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Citation of this paper

Associations of some candidate gene polymorphisms with growth traits in Duroc pigs

Hoang Thi Thuy1, Giang Thi Thanh Nhan, Pham Thi Phuong Mai, Tran Thi Thu Thuy, Le Quang Nam, Doan Phuong Thuy1, Nguyen Van Hung2, Tran Xuan Manh2, Doan Van Soan1 and Pham Doan Lan

Key Laboratory of Animal Cell Technology, National Institute of Animal Science, Thuy Phuong, Bac Tu Liem, Hanoi, Vietnam
pdlanvn@yahoo.com
1 Bac Giang Agriculture and Forestry University, Vietnam
2 Dabaco Nucleus Breeding Pig Company, Bac Ninh, Vietnam

Abstract

The objective of this study was to investigate the genetic variation of single nucleotide polymorphism (SNP) genotyping in four candidate genes including Growth Hormone (GH), Leptin (LEP), Class 3 phosphoinositide-3-kinase (PIK3C3) and Melanocortin 4 Receptor (MC4R) and their associations with average daily gain in Duroc pigs. Four known SNPs including G361A (GH/ForkI), T3469C (LEP/HinfI), C2604T (PIK3C/Hpy8I) and G892A ( MC4R/TaqI) were genotyped in 500 Duroc pigs using the PCR-RFLP method. A general linear model was used to test associations of these SNPs with average daily gain (ADG). The results showed that polymorphisms G361A-GH, T3469C-LEP and G892A -MC4R were significantly associated with the trait (p <0.05). Significantly positive effects were detected in genotype GG/ GH, CT/LEP and AA/MC4R on ADG trait. These results suggested the SNPs in GH, LEP and MC4R genes can be used for selection of growth trait in Duroc pigs.

Key words: average daily gain, GH, LEP, PIK3C3, MC4R


Introduction

Pork is the most -consumed meat in Vietnam. Having more than ninety million people, Vietnam has a high demand for meat production. Several commercial high-yielding pig breeds such as Duroc, Landrace, Pietrian and White Yorkshire were imported into Vietnam to improve productivity in order to meet the increasing in the demand for pork. Both traditional breeding based directly on phenotypic recording and breeding based on molecular genetic information have been adapted in breeding companies to improve productivity and reduce the breeding interval. Many single nucleotide polymorphism (SNPs) markers of porcine candidate genes have been reported to associate with growth traits. The G361A SNP at GH gene was found to have influence on the number of days when the experimental pigs reached 100 kg and on the weight of heart, lung, picnic shoulder and jowl (Bižienė et al 2011; Faria et al 2006). In LEP gene, the silent mutation T3469C is the most intensively studied. The polymorphism was indicated to affect average daily gain (ADG) (Mankowska et al 2015; Tempfli et al 2015; Urban et al 2002). A silent polymorphism C2604T in PIK3C3 gene was reported to associated with ADG during a period of body weight from 30 to 90 kg (Hirose et al 2011) Meanwhile the missense mutation G892A-MC4R had an effect on feed intake and ADG (Kim et al 2000; Meidtner et al 2006).

Therefore, the study aimed to investigate the associations of these selected polymorphisms on ADG in Duroc pigs raised in Vietnam in order to provide basic data for marker-assisted selection.


Materials and methods

Animals and data collection

The experimental Duroc pig population was established at Dabaco Nucleus Breeding Pig Company located in Tien Du district, Bac Ninh province, Vietnam. A total 500 Duroc pigs (including 362 females and 138 males) derived from a cross between 32 boars and 204 sows were genotyped. The ADG in the period from 30 to 100 kg of these animals were recorded for genotype-trait association analysis.

SNP genotyping of GH, GHRH, LEP, PIK3C3 and MC4R genes

Total genomic DNA was extracted from tail tissue clippings using GeneJET Genomic ADN Purification Kit (Thermo Fisher Scientific, Vilnius, Lithuania) following the manufacturer’s instructions. The GH, LEP, PIK3C3 and MC4R polymorphisms were genotyped using PCR-restriction fragment length polymorphism (PCR-RFLP) method. The specific pairs of primers (Table 1) as described by Faria et al (2006), Szydlowski et al (2004), Kim et al (2005) and Kim et al (2006) were used to amplify target sequences. A PCR test was prepared with a total volume of 25µl media which included 12.5 µM DreamTaq PCR Master Mix 2X (Thermo Fisher Scientific) 0.4 µM each primers, and 100 ng DNA. The PCR thermo cycler was set for denaturation at 95oC for 3 min, 35 cycles of denaturation (95oC for 30 second), annealing (Tao for 45 second) and extension (72oC for 1 min), final extension at 72oC for 5 min. The PCR products of each gene were digested by corresponding restriction enzyme given in Table 1.

