基于50K SNP芯片技术对金华猪和嵊县花猪繁殖性状的全基因组关联分析

本实验旨在利用全基因组关联分析(GWAS)搜寻与金华猪、嵊县花猪总产仔数(TNB)和产活仔数(NBA)相关的候选基因。选择205头金华猪和174头嵊县花猪为实验材料,通过提取血样DNA并利用Illumina猪50K SNP芯片进行基因型分型,利用PLINK v1.09对获得的基因型数据进行质控后用于GWAS研究。采用GEMMA软件中的混合线性模型(MLM)对每个SNP与性状做关联分析,定位出显著位点。结果表明:金华猪的20个SNPs呈基因组水平或染色体水平显著;嵊县花猪的2个SNPs呈基因组水平或染色体水平显著;META分析得到21个SNPs呈基因组水平或染色体水平显著。最终找到22个候选基因,根据基因功能注释推测NANOS1、E2F7、AEBP2是最可能影响总产仔数和产活仔数的候选基因。     

大白猪繁殖性状全基因组关联分析

本研究利用全基因组关联分析（GWAS）挖掘与大白猪总产仔数（TNB）、产活仔数（NBA）和健仔数（NHP）相关的候选基因。选择1 100头大白猪为实验材料，通过提取耳尾组织样DNA并利用“中芯一号”芯片进行基因型分型，采用PLINK v1.9对获得的基因型数据进行质控后用于GWAS研究。rMVP软件对每个SNP与性状做关联分析，确定出显著位点。结果表明：对于TNB性状共有3个SNPs呈基因组水平或染色体水平显著；NBA性状共有4个SNPs呈基因组水平或染色体水平显著；NHP分析得到18个SNPs呈基因组水平或染色体水平显著。在上述显著SNPs附近共有23个候选基因，根据基因功能注释推测ESR1、ZP3、YWHAG、HSPB1、MDH2、PCCB是能够影响繁殖性状的重要候选基因。     

荣昌猪初产繁殖性状的全基因组关联研究

旨在鉴定荣昌猪初产繁殖性状的重要变异位点和基因,为荣昌猪繁殖性状的遗传改良提供重要的分子标记和基因资源。本研究选取429头荣昌母猪进行猪50K芯片基因分型,经过质量控制和基因型填充后,保留35 046个SNPs用于分析。采用主成分分析法研究群体结构,利用混合线性模型(mixed-linear model, MLM)将出生年、出生月作为固定效应,将主成分值作为协变量对总产仔数、活产仔数、死胎数和初生窝重性状进行全基因组关联分析(GWAS)。结果显示,在全基因组显著水平上鉴定出2个影响荣昌猪初生窝重的SNPs和1个影响荣昌猪死胎数的SNP;在潜在显著水平上鉴定到5个影响荣昌猪总产仔数的SNPs, 3个影响荣昌猪活产仔数的SNPs和10个影响荣昌猪死胎数的SNPs。通过全基因组关联分析筛选到1个显著的SNP(SSC17:57 315 180 bp)同时影响荣昌猪总产仔数、活产仔数和初生窝重,1个显著的SNP(SSC1:279 214 647 bp)同时影响荣昌猪活产仔数和总产仔数,暗示基因在不同性状间具有一因多效性。本研究根据候选基因的相关分子生物学功能,确定BMP7基因为影响荣昌猪总产仔数...     

可乐猪乳头数性状全基因组关联分析

乳头数性状是猪最重要的繁殖性状之一,与养猪业的经济效益密切相关。本试验以Illunima Porcine SNP 60K芯片对22头可乐猪进行基因分型,通过Plink 1.07软件,基于混合线性模型对左乳头数、右乳头数和总乳头数性状进行全基因组关联分析。经过严格的质量控制和多重检验之后,共鉴定出全基因组水平潜在关联的SNPs位点4个（P<2.06E-5）;染色体水平显著关联位点3个,潜在关联位点18个;在关联SNP位点可能连锁的上、下游1 cM区间内检索到304个基因,其中Wnt及Fgf信号通路中的候选基因BTRC、FGF5、FGF8和BMP3、RASGEF1B、HMGB3可能影响猪的乳头数性状或繁殖性状。通过全基因组关联分析策略发掘出的关联SNP位点及潜在候选基因,将为可乐猪的选育保种奠定基础。     

