Received: 17 March 2021
Accepted for publication: 23 May 2022
Slov Vet Res 2022; 59 (2): 89–98
DOI 10.26873/SVR-1316-2022
UDC 636.082:637.54:598.261.7:577.171.6
Original Research Article
Introduction
The control of feed intake, energy balance and 
fat deposition have high economic importance 
in farm animals. The accumulation of excess fat 
affects meat quality, fertility, productivity, and 
whole-body metabolism (1, 2). Leptin activity at 
specific receptors in the hypothalamus suppresses 
feed intake, which increases the use of energy, 
and leptin is a polypeptide hormone that controls 
the body‘s energy balance (3, 4). Leptin receptor 
(LEPR) is a member of the class 1 cytokine 
receptor family that mediates most of LEP central 
EFFECTS OF SELECTION IN TERMS OF MEAT YIELD TRAITS ON 
LEPTIN RECEPTOR GENE IN JAPANESE QUAIL LINES 
Kemal Karabağ1, Sezai Alkan2*, Taki Karslı3, Cengiz İkten4, İnci Şahin5, Mehmet Mendeş6 
1Department of Agricultural Biotechnology, 3Department of Animal Science, 4Department of Plant Protection, Faculty of Agriculture, Akdeniz 
University, 07058 Antalya, 2Department of Animal Science, Faculty of Agriculture, Ordu University, 52200 Ordu, 5Department of Plant 
Protection, Faculty of Agriculture, Selçuk University, 42030 Konya, 6Department of Animal Science, Faculty of Agriculture, Çanakkale Onsekiz 
Mart University, Çanakkale, 17020, Turkey
*Corresponding author, E-mail: sezaialkan61@gmail.com
Abstract: This study was carried out to investigate the effects of selection on the single nucleotide polymorphisms (SNPs) 
in coding sequence of leptin receptor (LEPR) gene and possible associations between SNPs’ and some meat yield traits of 
Japanese quail lines. Fifteen generations divergently selected two lines (HBW and LBW) for 5-weeks of age body weight and 
a control were used as materials for this study. A 348-bp part of the LEPR coding region (18th exon) were sequenced in a total 
of 113 individuals from the three quail lines and shown that the fragments contained four SNPs loci (T490C, C528T, G537A, 
T571C) and five haplotypes (TTGT, CTGT, TCGT, TCAT, TCAC). T490C replacement caused the missense mutation of pheny-
lalanine to convert to leucine (Phe>Leu). However, other SNPs were synonymous and there were no changes in transcripts. It 
was determined that the quails with higher phenotypic values were in the TT genotype at the T390C locus. Statistical analyses 
showed that there were significant differences among the quail lines, SNP alleles and haplotypes in terms of interested pheno-
typic traits (P<0.05), and also SNP and haplotype distributions changed depending on quail lines (P<0.001). When all results 
were evaluated together, it was concluded that the fifteen generations of selection caused significant changes in the LEPR 
gene in terms of economically important traits in Japanese quail lines (C. coturnix japonica).
Key words: SNP; haplotype; leptin receptor; selection; Japanese quail
and peripheral effects (5). The presence of leptin 
in laying and broiler poultry genotypes decreases 
feed intake (6, 7). Quail chicks that were given 
recombinant mouse leptin on the fifth embryonic 
day were removed from incubation earlier (5-24 
hours) and reached a higher body weight than 
the control group (8). DNA sequence analysis 
of leptin from several mammalian and avian 
species, including livestock animals, showed 
that leptin is highly conserved among vertebrate 
species. Among vertebrates, the leptin amino 
acid sequence shows more than 80% homology 
(9). The entire coding region of the leptin receptor 
(LEPR) in Japanese quail (C. coturnix japonica) 
was sequenced by Wang et al. (10). Also, four 
alternative LEPR spliced variants (one long and 
three soluble) were identified in Japanese quails 
K. Karabağ, S. Alkan, T. Karslı, C. İkten, İ. Şahin, M. Mendeş90
(11). DNA sequencing methods have focused on 
single nucleotide polymorphisms (SNP) in recent 
years. SNPs of leptin and its receptors in relation 
to livestock yields has accelerated research 
efforts. Researchers are actively investigating 
the relationship between leptin and traits of 
high economic importance, such as feed intake 
(12, 13), fertility (14), milk production (15, 16) 
and meat production (17, 18). Tarabany et al. 
(19) has reported SNP haplotypes significantly 
associated with growth and egg production in 
Japanese quails. Also, a SNP of LEPR gene was 
significantly associated with abdominal fat in 
chickens (20).
Statistical analysis is an important part of 
scientific studies and there are different statistical 
tests and approaches have been developed for 
analyzing data sets which have been obtained 
the studies carried out for the same purpose. 
However, it is extremely important to use a 
statistical test or methods that will be able to 
give more detailed information about the effect 
of interested factor(s). Due to its advantages over 
classical methods (i.e., ANOVA and its parametric 
and nonparametric counterparts) Analysis of 
Mean Technique (ANOM) was used for analyzing 
data sets.
ANOM is not only a powerful tool for 
comparing means but also for comparing 
variances, proportions and other location and 
scale measures. This procedure can also be used 
efficiently as a multiple comparison test especially 
when there are a large number of groups (21). 
