畜牧兽医学报  2021, Vol. 52 Issue (10): 2772-2782. DOI: 10.11843/j.issn.0366-6964.2021.010.008    PDF    
不同来源大白猪总产仔数近交衰退评估
史良玉, 王立刚, 张鹏飞, 莫家远, 李洋, 王立贤, 赵福平     
中国农业科学院北京畜牧兽医研究所, 农业部动物遗传育种与繁殖(家禽)重点实验室, 北京 100193
摘要:旨在评估两个不同来源大白猪群体经过近8个世代的选育后总产仔数(total number of piglets born,TNB)近交衰退的程度。本研究对1 937头大白猪使用GeneSeek GGP Porcine HD芯片进行分型,其中1 039头来自加系大白猪和898头来自法系大白猪,且两品系均有表型记录和系谱记录,系谱共由3 086头大白猪组成。分别使用系谱、SNP和ROH进行个体近交系数估计,并将近交系数作为协变量利用动物模型对总产仔数进行近交衰退评估。为了精准定位导致总产仔数衰退的基因组片段,又进一步对每条染色体以及显著染色体分段计算近交系数并估计其效应,检测是否能引起总产仔数发生近交衰退现象。对于加系群体,FROHFGRMFPED估计的近交系数均值分别为0.124、0.042和0.013,其中FROHFPED相关最高,相关系数为0.358;对于法系群体,FROHFGRMFPED均值分别为0.123、0.052和0.007,其中FROHFGRM相关最高,相关系数为0.371。利用3种不同计算方法所得近交系数用于估计近交衰退时,加系群体的总产仔数均检测到显著的近交衰退,而且当FROHFGRMFPED每增加10%时,总产仔数分别减少0.571、0.341和0.823头;但法系群体仅有FROH估计的总产仔数检测到显著近交衰退,FROH每增加10%时,总产仔数减少0.690头。为了锁定相关的染色体和基因组区段,首先利用ROH估计每条染色体近交系数并进行近交衰退分析发现,加系群体中检测到第6、7、8和13号染色体产生了显著近的总产仔数交衰退,而法系群体未检测到与近交衰退相关的染色体。然后,又将与加系总产仔数近交衰退显著相关的4条染色体平均分为2、4、6、8个片段进行近交衰退检测,其中平均分成8段后的染色片段的长度范围为15.1~25.8 Mb。在第6、7和8号染色体分别检测到1、2和3个与总产仔数相关的近交衰退染色体片段。这些区域注释到了CUL7、MAPK14和PPARD基因与胎盘发育相关,AREGEREG基因与卵母细胞成熟有关。本研究利用3种近交系数计算方法对两个不同来源的大白猪总产仔数进行近交衰退评估,在加系大白猪中3种估计方法都能检测到近交衰退的现象,而法系群体中只有FROH才能检测到。而且通过ROH方法进一步确定了能引起加系大白猪总产仔数衰退的4条染色体和6个特定的染色体区段,还注释到了与繁殖相关的候选基因。这为揭示近交衰退的遗传机制提供了新的研究手段,也为基因组选种选配提供了参考依据。
关键词大白猪    总产仔数    连续纯合片段    近交系数    近交衰退    
Evaluation of Inbreeding Depression on the Total Numbers of Piglets Born in Different Groups of Large White Pigs
SHI Liangyu, WANG Ligang, ZHANG Pengfei, MO Jiayuan, LI Yang, WANG Lixian, ZHAO Fuping     
Key Laboratory of Animal Genetics, Breeding and Reproduction(poultry) of Ministry of Agriculture, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
Abstract: The purpose of this study was to evaluate the inbreeding depression for TNB in Large White pigs with different genetic background after about 8 generations of selection. A total of 1 937 sows with phenotypic and pedigree records were genotyped with GeneSeek GGP Porcine HD chip. Out of them, 1 039 Large White pigs were from the Canadian line and 898 were from the French line. The pedigree of the two lines consisted of 3 086 Large White pigs. Inbreeding coefficients were estimated using 3 different measures based on pedigree data, SNPs and runs of homozygosity (ROH), respectively. Inbreeding depression of TNB was evaluated using an animal model in which the inbreeding coefficient was treated as a covariate. To fine mapping the genomic regions that lead to inbreeding depression of TNB, the inbreeding coefficients of each autosome and significant autosome segments were calculated and their effects were estimated. And then all the significant autosomes were divided into several segments with equal size and these genomic regions were further tested whether they were associated to inbreeding depression of TNB. In Canadian line, the average inbreeding coefficients of FROH, FGRM and FPED estimated were 0.124, 0.042 and 0.013, respectively. Among pairwise correlations between the different inbreeding coefficients across individuals, the highest correlation was between FROH and FPED and the correlation coefficient was 0.358. In French line, the average inbreeding coefficients of FROH, FGRMand FPED estimated were 0.123, 0.052 and 0.007, respectively. The highest pairwise correlation was between FROH and FGRM, and the correlation coefficient was 0.371. On the whole genome level, significant inbreeding depression was found for TNB in Canadian line using all 3 measures of inbreeding. Estimates of inbreeding depression were -0.571, -0.341 and -0.823 for TNB per 10% increase in FROH, FGRMand FPED, respectively. While in French line, only using FROH could detect significant inbreeding depression and a 10% increase in FROH resulted in a decrease of 0.690 for TNB. On the chromosome level, ROH-based inbreeding coefficient for each chromosome was used to perform inbreeding depression analysis. The results showed that chromosome 6, 7, 8 and 13 in the Canadian line were identified to be significant related to inbreeding depression for TNB, but in French line, no chromosome was associated to inbreeding depression. To narrow down the genomic regions causing inbreeding depression, the 4 significant chromosomes in Canadian lines were further divided into 2, 4, 6, 8 segments with equal size. When these 4 autosomes were divided into 8 segment, the segment lengths ranged from 15.1 to 25.8 Mb. Finally, one, two and three genomic segments on chromosome 6, 7 and 8 were found to be significantly associated with inbreeding depression, respectively. These regions harbored CUL7, MAPK14 and PPARD genes that were associated with placental development, and AREG and EREG genes involved in oocyte maturation. Three calculation measures of inbreeding coefficients were used to evaluate inbreeding depression for TNB in Large White pigs with different genetic background. At the genome level, significant inbreeding depression in Canadian line was detected for TNB using all 3 measures of inbreeding, but only the effect of FROH was significant in French lines. At the chromosome level, 4 autosomes showed significant effects. Use of ROH further identified the 4 chromosomes and 6 specific genomic segments that could lead to significant reduction in TNB of Canadian line. These specific genomic segments were annotated candidate genes related to reproduction. The study results not only provided a new sight into revealing the genetic mechanism of inbreeding depression, but also provided a reference for carrying out genomic selection and mating schemes in pigs.
Key words: Large White pigs    total number of piglets born    runs of homozygosity    inbreeding coefficient    inbreeding depression    