Statistical analysis

To evaluate the association between each genotype and ADG the general linear model (GLM) was used (Minitab 16, Minitab, LLC.) as follows.

Yijk = µ + Gi + SEj + G*SEij + Sk + eijk,

Where Yijk is the observed values of trait; µ is the least square mean; Gi is the effect of genotype; i of each gene (i = GH genotype: AA/GG/AG, GHRH genotype: AA/BB/AB, LEP genotype: TT/CT, PIK3C3 genotype: TT/CC/CT and MC4R genotype: AA/GG/AG); SEj is the effect of sex j (j = male and female); G*SEij is the effect of interaction between genotype and sex, Sk is the effect of sires and eijk is the random error.

Table 1. PCR and RFLP conditions

SNP
site

Primers

Ta
(oC)

PCR
size

Endonuclease

Ti
(oC)

Alleles

Source

GH
G361A

5’-TTATCCATTAGCACATGCCTGCC-3’
5’-CTGGGGAGCTTACAAACTCCTT-3’

62

605 bp

FokI

37

A: 605 bp
G: 345 bp, 260 bp

Faria et al (2006 )

LEP
T3469C

5’-GGGTCACCGGTTTGGACTTCATCC-3’
5’-GCCCAGGCTCTCCAAGGTCTCC-3’

67

230 bp

HinfI

37

C: 186 bp, 44 bp
T: 230 bp

Szydlowski et al (2004 )

PIK3C3
C2604T

5'-ATTTCGTCTAGACCTGTCCG-3'
5'-TGAATCTGTTCTACCACCGC-3'

62

102 bp

Hpy8I

37

C: 67 bp, 35 bp
T: 102 bp

J. Kim et al (2005 )

MC4R
G892A

5’-TACCCTGACCATCTTGATTG-3’
5’-ATAGCAACAGATGATCTCTTTG-3’

56

226 bp

TaqI

37

A: 226 bp
G: 156 bp, 70 bp

K. Kim et al (2006 )

Ta: Temperature annealing; Ti: Temperature incubation


Results

Allelic and genotypic frequencies

The results of the PCR-RFLP analysis of four candidate genes G361A(GH), T3469C (LEP), C2604T (PIK3C3) and G892A (MC4R) are showed in Figure (1-4). The fragment size corresponding to different genotype after digestion a PCR product by restriction enzyme of each polymorphism are similar to previous publications (Faria et al 2006; Szydlowski et al 2004; Kim et al 2005; Kim et al 2006).

Figure 1. Genotyping at G361A-GH polymorphic site by ForkI. Figure 2. Genotyping at T3469C-LEP polymorphic site by HinfI.


Figure 3. Genotyping at C2604T-PIK3C3 polymorphic site by Hpy8I. Figure 4. Genotyping at G892A-MC4R polymorphic site by TaqI.

After genotyping of 500 Duroc pigs, all four genes showed polymorphic in investigated loci. Allele and genotype frequencies of four SNPs G361A(GH), T3469C (LEP), C2604T (PIK3C3) and G892A (MC4R) were presented in Table 2. Frequencies of alleles at polymorphism sites G361A and G892A were nearly equal: A = 0.402 and G = 0.598 and A = 0.414 and G = 0.586, respectively. Meanwhile polymorphism C2604T PIK3C3 frequency of T allele was considerably less than that of C allele (T = 0.318 and C = 0.619). In T3469C polymorphism, frequency of C allele was very low with 0.021 due to the absence of homozygous CC in experimental population.

Table 2. Allele and genotype frequencies of each polymorphisms

Gene

Allele frequency

Genotype frequency

GH
G361A

A: 0.402
G: 0.598

AA: 0.150 (75)
AG: 0.504 (252)
GG: 0.346 (173)

LEP
T3469C

T: 0.979
C: 0.021

TT: 0.958 (479)
CT: 0.042 (21)

PIK3C3
C2604T

T: 0.381
C: 0.619

CC: 0.360 (180)
CT: 0.518 (259)
TT: 0.122 (61)

MC4R
G892A

A: 0.414
G: 0.586

AA: 0.160 (80)
AG: 0.508 (254)
GG: 0.332 (166)

Effects of SNPs on growth trait

To estimate the effect of individual polymorphisms on average daily gain trait, genotype-trait association analysis was performed separately for each substitution in Duroc pigs (Table 3). The results demonstrated that three out of four polymorphisms including G361A (GH), T3469C ( LEP) and G892A (MC4R) had significant associations with ADG. For polymorphism G361A at GH gene, pigs carrying GG genotype had the highest ADG (p<0.05). The highest means for ADG was observed in pigs carrying AA genotype at G892A (MC4R) polymorphism ( p<0.01). In LEP-T3469C locus, the daily gain of pigs with heterozygous CT was significantly greater than that of pigs with homozygous TT (p<0.01).

