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Journal of Heredity Advance Access originally published online on November 2, 2005
Journal of Heredity 2005 96(6):698-703; doi:10.1093/jhered/esi114
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High Diversity of the Chicken Growth Hormone Gene and Effects on Growth and Carcass Traits

Q. Nie, B. Sun, D. Zhang, C. Luo, N. A. Ishag, M. Lei, G. Yang, and X. Zhang

From the Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong, China

Address correspondence to X. Zhang at the address above, or e-mail: xqzhang{at}scau.edu.cn.


   Abstract
Top
 Abstract
Materials and Methods
 Results
 Discussion
 References
 
The chicken growth hormone (cGH) gene plays a crucial role in controlling growth and metabolism, leading to potential correlations between cGH polymorphisms and economic traits. In this study, DNA from four divergent chicken breeds were screened for single nucleotide polymorphisms (SNPs) in the cGH gene using denaturing high-performance liquid chromatography and sequencing. A total of 46 SNPs were identified, of which 4 were in the 5' untranslated region, 1 in the 3' untranslated region, 5 in exons (two of which are nonsynonymous), with the remaining 36 in introns. The nucleotide diversity in the cGH gene ({theta} = 2.7 x 10–3) was higher than that reported for other chicken genes, even within the same breeds. The associations of five of these SNPs and their haplotypes with chicken growth and carcass traits were determined using polymerase chain reaction–restriction fragment length polymorphism analysis in a F2 resource population cross of two of the four chicken breeds (White Recessive Rock and Xinghua). This analysis shows that, among other correlations, G+1705A was significantly associated with body weight at all ages measured, shank length at three of four ages measured, and average daily gain within weeks 0 to 4. Thus, this cGH polymorphism, or another polymorphism that is in linkage disequilibrium with G+1705A, appears to correspond to a significant growth-related quantitative trait locus difference between the two breeds used to construct the resource population.

The chicken growth hormone (cGH) gene is considered one of the most important candidate genes that can influence chicken performance traits because of its crucial function in growth and metabolism (Byatt et al. 1993; Copras et al. 1993; Vasilatos-Younken et al. 2000). First isolated and sequenced by Lamb et al. (1988), polymorphisms in the cGH gene were widely studied by restriction fragment length polymorphisms (RFLPs) or sequencing. The gene encodes a 191–amino acid mature growth hormone protein and a 25–amino acid signal peptide. The cGH gene has 4,101 base pairs and consists of five exons and four introns, differing in this regard from its mammalian counterpart (Mou et al. 1995; Tanaka et al. 1992). A 50 bp deletion in intron 4 of the cGH gene was found in Chinese native Taihe Silkies chickens (Nie et al. 2002). The cGH gene in another native breed, Yellow Wai Chow, was found to have one silent substitution, 31 insertions, and other substitutions spread among the introns (Ip et al. 2001). A novel MspI site in the first intron (Ip et al. 2001) and a SacI and three MspI polymorphic restriction sites were also detected in the cGH gene (Fotouhi et al., 1993). A SacI polymorphism in the fourth intron of the gene was reported to be associated with the number of tissues with tumors in Marek's disease virus-infected White Leghorn chickens (Liu et al. 2001). Selection for abdominal fat appears to affect allele frequencies, and some alleles of these RFLPs were associated with juvenile body weight, egg weight, and egg-specific gravity (Feng et al. 1997; Fotouhi et al. 1993; Kuhnlein et al. 1997). Considerable diversity in the cGH gene existed between Chinese native breeds and commercial breeds such as Avian Parental, Arbor Acre broilers, and Hy-Line layers (Ip et al. 2001; Nie et al. 2002). Chinese native chickens are genetically diverse (Zhang et al. 2002) and have distinctive characteristics, including differences in feather color, growth rate, meat characteristics, and reproductive performance.