ANOM is accepted as a graphical counterpart 
to ANOVA for comparing group means. Since 
it presents the comparisons graphically, the 
researchers can easily see which treatment mean 
(s) are different. This is a big advantage especially 
for non-statisticians (21 - 23).
The aim of this study is to investigate the 
relationships between SNPs in the coding sequences 
(18th exon) of the leptin receptor (LEPR) gene, which 
may occur as a result of 15 generations of long-term 
selection in Japanese quail (C. coturnix japonica) 
lines, and some phenotypic features.
Material and methods
All the experimental procedures were reviewed 
and approved by Akdeniz University Local 
Committee on Animal Research Ethics (Protocol 
number: 2012.02.02).
Animal
The material of this study was consisted of three 
different Japanese quail (C. coturnix japonica) 
lines (C: control, HBW: high body weight and LBW: 
low body weight). Control group was not selected 
previously while the quails in the treatment 
groups were divergently selected according to 
their high and low body weight at the fifth week 
for 15 generations. Quail lines were obtained in 
previous project which was supported by the 
Scientific Research Projects Coordination Unit of 
Akdeniz University (Project ID: 2003.03.121.004). 
The data sets used in this study were obtained 
from the projects supported by the Scientific 
Research Projects Coordination Unit of Akdeniz 
University (Project ID: 2012.01.0104.002) and the 
Scientific and Technological Research Council of 
Turkey (Project ID: 114O047).
Raising of Material
Fertilized eggs were collected from the HBW, 
LBW and C lines for a week and stored at 15-
20 °C with 75-80% humidity. These eggs were 
incubated at 36.5 °C with 65% humidity for the 
first 14 days and at 36.0 °C and 55% humidity 
for the last 4 days. Hatching weight (HW) of 
chicks were weighed individually using 0.01 g 
precision scales, and an aluminum ID number 
was attached to the left wings of chicks after 
incubation. These chicks were fed 24% crude 
protein and 2900 kcal/kg ME (metabolic energy) 
during the first four weeks in a breeding cage. 
Sex determination was performed by observing 
the cloaca and breast feather color at the end 
of the fourth week. 50 males and 50 females 
were selected randomly from each quail line and 
transferred to individual breeding cages for 10 
weeks. All birds were fed with 21% crude protein 
and 2800 kcal/kg ME for ten weeks. Lighting 
was applied continuously for the first four weeks 
and then 16 hours a day.
Feed Intake (FI)
Since the animals were not fed on the day of 
weighing the differences due to feed intake was 
fixed. Thus, 10 weeks of individual feed intake (FI) 
were recorded as grams per day. A total of FI for 
per individual was calculated from these records.
Effects of selection in terms of meat yield traits on leptin receptor gene in Japanese quail lines 91
Sexual Maturity
The first ovulation day and the first day of 
release foam were considered as sexual maturity 
for females and males, respectively. Sexual 
maturity weight (SMW) of males and females were 
determined on the same day.
Body Weight and Carcass Weight
A total of 50 quails (25 males and 25 females) 
were selected randomly from the HBW, LBW and 
C groups, respectively. Then were introduced to 
the cutting process which was performed at the 
end of the 15th week. The body weights (BW) of 
the birds were measured just before cutting using 
0.01 g precision scales from hatching to the 15th 
week on the same day each week. Low-voltage 
electrical current (100 mA, 50 Hz) was used to 
stun animals as recommended in the relevant 
scientific literature (24, 25), and then the jugular 
vein was cut. After the blood flow was over, the 
feathers were cleaned, and the internal organs 
were removed. Eventually, the carcass weights 
(CW) were measured using a precision scale of 
0.01 g.
Tissue Samples and Total RNA Extraction
Liver tissue samples from each individual 
were isolated using sterile forceps and scissors 
immediately after cutting and placed into 
numbered tubes (Corning, New York, USA) 
containing RNAsave. These tissues were stored at 
-80 °C until use. RNA extractions from liver tissue 
samples were performed using a commercial kit 
(Axygen) after cellular degradation of the liver 
tissues using a lyser with tungsten beads. The 
concentrations of isolated RNAs were measured 
using a biodrop. Also, RNA gel analysis (Reliant 
Gel System) was performed to determine RNA 
quality. For this purpose, 3μL of each Total RNA 
sample from each quail and 3μL of formaldehyde 
were added to a microcentrifuge tube and 
centrifuged for 10 seconds.  Then, the samples 
were heated at 65 °C for 15 min. Total RNAs were 
loaded individually into the RNA gel and run on an 
electrophoresis device for 2 hours. For staining, 
5μL of ethidium bromide was added into 50 mL 
TE Buffer. The running RNA gel was immersed in 
this buffer for about 10 hours at slow speed on a 
magnetic stirrer. UV imaging device was used to 
visualize RNA gel results. Finally, RNAs obtained 
from 150 quails were stored at –80 °C until use.
cDNA Synthesis and PCR Amplification
cDNA contains only exons and is representative 
of the expressed genes of the cell. cDNA sequencing 
results are clearer because primers do not bind 
non-specifically. A commercial kit (Thermo 
Scientific #K1621) was used to synthesize cDNAs 
from total RNAs using the following protocol: 60 
min at 42 °C, 5 min at 70 °C. Primers (forward, 
gcttgctcaggtagctcctg and reverse, tgcggcacgta 
tggcacgat) based on the recommendations of 
Dridi et al. (26) were used to PCR amplify a 348bp 
LEPR coding region (18th exon), from cDNA. 
