Semen quality serves as a vital indicator of male fertility, yet its underlying genetic and regulatory mechanisms remain poorly understood. Here, 1.15 million records of six semen quality traits from 14 210 boars in four distinct breeds were collected. These traits have low to moderate heritability (0.12-0.26), and are genetically correlated with growth traits like average daily gain. Genome-wide association study (GWAS) and multi-breed meta-analysis detected 234 loci associated with semen quality. Systematic integration of the Pig Genotype-Tissue Expression resource with these GWAS loci allowed the prioritization of 93 causal variants targeting 134 genes. For instance, the expression quantitative trait loci (eQTL) of NAXE in multiple tissues were colocalized with a GWAS loci of the number of sperms, while eQTL of LEFTY2 in the testis was exclusively colocalized with in a GWAS loci of semen volume. Through examining GWAS of semen quality traits in cattle and human complex traits, the ortholog genes (e.g., AURKAIP1 and ADRA2A) significant in pigs also regulated bovine semen quality, and were significantly enriched for heritability of human birth weight and height. This study provides novel insights into semen quality traits in mammals, which will provide candidate genes for pig selective breeding and potential targets for human male infertility research.

Genomic selection (GS) has been widely used in livestock, which greatly accelerated the genetic progress of complex traits. The population size was one of the significant factors affecting the prediction accuracy, while it was limited by the purebred population. Compared to directly combining two uncorrelated purebred populations to extend the reference population size, it might be more meaningful to incorporate the correlated crossbreds into reference population for genomic prediction. In this study, we simulated purebred offspring (PAS and PBS) and crossbred offspring (CAB) base on real genotype data of two base purebred populations (PA and PB), to evaluate the performance of genomic selection on purebred while incorporating crossbred information. The results showed that selecting key crossbred individuals via maximizing the expected genetic relationship (REL) was better than the other methods (individuals closet or farthest to the purebred population, CP/FP) in term of the prediction accuracy. Furthermore, the prediction accuracy of reference populations combining PA and CAB was significantly better only based on PA, which was similar to combine PA and PAS. Moreover, the rank correlation between the multiple of the increased relationship (MIR) and reliability improvement was 0.60-0.70. But for individuals with low correlation (Cor(Pi, PA or B), the reliability improvement was significantly lower than other individuals. Our findings suggested that incorporating crossbred into purebred population could improve the performance of genetic prediction compared with using the purebred population only. The genetic relationship between purebred and crossbred population is a key factor determining the increased reliability while incorporating crossbred population in the genomic prediction on pure bred individuals.

The strategy of combining reference populations has been widely recognized as an effective way to enhance the accuracy of genomic prediction (GP). This study investigated the efficiency of genomic prediction using prior information and combined reference population. In total, prior information considering trait-associated single nucleotide polymorphisms (SNPs) obtained from meta-analysis of genome-wide association studies (GWAS meta-analysis) was incorporated into three models to assess the performance of GP using combined reference populations. Two different Yorkshire populations with imputed whole genome sequence (WGS) data (9,741,620 SNPs), named as P1 (1259 individuals) and P2 (1018 individuals), were used to predict genomic estimated breeding values for three live carcass traits, including backfat thickness, loin muscle area, and loin muscle depth. A 10 × 5 fold cross-validation was used to evaluate the prediction accuracy of 203 randomly selected candidate pigs from the P2 population and the reference population consisted of the remaining pigs from P2 and the stepwise added pigs from P1. By integrating SNPs with different p-value thresholds from GWAS meta-analysis downloaded from PigGTEx Project, the prediction accuracy of GBLUP, genomic feature BLUP (GFBLUP) and GBLUP given genetic architecture (BLUP|GA) were compared. Moreover, we explored effects of reference population size and heritability enrichment of genomic features on the prediction accuracy improvement of GFBLUP and BLUP|GA relative to GBLUP. The prediction accuracy of GBLUP using all WGS markers showed average improvement of 4.380% using the P1 + P2 reference population compared with the P2 reference population. Using the combined reference population, GFBLUP and BLUP|GA yielded 6.179% and 5.525% higher accuracies than GBLUP using all SNPs based on the single reference population, respectively. Positive regression coefficients were estimated in relation to the improvement in prediction accuracy (between GFBLUP/BLUP|GA and GBLUP) and the size of the reference as well as the heritability enrichment of genomic features. Compared to the classic GBLUP model, GFBLUP and BLUP|GA models integrating GWAS meta-analysis information increase the prediction accuracy and using combined populations with enlarged reference population size further enhances prediction accuracy of the two approaches. The heritability enrichment of genomic features can be used as an indicator to reflect weather prior information is accurately presented.