Most of the variations in a gene are single nucleotide polymorphisms (SNPs) arising from substitution, deletion, or insertion of a single nucleotide. A single SNP can greatly affect performance traits. For example, the sex-linked dwarf allele in chickens is a single nucleotide mutation at an exon-intron junction of the GH receptor gene (GHR; Huang et al. 1993). Recently, significant progress has been made in associating quantitative trait loci (QTL) with SNPs in domestic animals. Van Laere et al. (2003) showed that a QTL for muscle growth in pigs was caused by a nucleotide substitution in intron 3 of the insulin-like growth factor 2 gene (IGF2). Amills et al. (2003) identified three SNPs in chicken IGF1 and IGF2 that were associated with growth and feeding traits. SNPs can be genotyped with many techniques (Vignal et al. 2002). Denaturing high-performance liquid chromatography (DHPLC) is a highly sensitive and automated method based on the capability of ion-pair reverse-phase liquid chromatography to resolve homoduplex from heteroduplex molecules under conditions of partial denaturation, and it has proven to be an efficient method for discovering and genotyping SNPs (Abbas et al. 2004; Han et al. 2004; Nie et al. 2004). In the present study, the cGH gene was scanned for SNPs in 40 individuals of four different chicken breeds. Associations of these SNPs and their haplotypes with growth and carcass traits were analyzed in a F2 resource population derived from a cross of a fast-growing line, White Recessive Rock (WRR), and a slow-growing line, Xinghua (X).


   Materials and Methods
Top
 Abstract
 Materials and Methods
Results
 Discussion
 References
 
Chicken Populations
Leghorn (L), WRR, Taihe Silkies (TS) and X chickens with different growth rates and morphological characteristics were used to screen for SNPs in the cGH gene. Genomic DNA of 10 individuals in each breed was extracted from EDTA-anticoagulated blood. Both TS and X are Chinese native breeds with slow growth rates. A F2 resource population was constructed by crossing the WRR and X breeds to analyze the association between cGH SNPs and chicken growth and carcass traits. Nine WRR males were crossed to nine X females, and six WRR females were crossed to six X males, producing 17 F1 families and 454 F2 full-sib individuals. F2 chickens were raised in floor pens and fed with commercial corn- and soybean-based diets that met all National Research Council requirements. Body weight (BW) and shank length (SL) at different ages were recorded, along with hatch weight (HW) and average daily gain from 0 to 4 weeks of age (ADG0-4). All chickens were slaughtered at 90 days of age, and carcass traits were measured—including abdominal fat weight (AFW), small intestine length (SIL), cross-sectional area of leg muscle fiber (LA), and fat content of leg muscle (LFC). LFC was determined by the Soxtec system HT 1043 extraction unit (Tecator, Sweden).

Polymerase Chain Reaction Amplification, SNP Detection by DHPLC, and Sequencing Confirmation
Primers 101–109 of Nie et al. (2005) were used to amplify the full length of the cGH gene, and primer PM3, as described by Kuhnlein et al. (1997), was used to detect their reported polymorphisms in the cGH gene (Figure 1). Polymerase chain reaction (PCR) reactions and DHPLC analysis were performed and analyzed as described previously (Nie et al. 2005). According to the DHPLC profiles, representative PCR products with different mutations were purified and sequenced by BioAsia Biotechnology (Shanghai, China). For each PCR product, both forward and reverse sequencing were conducted. The sequencing results were analyzed with BLAST implemented in the DNASTAR program (http://www.biologysoft.com).



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  		Figure 1.. Location of primers 101–109, PM3 in the chicken growth hormone gene.

 
PCR-RFLP Analysis of F2 Individuals in the Resource Population
Among the 46 SNPs found in the cGH gene, C-121T, G+119A, G+1705A, and G+3037T were in restriction sites for PagI, MspI, EcoRV and Bsh1236I, respectively. Another SNP, C+385T, reported by Fotouhi et al. (1993) and Kuhnlein et al. (1997) and confirmed in the draft sequence of the chicken genome (http://www.genome.wustl.esu/projects/chicken/; nt 144843 of chromosome 27), was also assayed in this study by MspI digestion. After amplification with primer pairs 101 (for C-121T), 151 (for G+119A and C+385T), 105 (for G+1705A), and 108 (for G+3037T), PCR products were digested at 37°C overnight with PagI, MspI, EcoRV, and Bsh1236I, respectively. The digestion mixture contained 8 µL PCR products, 1x digestion buffer, and 3.0 units of enzyme. All 454 F2, 34 F1 and 30 F0 individuals in the full-sib resource population were genotyped.

