ГЕНЕТИКА, 2015, том 51, № 3, с. 371-378


УДК 575.17:599.731.1


© 2015 Y. Long1, *, G. R. Ruan2, *, Y. Su1, S. J. Xiao1, Z. Y. Zhang1, J. Ren1, N. S. Ding1, and L. S. Huang1

1 Key Laboratory for animal biotechnology of Jiangxi province and the ministry of agriculture of China, Jiangxi agricultural university, Nanchang 330045, P.R. China e-mail: dingyd2005@hotmail.com 2Fujian vocational college of agriculture, Fuzhou, 360119, P.R. China Received March 28, 2014

Backfat thickness (BFT) and average daily gain (ADG) are two important economic traits in commercial swine production. Identifying QTLs and uncovering the molecular mechanism for BFT and ADG would greatly help to speed up the breeding progress. In current breeding program, EBV for these two traits are calculated and formulated a comprehensive breeding index, which then be used to improve pig performance. Using Illumina PorcineSNP60 BeadChip, a pilot genomewide association studies (GWAS) for BFT and ADG in 83 Duroc pigs were performed. A total of 31 genome-wise significant SNPs were detected to be associated with BFT on SSC 4, 9, 11, 12 and 14, ten of which were coincident with previously reported QTL regions. There are two genome-wise loci prominently associated with ADG on SSC2 and SSC13, respectively. The two loci on SSC2 are well overlapped with the QTL regions previously reported. All the 31 significant SNPs associated with BFT are verified on 219 outbreed pigs, six SNPs reach an extreme significant level and seven SNP reaches a significant level, CACNA1E and ACBD6 are chosen as positional candidate genes. Our findings not only confirmed previously findings, but also revealed a number of novel SNPs associated with BFT and ADG. Two positional candidate genes CACNA1E and ACBD6were identified for further study. These results would facilitate the identification of causative genes for BFT and ADG.

DOI: 10.7868/S0016675814100087

The domestic pig has undergone a long history of extensive natural and artificial selection to meet human dietary needs [1]. In the past decades, conventional genetic improvement was mainly relying on EBV, phenotype, and pedigree information. With the development of modern biotechnology, it is possible to further increase the rate of genetic improvement by understanding the interplay between genetic and environmental factors controlling complex agriculturally important production traits [2]. This information could be integrated with marker-assisted selection (MAS) schemes to increase selection accuracy, shorten generation interval, and accelerate genetic improvement.

Many QTL associated with pig economically important traits have been detected since the 2000s [3]. BFT and ADG are both important economical traits in pig breeding. The heritability of BFT ranges from 0.27 to 0.83 [4-7]. While the heritability of ADG ranges from 0.32 to 0.38 [4, 8]. To date, a total of 210 and 229 QTLs associated with BFT and ADG have been reported respectively (http://www.animalge-nome.org/cgi-bin/QTLdb/SS/browse). But there

*Both authors contributed equally to this study and should be considered as co-first authors.

were still no conclusive results showing functional mutations or causal genes affecting BFT and ADG.

With the development of sequencing technology, SNP have been widely used for the detection and localization of QTL for complex traits in many species [9—14]. The objective of this study was to perform a GWAS with the porcine 60K SNP BeadChip and to identify candidate SNPs/genes and chromosomal regions associated with BFT and ADG, which could be used in MAS and genomic selection. Furthermore, this study could contribute to better understand the genetic control of BFT and ADG in pigs.


Animals and phenotypes for GWAS. A total of 83 duroc belong to 25 families were collected from the breeding stock field of WENS Group, BFT was measured between the 10th and 11th rib of pigs at the weight of100 ± ± 5 kg, using the B ultrasound, machine Preg-Alert Pro (Renco Corporation, Minneapolis, MN 55401 USA). ADG is the average daily gain during the period of birth weight to 100 ± 5 kg.

The EBV rather than raw phenotypes was estimated for the GWAS. EBV has the advantage that they are free of systematic environmental effects on measured

Table 1. Descriptive statistics for traits measured

Trait N Mean SD Min Max


BFT 83 -0.43 0.58 -2.01 0.76

ADG 83 9.64 24.53 -22.38 45.82


BFT 219 -0.04 0.70 -1.69 3.21

Notes: Combined: are consisted of 15 Duroc, 69 Landrace, and 135 Yorkshire. BFT, backfat thickness; ADG, average daily gain; Min, minimum; Max, maximum.

phenotypes, as these effects are considered in the statistical model used for estimation of EBV. Additionally, they reflect the genetic makeup more accurately because they do not solely rely on its own records but in-


Histogram of BFTEBV

-1.5 -1.0 -0.5 0 BFTEBV (b)

Histogram of ADGEBV


0.02 -


e De

0.01 -

0 -


Fig. 1. The distribution of EBV for backfat thickness (BFT) (a) and average daily gain (ADG) (b). The p-value is 0.2413 for histogram of BFT and 0.5559 for ADG.

clude information from all measured relatives [15]. The calculation of EBV is listed below:

EBV = bAP(P* - P),

b = rAnh2 AP 1 + ( n - 1 ) r,

n is the number of individuals in the same population, rA is the relationship coefficient of the individuals which provide information and the evaluated individuals, r is repetitive rate and P is the phenotype.