基于SNP芯片技术对猪性状的应用及其研究进展

SNP具有分布广、数量多,易检测和便于分型等优点,在动植物分子育种方面已经得到广泛应用,并不断出现新的分析检测方法。相对全基因组重测序的成本而言,SNP芯片检测的成本较低,使得利用SNP芯片技术在全基因组范围内寻找与人类疾病和动植物性状相关的SNPs成为可能。利用SNP芯片技术结合全基因组关联分析(GWAS),已经检测到了与猪性状显著相关的SNPs位点和候选基因,为未来猪的分子育种提供理论依据。该文主要就SNP芯片技术的特点、原理和方法以及在猪性状方面的应用加以综述。     

大白猪产仔数性状全基因组关联分析

在猪业生产中,产仔数高低是评价母猪繁殖性能的重要指标。本研究以738头大白猪群体为研究对象,收集繁殖记录,并计算1～4胎次总的产仔数（Total Number Born,TNB）、总的产活仔数（Number Born Alive,NBA）性状。利用猪80K芯片对个体进行基因分型,采用GCTA软件对TNB、NBA性状进行全基因组关联分析。结果显示,在15号染色体上,共鉴定到7个与NBA性状显著关联的SNP位点,构成1个327kb的单倍型块。与猪QTL数据库比对,这些显著关联的SNP位于3个与繁殖性状相关的QTL区域内,与黄体数、乳头数等性状相关。在显著SNP位点上、下游500 kb区域内共包含7个基因,其中,IRS1、RHBDD1为产仔数性状相关基因。本研究为进一步鉴定猪繁殖性状关键基因提供理论依据。     

猪3号染色体上与产仔性状和窝内仔猪初生重整齐度显著关联的标记鉴定

试验旨在寻找与猪产仔性状和窝内仔猪初生重整齐度显著关联的分子标记,为猪繁殖性状的遗传改良提供依据。在课题组前期进行的猪全基因组清扫分析的基础上,选定猪3号染色体上的2个SNPs位点（rs338309012和rs335824784）,利用目标序列捕获测序分型技术,在丹系大白猪和美系大白猪群中对这2个SNPs位点与猪产仔性状（包括总产仔数、产活仔数、死胎及木乃伊胎数等）及窝内仔猪初生重整齐度进行关联分析。结果显示,rs338309012位点与总产仔数、木乃伊胎数显著关联（P<0.05）,AC基因型母猪的总产仔数、木乃伊胎数均显著高于CC基因型（P<0.05）;rs335824784位点与有效活仔数、木乃伊胎数显著关联（P<0.05）,与产活仔数和死胎数极显著关联（P<0.01）,不同基因型对产活仔数和有效活仔数的影响为GG > CG > CC,与之相反,对窝内仔猪初生重的变异系数、死胎及木乃伊胎数的影响为GG < CG < CC。因此,rs335824784位点GG基因型猪不仅产活仔数多,而且窝内仔猪初生重整齐,死胎和木乃伊胎数低,可以作为提高猪产仔性状和窝内仔猪初生重整齐度的分子标记。     

全基因组关联分析及其在猪育种中的研究进展

近年来,随着高通量单核苷酸芯片和基因分型技术的不断发展,利用全基因组关联分析猪的性状成为可能。全基因组关联分析是一种新兴的遗传分析方法,能有效进行复杂疾病和性状的研究。国内外相关研究人员针对猪性状进行全基因组关联分析,积累了大量的单核苷酸多态性(SNP)标记、候选基因以及数量性状位点,为猪分子育种提供基础。该文主要对全基因组关联分析的基本原理、分析方法以及对猪性状的研究进展进行综述。     

大白公猪精液相关性状全基因组关联分析

本研究旨在通过全基因组关联分析技术挖掘大白公猪原精体积、原精密度、精子畸形率、精子总数和有效精子数等性状的关联SNP位点及候选基因。选取498头大白公猪,提取精液DNA,利用Gene Seek 50K芯片进行基因分型,通过混合线性模型计算个体随机效应值来作为全基因组关联分析表型值,利用Farm-CPU法进行全基因组关联分析。结果显示:发现4个与原精体积显著关联的位点,3个与畸形率显著关联的位点;各精液性状共19个潜在关联SNPs,其中17号染色体上的M1GA0021799位点与原精体积、精子畸形率和精子总数均有关联。根据文献和生物学过程推测认为FOXA2、PTMA、TCTE3、CAPN7、SH3P13和CSTS家族基因共9个基因可作为大白公猪精液性状重要候选基因。     