Statistical Analysis
To estimate the nucleotide diversity of the cGH gene, the normalized numbers of variant sites ({theta}) was calculated as the number of observed nucleotide changes (K) divided by the total sequence length in base pairs (L), corrected for sample size (n), as described by Cargill et al. (1999).

Five SNPs—C-121T, G+119A, C+385T, G+1705A, G+3037T—were used to reconstruct haplotypes with PHASE 2.0 software (Stephens et al. 2001). Marker-trait linkage analysis was performed by the SAS GLM procedure (SAS Institute 1996), and the genetic effects were analyzed using the following mixed model:

where Y is a trait observation, µ is the overall population mean, G is the fixed effect of genotype, D is the random effect of dam, H is the fixed effect of hatch, S is the fixed effect of sex (male or female), and e is the residual random error.


   Results
Top
 Abstract
 Materials and Methods
 Results
Discussion
 References
 
SNPs and Nucleotide Diversity of the cGH Gene
PCR amplification of the cGH gene surveyed a region of 3,948 bp in four chicken breeds, 10 individuals from each breed. Forty-six SNPs were found (Table 1), or one SNP per 86 bp on average. Most of these SNPs (36 of 46) were located in introns, with four in the 5'UTR, one in the 3'UTR, and five in coding exons. Two of the five coding SNPs led to amino acid changes. All 46 SNPs were nucleotide substitutions, and transitions (38) occurred more frequently than transversions (8). One of two nonsynonymous coding SNPs (G+951A) altered an amino acid in the cGH precursor (A13T), and the other (G+1532A) changed an amino acid in the mature cGH (R59H).


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  		Table 1.. Single nucleotide polymorphisms (SNPs) detected by denaturing high-performance liquid chromatography and sequencing in the chicken growth hormone gene

 
The adjusted nucleotide ({theta}) diversity of the total cGH gene was 2.7 x 10–3 overall, whereas it was 3.1 x 10–3 within introns. When compared with some other chicken genes—such as GHR, ghrelin, the growth hormone secretagogue receptor (GHSR), IGF1 and IGF2, the insulin-like growth factor binding protein 2 (IGFBP-2), the leptin receptor (LEPR), the pituitary-specific transcription factor-1 (PIT-1), the bone morphogenetic protein receptor type II (BMPR2), and the phosphoenolpyruvate carboxykinase-C (PEPCK-C) gene—the nucleotide diversity of the cGH gene was somewhat higher (Table 2), even within a similar base populations (Nie et al. 2005).


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  		Table 2.. Nucleotide diversity of the chicken growth hormone gene and others reported in chicken

 
Associations of Single SNP With Chicken Growth and Carcass Traits
Association analysis of cGH SNP with chicken growth and carcass traits in a F2 reciprocal cross between the WRR and X breeds showed that genotypes at C-121T were significantly (P < .05) associated with LA and LFC and with SL at the ages of 70 and 84 days. SNP G+119A was significantly associated with AFW and highly significant (P < .01) with SIL. No significant associations between C+385T and any growth-related traits were observed. SNP G+1705A was significantly associated with BW at the ages of 14, 35, 42, 49, 63, 77 days and with SL at the ages of 49, 56, and 84 days and highly significant with BW21, 28, 70, 84, and ADG0-4. Finally, SNP C+3037T was significantly associated with HW and highly significant with SL70 and SL84 (Table 3). The effect of the G+1705A SNP genotype on the various BW, SL traits, and ADG0-4 appeared to be additive, although in some cases the heterozygous (AG) trait measure did not significantly differ from one or both homozygotes (Table 4). For all the traits listed, the AA homozygote differed from the GG homozygote at the significant or highly significant level.