The mean of BFT (EBV) and ADG (EBV) was —0.43 and 9.64 with a standard deviation of 0.58 and 24.53, respectively (Table 1). The density distribution of values for BFT (EBV) (Fig. 1a) and ADG (EBV) (Fig. 1b) were not significantly deviated from normal distribution.

Animals and phenotypes for verification. Additional 219 pigs (also genotyped on Illumina Beadchip), including 15 Duroc, 69 Landrace and 135 Yorkshire that collected from 72 families in 4 national pig nuclear breeding farms were used for the verification test of significant SNPs for BFT. The measurement standard of BFT is the same with the previous methods used for the 83 Duroc. The mean of BFT (EBV) of 219 pigs are —0.04 with a standard deviation of 0.70 (Table 1).

Genotyping and quality control. DNA was collected from ear tissue using the conventional methods of phenol-chloroform extraction and normalized to 50 ng/^L. The DNA quality was assessed by 260/280 and 260/230 ratios and electrophoresis. Genotyping was performed using the porcine SNP60K Beadchip of Illumina (San Diego, CA, USA) according to Antonio et al. [16]. A total of 83 samples (including sires and dams) were genotyped. Quality control (QC) was performed with MAF > 0.05, call rate per individual >90%, HWE > 0.01, Missing rate per SNP < 10% using PLINK v. 1.07 [http://pngu.mgh.harvard.edu/pur-cell/plink/]. Following the quality control, 83 individuals and 37,478 SNPs were selected for the GWAS.

Genome-wide association study. GWAS was performed using Wald test in the software described above. The phenotype difference among different genotypes was tested. BFT and ADG were analyzed using the linear regression framework. Linkage disequilibrium (LD) between SNPs was quantified as r2 on all animals



1 2 3 4 5 6 7 8 9 10 12 14 15 16 18 X




1 2 3 4 5 6 7 8 9 10 12 14 15 16 18 X


Fig. 2. Genome wide association study for EBV of Backfat thickness (BFT) (a) and Average daily gain (ADG) (b), using the Wald test. Each dot represents one SNP. On the y-axis are —log10 (P-values), and on the x-axis are the physical positions of the SNPs by chromosome. The imaginary line represents the Bonferroni-corrected significance threshold (5.85).

of the GWAS using haploview 9 v. 4.2 [17], and the LD block was defined by the criteria of Kent et al. [18]. The Bonferroni corrected P-value (P = 0.05/Number of SNPs) was defined as the genome-wise significance threshold.

Candidate genes identification. Significant SNPs detected in GWAS were verified in the extended 219 pigs mentioned above. Candidate genes containing at least one prominent SNP tested in both populations were identified according to their biological function directly or indirectly regulating the development process of the investigated traits.


QC of phenotypes and genotypes

The current Porcine 60K Beadchip has 64,232 SNPs [19]. Quality control procedures of the genotype data were carried out using Plink (Version 1.07) (http:// pn-gu.mgh.harvard.edu/purcell/plink/). 19,128 SNPs were excluded as HWE (P < 10E-05), 3531 SNPs were discarded for Call rate <90%, 8745 SNPs removed because of MAF < 0.05. After quality control a subset of 37,478 SNPs excluding SNPs on the Y chromosomes and those ambiguously mapped to the current pig genome assembly (Sscrofa10.02) were used for subsequent GWAS. The average physical distance between any two neighboring SNPs on the same chromosome was approximately 0.07 Mb, ranging from 0.06 Mb (SSC14) to 0.17 Mb (SSCX).

GWAS and verification

83 Duroc pigs were genotyped using the Illumina Porcine 60K SNP beadchips. The GWAS was performed for the traits of BFT and ADG. After Bonferroni correction (Bonferroni P < 0.05), a total of 31 genome-wise significant SNPs including 11 on SSC4, five on SSC9, one on SSC11, eight on SSC12, and six on SSC14 were identified to be associated with BFT, while the number of genome-wise significant SNPs for ADG is four (Table 2). Linkage disequilibrium (LD) was calculated among all the significant SNPs for BFT in the region between 9.45 and 9.51 Mb on SSC4 and 2.6-2.8 Mb on SSC12. Two large block of strong LD in these regions are observed (Fig. 4). The strong LD region may reflect the action of positive selection for BFT. The most significant SNP ALGA0055091 (P = = 6.24E-08) at 13.5 Mb o

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