简化基因组测序在安格斯牛繁殖性状候选基因筛选中的应用研究

为了确定与安格斯牛繁殖性状相关的遗传标记和功能基因,试验采用简化基因组测序(dd-RAD)技术对安格斯牛繁殖相关基因进行研究,与初配月龄(AFS)、初产日龄(AFC)和产犊间隔(CI)等性状进行全基因组关联分析。结果表明：共检测到314 718个SNPs位点,与AFS和AFC性状显著关联的SNPs位点各27个,两性状相同候选基因为16个;与CI性状显著关联的SNPs位点和候选基因各3个。GO功能注释分析发现位于6,24,15,10号染色体的SLIT2、LAMA3、TEAD1和MCC基因为AFS和AFC性状的共同关键候选基因,5号染色体的KCNC2基因为CI性状的关键候选基因。说明筛选到的SLIT2、LAMA3、TEAD1、MCC和KCNC2基因可能是安格斯牛繁殖性状选育的分子标记。     

Genome-wide Association Study on Alive Litter Size Trait in Bama Xiang Pigs

In order to identify the molecular markers related to alive litter size of Bama Xiang pigs,the genome-wide association study (GWAS) was used to map and screen the candidate genes affecting the alive litter size trait.Ear tissue samples of 297 Bama Xiang pigs with multiple parity records were collected,and DNA was extracted and genotyped by porcine 50K SNP beadchip.After quality control and genotype imputation,the alive litter size of Bama Xiang pigs were GWAS by Tassel.The results showed that the average number born alive per litter of Bama Xiang pigs increased gradually with the increasing of parity in the range of 1-9 parities.A total of 32 816 SNPs were obtained after quality control and filtration.8 SNPs related to alive litter size of Bama Xiang pigs were screened by genome-wide association analysis,which were significant at genome or chromosome level.Based on the enrichment analysis of the coding genes in the region between 500 kb upstream and downstream of the associated significant SNP loci,and the QTL regions and gene functions related to porcine reproductive traits,4 genes (CAPZB,MSH3,CITED2 and HSD17B7) were finally identified to be candidate genes related to alive litter size of Bama Xiang pigs.     

Detection of Genome-wide Copy Number Variation Using Porcine 1.4M High-density SNP Chips in Bama Xiang Pigs

The aim of this study was to detect the copy number variation (CNV) in the genome of Bama Xiang pigs and investigate the effect of marker density on the efficiency and accuracy of CNV detection. PennCNV and R-Gada were employed to detect CNVs using the 1.4M high-density SNP chip data of 319 (160 hogs and 159 gilts) Bama Xiang pigs, and the CNV region (CNVR) was constructed by merging overlapping CNVs. Only the CNVR with higher frequency than 5% was verified by the genome-wide association study (GWAS). Finally, according to the marker densities, a certain number of SNPs were evenly extracted, and the effect of marker density on CNV detection efficiency and accuracy was explored. There were 6 327 CNVs detected by PennCNV and 3 489 CNVs detected by R-Gada, which made up of 795 and 340 CNVRs, respectively, including 226 CNVRs identified by both programs. Among the 226 CNVRs, the shortest was 3.98 kb, the longest was 1 297.78 kb, and their total length was 33.27 Mb, of which 102 (45%) overlapped the CNVRs reported previously. Among the 795 CNVRs detected by PennCNV, 135 had a higher frequency than 5%, 20 of which had been verified by GWAS, and the verification rate was 15%. With the SNP density increasing, the efficiency and accuracy of CNV detection were increased, especially for the small size CNVs. A CNVR sketch of Bama Xiang pigs had been drawn using 1.4M SNP chips, which was helpful to identify CNVRs associated with important economic traits in the future. At the same time, we revealed the positive effect of marker density on the efficiency and accuracy of CNV detection, and the results provided a reference of choosing marker density for the follow-up research of CNV detection.     

