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Frontiers of Agriculture in China

ISSN 1673-7334

ISSN 1673-744X(Online)

CN 11-5729/S

Front Agric Chin    2009, Vol. 3 Issue (3) : 319-324     DOI: 10.1007/s11703-009-0048-4
RESEARCH ARTICLE |
Variation of 184C→T of goat callipyge gene in different populations and its effect on body weight
Xianglong LI(), Hailiang WANG, Rongyan ZHOU, Guiru ZHENG, Lanhui LI, Zunan SHEN
College of Animal Science and Technology, Agricultural University of Hebei, Baoding 071000, China
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Abstract  

In order to investigate its distribution in different goat populations, one SNP (184C→T, corresponding to AY850925) of goat callipyge (CLPG) gene recognized by Fork I was identified after sequencing 23 individuals from 10 breeds. PCR-RFLP was carried out according to the variation site in 584 goats of 14 populations from 11 provinces and autonomous regions in China. An interesting result was found that the Boer goat having the characteristics of double muscle had significantly higher T allele (0.2465) frequency and lower C allele (0.7535) frequency compared to other breeds. It could be inferred that the 184C→T mutation might be related to the double muscle characteristics of the Boer goat. The general linear model analysis showed that parental genotype had significant effect on the body weight of their offspring at different ages. It could be inferred that transition of 184C→T might be a paternal imprinting form, a polar over-dominance, in which only individuals that received the allele from their mother expressed the callipyge phenotype. The double muscle characteristics of the Boer goat might be related to its maternal genotype. More data with detailed information need to be investigated in order to confirm this assumption.