近交是将有亲缘关系的个体进行交配。在畜牧生产中,群体规模有限,近交难以避免。近交水平的增加会导致基因组中有害纯合子的增加,产生近交衰退,导致后代生产性能降低[1]。目前众多研究表明,在不同物种中,近交会影响动物的生产性能[1-3],尤其是牛的繁殖性能[4-6],但近交对猪繁殖性能影响的研究相对较少[7]。传统的近交系数计算方法是基于完整的系谱记录信息。随着基因组数据的不断涌现,从基因组层面能找到共同祖先传递下来的相同单倍型片段,即连续纯合基因型片段(runs of homozygosity, ROH)。根据ROH片段提供的遗传信息可以有效的估计出个体实现的近交系数,这为计算个体近交系数提供了新的途径[8]。另外,还可以利用ROH对每条染色体或某个染色体片段进行特定基因组区段的近交系数估计,并进一步估计其对近交衰退的影响程度。

本研究分别使用系谱、全基因组SNP标记和ROH计算个体的近交系数,并利用混合线性模型检测近交系数与加系和法系大白猪群体的总产仔数(total number of piglets born, TNB)的相互关系,从而评估近交衰退程度,并进一步定位导致大白猪总产仔数近交衰退具体的染色体区域,为基因组选种和选配提供参考。

