基于全基因组关联研究技术筛选鸡产肉和肉品质性状相关候选基因
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摘要
产肉和肉品质性状是鸡重要经济性状,受饲粮营养和遗传因子的协同作用。随着分子营养研究的逐步深入,探明影响目标性状的关键调控基因及分子机制至关重要。随着鸡高密度SNP分型芯片的出现以及统计分析方法的日臻成熟,应用全基因组关联研究(GWAS)挖掘和鉴定鸡产肉和肉品性状的功能基因成为可能。
试验选用北京油鸡公鸡和科宝公司的快大型白羽肉鸡母鸡杂交构建了中国农业科学院(CAAS)鸡F2资源群体。选取资源群体中6个半同胞家系,共计400只鸡,包括亲本14只,F1代19只,F2代公鸡184只、母鸡183只。在93日龄时进行屠宰,测定11个产肉和16个肉品质性状。使用鸡60K SNP分型芯片对个体gDNA进行基因分型。分型结果经过质量控制后,剩余328只F2代个体和42585个SNPs.使用广义的线性模型(GLM)和压缩的混合线性模型(MLM)对鸡产肉和肉品质性状进行全基因组关联研究。模型中以群体结构中的第一主成分为协变量,批次、性别为固定效应。在MLM中,亲缘全系矩阵为随机效应。结果以MLM分析为主,同时兼顾GLM模型。同时,选取GWAS中鉴定的基因在高性状值组和低性状值组中进行表达验证。结果表明：
(1)本研究鉴定出11个产肉性状的64个SNPs效应位点,达到全基因组显著或潜在关联水平(P<2.98x10-6或5.96×10-5)。其中有22个SNPs效应位点在GLM模型中达到全基因组显著水平(P<2.98×10-6)。其中4号染色体78.11-84.94Mb(6.83Mb)区间内7个SNPs与多个产肉性状关联,区间内涉及到4个基因,包括SLIT2、QDPR、AFAP1和LRPAP1,它们的功能与产肉性状密切相关。此外,WNT信号通路中翅膀重的候选基因RUVBL1,腿肌重候选基因WNT4;其它染色体上影响多个产肉性状的候选基因包括SYT1、WAPAL、 MAPK和EFNA5。
(2)本研究发现33个SNPs与10个肉品质性状关联(P<4×10-4),这些性状包括胸肌干物质含量、腿肌干物质含量、胸肌肌内脂肪含量、肉色L*和b*、皮肤颜色L*、a*和b*,腹脂重和腹脂率。其中8个重要候选基因的功能与肉品质性状密切相关,包括胸肌肌内脂肪含量的候选基因TYRO3和MGST1,胸肌肉色的获选基因COL1A2,皮肤颜色的候选基因SPINK5,腹脂重和／或腹脂率的候选基因RET、NPPB、SREBFl和LOC431251。
(3)4个胸肌重的候选基因RAB2A、QDPR、EFNA5和OTUD6B在高胸肌重组中显著下调表达(P<0.01)。肉品质性状的17个候选基因中,14个在胸肌或腹脂组织高低性状值组中显著差异表达(P<0.05或0.01)。
本研究通过GWAS鉴定产肉和肉品质性状的候选区域和基因的功能需要进一步的研究,也为探索产肉和肉品质性状的分子机制提供了新的线索。
Meat production and quality are important economic traits in chickens, which were synergisticly influenced by feed nutrition and genetic factor. With the development of molecular nutrition research, it is important to understand the key regulatory gene and molecule mechanism underlying the target traits. The developments of high-throughput genotyping platforms and relevant statistical methods have enabled genome-wide association study (GWAS) for meat production and quality traits in chickens.
To identify loci and genes associated with meat production and quality traits, we conducted the GWAS of F2populations derived from a local Chinese breed (Beijing-You chickens) and a commercial fast-growing broiler line (Cobb-Vantress). In this study,400chickens including14parents,19F1chickens, and367F2chickens (184male and183female)from five batches at two-week intervals were genotyped and used. At the day of93, a total of11meat production and16quality traits of chickens from the F2generation were measured.