陆川猪是我国优良的地方品种,但由于非洲猪瘟的影响导致其养殖量急剧下降,对其进行种质资源保护刻不容缓.本研究旨在通过SNP芯片分析陆川猪遗传结构和遗传多样性,为该群体后续保种策略提供一定的参考.本研究基于 269 头能繁公母猪SNP芯片信息,分析该群体遗传结构、亲缘关系、家系划分以及近交系数.结果显示,该群体部分个体遗传关系较近,IBS遗传距离在 0.09～0.31,平均值为 0.25;通过聚类分析和G矩阵结果,将 269 头陆川猪分为 3 个家系,分别有 9、3、6 头公猪,母猪在家系间存在交叉;ROH分析发现该群体平均ROH长度为(503.77±8.89)Mb,主要分布在 388～475 Mb,FROH主要分布在 0.13～0.23,其平均FROH为 0.21±0.004.研究表明,该群体陆川猪家系较少,ROH数量多且较长,近交风险较大,急需引入外源血统丰富其遗传多样性,并根据芯片结果,合理规划配种策略,降低群体近交水平.

Growth and carcass traits are of economic importance in the pig production, which affect pork quality and profitability of finishing pig production. This study used whole-genome and transcriptome sequencing technologies to identify potential candidate genes affecting growth and carcass traits in Duroc pigs. The medium (50-60 k) single nucleotide polymorphism (SNP) arrays of 4 154 Duroc pigs from three populations were imputed to whole-genome sequence data, yielding 10 463 227 markers on 18 autosomes. The dominance heritabilities estimated for growth and carcass traits ranged from 0.000 ± 0.041 to 0.161 ± 0.054. Using non-additive genome-wide association study (GWAS), we identified 80 dominance quantitative trait loci for growth and carcass traits at genome-wide significance (false discovery rate < 5%), 15 of which were also detected in our additive GWAS. After fine mapping, 31 candidate genes for dominance GWAS were annotated, and 8 of them were highlighted that have been previously reported to be associated with growth and development (e.g. SNX14, RELN and ENPP2), autosomal recessive diseases (e.g. AMPH, SNX14, RELN and CACNB4) and immune response (e.g. UNC93B1 and PPM1D). By integrating the lead SNPs with RNA-seq data of 34 pig tissues from the Pig Genotype-Tissue Expression project (https://piggtex.farmgtex.org/), we found that the rs691128548, rs333063869, and rs1110730611 have significantly dominant effects for the expression of SNX14, AMPH and UNC93B1 genes in tissues related to growth and development for pig, respectively. Finally, the identified candidate genes were significantly enriched for biological processes involved in the cell and organ development, lipids catabolic process and phosphatidylinositol 3-kinase signalling (P < 0.05). These results provide new molecular markers for meat production and quality selection of pig as well as basis for deciphering the genetic mechanisms of growth and carcass traits.

Porcine teat numbers are crucial indicators of the reproductive performance of sows in the pig industry.During lactation periods,sows with fewer teats may lead to inadequate colostrum intake in piglets,which affects piglet weight gain and mortality(Tummaruk,2013).In pig breeding,high-intensity artificial selection on litter traits potentially gives rise to the functional weakening of teat traits due to the pleiotropic effects of genes affecting both traits(Chen et al.,2022).In recent years,several single-marker genome-wide associa-tion studies(GWASs)have been conducted to explore the genetic ar-chitecture of teat traits in pigs(Zhuang et al.,2020;Li et al.,2021).