1 材料与方法 1.1 试验材料

本研究选取上海某公司1 937头大白猪,其中1 039头来自加系,898头来自法系,且两群体无亲缘关系。加系和法系群体分别饲养在两个不同的场,且两场营养管理水平基本相同。两群体系谱共由3 086头大白猪组成,系谱记录时间为2012—2019年,大约8个世代。仅对有芯片且有系谱的1 937头大白猪个体进行近交系数的计算及近交衰退分析。

1.2 基因型数据及质控

对1 937头大白猪使用GeneSeek GGP Porcine HD芯片进行分型。由于该芯片根据Sus scrofa 10.2版本设计,将其更新为Sus scrofa 11.1版本进行后续分析。使用PLINK v1.90软件[9]进行质控,质控条件如下:个体基因型检出率>90%,标记基因型检出率>90%,最小等位基因频率>0.05,仅保留常染色体SNP标记。质控后剩余37 310个SNPs,1 937头大白猪。

1.3 近交系数估计

1.3.1 基于ROH的近交系数估计   使用PLINK v1.90软件[9]进行ROH检测。ROH的鉴定标准为:1)ROH的最小长度为1 Mb;2)每个ROH至少由45个SNPs组成,该参数计算公式由Lencz等[10]提出:

$ l = \frac{{{{\log }_e}\frac{\alpha }{{{n_s} \times {n_i}}}}}{{{{\log }_e}\left( {1 - \overline {het} } \right)}} $

其中,α为ROH假阳性率(本研究中设置为0.05),ns为每个个体SNPs数目,ni为个体数,het 为全部SNPs中杂合子比例;3)连续SNPs间距离小于1 Mb;4)ROH最小密度为100 kb/SNP;5)以50个SNPs组成滑动窗口,每次滑动1个SNP;6)每个ROH中最多允许5个缺失及1个杂合子;7)窗口阈值为0.01。

基于ROH估计的近交系数(FROH)计算公式为:

$ {F_{{\rm{ROH}}}} = \frac{{\sum {_i{L_{RO{H_I}}}} }}{{{L_{auto}}}} $

其中,LROHi为个体i的ROH长度,Lauto为芯片中常染色体SNPs覆盖长度。

1.3.2 基于SNPs的近交系数估计   基于SNPs估计的近交系数(FGRM)计算公式[11]为:

$ \begin{array}{l} {F_{{\rm{GRM}}}} = \sum\nolimits_{i = 1}^m {({{\left[ {{x_i} - E\left( {{x_i}} \right)} \right]}^2}/[2{p_i}\left( {1 - {p_i}} \right) - } \\ 1])/m \end{array} $

其中,xi为第i个SNP主等位基因的数量,m为SNPs数量,pi为主等位基因频率。

1.3.3 基于系谱的近交系数估计   使用BLUPF90家族程序(http://nce.ads.uga.edu/wiki/doku.php?id=application_programs)对系谱进行检测校正。校正后的系谱可追溯世代数为1~8代,平均世代数为5.33代。使用R pedigreemm包[12]利用校正后的系谱估计近交系数(FPED)[13]

1.4 近交衰退分析

由于加系和法系大白猪拥有不同的遗传背景,因此本研究使用DMU软件分别对两个品系大白猪的总产仔数进行近交衰退评估,采用分析模型如下:

$ y_{i j k}=\mu+Y S_{i}+P_{j}+\beta F_{k}+a_{k}+P e_{k}+e_{i j k} $

其中,yijk是在第i个年季的第j个胎次的第k个体的总产仔数,其中i划分了22个水平,j划分为了7个水平,k为两个品系中的个体数;μ为总体均值;YSi为第i个产仔年季效应;Pj为胎次效应;Fk为第k个个体近交系数协变量;β为对应协变量的回归系数,即近交衰退效应值;ak为个体k的加性遗传效应,服从N(0, σA2)分布;Pek为个体k永久环境效应,服从N(0, σPe2)分布;eijk为随机残差,服从N(0, σe2)分布。虽然两个品系分别饲养在不同的场,但采用了公司统一的饲养管理方式,且对两个品系分别进行分析,所以模型中没有考虑场效应。