Table 3. The association of studied SNPs with average daily weight gain

SNP site

ADG (gam/day)ǂ
Genotypes

p values

GH
G361A

AA
n = 75

AG
n = 252

GG
n = 173

818.3ab ± 10.128

809.0b ± 6.365

832.3a ± 7.266

0.014

LEP
T3469C

TT
n = 479

CT
n = 21

817.1b ± 5.311

870.7a ± 20.238

0.008

PIK3C3
C2604T

TT
n = 61

CT
n = 259

CC
n = 180

829.0 ± 10.904

812.7 ± 6.444

822.7 ± 7.318

0.227

MC4R
G892A

AA
n = 80

AG
n = 254

GG
n = 166

853.3a ± 9.597

820.4b ± 6.364

790.4c ± 7.309

0.000

ǂ ADG, average daily gain during the test period (Least square mean values ± SE).
a, b, c: values within a row of table with different superscript differ significantly (p <0.05)


Discussion

The present study allows the detection of individual effects of SNPs on ADG in a commercial Duroc pigs population established in a Vietnamese pig breeding company.

The results demonstrated significant association between investigated SNPs (G361A of GH, T3469C of LEP and G892A of MC4R) and ADG trait in the experimental population. These results are also in accordance with previous studies. Effect of G361A on ADG trait was identified in various breed pigs such as Lithuanian White, old - type Lithuanian White, Large White, Landrace, Yorkshire and Large White hybrid (Bižienė et al 2011). In this study, the lowest daily gain was identified in AG genotype in GH gene, while AA genotype showed lowest values for ADG in the study of Bižienė et al (2011). The SNP G892A of MC4R was also reported to be associated with ADG in Duroc pigs (Kim et al 2006), in Large White pigs (Houston et al 2004) and in F2 Mangalitsa x Pietrain pigs (Meidtner et al 2006) In terms of mutation T3469C in LEP, the results of the analysis of the experimental pigs with CT genotype had higher ADG than those of pigs with TT genotypes, and these outcomes are consistent with previous studies in other pig populations such as Polish Landrace (Kulig et al 2001), Duroc (Urban et al 2002) and Mangalica x Duroc (Tempfli et al 2015). However, the study of Kennes et al (2001) on Landrace pigs reported an opposite trend as TT homozygous genotype had higher ADG than that of the CT heterozygous genotype. However, Hirose et al (2014) did not observe the a significant association between T3469C polymorphism of LEP gene with ADG (Hirose et al 2014). To explain the influence of these polymorphisms on ADG, two hypotheses were proposed. The first one is that these mutations effect directly on observed trait through increased or decreased synthesis of important proteins or involvement in different stages of gene expression process ( Faria et al 2006; Tempfli et al 2015). The second hypothesis is that polymorphisms have linkage disequilibrium with causal mutation for the trait (Faria et al 2006; Mankowska et al 2015; Tempfli et al 2015).

On the other hand, this study could not find any potential relationship of C2604T mutation of PIK3C3 with ADG. In contrast, Hirose and et al (2011) in Duroc pigs indicated that pigs carrying CC genotypes had greater ADG than pigs with TT genotypes. Another research in F2 pigs (Korean native x Landrace) also revealed the effect of C allele on the body weight at 30 weeks of age (Kim et al 2005).

The evaluation and comparison of our study with previous studies presents interesting results, but there are also notable differences in the association between candidate gene polymorphisms with ADG trait in studied the Duroc pig population. The cause of these differences probably related to variations in experimental design. That is the difference in size of samples and mating systems that have led to variations in allelic and genetic frequencies. Breeding season, the other effects of environmental factors and different statistical models could also increase or decrease the effect of genes on the ADG trait.


Conclusions


Acknowledgements

This work was financially supported by the Ministry of Science and Technology and Ministry of Agriculture and Rural Development.


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Received 6 July 2019; Accepted 14 September 2019; Published 2 October 2019

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