Genotyping was performed with50ng/μL gDNA using the Illumina60K Chicken SNP Beadchip. After quality control steps,42,585SNPs and328chickens were used for the GWAS. The GWAS analysis for meat prodution and quality traits used the compressed MLM and the results from GLM model are also indicated. Both models were performed with the first MDS component as covariates, with batch and sex as fixed effects. In the compressed MLM, relative kinship matrix was a random effect. For AbFW, the eviscerated weight (EW) was a covariate in both models. The mRNA expression patterns of candidate genes from GWAS results were measured using real-time quantity PCR (Q-PCR) from the extremes tratis groups.
The results showed that:
(1) In this study,64SNP effects involving44SNPs were detected for11meat production traits with genome-wide significance or suggestive (P<5.96×10-5) from compressed mixed linear model (MLM). Twenty-two of44these SNPs were genome-wide significance associated with the traits from general linear moldel (GLM)(P<2.98×10-6). The6.83Mb (78.11-84.94Mb) region on GGA4involving seven SNPs and four genes (SLIT2, QDPR, AFAP1, LRPAP1) were influenced most of these triats. The candidate gene RUVBL1for WW and WNT4for ThW were in WNT signaling pathway. In other chromosomes, some candidate genes, e.g. SYT1, WAPAL, MAPK and EFNA5, influenced most of meat production triats.
(2) In the present study,33association signals were detected from the compressed mixed linear model (MLM) for ten meat quality traits:DMBr, DMTh, IMFBr, meat colour L*and b*values, skin colour L*, a*and b*values, AbFW and AbFP. The mRNA expressions of candidate genes identified near significant signals were compared between High and Low phenotype groups. A total of14genes associated with IMFBr, meat colour L*, AbFW, and AbFP, exhibited differential expression levels between the High and Low phenotype groups. These genes were important candidate genes for meat quality traits, such as the protein tyrosine kinase TYRO3and microsomal glutathione S-transferase1(MGST1) for IMFBr, collagen, type I, alpha2(COL1A2) for meat colour L*, the RET proto-oncogene (RET), natriuretic peptide B (NPPB) and sterol regulatory element binding transcription factor1(SREBF1) for abdominal fat (AbF) traits.
(3) A total of21candidate genes were selected to validate the accuracy of GWAS method.18including four genes for BrW and14for meat quality traits were significant differentially expressed in the High and Low groups (P<0.05or0.01). The Q-PCR showed that the efficiency of the GWAS was about85%.
The results provided new clues for deciphering the molecular mechanisms underlying meat prodution and quality traits in chicken. The exploring of causal variants in these regions and functional characterization of these genes will be required.
试验选用北京油鸡公鸡和科宝公司的快大型白羽肉鸡母鸡杂交构建了中国农业科学院(CAAS)鸡F2资源群体。选取资源群体中6个半同胞家系,共计400只鸡,包括亲本14只,F1代19只,F2代公鸡184只、母鸡183只。在93日龄时进行屠宰,测定11个产肉和16个肉品质性状。使用鸡60K SNP分型芯片对个体gDNA进行基因分型。分型结果经过质量控制后,剩余328只F2代个体和42585个SNPs.使用广义的线性模型(GLM)和压缩的混合线性模型(MLM)对鸡产肉和肉品质性状进行全基因组关联研究。模型中以群体结构中的第一主成分为协变量,批次、性别为固定效应。在MLM中,亲缘全系矩阵为随机效应。结果以MLM分析为主,同时兼顾GLM模型。同时,选取GWAS中鉴定的基因在高性状值组和低性状值组中进行表达验证。结果表明：
(1)本研究鉴定出11个产肉性状的64个SNPs效应位点,达到全基因组显著或潜在关联水平(P<2.98x10-6或5.96×10-5)。其中有22个SNPs效应位点在GLM模型中达到全基因组显著水平(P<2.98×10-6)。其中4号染色体78.11-84.94Mb(6.83Mb)区间内7个SNPs与多个产肉性状关联,区间内涉及到4个基因,包括SLIT2、QDPR、AFAP1和LRPAP1,它们的功能与产肉性状密切相关。此外,WNT信号通路中翅膀重的候选基因RUVBL1,腿肌重候选基因WNT4;其它染色体上影响多个产肉性状的候选基因包括SYT1、WAPAL、 MAPK和EFNA5。
(2)本研究发现33个SNPs与10个肉品质性状关联(P<4×10-4),这些性状包括胸肌干物质含量、腿肌干物质含量、胸肌肌内脂肪含量、肉色L*和b*、皮肤颜色L*、a*和b*,腹脂重和腹脂率。其中8个重要候选基因的功能与肉品质性状密切相关,包括胸肌肌内脂肪含量的候选基因TYRO3和MGST1,胸肌肉色的获选基因COL1A2,皮肤颜色的候选基因SPINK5,腹脂重和／或腹脂率的候选基因RET、NPPB、SREBFl和LOC431251。
(3)4个胸肌重的候选基因RAB2A、QDPR、EFNA5和OTUD6B在高胸肌重组中显著下调表达(P<0.01)。肉品质性状的17个候选基因中,14个在胸肌或腹脂组织高低性状值组中显著差异表达(P<0.05或0.01)。
本研究通过GWAS鉴定产肉和肉品质性状的候选区域和基因的功能需要进一步的研究,也为探索产肉和肉品质性状的分子机制提供了新的线索。
Meat production and quality are important economic traits in chickens, which were synergisticly influenced by feed nutrition and genetic factor. With the development of molecular nutrition research, it is important to understand the key regulatory gene and molecule mechanism underlying the target traits. The developments of high-throughput genotyping platforms and relevant statistical methods have enabled genome-wide association study (GWAS) for meat production and quality traits in chickens.