2 结果 2.1 表型数据描述性统计

对于加系群体,共有4 710条产仔记录,平均胎次为3.220;法系群体共有3 546条产仔记录,平均胎次为3.049。两品系总产仔数基本统计量见表 1

表 1 两品系总产仔数基本统计量 Table 1 The basic statistics for the total number of piglets born in two different lines
2.2 两品系近交系数估计

表 2所示,对于两个品系,基于基因组信息估计的近交系数(FROHFGRM)均值均高于基于系谱估计的近交系数(FPED)。加系群体FROHFPED均值均高于法系群体,FGRM均值低于法系群体。在两个品系中,不同方法估计的近交系数之间的皮尔逊相关均为正相关(表 3)。对于加系群体,FROHFPED之间的相关最高,相关系数为0.358;对于法系群体,FROHFGRM之间的相关最高,相关系数为0.371。

表 2 基于基因组信息和系谱估计的近交系数分布 Table 2 Distribution of the estimated inbreeding coefficients based on pedigree and genomic information
表 3 不同方法估计的近交系数的皮尔逊相关 Table 3 Pearson correlations between different inbreeding coefficients estimated by different methods

两品系近交系数随个体出生年份变化如图 1所示。由于2014年仅1头个体出生,故在趋势分析中不考虑。2015—2019年间出生的个体,随着年份的增加,两品系FPED均呈现上升趋势,且加系群体FPED均高于法系群体。FROH波动趋势基本相同,2018—2019年出生个体的FROH高于2015—2017年出生个体。对于加系群体,FGRM随着个体出生年份增加呈现上升趋势;对于法系群体,FGRM随着个体出生年份增加呈现先下降再上升趋势。

图 1 两品系2014—2019年出生个体不同方法估计的近交系数 Fig. 1 The inbreeding coefficients for pig born between 2014 and 2019 estimated by different methods
2.3 两品系大白猪不同染色体及片段近交衰退估计

基于基因组近交系数(FROHFGRM)和系谱近交系数(FPED),利用混合线性模型对大白猪总产仔数的近交衰退进行评估,以近交系数这一协变量的回归系数β作为近交衰退效应大小,结果见表 4。尽管不同方法估计近交系数所得近交衰退效应大小不同,但随着近交系数的增加,加系群体总产仔数均显著减少。FPED每增加10%,加系群体总产仔数减少(0.823±0.276)头。FROH每增加10%,加系群体和法系群体总产仔数分别减少(0.571±0.178)、(0.690±0.324)头。

表 4 两品系近交系数每增加10%总产仔数近交衰退估计 Table 4 Estimation of inbreeding depression (SE) for per 10% increase in inbreeding coefficients for total number of piglets born in two lines

使用FROH对每条常染色体进行两个品系总产仔数近交衰退估计,结果显示,加系群体第6、7、8和13号染色体效应显著,而法系群体未发现显著产生近交衰退的常染色体(图 2)。为了检测加系群体中导致近交衰退特定的基因组区域,将对随着近交系数增加总产仔数显著降低的染色体进行分段分析。根据第6、7、8和13号染色体在芯片中覆盖的长度分别平均分成2、4、6、8条片段,利用在相应片段内的FROH进行近交衰退分析。不同染色体不同片段结果如表 5表 6表 7表 8所示,当染色体分割成2个片段时,6号和8号染色体的第一段显著,7号染色体第一段极显著。当将染色体分割为8条片段时,对于6号染色体,仅第一条片段效应显著,该片段位于6号染色体0.052~21.347 Mb之间;对于7号染色体,第三条片段(30.445~45.667 Mb)效应极显著,第六条片段(76.112~91.335 Mb)效应显著;对于8号染色体,第一条片段(0.075~17.360 Mb)效应极显著,第三条片段(34.719~52.079 Mb)效应显著,第五条片段(69.438~86.798 Mb)效应显著。无论将染色体分割为几段,第13号染色体中的片段均不显著。