PCR products (15 µL) were evaluated for a 348 
bp length using 2% agarose gels (electrophoresed 
at 80 V/2 h) and stained with ethidium bromide. 
Separated fragments in the electrophoresis gel 
were cut with a sterile scalpel under UV light and 
transferred to individual 1.5 mL pre-numbered 
tubes. The PCR reactions were performed in 20 
µL reaction volumes with 2 µL of genomic DNA (20 
ng) as a template, 2 µL of buffer (NH2SO4), 0.4 
µL of a dNTP mix (2.5 mmol/L), 0.5 mL of each 
primer (20 nmol/ mL), 1.25 µL of MgCl2 (25 mM) 
and 0.15 µL of EX Taq polymerase (Takara Bio Inc. 
Shiga, Japan). Amplifications were performed using 
a thermal cycler (Thermo Arktik) with the following 
conditions: 3 min for an initial denaturation at 
94 °C, 35 cycles at 94 °C for 30 s for denaturation, 
30 s for annealing at 60 or 62 °C, 45 s for extension 
at 72 °C, and a final extension for 5 min at 72 °C. 
β-actin gene primers (F:caaggagaagctgtgctacgtgc 
and R: ttaatcctgagtcaagcgcc) were used to determine 
that the PCR protocol worked (13).
Sequence Analysis and SNP Determination
cDNA samples were concentrated in the PCR 
and sequenced directly in a sequencing instrument 
(ABI-3730) after being purified from a gel and 
denatured at 94°C. LEPR gene fragments were 
sequenced for total of 150 individuals from the 
HBW, LBW and C lines. Firstly, in order to confirm 
the accuracy of the readings obtained as a result 
of sequence analysis, the nucleotides‘ peaks were 
examined using Chromas Pro software (version 
2.1.3). Eventually, a total of 113 DNA sequences 
(HBW=33, LBW=44, and C=36) were used in this 
study. The BLAST online software (http://blast.
K. Karabağ, S. Alkan, T. Karslı, C. İkten, İ. Şahin, M. Mendeş92
ncbi.nlm.nih.gov/Blast.cgi) was used to determine 
the location of 348 bp long fragment in the in 
the 18th exon of LEPR gene whose sequence was 
determined in this study. After this examining, 
the DNA sequences of the individuals belonging 
to the quail lines were aligned by using Mega6.0 
software (version 6.06). According to SNP points 
seen in individuals, haplotype distributions of 
populations were determined in DnaSP software 
(version 5.10).
Statistical Analyses
SNP alleles were detected in each individual 
from each quail population and SNP haplotypes 
were coded numerically and phenotypic 
measurements (HW, BW, SMW, CW and FI) of 
these individuals were matched to these codes. 
Results of Kolmogorov-Smirnov test showed that 
the normality assumption was not fulfilled in data 
sets. Analysis of Means (ANOM) technique was 
used to compare quail genotypes, SNPs and SNP 
haplotypes in terms of measured phenotypic traits. 
Although, the ANOM is accepted as a graphical 
alternative to ANOVA, it has two advantages over 
ANOVA especially when researchers are interested 
in studying main effects. The advantages of the 
ANOM over the ANOVA are: a) if any of the group 
mean is statistically different from the others, it 
enables the researchers to see exactly which one is 
Computation of UDL and LDL for unequal 
sample size:
Figure 1: Sequenced 18th exon region of LEPR. Bold letters are SNPs, Underlined sequences are primer binding 
sites
different easily and b) since the ANOM is a graphical 
technique, it presents the results visually that 
provides a quick way for researchers and readers 
to evaluate both practical and statistical significant 
differences between the treatment groups and the 
overall mean (21-23).
The results of the ANOM technique are based 
on confidence interval or decision lines (upper 
decision line (UDL) and lower decision line (LDL). 