Preselected variants associated with the trait of interest from genome-wide association studies (GWASs) are available to improve genomic prediction in pigs. The objectives of this study were to use preselected variants from a large GWAS meta-analysis to assess the impact of single-nucleotide polymorphism (SNP) preselection strategies on genome prediction of growth and carcass traits in pigs. We genotyped 1018 Large White pigs using medium (50k) SNP arrays and then imputed SNPs to sequence level by utilizing a reference panel of 1602 whole-genome sequencing samples. We tested the effects of different proportions of selected top SNPs across different SNP preselection strategies on genomic prediction. Finally, we compared the prediction accuracies by employing genomic best linear unbiased prediction (GBLUP), genomic feature BLUP and three weighted GBLUP models. SNP preselection strategies showed an average improvement in accuracy ranging from 0.3 to 2% in comparison to the SNP chip data. The accuracy of genomic prediction exhibited a pattern of initial increase followed by decrease, or continuous decrease across various SNP preselection strategies, as the proportion of selected top SNPs increased. The highest level of prediction accuracy was observed when utilizing 1 or 5% of top SNPs. Compared with the GBLUP model, the utilization of estimated marker effects from a GWAS meta-analysis as SNP weights in the BLUP|GA model improved the accuracy of genomic prediction in different SNP preselection strategies. The new SNP preselection strategies gained from this study bring opportunities for genomic prediction in limited-size populations in pigs.

The purpose was to explore candidate genes related to the eye muscle area, predicted lean meat percentage and average backfat thickness of Large White pigs by using the weighted single-step genome wide association study and making full use of the phenotype, pedigree and genotype information of the population. The phenotypic record data of eye muscle area, predicted lean meat percentage and average backfat thickness of 21 754 Large White pigs were collected, including 1 259 individuals with genotype data. Through analysis of variance and the weighted single-step genome wide association study, quantitative trait loci（QTL） that are significantly related to traits were determined. The gene annotation, gene ontology（GO） and kyoto Encyclopedia of genes and genes（KEGG） pathway enrichment analysis were carried out. The results showed that the heritability of eye muscle area, predicted lean meat percentage and average backfat thickness in Yorkshire pigs were 0.450 6±0.017 3, 0.496 8±0.017 4 and 0.475 8±0.017 2, respectively. Using the weighted single-step genome wide association study, 10 candidate QTL regions significantly associated with eye muscle area, 8 candidate QTL regions significantly associated with predicted lean meat percentage, and 12 candidate QTL regions significantly associated with average backfat thickness were localized. Follow-up gene annotation, GO function and KEGG pathway enrichment analysis revealed 36 candidate genes significantly associated with eye muscle area, with a total of 7 terms enriched; 29 candidate genes significantly associated with predicted lean meat percentage, with a total of 2 terms enriched; and 41 candidate genes significantly associated with average backfat thickness, with a total of 11 terms enriched. Analysis of the genes contained in these terms showed that some of these candidate genes were associated with growth and development, muscle fat and bone development. For example, ADAL gene affects adipocyte differentiation and other activities; FGF9 gene is reported to be involved in bone development and other processes. In this study, the important candidate genes related to growth traits of Yorkshire pigs were located through the weighted single-step genome wide association study. The results extended the related research of growth traits of Yorkshire pigs, and provide important molecular markers for genetic improvement of growth traits in the future.

血清免疫指标是衡量动物健康水平的重要指标.本研究采取南宁某大型核心种猪场标准饲养模式下的育肥期(80日龄)大白猪血清样品,其中公猪105头,母猪119头.检测肿瘤坏死因子α(TNFα)、白细胞介素-6(IL-6)、C-反应蛋白(CRP)的免疫水平,通过各指标的相关性分析及正态分布检验得出3项免疫指标的相关性及群体分布情况,为猪育肥期免疫指标的正常范围值和健康状况检测提供理论参考.结果表明,80日龄大白猪的TNFα、IL-6、CRP等3项指标间具有极显著相关性(P＜0.01),各指标间相关系数均在0.4以上;性别因素对该时期指标表型的影响不显著.