Keywords goat      callipyge      184C→T      double muscle      body weight     
Corresponding Authors: LI Xianglong,Email:lixianglongcn@yahoo.com   
Issue Date: 05 September 2009
URL:  
http://academic.hep.com.cn/fag/EN/10.1007/s11703-009-0048-4     OR     http://academic.hep.com.cn/fag/EN/Y2009/V3/I3/319
groupbreedlocation(province)num.genotypefrequency/%
CCCTTTCT
northLiaoning cashmere goatLiaoning7171001.0000aA0
Jining grey goatShandong6964500.9637aA0.0363
Chengde polled goatHebei5555001.0000aA0
Taihang mountain goatHebei3333001.0000aA0
Inner Mongolia cashmere goatInner Mongolia2218400.9091a0.0909
Shannan white goatShanxi2020001.0000aA0
southChengdu brown goatSichuan5454001.0000aA0
Nanjiang brown goatSichuan6156500.9590aA0.0410
Guizhou white goatGuizhou3030001.0000aA0
Yichang white goatHubei1816200.9446a0.0554
Duan goatGuangxi1917200.9473a0.0527
Guizhou black goatGuizhou2524100.9800aA0.0200
Leizhou goatGuangdong3635100.9861aA0.0139
foreignBoer goatHebei71432170.7535bB0.2465
total584536417--
Tab.1  Distribution of genotypes and alleles in different populations
Fig.1  Alignment of varied individuals, SNP identification and PCR-RFLP by Fork I
Note: (a) represents the alignment of varied individuals. (b) represents the result of PCR-RFLP by Fork I. M refers to DNA marker. Lane 1 illustrates PCR products of . Lanes 2, 3, 5 and 6 illustrate genotype CC with bands of 444 bp and 49 bp (invisible). Lanes 4, 7, 9 and 10 illustrate genotype CT with bands of 444 bp, 250 bp, 194 bp and 49 bp (invisible). Lane 8 illustrates genotype TT. (c), (d) and (e) are SNP identification for genotype TT, CC and CT (Y), respectively.
traitmodelBSTPMP*MGR2
BW0/kg0.0000.0000.0250.0000.0130.0030.0400.4510.977
BW1/kg0.0000.0010.0300.0000.0430.0080.0110.2340.979
BW2/kg0.0000.0040.0310.0000.0410.0060.0460.3670.981
BW3/kg0.0000.1080.2130.0000.0460.0080.0390.5560.978
BW4/kg0.0000.0840.4360.0000.0330.0140.0440.4150.975
BW8/kg0.0000.6530.2200.0040.0460.0310.0360.5910.969
BW12/kg0.0000.9700.2000.0080.0350.0380.0410.6010.964
BW16/kg0.0000.4300.1330.0030.0380.0440.0380.4550.971
Tab.2  The effects ( values) of the model and factors included in the model
traiteffect of paternal genotypeeffect of maternal genotypeeffect of individual genotype
CCCTCCCTCCCT
BW0/kg3.61 ± 0.10 (148)a3.17 ± 0.16 (43)b3.13 ± 0.23 (73)A3.65 ± 0.11 (66)B3.43 ± 0.15 (123)3.57 ± 0.18 (36)
BW1/kg5.96 ± 0.31 (138)a4.02 ± 0.31 (38)b4.48 ± 0.31 (70)A5.18 ± 0.30 (58)B4.53 ± 0.19 (118)5.02 ± 0.22 (35)
BW2/kg6.96 ± 0.29 (133)a5.05 ± 0.32 (38)b5.34 ± 0.32 (69)A6.17 ± 0.28 (58)B5.48 ± 0.23 (118)6.03 ± 0.26 (35)
BW3/kg7.17 ± 0.37 (131)a6.36 ± 0.41 (37)b6.22 ± 0.42 (68)A7.30 ± 0.36 (58)B6.55 ± 0.30 (118)6.97 ± 0.33 (35)
BW4/kg8.95 ± 0.46 (131)a7.86 ± 0.52 (37)b7.81 ± 0.52 (68)a8.99 ± 0.45 (58)b7.68 ± 0.37 (118)8.45 ± 0.42 (35)
BW8/kg13.20 ± 0.84 (131)a11.42 ± 0.90 (37)b11.41 ± 0.92 (66)a13.21 ± 0.78 (53)b12.06 ± 0.63 (115)13.02 ± 0.72 (35)
BW12/kg16.28 ± 1.20 (125)a14.09 ± 1.31 (33)b14.92 ± 1.17 (61)a16.95 ± 1.15 (47)b15.81 ± 0.91 (109)16.98 ± 1.01 (33)
BW16/kg20.73 ± 1.34 (108)a17.31 ± 1.54 (26)b18.32 ± 1.62 (50)a20.97 ± 1.28 (42)b18.99 ± 1.05 (95)19.80 ± 1.64 (30)
Tab.3  Pair wise comparisons between estimated marginal means of body weight at different ages from paternal, maternal and individual genotypes
traitmating type
CC(P)×CC(M)CC(P)×CT(M)CT(P)×CC(M)CT(P)×CT(M)
BW0/kg3.49 ± 0.14 (41)b3.72 ± 0.12 (43)b2.46 ± 0.24 (33)a3.58 ± 0.19 (11)b
BW1/kg5.01 ± 0.29 (41)b5.26 ± 0.25 (43)b3.28 ± 0.35 (31)a5.08 ± 0.33 (11)b
BW2/kg5.92 ± 0.35 (40)b6.20 ± 0.29 (43)b4.36 ± 0.41 (31)a6.04 ± 0.39 (11)b
BW3/kg6.81 ± 0.47 (40)b7.52 ± 0.37 (43)b5.13 ± 0.52 (31)a7.08 ± 0.50 (11)b
BW4/kg8.52 ± 0.57 (40)b9.37 ± 0.47 (42)b6.19 ± 0.66 (31)a8.62 ± 0.64 (11)b
BW8/kg12.26 ± 1.04 (40)a15.14 ± 0.84 (42)b11.55 ± 1.14 (31)a12.28 ± 1.09 (11)a
BW12/kg14.02 ± 1.49 (37)a18.74 ± 1.20 (38)b13.32 ± 1.62 (30)a14.36 ± 1.65 (10)a
BW16/kg18.39 ± 1.72 (33)a22.07 ± 1.09 (36)b17.25 ± 2.11 (29)a18.38 ± 2.23 (10)a
Tab.4  Interaction between paternal and maternal genotype
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