The computation of the upper and lower decision 
lines is given as below (18,19). Computation of UDL 
and LDL for equal sample size:
Effects of selection in terms of meat yield traits on leptin receptor gene in Japanese quail lines 93
Figure 1: ANOM for comparing quail lines (a), haplotypes (b), SNP1 (c), SNP2 (d), SNP3 (e), and SNP4 (f) in terms 
of HW (Hatching Weight), SMW (Sexual Maturity Weight), BW (Body Weight), CW (Carcass Weight), and FI (Feed 
Intake), respectively
                                                  
 
 
         
a 
         
b 
         
c 
         
d 
         
e 
         
f 
LBWHBWCONTROL
11
10
9
8
7
6
5
M
e
a
n
s 
o
f 
H
W
7,89
7,672
8,108
LBWHBWCONTROL
350
300
250
200
150
100
M
e
a
n
s 
o
f 
S
M
W
201,1
193,8
208,5
LBWHBWCONTROL
350
300
250
200
150
100
M
e
a
n
s 
o
f 
B
W
223,6
216,3
231,0
LBWHBWCONTROL
250
200
150
100
M
e
a
n
s 
o
f 
C
W
154,5
149,5
159,5
LBWHBWCONTROL
2750
2500
2250
2000
1750
1500
1250
1000
M
e
a
n
s 
o
f 
F
I
1686
1536
1836
HAP5HAP4HAP3HAP2HAP1
10
9
8
7
6
M
e
a
n
s 
o
f 
H
W
7,89
7,164
8,616
HAP5HAP4HAP3HAP2HAP1
300
250
200
150
M
e
a
n
s 
o
f 
S
M
W
201,1
172,5
229,8
HAP5HAP4HAP3HAP2HAP1
325
300
275
250
225
200
175
150
M
e
a
n
s 
o
f 
B
W
223,6
192,0
255,3
HAP5HAP4HAP3HAP2HAP1
240
220
200
180
160
140
120
100
M
e
a
n
s 
o
f 
C
W
154,5
130,4
178,6
HAP5HAP4HAP3HAP2HAP1
2400
2200
2000
1800
1600
1400
1200
1000
M
e
a
n
s 
o
f 
F
I
1686
1346
2026
TTCTCC
9,5
9,0
8,5
8,0
7,5
7,0
6,5
6,0
M
e
a
n
s 
o
f 
H
W
7,89
7,637
8,143
TTCTCC
250
225
200
175
150
M
e
a
n
s 
o
f 
S
M
W
201,1
190,1
212,2
TTCTCC
275
250
225
200
175
150
M
e
a
n
s 
o
f 
B
W
223,6
212,0
235,2
TTCTCC
200
180
160
140
120
100
M
e
a
n
s 
o
f 
C
W
154,5
145,4
163,6
TTCTCC
2200
2000
1800
1600
1400
1200
1000
M
e
a
n
s 
o
f 
F
I
1686
1569
1803
TTCTCC
9,5
9,0
8,5
8,0
7,5
7,0
6,5
6,0
M
e
a
n
s 
o
f 
H
W
7,89
7,215
8,565
TTCTCC
260
240
220
200
180
160
140
120
100
M
e
a
n
s 
o
f 
S
M
W 201,1
172,1
230,2
TTCTCC
300
250
200
150
M
e
a
n
s 
o
f 
B
W
223,6
191,5
255,7
TTCTCC
200
175
150
125
100
M
e
a
n
s 
o
f 
C
W 154,5
129,7
179,3
TTCTCC
2200
2000
1800
1600
1400
1200
1000
M
e
a
n
s 
o
f 
F
I
1686
1341
2031
GGAA
9,0
8,5
8,0
7,5
7,0
M
e
a
n
s 
o
f 
H
W
7,89
7,602
8,178
GGAA
240
230
220
210
200
190
180
170
M
e
a
n
s 
o
f 
S
M
W
201,15
188,84
213,46
GGAA
260
250
240
230
220
210
200
190
M
e
a
n
s 
o
f 
B
W
223,63
210,02
237,25
GGAA
180
170
160
150
140
130
M
e
a
n
s 
o
f 
C
W
154,49
143,92
165,06
GGAA
2100
2000
1900
1800
1700
1600
1500
1400
M
e
a
n
s 
o
f 
F
I
1686,1
1551,8
1820,3
GGAA
9,0
8,5
8,0
7,5
7,0
M
e
a
n
s 
o
f 
H
W
7,89
7,602
8,178
TTCTCC
300
250
200
150
100
M
e
a
n
s 
o
f 
S
M
W
201,1
193,3
209,0
TTCTCC
350
300
250
200
150
100
M
e
a
n
s 
o
f 
B
W
223,6
215,3
232,0
TTCTCC
250
200
150
100
50
M
e
a
n
s 
o
f 
C
W
154,5
148,1
160,8
TTCTCC
3000
2500
2000
1500
1000
500
M
e
a
n
s 
o
f 
F
I
1686
1599
1773
K. Karabağ, S. Alkan, T. Karslı, C. İkten, İ. Şahin, M. Mendeş94
Where    , h, k, and MSE denote overall mean, 
critical table values for the ANOM technique based 
on α number of treatment group number and mean 
square error (21-23). 
The decision is set as follows: if all means fall 
between the UDL and LDL, then the null hypothesis 
is accepted, and it is concluded that all means are 
equal. Any of the group mean, on the other hand, falls 
outside the decision lines, then the null hypothesis 
is rejected, and it is concluded that at least one 
group mean is significantly different from the overall 
or grand mean. In addition, Chi-square analysis 
was used on each of the haplotypes and SNPs to 
determine whether the ratio was due to genotype 
possession.
Results
A 348-bp fragment at the 18th exon of the 
LEPR gene was sequenced in 113 individuals 
from three quail lines. This fragment was BLAST 
searched against GenBank to confirm its identity 
as fragment of the LEPR gene. The 348 bp part 
of the sequence uploaded with KP674327.1 
accession number that we identified exactly 
matched bases from 3163 to 3511 of the 3579 
bp of whole LEPR sequence. Also, this region’s 
position on the transcripts is between 811. 
codon and 926. codon in the entire gene (NCBI: 
XP_032302064.1). The sequenced fragments in 
this study were contained four SNPs loci (T490C, 
C528T, G537A, T571C) and five haplotypes (TTGT, 
CTGT, TCGT,TCAT, TCAC). When investigated 
the transcripts of the sequences, we found that 
the first SNP (T490C) caused with changing of 
phenylalanine to leucine (Phe-Leu) by occurring 
missense mutation. However, the other SNPs 
were synonyms and there were no changes on the 
transcripts. Loci of the four SNPs were marked in 
bold and locations of primers were underlined as 
shown Figure 1.  