图 2 加系群体和法系群体总产仔数每条染色体每增加10% FROH近交衰退估计值及95%置信区间 Fig. 2 Inbreeding depression estimation in total number of piglets born per 10% increase in FROH and 95% confidence interval across autosomes for Canadian line and French line
表 5 加系群体6号染色体不同区域总产仔数近交衰退估计 Table 5 Estimation of inbreeding depression for different regions on SSC6 for total number of piglets born in Canadian line Large White pigs
表 6 加系群体7号染色体不同区域总产仔数近交衰退估计 Table 6 Estimation of inbreeding depression for different regions on SSC7 for total number of piglets born in Canadian line Large White pigs
表 7 加系群体8号染色体不同区域总产仔数近交衰退估计 Table 7 Estimation of inbreeding depression for different regions on SSC8 for total number of piglets born in Canadian line Large White pigs
表 8 加系群体13号染色体不同区域总产仔数近交衰退估计 Table 8 Estimation of inbreeding depression for different regions on SSC13 for total number of piglets born in Canadian line Large White pigs
3 讨论

本研究采用了3种计算近交系数的方法对大白猪总产仔数的近交衰退进行评估。FPED的计算完全依赖于系谱信息,而实际生产中系谱常会出现记录错误和缺失的现象[14-15],并且假定基础群个体间无亲缘关系,这些都可能会低估近交水平。利用SNP计算近交系数时,很难辨别SNP是否是同源相同(identical by descent, IBD)还是同态相同(identical by state, IBS),常会高估近交水平[16]。另外,SNP对最小等位基因频率更加敏感,可能会导致FGRM估计准确性降低[17]。当有基因型的个体较少时FGRM估计不够准确,这会降低近交衰退估计的统计能力[18]。ROH是父母将来自共同祖先同一段单倍型传递给后代所形成的,所以ROH一般都属于IBD单倍型片段。因此,ROH近交系数既能避免系谱近交系数低估情况,又能避免SNP近交系高估的问题。而且FROH主要基于个体的基因组数据,不再依赖于系谱记录,能提供更准确的近交系数[19]。另外ROH还能够精细的定位因近交而造成衰退的特定基因组区段。所以,FROH已被认为是评估畜禽亲缘关系和近交系数的一种有效且准确的替代方法[20]

本研究中法系群体FROHFGRM与之间的相关高于其他对大白猪的研究报道[21],可能是由于本研究中大白猪群体产生了遗传漂变。尽管相比系谱使用基因组数据能够提高亲缘关系估计的准确性[22],但是FGRM有可能会得到负值。随着个体出生年份的增加,两品系FPED呈上升趋势。系谱中个体最早出生于2012年,而且假设基础群个体间无亲缘关系,因此2015年出生个体近交程度相对较低。法系群体在2018年之前使用系谱进行选择,自2018年起使用基因组选择,选择更加准确,可能会使基因型的同质性增加。另外,法系群体相对较小,利用SNP进行近交系数计算时,由于该方法对最小等位基因频率敏感,使近交系数有波动的现象。本研究群体中并未再引种而导入外源血统,FPED会随着年份的增长而增加。FROHFPED之间的相关在两个品种中较低,分别为0.358、0.275,该结果与先前其他研究一致[23-24]。加系群体FROHFPED与之间的相关高于法系群体,可能是加系群体具有更加完整的系谱记录,可追溯的平均世代数为5.493。

