ab
205.514 ±
3.621a
204.156 ±
3.193a
192.476 ±
4.674b
199.069 ±
3.978
200.143 ±
5.725
201.415 ±
3.345
190.700 ±
4.790bc
HW
(cm)
45.200 ±
1.897a
45.023 ±
0.738a
45.471 ±
1.014a
45.344 ±
0.894A
43.310 ±
1.309
44.190 ±
1.114
45.286 ±
1.603a
43.341 ±
0.937
41.100 ±
1.341Bb
SW
(cm)
28.500 ±
1.456A
28.659 ±
0.567A
28.586 ±
0.778A
27.489 ±
0.687A
27.548 ±
1.005A
26.914 ±
0.855A
28.107 ±
1.231A
25.549 ±
0.719a
22.600 ±
1.030Bb
HHC
(cm)
129.300 ±
2.691
129.394 ±
1.048
131.357 ±
1.438
129.122 ±
1.269
129.238 ±
1.857
131.621 ±
1.580
128.214 ±
2.274
132.232 ±
1.329
128.575 ±
1.903
BW
(kg)
391.453 ±
32.883
388.720 ±
12.800
413.462 ±
17.577a
399.380 ±
15.501
385.273 ±
2.691
391.784 ±
19.310
378.964 ±
27.791
391.686 ±
16.240
350.251 ±
3.252b
BPI
(kg cm−1)
3.017 ±
0.194
3.001 ±
0.076
3.113 ±
0.104a
3.045 ±
0.092
2.906 ±
0.134
2.987 ±
0.114
2.962 ±
0.164
2.956 ±
0.096
2.738 ±
0.137b
BH: body height; BL: body length; HG: heart girth; AC: abdominal circumference; HW: hip width; SW: sciatic width; HHC: height at hip cross; BW: body weight;
BPI: beef performance index.
Lowercase letters mean difference of the value at P<0.05; uppercase letters mean difference of the value at P <0.01.
region (SNP1, rs208371564), AC_000180.1:g.9341130
A > G in intron 2 (SNP2, rs470835077), and
AC_000180.1:g.9352706 T > C in intron 6 (SNP3,
rs207513597). A total of 3801 SNPs of the bovine
PPARD gene can be searched in the SNP database of NCBI
(https://www.ncbi.nlm.nih.gov/snp/), including 710 detected
by cluster and 3091 with no information. No more SNPs
could be found from other studies. Thus, the three SNPs
detected in this study were not further analyzed although
they had been detected by cluster previously.
Then, genetic characteristics of SNPs were investigated
based on the genotyping result (Table S2). We noted that the
AA genotype of SNP2 was absent in all of the populations in
this study. At the same time, the A allele was not rare in Chi-
nese cattle. Therefore, we speculated that individuals with
the AA genotype of SNP2 died during the embryonic stage
or were culled because of disease at an early age. Amazingly,
approximately half of the breeds were not in agreement with
the HWE (P <0.05) at each of these SNP loci, suggesting
that they might undergo selection pressure. All of the three
SNP loci showed moderate diversity (0.25< PIC< 0.5), indi-
cating their relatively high selection potential. Further selec-
tion could be implied if a positive effect were found among
these SNPs in cattle breeds investigated.
3.3 Association study between PPARD and growth traits
Potential genomic mutations of the PPARD gene might be
related to growth traits of cattle. First, relationship between
PPARD and growth traits were investigated in 173 Henan cat-
tle based on a single SNP locus (Table S3). Several signif-
icant differences were identified without regularity. Gener-
ally, the phenotypic value should change along with the vari-
ation in genotype (in the order of wild type, heterozygous
type, and homozygous mutant type) with a specific trend.
Moreover, this trend should be the same among different
breeds and ages. However, significant differences detected in
Table S3 did not conform to such trends and showed disor-
der. This might be due to the low sample size, or else multiple
loci affect the same traits with different weight. Therefore, it
was hard to estimate the real association between these SNPs
and growth traits in cattle.
We speculated that coordination among multiple SNPs
loci might contribute to development or be linked with
Arch. Anim. Breed., 60, 357–362, 2017 www.arch-anim-breed.net/60/357/2017/
J. Huang et al.: A combined genotype of three SNPs 361
growth traits of cattle. Based on such a hypothesis, associ-
ation analysis between combined genotypes of these three
SNPs and growth traits of 300 adult cattle was performed.
Combined genotypes with less than 10 individuals were re-
moved. In total, nine combined genotypes were used for
analysis (Table 3). Interestingly, all traits showed the high-
est values in the GAAGTT combined genotype. Among
these, abdominal circumference, hip width, sciatic width,
body weight, and beef performance index showed signifi-
cant differences. Obviously, individuals with the GAAGTT
combined genotype of these three SNPs showed optimal
growth performance. In fact, association analysis based on
combined genotype has been widely used in studies on the
relationship between genetic variation and diseases in hu-
mans (Kamitani et al., 1995; Boulet et al., 2008; Stelma
et al., 2016) and traits in livestock animals (Garaulet et
al., 2012). However, results from this analytical method
need further verification from multiple points. The bovine
PPARD gene is identified in chromosome 23 (9.27–9.36 Mb).
By searching the quantitative trait locus (QTL) database
of cattle (http://www.animalgenome.org/cgi-bin/QTLdb/BT/
browse) for those QTLs associated with growth trait, four
QTLs were obtained, including a QTL (5.9–16.3 Mb) for
body weight of adult cattle (McClure et al., 2010), a QTL
(0.6–17.5 Mb) for body weight before slaughter (Elo et al.,
1999), a QTL (7.2–21.1 Mb) for body weight at weaning
(McClure et al., 2010), and a QTL (7.2–21.1 Mb) for body
weight at 12 months (McClure et al., 2010). These QTLs fur-
ther suggested that PPARD was a potential significant candi-
date gene for production traits of cattle. Three SNPs iden-
tified in this study were in the non-coding region. In recent
years, transcripts (non-coding RNAs) from non-coding re-
gion have been shown to regulate the transcription of the
origin genes and then affect the biological function of the
origin genes. However, the non-coding region might provide
the binding site for some enzymes relating to transcription.
Thus, mutations in the non-coding region could play a role
in the regulation mechanism. However, SNPs may only be
markers associated with production traits and do not affect
any biological process.
4 Conclusions
The bovine PPARD gene is expressed widely in the main
tissues of adult cattle. Three SNPs of PPARD were iden-
tified in Chinese cattle. The GAAGTT combined genotype
of these three SNPs showed optimal growth performance,
which could be a potential marker for MAS of cattle. How-
ever, further identification should be performed in larger pop-
ulations before being applied to breeding of cattle.
Data availability. The original data are available upon request
from the corresponding author.
The Supplement related to this article is available online
at https://doi.org/10.5194/aab-60-357-2017-supplement.
Author contributions. YM and FL designed experiments and
collected samples. QZ, SW, QZ, LJ and RH carried out the experi-
ment; JH analyzed the data and wrote the manuscript.
Competing interests. The authors declare that they have no con-
flict of interest.
Acknowledgements. This study was supported by the National
Natural Science Foundation of China (no. 31672403), the Chinese
National High Technology Research and Development Program
(no. 2013AA102505-4), the Technology Innovation Teams in
Universities of Henan Province (no. 14IRTSTHN012), and the
Nanhu Scholars Program for Young Scholars of XYNU.
Edited by: Steffen Maak
Reviewed by: three anonymous referees
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