Effect of Polymorphisms in Four Candidate Genes for Fertility on Litter Size in a German Pig Line

We carried out an SNP discovery project in pigs for candidate genes playing potentially important roles in embryonic development. Using eight pigs one each from eight breeds (Meishan, Mangalitza, Duroc, Pietrain, German Landrace, Hampshire, Husum Red Pied, German Large White), 36 SNPs were identified in intronic sequences of 21 porcine candidate genes based on sequencing of PCR products. The primer pairs were designed using porcine EST sequences allowing amplification of introns. These SNPs were tested for their association with the number of piglets born alive in German Large White sows using a discordant approach. Significant effects (p < 0.001 and p < 0.05, respectively) of intronic SNPs on litter size were found for four genes: mitogen‐activated protein kinase kinase kinase 3 (MAP3K3), vascular endothelial growth factor receptor (KDR), erbb2 interacting protein (ERBB2IP) and peroxisome proliferator‐activated receptor delta (PPARD). These SNPs can be further tested in upcoming association studies for their influence on litter size in different breeds using larger sample sizes.     

利用猪1.4M高密度SNP芯片检测巴马香猪全基因组拷贝数变异

旨在检测巴马香猪基因组上的拷贝数变异（CNV）,并探究标记密度对于CNV检测效率和准确率的影响。本研究利用319头巴马香猪（其中阉公猪160头和母猪159头）1.4M高密度SNP芯片的数据,采用PennCNV和R-Gada两种软件进行CNVs检测;然后通过重叠CNV融合法,构建拷贝数变异区域（CNVR）,并用全基因组关联分析（GWAS）对频率大于5%的CNVR进行验证;最后根据不同的标记密度,均匀抽取一定数目的SNPs来探究标记密度对CNV检测效率和准确性的影响。结果,PennCNV和R-Gada软件分别检测到6 327和3 489个CNVs,分别构成795和340个CNVRs,其中226个为共同CNVRs。在这226个共同CNVRs中,最短的为3.98 kb,最长的为1 297.78 kb,总长度为33.27 Mb,其中102个（45%）与前人报道的CNVRs重叠。在PennCNV检出的795个CNVRs中,有135个频率大于5%,其中20个得到GWAS验证,验证率为15%。随着SNP密度的逐渐增加,CNV的检测效率和检测准确性不断提高,尤其是小片段CNVs的检测效率。本研究利用1.4M SNP芯片的数据,通过PennCNV和R-Gada软件绘制巴马香猪CNVR的草图,为将来鉴别与重要经济性状相关的CNVRs奠定了基础。同时,揭示了标记密度对CNV检测效率和准确性有正面影响,为后续CNV研究选择合适的标记密度提供了一定的参考。     

Genome-wide Association Study of Teats Number Traits in Kele Pigs

Teats number is one of the most important reproductive traits,and closely related to the economic benefit in pig industry.In order to reveal the underlying genetics of left teats number,right teats number and total teats number traits,a genome-wide association study（GWAS）was performed.Samples of DNA were collected to genotyping for 22 Kele pigs using the Illumina Porcine SNP 60K Chip.The GWAS was performed using a mixed-effects model and linear regression approach.When a genome-wide threshold was determined using the Bonferroni method（P<2.06E-5),4 single nucleotide polymorphism（SNP）markers were potentially associated with left teats number,right teats number and total teat number.However,3 SNPs were significant associated and 18 SNPs were potentially associated in chromosomes level.304 Ensembl genes were retrieved around 1 cM of the associated SNPs.The candidate genes in Wnt and Fgf signaling pathway（BTRC,FGF5,FGF8,BMP3,RASGEF1B and HMGB3）might have effect on target traits.These results provided valuable information about the selective breeding for Kele pigs.     