ANOM technique was used to investigate the 
effects of quail lines, SNPs and haplotypes on HW, 
SMW, BW, CW, and FI and the results have been 
presented in Figure 2a-f, respectively.
The results of the ANOM technique are based on 
confidence interval or decision lines (UDL: upper 
decision line and LDL: lower decision line). UDL and 
LDL are shown with red lines. Differences outside 
the UDL and LDL boundaries are indicated by the 
red dot.
When the results of ANOM for comparing quail 
lines in terms of HW, SMW, BW, CW, and FI were 
examined, it was clearly seen that the results were 
generally very similar for all traits except FI. As 
it can be seen from the Figure 2a, at least one 
mean falls outside the decision lines, that means 
there were statistical significance differences 
among the genotypes in terms of HW, SMW, BW, 
CW, and FI.  The highest values for all traits have 
been observed for the HBW genotype while the 
least values observed for the LBW. The values 
of means from control population were generally 
located between decision lines. That means there 
were statistically significant differences among 
the quail lines in terms of studied phenotypic 
traits. Therefore, it was possible to conclude that 
there were statistically significant changes in 
the gene of the LEPR due to long-term selection. 
This suggests that long-term divergent selection 
for body weight in quail’s results in different 
changes in the same locus of the LEPR gene. As 
seen in Figure 1b, all haplotypes except the fourth 
haplotype affected HW, BW, SMW, CW, and FI. 
The Hap1 and the Hap5 have positive affect while 
the Hap2 and the Hap3 have negative affect on 
interested traits in this study. The highest and the 
lowest HW values were obtained for the Hap5 and 
the Hap3, respectively.
For the effect of SNP1, obvious differences 
have been observed among the CC, CT, and TT 
genotypes.  As it is seen from the Figure 2c, the 
HW, SMW, BW, CW and FI values for the TT were 
obviously higher than that of the CC and CT. 
Therefore, it can be concluded that the TT has 
a positive impact on the phenotypic traits while 
the CC and CT have negative. When the effect of 
SNP2 was examined, it was not difficult to observe 
that the CC genotype has positive impact, and the 
highest phenotypic values were obtained for the 
CC. The CT and TT genotypes, on the other hand, 
have negative affect and the lowest values were 
observed for the TT (Figure 2d). When Figure 1e is 
examined, it can be seen that the AA genotype has 
obviously positive impact while the GG genotype 
has negative affect on the phenotypic traits. The 
CC genotype at the SNP4 loci has positive affect on 
the HW, SMW, BW, CW and FI, while the TT has 
negative (Figure 2f). All means fall between lower 
and upper decision lines for the CT genotype that 
just has positive affect on the FI.
The distribution of the SNP genotypes and 
the haplotypes in quail lines are not the same 
Effects of selection in terms of meat yield traits on leptin receptor gene in Japanese quail lines 95
(Table 1, P<0.01). The allele numbers were found 
as almost same for the SNP1 locus in the LBW 
quails. However, this case was not valid for the 
control and HBW quail lines. It is possible to say 
that the selection results in favor of the TT at SNP1 
locus in LBW because of there were no CC and CT 
genotypes in control line, and just 2 individuals in 
HBW (Table 1). 
Table 1: Results of Pearson chi-square test of distributions 
of SNP genotypes in quail lines
Discussion
LEP and LEPR are excellent candidate genes 
for livestock production, as it is associated with 
features of economic importance. Indeed, in 
recent years, leptin gene polymorphism studies of 
several single nucleotide polymorphisms (SNPs) 
have been identified in cows and pigs, and several 
SNPs have been identified that are associated with 
important economic traits, such as milk yield, 
feed intake, adiposity, growth, and carcass quality 
(12-18, 27). The reasons for focusing on exon 
18 in this study is that exon 18 polymorphisms 
are important on backfat thickness, feed yield 
and reproduction traits (28). When investigated 
the transcripts of the sequences, we found that 
the first SNP1 (T490C) caused with changing of 
phenylalanine to leucine (Phe-Leu) by occurring 
missense mutation. However, the other SNPs 
were synonyms and there were no changes on 
the transcripts in current study. El Moujahid et 
al. (29) found a significant association between 
4 previously reported non-synonymous SNPs 
and the growth performance traits in meat-type 
chickens. In this study, the HW, SMW, BW, CW 
and FI values for the TT genotype were obviously 
higher than that of the CC and CT at SNP1 locus. 
When the effect of SNP2 was examined, it was 
not difficult to observe that the CC genotype 
has positive impact, and the highest phenotypic 
values were obtained for the CC. According to 
SNP3 the AA genotype has obviously positive 
impact while the GG genotype has negative affect 
on the phenotypic traits. The CC genotype at the 
SNP4 loci has positive relation on the HW, SMW, 
BW, CW and FI, while the TT has negative. Also, 
Hap1 (TTGT) and Hap5 (TCAC) have positive affect 
while the Hap2 (CTGT) and the Hap3 (TCGT) have 
negative affect on interested traits (HW, BW, SMW, 
CW, and FI).