To identify loci and genes associated with meat production and quality traits, we conducted the GWAS of F2populations derived from a local Chinese breed (Beijing-You chickens) and a commercial fast-growing broiler line (Cobb-Vantress). In this study,400chickens including14parents,19F1chickens, and367F2chickens (184male and183female)from five batches at two-week intervals were genotyped and used. At the day of93, a total of11meat production and16quality traits of chickens from the F2generation were measured.
Genotyping was performed with50ng/μL gDNA using the Illumina60K Chicken SNP Beadchip. After quality control steps,42,585SNPs and328chickens were used for the GWAS. The GWAS analysis for meat prodution and quality traits used the compressed MLM and the results from GLM model are also indicated. Both models were performed with the first MDS component as covariates, with batch and sex as fixed effects. In the compressed MLM, relative kinship matrix was a random effect. For AbFW, the eviscerated weight (EW) was a covariate in both models. The mRNA expression patterns of candidate genes from GWAS results were measured using real-time quantity PCR (Q-PCR) from the extremes tratis groups.
The results showed that:
(1) In this study,64SNP effects involving44SNPs were detected for11meat production traits with genome-wide significance or suggestive (P<5.96×10-5) from compressed mixed linear model (MLM). Twenty-two of44these SNPs were genome-wide significance associated with the traits from general linear moldel (GLM)(P<2.98×10-6). The6.83Mb (78.11-84.94Mb) region on GGA4involving seven SNPs and four genes (SLIT2, QDPR, AFAP1, LRPAP1) were influenced most of these triats. The candidate gene RUVBL1for WW and WNT4for ThW were in WNT signaling pathway. In other chromosomes, some candidate genes, e.g. SYT1, WAPAL, MAPK and EFNA5, influenced most of meat production triats.
(2) In the present study,33association signals were detected from the compressed mixed linear model (MLM) for ten meat quality traits:DMBr, DMTh, IMFBr, meat colour L*and b*values, skin colour L*, a*and b*values, AbFW and AbFP. The mRNA expressions of candidate genes identified near significant signals were compared between High and Low phenotype groups. A total of14genes associated with IMFBr, meat colour L*, AbFW, and AbFP, exhibited differential expression levels between the High and Low phenotype groups. These genes were important candidate genes for meat quality traits, such as the protein tyrosine kinase TYRO3and microsomal glutathione S-transferase1(MGST1) for IMFBr, collagen, type I, alpha2(COL1A2) for meat colour L*, the RET proto-oncogene (RET), natriuretic peptide B (NPPB) and sterol regulatory element binding transcription factor1(SREBF1) for abdominal fat (AbF) traits.
(3) A total of21candidate genes were selected to validate the accuracy of GWAS method.18including four genes for BrW and14for meat quality traits were significant differentially expressed in the High and Low groups (P<0.05or0.01). The Q-PCR showed that the efficiency of the GWAS was about85%.
The results provided new clues for deciphering the molecular mechanisms underlying meat prodution and quality traits in chicken. The exploring of causal variants in these regions and functional characterization of these genes will be required.
引文
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