Abstract: The aim of this study was to investigate the rs16681031 SNP located in seed regions of chicken gga-mir-1658* gene with PCR-RFLP using PvuII nuclease in 6 chicken populations 180 individuals. The finding represents that genotype frequencies of the gga-mir-1658* gene C>G has significant differences in Beijing Fatty and other chicken breeds. Bioinformatics analyses indicated that gga-mir-1658* gene C>G polymorphism may alter target selection and secondary structure. The findings indicate that the rs16681031 SNP may exert profound biological effects in the formation of some special phenotype of chicken and enables functional annotation of gga-mir-1658* gene.

INTRODUCTION

The rs16681031 SNP is located in seed regions of chicken gga-mir-1658* gene which resides in the intron 13 of Guanine Monphosphate Synthetase (GMPS) gene (Griffiths-Jones et al., 2008). Many evidences indicated that microRNA-SNPs may modify various biological processes by influencing the processing and/or target selection of microRNAs having long ranging phenotypic effects (Mishra et al., 2008; Sun et al., 2009). This SNP has not been studied in details so far. Therefore, the objectives of the present study were to elucidate the effect of the rs16681031 SNP on pre-gga-mir-1658*'s secondary structure, investigate the distribution of the C>G polymorphisms of gga-mir-1658* gene among six chicken populations and identify putative target genes of gga-mir-1658* gene.

MATERIALS AND METHODS

DNA samples: A total of 180 samples were obtained from 6 breeds including 30 Beijing Fatty chickens (BF), 30 Jiningbairi chickens (JB), 30 Langya chickens (LY), 30 Siyuwugu chickens (WG) (30), 30 Wenshangluhua chickens (WL) and 30 Leghorn chicken (LH). Genomic DNA was extracted from chicken venous blood through classical phenol-chloroform method.

PCR-RFLP: A 239-base pair (bp) fragment of the gga-mir-1658* gene was amplified using forward (5'-ATAC CAGTGTGTGTTTCTCACA-3') and reverse (5'-GCCTCA CAGCAGGATTTACT-3') primers. The PCR reaction volume of 25 μL contained approximately 50 ng of genomic DNA, 1.25 mM Taq DNA polymerase, 2.5 μL of 1xPCR buffer, 1.5 mM MgCl₂, 0.2 mM dNTP and 10 pM of each primer. Amplification conditions included an initial denaturation at 94°C for 4 min followed by 35 cycles at 94°C for 30 sec, 58°C for 30 sec and 72°C for 30 sec, followed by a final extension at 72°C for 10 min. The gga-mir-1658* gene PCR product was digested was digested with 10 units of PvuII restriction enzyme and 10 μL of PCR product at 37°C overnight in a water bath. The digested products were detected by electrophoresis in 3.5% agarose gel stained with Ethidium Bromide (EB).

Secondary structure alterations of variant gga-mir-1658* precursors: The most stable secondary RNA structure with the lowest free energy for pre-gga-mir-1658* with G>C alleles were calculated using Mfold (Zuker, 2003). The absolute difference of free energy for pre-gga-mir-1658* with different alleles were used as the parameter for the assessment of the impact on secondary structure of pre-gga-mir-1658*.

Impact of SNP on gga-mir-1658* target genes: The chicken Unigene (NCBI) was scanned for potential gga-mir-1658* targets using the miRanda algorithm (version 3.1) (Enright et al., 2003) with the default parameters for score threshold (>130) and free energy threshold (<-16). The predicted targets were further filtered using more stringent criteria in which they must contain either:

Statistical methods: The allelic frequencies were tested using the PopGene v.3.1 (Yeh et al., 1999). The heterogeneity between population samples was evaluated by Fisher’s exact test. A p<0.05 was considered statistically significant.

RESULTS AND DISCUSSION

RFLP: The profile of gga-mir-1658* gene G>C polymorphism is shown in gel photograph (Fig. 1). After digestion, the CC genotype had 176 bp and 61 bp bands, the GC genotype had 176, 61, 41 and 20 bp bands and the GG genotype had a 176, 41 and 20 bp bands.

Allele frequency, genetypic frequency: gga-mir-1658* genotypes and alleles frequencies detected by PCR-RFLP in 6 chicken breeds were shown in Table 1. In 6 breeds most had 2 alleles A and G, 3 genotypes AA, AG and GG except WG chicken. The lowest frequency of the G allele was found in the WL (0.1833) and in the highest frequency in the BF (0.8000). In addition, the results of Fisher’s exact test indicated that there was a significant difference for allele frequencies of G>C of the gga-mir-1658* gene between the BF and other chicken breeds (p<0.01 or p<0.05).

Secondary structure alterations of variant gga-mir-1658* precursors: The G>C located in the seed region of gga-mir-1658* could introduce a base-pairing mismatch, alter free energy values create a new RNA bulge and alter the predicted RNA secondary structure with Mfold program (Fig. 2).

Impact of SNP on gga-mir-1658* target genes: The SNP is located in the crucial seed sequence of gga-mir-1658* gene so it determines its complementarity to potential target genes affecting the functionality of both isoforms. Using the miRanda software, researchers predicted to have profoundly different target genes (82 genes for gga-mir-1658*-G and 67 genes for gga-mir-1658*-C) with only PRPS2 and VSX1 genes being shared by the two isoforms (Fig. 3 and Table 1). Of note, one of the shared genes both PRPS2 and GMPS which gga-mir-1658* hosted gene are involved in the purine metabolism processes (Kanehisa et al., 2010).

Fig. 1:	PCR-RFLP patterns of the chicken gga-mir-1658*, M = Marker 50 bp ladder

Fig. 2:	The predicted structure of pre-gga-mir-1658* (a) gga-mir-1658*-G, ΔG = -36.10 kcal moL-1 (b) gga-mir-1658*-C, ΔG = -40.80 kcal moL-1

Fig. 3:	Target genes of the mature products of gga-mir-1658*

MicroRNAs comprise a growing class of non-coding RNAs that are believed to regulate gene expression via translational repression. Sequence variations within the microRNA genes could potentially influence the processing and/or target selection of microRNAs. Recently, Mir-146a-SNP (rs2910164) within the pre-miR-146a sequence reduced both the amount of pre-miR-146a and mature miR-146a and apparently affected the Drosha/DGCR8 processing step (Jazdzewski et al., 2008). In current study, researchers perform a systematic analysis of SNPs associated with gga-mir-1658* gene. The results suggest that the gga-mir-1658* SNP have a larger impact on secondary structure and may alter the maturation of gga-mir-1658*. Additionally, researchers also found the SNP would theoretically alter gga-mir-1658*s targets selection and >145 different mRNAs were predicted.

Table 1:	Allele frequencies, genetypic frequencies and the p value of Fisher’s exact test of gga-mir-1658* gene in 6 chicken breeds

Table 2:	Impact of SNP on gga-mir-1658* target genes

From the result of genetic polymorphism at gga-mir-1658* were found to differ significantly in 6 typical chicken breeds. This result has provided instructive significance for study the phenotypic differences between BF chickens and other populations.

CONCLUSION

Findings presented in this study indicated that the rs16681031 SNP in seed regions of chicken gga-mir-1658* gene may be a functional sites which plays an important roles in the formation of some special phenotype of BF chicken. Furthermore, the bioinformatics analysis also provides a basis for functional annotation of gga-mir-1658* gene orthologs in other species.

ACKNOWLEDGEMENTS

This research was supported by National Science Foundation for Youths (No. 31001003), Natural Science Foundation of Hebei Province (No. C2008001308) and Supported by Natural Science Foundation for Higher Education of Hebei Province (No. C2010129).