De Vuyst et al. (30) found that both crossbred 
CT and TT beef cows wean significantly heavier 
beef calves than CC cows. There were several 
SNPs found in the porcine LEP and LEPR genes, 
suggesting that the SNPs lead to increased growth 
and fat (31). Buchanan et al. (32) revealed a SNP in 
the leptin gene of dairy cattle. This polymorphism, 
in which the first nucleotide is a thymine instead 
of cytosine in the 25th codon, changed arginine 
to a cysteine. However, homozygous animals 
carrying the T allele show no difference compared 
to animals carrying the C allele in terms of milk 
SNPs
LBW
Quail Lines
Chi-squareC HBW
T
103
C
CC
CT
TT
11
22
11
0
0
36
2
2
29
0.000*
C
141
T
CC
CT
TT
5
22
17
23
12
1
32
1
0
0.000*
G
150
A
AA
GG
5
39
23
13
16
17 0.000
*
T
184
C
CC
CT
TT
0
0
44
4
4
28
14
0
19
0.000*
*p<0.01
Absence of the CC and CT and present of the 
TT in all individuals in LBW quail line suggests 
that negative selection in terms of low body 
weight effective in favor of the TT for SNP4. It 
was possible to claim that similar situation may 
be valid for the GG genotype at SNP3 locus. 
However, the numbers of TT at SNP1 and CC at 
SNP2 have increased by long term selection in 
terms of high body weight. The hap1 and hap5 
were mostly observed in the HBW genotype while 
the hap 2 and hap 3 were mostly observed in the 
LBW. The most commonly observed haplotype 
for the control group was hap 4 (Table 2). As in 
the SNP alleles the haplotypes have also been 
formed in different quail lines resulting in long-
term selection.
Haplotypes
Quail Lines
Chi-squareLBW C HBW
Hap-1 5 7 13
0.000*
Hap-2 22 0 4
Hap-3 12 6 0
Hap-4 5 17 0
Hap-5 0 6 16
*p<0.01
Table 2: Results of Pearson chi-square test of distributions 
of haplotypes in quail lines
K. Karabağ, S. Alkan, T. Karslı, C. İkten, İ. Şahin, M. Mendeş96
fat and milk protein production and a daily milk 
yield of more than 1.5 kg. In addition, homozygous 
T allele-bearing animals developed higher fatty 
carcasses than those with the C allele (33). Also, El 
Moujahid et al. (29) reported relation of LEPR gene 
polymorphisms with growth and feed efficiency in 
meat-type chickens. Wang et al. (34) found a single 
nucleotide polymorphism (C/A) and three SNP 
genotypes in LEPR associated with fatness traits 
in chickens. Abbasi et al. (35) screened exons 
9–11 of chicken LEPR but did not find any SNPs. 
Tarabany et al. (19) To the best of our knowledge, 
this is the first study to report the presence of 
two adjacent novel SNPs (A277G and A304G) in 
intron 8 of the LEPR gene of Japanese quail. GG/
GG quails had significantly lower egg production 
and feed intake. Four SNPs loci (T490C, C528T, 
G537A, T571C) and five haplotypes (TTGT, CTGT, 
TCGT, TCAT, TCAC) were determined and the 
distributions of the SNP alleles and the haplotypes 
in quail lines were not the same in this study. This 
suggests that long-term selection for high body 
weight and low body weight in quail’s results in 
different changes in the same locus of the LEPR 
gene.
Feed consumption, growth, development, energy 
metabolism and immune system functioning have 
a high economic importance in livestock. In this 
regard, there is a need for additional studies on 
genes that affect animal feed intake, the regulation 
of energy metabolism, yield and health. Leptin 
plays an important role in all of these mechanisms 
of economic importance in livestock. Therefore, 
studies of leptin will significantly contribute 
to animal nutrition, breeding and health. Yet, 
effects of the single nucleotide polymorphisms of 
leptin and LEPR genes in poultry animals are not 
adequately explained.
Therefore, it is possible to conclude that 
the effects of different genotypes, haplotypes, 
and SNPs on HW, SMW, BW, CW and FI are 
considerable. Since expectation of high correlation 
between the studied traits, that it is not a 
surprise to get these results of the long term bi-
direction selection. These changes can be altered 
the function of the LEPR. However, to achieve a 
more accurate understanding of the role of leptin 
and its receptor, the DNA sequence of all of the 
SNP changes that benefit individuals and alter 
protein structure should be identified. However, 
conclusively demonstration of this effect requires 
the identification of all of the SNPs in the entire 
sequence of the LEPR in quails. Although it is very 
hard to interpret this data into livestock weight, 
surely these polymorphisms are worth a further 
investigation.
Acknowledgement
Selection studies were supported by the 
Scientific Research Projects Coordination Unit of 
Akdeniz University (Project ID: 2003.03.121.004). 
Molecular studies were supported by the Scientific 
Research Projects Coordination Unit of Akdeniz 
University (Project ID: 2012.01.0104.002) and the 
Scientific and Technological Research Council of 
Turkey (Project ID:114O047).