试验数据来源于2018年测定的广西某种猪场栏内444头长白猪使用自动喂料系统(FIRE)的采食情况,每日记录长白猪生长育肥阶段(90～160日龄)的采食量和采食行为.分析长白猪随日龄变化的采食行为规律,以及性别、胎次、气候因素对猪采食行为和饲料利用效率的影响,以期为育肥猪采食行为性状选育、提高经济效益及科学高效养殖提供理论依据.结果表明:①公猪和母猪采食行为区别不大,但在每日采食次数上表现出差异;②在生长育肥阶段,公猪的生长性能高于母猪;③较冷环境下的育肥猪平均每日采食量更多、平均日增重更高、采食速度更快.

近几年来,虽然人们的生活水平在不断地提高,但是猪肉消费量却呈现出了下滑的趋势,生猪产业可以说是我国最重要、最关键的基础产业之一,在实现乡村振兴,提高农民收入等方面有着至关重要的作用.但是因为生猪养殖行业缺乏健全、完善、行之有效的价格指导方法,以至于造成我国的生猪价格出现了波动问题.本文主要针对生猪期货对猪价波动的平抑作用进行了分析,并提出了确保生猪期货功能顺利发挥的方法与对策,以做参考之用.

[目的]对受长期选择的实际杜洛克猪育种群体3个重要经济性状进行遗传参数估计,分析各性状取得的遗传进展,并探讨实际育种群体中长期选择等因素对群体遗传参数的影响.[方法]收集广西某种猪场核心育种群杜洛克猪2003—2018年共计15 760条生长性能测定记录.运用DMU软件的DMUAI模块和DMU4模块,利用多性状动物模型估计3个重要经济性状的群体遗传参数和个体育种值.并通过估计该群体的年度累计群体遗传参数以评估该群体在长期选择过程中遗传参数的变化情况.[结果]杜洛克猪3个重要经济性状(达100 kg体质量日龄、背膘厚和眼肌面积)的估计遗传力分别为0.354、0.477和0.479,均属中高遗传力性状.3个性状间的遗传相关范围为?0.110～0.039,表型相关范围为?0.076～0.082,均属于弱相关.性状达100 kg体质量日龄在长期选择中取得了较大的遗传进展,而性状达100 kg体质量背膘厚和达100 kg体质量眼肌面积取得的遗传进展较小.分析年度累积群体估计的遗传参数发现,3个经济性状的加性遗传方差出现了不同程度的变化.[结论]杜洛克猪群体3个重要经济性状均为中高遗传力性状且性状间相关性较弱.在实际育种群体中,长期选择及引种等因素会导致群体遗传参数发生变化,育种实践中应及时开展遗传参数估计,以获得准确的遗传评估结果,加速群体遗传改良.

试验研究了猪冷冻精液在规模化猪场的应用.通过引进加拿大猪冷冻精液150剂,在广西农垦良圻原种猪场两个规模化种猪场进行配种.试验表明:猪冷冻精液输精受胎率、分娩率约是常规鲜精组的57％、75％(P<0.01),窝均产仔总数、健仔数约是常规鲜精组的75％、80％(P<0.01).在规模化猪场推广猪冷冻精液配种技术,需要严格的猪冷冻精液的保存条件、运输条件、配种时间以及猪场的环境控制工艺、生物安全体系模式.

随着养猪业的规模化发展,中国与美国的养猪模式越来越接近,猪场生产高度集约化,猪群健康度成为企业能否盈利的关键因素之一.美国每年因PRRS引起的损失约5.6亿美元;加拿大The George Morris中心估计PRRS每年给加拿大养猪业造成的损失至少1.3亿加元;在中国PRRS造成的损失也是难以估算的.