Effect of candidate gene polymorphisms on reproductive traits in a Large White pig population

The objective of this study was to test for association of candidate single nucleotide polymorphisms (SNPs) with sow prolificacy reproductive traits, such as litter size, ovulation rate and lifetime performance, in gilts of a Large White pig population. Preliminary research on 25 animals selected from the high‐ and low‐performance groups of 347 animals with case‐control studies indicated that seven genes were associated with total number of piglets born (TNB). Six of the seven genes were associated with reproductive traits, including TNB, number of piglets born alive (NBA) and average weight of piglet weaning (AWW). A MBL2 SNP was significantly associated with TNB and NBA in first parity. A CFB SNP was associated with TNB in first parity. An ACE SNP was associated with TNB in first and second parities. An EGF polymorphism was associated with TNB, NBA and AWW in second parity. A KCNC2 polymorphism was significantly associated with TNB and NBA in second parity. A SLC22A5 SNP was associated with TNB and NBA in second parity. Six candidate SNPs were associated with TNB; the only exception was a PRKAG3 polymorphism. A candidate gene approach enables some of these polymorphisms to be used in genetic improvement programs based on marker‐assisted selection.     

巴马香猪VRTN基因克隆、表达及其多态性与繁殖性状的关联分析

旨在研究VRTN（vertebrae development homolog）基因在巴马香猪群体中的编码区序列特征、组织表达情况、脊椎数性状因果突变位点ins291的等位基因频率及其与乳头数和产仔数性状的关联。本研究采集3头0日龄巴马香猪组织,利用cDNA克隆技术获得VRTN基因编码区全长序列并进行生物信息学分析,利用荧光定量PCR技术检测VRTN在心、肝、脾、肺、肾、背最长肌和皮下脂肪组织中的表达情况;采集279头经产巴马香猪母猪血液,检测ins291位点在该群体中的频率分布,并与乳头数、产仔数性状进行关联分析。结果表明,巴马香猪VRTN基因编码区全长2 097 bp,其编码的氨基酸序列在不同物种间存在大量保守区域;VRTN基因编码698个氨基酸,预测为亲水性蛋白质,存在1个螺旋转角螺旋域超家族结构功能区、2个低复杂度区域和2个内部重复结构,并与核受体辅抑制子1（NR6A1）、果蝇同源框基因Prospero的脊椎动物同源蛋白2（PROX2）和富亮氨酸重复序列74亚基（LRRC74A）等蛋白具有相互作用;VRTN基因在0日龄巴马香猪各组织中均有表达,其中在背最长肌组织中表达量最高;巴马香猪保种群体中VRTN基因有利突变位点ins291的等位基因频率为21.15%,不同基因型个体之间平均产仔数、总乳头数、左侧乳头数、右侧乳头数和单侧最大乳头数性状均无显著差异（P>0.05）,但纯合突变型（ins/ins）个体的乳头数性状均高于其他基因型个体。结果提示,在巴马香猪产业化生产中可通过分子育种手段提高VRTN ins291有利等位基因频率,但不影响其产仔数性状。     

Identification of Markers Significantly Associated with Litter Size Traits and Uniformity of the Piglet's Birth Weight on Porcine Chromosome 3

This study was aimed to find the molecular markers significantly associated with litter size traits and uniformity of the piglet's birth weight,and provided a basis for genetic improvement of reproductive traits in pigs.This study was based on the genome-wide selective sweep analysis of pig conducted by the research group in the previous studies,two SNPs (rs338309012 and rs335824784) on porcine chromosome 3 were selected,and the genotyping-in-thousand by sequencing was used,the relationship between two SNPs and litter size traits (including total number born,total number born alive,number of stillborn pigs and number of mummified pigs,etc.) and the uniformity of the piglet's birth weight was association analyzed in Danish Yorkshire and American Yorkshire pigs.The results showed that rs338309012 were significantly associated with the total number born and the number of mummified pigs (P<0.05),and the total number born and the number of mummified pigs of AC genotype sows was significantly higher than CC genotype (P<0.05).rs335824784 was significantly associated with the effective number of born alive and the number of mummified pigs (P<0.05),and was also extremely significantly associated with the total number born alive and the number of stillborn pigs (P<0.01).The effect of different genotypes on the total number born alive and effective number of born alive were GG > CG > CC.On the contrary,the effect of different genotypes on the coefficient of variation of the birth weight of piglets,the number of dead and mummified fetuses were GG < CG < CC.Thus,the GG genotype sows with rs335824784 not only had more total number born alive,but also had regular piglet's birth weight and lower number of stillborn and mummified pigs,which could be used as a molecular marker to improve the litter size traits and uniformity of the piglet's birth weight.