The authors certify that there is no conflict of 
interest with any financial organization regarding 
the material discussed in the manuscript.
References
1. Macajova M, Lamosova D, Zeman M. Role 
of leptin in Japanese quail development. Acta 
Vet Brno 2002; 71: 473–9.
2. Macajova M, Lamosova D, Zeman M. Role 
of leptin in farm animals: a review. J Vet Med A 
2004; 51: 157–66. 
3. Taouis M, Chen JW, Daviaud C, Dupont J, 
Derouet M, Simon J. Cloning the chicken leptin 
gene. Gene 1998; 208: 239–42. 
4. Ashwell CM, Czerwinski SM, Brocht D, 
McMurtry M. Hormonal regulation of leptine ex-
pression in broiler chickens. Am J Physiol 1999; 
276: 226–32.
5. Horev G, Einat P, Aharoni T, Eshdat Y, 
Friedman- Einat M. Molecular cloning and prop-
erties of the chicken leptin-receptor (CLEPR) 
gene. Mol Cell Endocrinol 2000;162(1/2): 95–
106.
6. Denbow DM, Meade S, Robertson A, Mc 
Murtry JP, Richards M, Ashwell C. Leptin-in-
duced decrease in feed intake in chickens. Phys-
iol Behav 2000; 69: 359–62.
7. Kuo AY, Cline MA, Werner E, Siegel PB, 
Denbow DM. Leptin effects on feed and water in-
take in lines of chickens selected for high or low 
body weight. Physiol Behav 2005; 84: 459–64.
8. Lamosova D, Macajova M, Zeman M, 
Mozes S, Jezova D. Effect of in ovo leptin admin-
istration on the development of Japanese quail. 
Physiol Res 2003; 52: 201–9.
Effects of selection in terms of meat yield traits on leptin receptor gene in Japanese quail lines 97
9. Doyon C, Drouin G, Trudeau VL, Moon TW. 
Molecular evolution of leptin. Gen Comp Endo-
crinol 2001; 124: 188–98. 
10. Wang D, Jiang R, Wang T, Xu C, Kang X, Liu 
X. 2014. http://www.ncbi.nlm.nih.gov/nuccore/
KJ639903
11. Wang D, Xu C, Wang T, et al. Discovery 
and functional characterization of leptin and its 
receptors in Japanese quail (Coturnix japonica). 
Gen Comp Endocrinol 2016; 225: 1–12.
12. Lagonigro R, Wiener P, Pilla F, Woolliams 
JA, Williams JL. A new mutation in the coding re-
gion of the bovine leptin gene associated with feed 
intake. Anim Genet 2003; 34: 371–4.
13. Huang JX, Lu L, Xi L, Luo XG, Liu B. Ef-
fects of age and strain on the expression of leptin 
receptor, neuropeptide Y and pro-opiomelanocor-
tin in the hypothalamus of young chickens. Br 
Poult Sci 2011; 51: 696–702.
14. Liefers SC, Te-Pas MF, Veerkamp RF, Van-
Der-Lende T. Associations between leptin gene 
polymorphisms and production, live weight, en-
ergy balance, feed intake, and fertility in Holstein 
heifers. J Dairy Sci 2002; 85: 1633–8.
15. Banos G, Woolliams JA, Woodward BW, 
Forbes AB, Coffey MP. Impact of single nucleotide 
polymorphisms in leptin, leptin receptor, growth 
hormone receptor, and diacylglycerol acyltrans-
ferase (DGAT1) gene loci on milk production, feed, 
and body energy traits of UK dairy cows. J Dairy 
Sci 2008; 91: 3190–200.
16. Chebel RC, Santos JEP. Association be-
tween leptin single nucleotide polymorphism and 
reproductive performance of lactating Holstein 
cows. Anim Reprod Sci 2011; 127: 126–34.
17. Lusk JL. Association of single nucleo-
tide polymorphisms in the leptin gene with body 
weight and back fat growth curve parameters for 
beef cattle. J Anim Sci 2007; 85: 1865–72.
18. Boucher D, Palin MF, Castonguay F, 
Gariépy C, Pothier F. Detection of polymorphisms 
in the ovine leptin (lep) gene: association of a sin-
gle nucleotide polymorphism with muscle growth 
and meat quality traits. Can J Anim Sci 2006; 
86(1): 31–5.
19. El Tarabany MS, Saleh AA, El Araby IE, 
El Magd MA. Association of LEPR polymorphisms 
with egg production and growth performance in 
female Japanese quails.
20. Lei MM, Wu SQ, Li XW, Wang CL, Chen Z, 
Shi ZD. Leptin receptor signaling inhibits ovari-
an follicle development and egg laying in chicken 
hens. Reprod Biol Endocrinol 2014; 12: e25. doi: 
10.1186/1477-7827-12-25
21. Nelson PR, Wludyka PS, Copeland KA. The 
analysis of means: a graphical method for com-
paring means, rates, and proportions. Philadel-
phia : Society for Industrial and Applied Mathe-
matics, 2005. 
22. Mendeş M, Yiğit S. Comparison of ANO-
VA-F and ANOM tests with regard to type I error 
rate and test power. J Stat Comput Simul 2013; 
83(11): 2093–104. 