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  		Table 3.. The probability of associations (P value) of polymorphisms in five single SNPs (single nucleotide polymorphisms) and their haplotypes with growth and carcass traits

 

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  		Table 4.. Differences in growth and body composition traits between chickens with different genotypes of G+1705A

 
Haplotype Reconstruction and Linkage Analysis
When considering these five cGH SNPs as a whole, we found 15 haplotypes of H1–H15 and 44 diplotypes in our F2 reciprocal cross. Of these 15 haplotypes, H1 (C/G/T/G/G) and H2 (C/A/T/G/G) were the most common, at frequencies of 32% and 23%, respectively, whereas H8 (C/G/T/G/T), H9 (T/G/T/G/G), H10 (T/G/T/G/T), H11 (C/A/T/A/T), and H12 (C/G/T/A/G) were minor haplotypes, with frequencies of less than 5%; H13 (C/G/C/G/T), H14 (T/A/T/G/G), and H15 (C/G/C/A/G) were rare (1%). Linkage analysis showed that diplotypes based on all haplotypes were significantly associated with only BW14 (P < .05). However, significant associations of diplotypes with SL84 (P < .05) and LA (P < .01) were observed when considering the major haplotypes with frequencies more than 5% (Table 3).


   Discussion
Top
 Abstract
 Materials and Methods
 Results
 Discussion
References
 
The diversity of the cGH gene detected in this study was substantial. In the past, only a few cGH SNPs (i.e., G+119A, C+385T, T+2551C, and T+2556C) had been found (Fotouhi et al. 1993; Kuhnlein et al. 1997; Liu et al. 2001; Nie et al. 2002), and no variation had been reported in its 5'-regulatory region (Zhang et al. 1998). In this study, 46 point mutations were identified across the whole cGH gene within four divergent chicken breeds (Table 1). The nucleotide diversity of the cGH gene (corrected {theta} = 2.7 x 10–3) was higher than those of several other chicken genes (Table 2), even when those genes were sampled in the same four breeds (Nie et al. 2005). Furthermore, after correcting for sample size, the {theta} value of the cGH gene was higher than those reported in chickens (Schmid et al. 2000; Vignal et al. 2000), humans (Cargill et al. 1999), pigs (Jungerius et al. 2003), and cattle (Heaton et al. 2001). The high diversity of the cGH gene appears to be confirmed in a preliminary genome-wide scan for chicken SNPs that reported 2.8 million SNPs across the whole chicken genome, with 23 SNPs located in the region (chr27: 141644–145748) of the cGH gene (International Chicken Polymorphism Map Consortium 2004).

It was interesting that G+1705A was significantly associated with almost all growth traits (Table 3), with the A allele exhibiting a generally positive effect on chicken growth (Table 4). This was consistent with the higher A frequencies in F0 chickens of WRR than in those of X, even though G was still the dominant allele in both breeds and, therefore, fewer F2 individuals with AA genotype (18) were generated. Previous studies on other polymorphisms in introns of the cGH gene indicated associations with chicken growth, fat deposition, and egg production (Feng et al. 1997; Fotouhi et al. 1993; Kuhnlein et al. 1997). A recent study showed that a single mutation in intron 3 of the IGF2 gene encoded a major QTL affecting pig muscle growth (Van Laere et al. 2003). As in this case, the G+1705A in intron 3 of cGH could have a direct effect on chicken growth via an influence on cGH gene expression. On the other hand, the G+1705A cGH polymorphism may be in linkage disequilibrium with some other causative polymorphism that influences growth traits in our resource population. The other four cGH SNPs that we tested may fail to exhibit this level of disequilibrium with the growth trait QTL due to their different respective histories within the two parental breeds employed. Further analysis will be required to differentiate between these possibilities.


   Acknowledgments
 
This work was funded by project under the Major State Basic Research Development Program, China, project G2000016102. Dr. Y. Da in the University of Minnesota, Minnisapolis, gave helpful suggestions on resource population construction.


   Footnotes
 
Corresponding Editor: Jerry Dodgson

Received May 17, 2005
Accepted September 21, 2005


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