目前关于猪繁殖性状近交衰退的研究较少。周平等[25]根据近交系数在0~20%范围内将大白猪分为4组,结果表明,近交程度对相同胎次产仔数的影响不大,与胎次关系较为密切。但该研究仅采用简单的方差分析,未能消除胎次等效应因近交对产仔数的影响。Miglior等[26]使用系谱对奶牛泌乳期平均体细胞评分进行近交衰退估计,结果表明, 近交系数每增加1%奶牛泌乳期平均体细胞评分增加0.012。已有研究利用SNP和ROH进行近交系数估计,从而评估近交衰退程度,其中仅少数几个研究定位了近交衰退片段[27-30]。Saura等[16]利用ROH计算109头母猪近交系数并鉴定到13号染色体一个近交衰退片段。本研究检测出13号染色能引起加系大白猪群体的总产仔数产生近交衰退现象,但未能检测到具体的染色体片段。分析原因有:1)在13号染色体86.188~160.936 Mb每个个体均未检测到ROH;2)本研究只是按照染色体的长度将其平均划分为2~8段,这种分段方法也可能使原有近交衰退片段被打断。

本研究使用BioMart工具(ensembl.org/bio -mart)进一步对第6、7和8号染色体上存在近交衰退的ROH片段进行基因注释,共注释到601个基因。其中与繁殖性状相关的功能基因有5个,分别位于7号染色体30.5~45.7 Mb的ROH区段中的CUL7、MAPK14、PPARD基因和位于8号染色体69.4~86.8 Mb处ROH片段上的AREGEREG基因。研究发现,CUL7[31-32]MAPK14[33]PPARD基因[34-35]与胎盘发育相关,AREGEREG基因与卵母细胞成熟相关[36-38]。由于近交导致以上基因中隐性有害纯合子的增加,造成总产仔数的下降。

4 结论

本研究针对两个不同背景来源的大白猪在经过约8个世代的选育后,利用基于系谱和基因型数据信息的3种方法估计近交系数,并评估近交对总产仔数的负面影响。加系和法系大白猪FROH的平均值分别为0.124、0.123。随着个体出生年份的增加,FPED也随之呈现上升趋势。对于加系群体,3种方法都检测到随着近交系数的增加,大白猪总产仔数呈现不同程度的降低,FROHFPED结果更为接近。而在法系群体中,仅FROH检测到了近交衰退。利用FROH还检测到4条染色和多个特定染色体区域存在近交衰退的现象。本研究不仅为系谱数据缺失的群体,开展近交衰退估计提供新的研究方法,也为避免近交实施猪基因组选种选配工作提供了参考依据。