23. Mendeş M, Yiğit S. An alternative approach 
for multiple comparison problems when there are 
a large number of groups: ANOM technique. J 
Anim Plant Sci 2018; 28: 1074–9.
24. Yalçin S, Oğuz I, Otles S. Carcass char-
acteristics of quail (Coturnix coturnix japonica) 
slaughtered at different ages. Br Poult Sci 1995; 
36: 393–9.
25. Göksoy EO, Mc Kinstry LJ, Wilkins LJ, et 
al. Broiler stunning and meat quality. Poult Sci 
1999; 78: 1796–800.
26. Dridi S, Buyse J, Decuypere E, Taouis M. 
Potential role of leptin in increase of fatty acid 
synthase gene expression in chicken liver. Do-
mest Anim Endocrinol 2005; 29: 646–60. 
27. Jiang ZH, Gibson JP. Genetic polymor-
phisms in the leptin gene and their association 
with fatness in four pig breeds. Mamm Genome 
1999; 10: 191–3.
28. Chen CC, Chang T, Su HY. Characteriza-
tion of porcine leptin receptor polymorphisms and 
their association with reproduction and produc-
tion traits. Anim Biotechnol 2007; 15: 89–102.
29. El Moujahid EM, Chen S, Jian S, Lu Y, 
Zhang D, Congliang, J, Yang N. Association of 
leptin receptor gene polymorphisms with growth 
and feed efficiency in meat-type chickens. Poult 
Sci 2014; 93: 1910–5.
30. De Vuyst EA, Bauer ML, Cheng FC, Mitch-
ell J, Larson D. The impact of a leptin gene SNP 
on beef calf weaning weights. Anim Genet 2008; 
39: 284–6.
31. Perez-Montarelo D, Fernandez A, Folch JM, 
et al. Joint effects of porcine leptin and leptin re-
ceptor polymorphisms on productivity and quality 
traits. Anim Genet 2012; 43: 805–9.
32. Buchanan FC, Van Kessel AG, Waldner C, 
Christensen DA, Laarveld B, Schmutz SM. Hot 
topic: an association between a leptin single nu-
cleotide polymorphism and milk and protein yield. 
J Dairy Sci 2003; 86:3164–6.
K. Karabağ, S. Alkan, T. Karslı, C. İkten, İ. Şahin, M. Mendeş98
33. Buchanan FC, Fitzsimmons CJ, Van Kes-
sel AG, Thue TD, Winkelman-Sim DC, Schmutz 
SM. Association of a missense mutation in the bo-
vine leptin gene with carcass fat content and lep-
tin mRNA levels. Genet Sel Evol 2002; 34: 105–16.
34. Wang Y, Li H, Zhang YD, Gu ZL, Li ZH, 
Wang QG. Analysis on Association of a SNP in the 
chicken OBR gene with growth and body compo-
sition traits. Asian-Aust J Anim Sci 2006; 19(12): 
1706–10.
35. Abbasi HA, Gharahveysi S, Abdullahpour 
R. Study of polymorphism of leptin gene receptor 
in Mazandaran fowls. Afr J Biotechnol. 2011; 10: 
4024–8.
UČINKI SELEKCIJE LINIJ JAPONSKIH PREPELIC NA GEN ZA LEPTINSKI RECEPTOR, 
POVEZAN S PRIREJO MESA
K. Karabağ, S. Alkan, T. Karslı, C. İkten, İ. Şahin, M. Mendeş
Izvleček: Ta študija je bila izvedena z namenom raziskati učinke selekcije na polimorfizme posameznih nukleotidov (Angl., 
Single Nucleotide Polymorphism, SNP) v kodnem zaporedju gena za leptinski receptor (LEPR) in možne povezave med SNP 
in nekaterimi značilnostmi prireje mesa pri japonskih prepelicah. V študiji je bilo poleg kontrole uporabljenih petnajst gener-
acij različno izbranih dveh linij (HBW in LBW) s telesno maso pri starosti petih tednov. 348-bp del kodne regije LEPR (18. ek-
son) je bil sekvenciran pri skupno 113 posameznikih iz treh linij prepelic, fragmenti pa so vsebovali štiri lokuse SNP (T490C, 
C528T, G537A, T571C) in pet haplotipov (TTGT, CTGT, TCGT, TCAT, TCAC). Zamenjava T490C je povzročila drugačnosmiselno 
mutacijo fenilalanina v levcin (Phe > Leu), vendar so bili drugi SNP-ji sinonimni in v transkriptih ni bilo sprememb. Ugotovljeno je 
bilo, da so prepelice z višjimi fenotipskimi vrednostmi imele genotip TT na lokusu T390C. Statistične analize so z vidika fenotip-
skih lastnosti pokazale značilne razlike med linijami prepelic, aleli SNP in haplotipi (P < 0,05), med linijami prepelic pa je bila 
različna tudi porazdelitev SNP in haplotipov (P < 0,001). Na podlagi vrednotenja vseh rezultatov smo ugotovili, da je selekcija 
petnajstih generacij linij japonskih prepelic (C. coturnix japonica) povzročila ključne spremembe v genu LEPR, povezanim z 
gospodarsko pomembnimi lastnostmi prepelic.
Ključne besede: SNP; haplotip; leptinski receptor; selekcija; japosnka prepelica