0 前言 高度生物安全的公猪站,使种猪优良基因的推广、精液的流通交换等过程中广大猪场担心疾病传播的问题迎刃而解,是开展联合育种必不可少的基础.2016年9月农业部畜牧业司制定了《全国生猪遗传改良计划种公猪站建设方案(试行)》.建立和认定一批具有高健康、一定规模、质量好的国家种公猪站,对促进国家生猪核心育种场间的遗传交流,加快推进我国生猪联合育种十分必要.广西农垦永新畜牧集团有限公司良圻原种猪场依据方案积极组织申报,经过全国生猪遗传改良计划工作领导小组办公室和专家组到现场对公猪站生产工艺、生物安全、疫病防控、生产管理、种公猪生产性能、精液品质、遗传交流执行情况等方面的认真审核,获评首批全国生猪遗传改良计划种公猪站.

本试验旨在研究高梁日粮中添加500 g/t复合酶制剂对生长猪育肥后阶段的生产性能和经济效益有何影响.结果显示:与对照组相比,在高梁日粮中添加复合酶制剂可以显著提高育肥猪日增重5.58％,降低料肉比0.29(P＜0.01),降低死亡率1.33％(P＜0.05),降低育肥猪的单位增重成本0.62元/kg,增加经济效益35.07元/头.试验表明,在生长育肥猪日粮中添加复合酶制剂500g/t,有利于生长猪在育肥后阶段对饲料营养物质的吸收,提高生产性能,降低生产成本,增加经济效益.

为构建稳定的抗应激核心猪群,进一步净化隐性氟烷基因,采用PCR-RFLP技术检测了良圻原种猪场公猪站在群公猪大约克夏、长白、杜洛克3个品种合计216头生产公猪氟烷基因分布情况,并通过直接测序法对检测结果进行验证.结果表明,在群的216头生产公猪中只检测到氟烷基因显性纯合子(Hal NN),并未检测出Hal Nn、Hal nn两种类型的个体,氟烷显性基因Hal N频率和隐性基因Hal n频率分别为1.00和0,并在Hal基因第16内含子上发现3个新的碱基突变位点.在生产公猪中,已实现氟烷隐性基因的剔除,为培育优质瘦肉型配套系种猪选育工作提供了有力的保障.

长期以来,我国大多数种猪育种企业缺乏对育种过程监控的意识,在实际种猪选育时主要注重结果,很少关注到过程变异的控制与管理.本文在简述过程基本原则和方法的基础上,从育种过程监控步骤与数据分类、控制图判定准则、育种数据监控等方面,阐述了SPC控制图在种猪育种与生产过程数据监控中的应用,利用多年跟踪部分核心育种场的实际育种数据,阐释了部分育种相关指标的过程监控分析结果,可为育种企业提供过程监控的借鉴.建议种猪育种企业高度重视育种过程监控管理,强化育种工作的计划性,选择合理适用的监控模式和方法,全程监控育种过程关键环节,通过育种流程标准化建设,实时纠正育种过程偏差,确保种猪育种工作的持续平稳运行.

项目采取建立生物安全体系、饲养环境控制、精准营养设计与精准饲喂、动态管理核心群等新技术,取得良好效果.项目出栏猪13.36万头,母猪年产活仔数24.38头；断奶仔猪头均耗料量53.11 kg,全群料重比3.00,肥育猪料重比2.65；全群死亡率5.18％,其中哺乳仔猪2.94％,保育猪2.60％,肥育猪1.73％；母猪年提供商品猪20.63头；新增产值、增收节支分别为6.07亿元、1.86亿元,新增纯收益4.25亿元,利润747元/头；推广种猪7.84万头,带动农民4.3万户,增收11.61亿元；直养人员人均出栏猪2 386头,人均利润58.90万元.

<正>广西农垦永新畜牧集团有限公司良圻原种猪场于2008年10月从美国引进600头美系SPF原种猪,具有体型高长、背腰宽阔平直、肢蹄结实、腿臀丰满等特点。经过一年多的饲养管理和驯化,适应了广西的气候环境,目前种公猪均可正常生产优