参考文献
[1]
CHARLESWORTH D, WILLIS J H. The genetics of inbreeding depression[J]. Nat Rev Genet, 2009, 10(11): 783-796. DOI:10.1038/nrg2664
[2]
HOWARD J T, PRYCE J E, BAES C, et al. Invited review: Inbreeding in the genomics era: Inbreeding, inbreeding depression, and management of genomic variability[J]. J Dairy Sci, 2017, 100(8): 6009-6024. DOI:10.3168/jds.2017-12787
[3]
LEROY G. Inbreeding depression in livestock species: review and meta-analysis[J]. Anim Genet, 2014, 45(5): 618-628. DOI:10.1111/age.12178
[4]
MARTIKAINEN K, SIRONEN A, UIMARI P. Estimation of intrachromosomal inbreeding depression on female fertility using runs of homozygosity in Finnish Ayrshire cattle[J]. J Dairy Sci, 2018, 101(12): 11097-11107. DOI:10.3168/jds.2018-14805
[5]
GONZÁLEZ-RECIO O, DE MATURANA E L, GUTIÉRREZ J P. Inbreeding depression on female fertility and calving ease in Spanish dairy cattle[J]. J Dairy Sci, 2007, 90(12): 5744-5752. DOI:10.3168/jds.2007-0203
[6]
FERENČAKOVIĆ M, SÖLKNER J, KAPŠ M, et al. Genome-wide mapping and estimation of inbreeding depression of semen quality traits in a cattle population[J]. J Dairy Sci, 2017, 100(6): 4721-4730.
[7]
CASELLAS J, IBÁÑEZ-ESCRICHE N, VARONA L, et al. Inbreeding depression load for litter size in Entrepelado and Retinto Iberian pig varieties1[J]. J Anim Sci, 2019, 97(5): 1979-1986.
[8]
SHI L Y, WANG L G, LIU J X, et al. Estimation of inbreeding and identification of regions under heavy selection based on runs of homozygosity in a Large White pig population[J]. J Anim Sci Biotechnol, 2020, 11: 46.
[9]
PURCELL S, NEALE B, TODD-BROWN K, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses[J]. Am J Hum Genet, 2007, 81(3): 559-575.
[10]
LENCZ T, LAMBERT C, DEROSSE P, et al. Runs of homozygosity reveal highly penetrant recessive loci in schizophrenia[J]. Proc Natl Acad Sci U S A, 2007, 104(50): 19942-19947.
[11]
YANG J, LEE S H, GODDARD M E, et al. GCTA: a tool for genome-wide complex trait analysis[J]. Am J Hum Genet, 2011, 88(1): 76-82.
[12]
VAZQUEZ A I, BATES D M, ROSA G J M, et al. Technical note: an R package for fitting generalized linear mixed models in animal breeding[J]. J Anim Sci, 2010, 88(2): 497-504.
[13]
WRIGHT S. Evolution in Mendelian populations[J]. Genetics, 1931, 16(2): 97-159.
[14]
UIMARI P, TAPIO M. Extent of linkage disequilibrium and effective population size in Finnish Landrace and Finnish Yorkshire pig breeds[J]. J Anim Sci, 2011, 89(3): 609-614.
[15]
WANG L, SØRENSEN P, JANSS L, et al. Genome-wide and local pattern of linkage disequilibrium and persistence of phase for 3 Danish pig breeds[J]. BMC Genet, 2013, 14: 115. DOI:10.1186/1471-2156-14-115http:/link.springer.com/content/pdf/10.1186/1471-2156-14-115.pdf
[16]
SAURA M, FERNÁNDEZ A, VARONA L, et al. Detecting inbreeding depression for reproductive traits in Iberian pigs using genome-wide data[J]. Genet Sel Evol, 2015, 47: 1.
[17]
SUMREDDEE P, TOGHIANI S, HAY E H, et al. Inbreeding depression in line 1 Hereford cattle population using pedigree and genomic information[J]. J Anim Sci, 2019, 97(1): 1-18.
[18]
KELLER M C, VISSCHER P M, GODDARD M E. Quantification of inbreeding due to distant ancestors and its detection using dense single nucleotide polymorphism data[J]. Genetics, 2011, 189(1): 237-249.
[19]
PERIPOLLI E, STAFUZZA N B, MUNARI D P, et al. Assessment of runs of homozygosity islands and estimates of genomic inbreeding in Gyr (Bos indicus) dairy cattle[J]. BMC Genomics, 2018, 19(1): 34.
[20]
PURFIELD D C, BERRY D P, MCPARLAND S, et al. Runs of homozygosity and population history in cattle[J]. BMC Genet, 2012, 13: 70.
[21]
SHI L Y, WANG L G, LIU J X, et al. Estimation of inbreeding and identification of regions under heavy selection based on runs of homozygosity in a Large White pig population[J]. J Anim Sci Biotechnol, 2020, 11: 46.
[22]
GODDARD M. Genomic selection: prediction of accuracy and maximisation of long term response[J]. Genetica, 2009, 136(2): 245-257.
[23]
ZANELLA R, PEIXOTO J O, CARDOSO F F, et al. Genetic diversity analysis of two commercial breeds of pigs using genomic and pedigree data[J]. Genet Sel Evol, 2016, 48: 24.
[24]
LOPES M S, SILVA F F, HARLIZIUS B, et al. Improved estimation of inbreeding and kinship in pigs using optimized SNP panels[J]. BMC Genet, 2013, 14: 92.
[25]
周平, 徐敏祥, 林泳祥, 等. 大白猪不同近交程度对繁殖性能的影响[J]. 养猪, 2013(1): 67-68.
ZHOU P, XU M X, LIN Y X, et al. Effects of different inbred degrees on reproductive performance of large white pigs[J]. Swine Product, 2013(1): 67-68. (in Chinese)
[26]
MIGLIOR F, BURNSIDE E B, DEKKERS J C M. Nonadditive genetic effects and inbreeding depression for somatic cell counts of Holstein cattle[J]. J Dairy Sci, 1995, 78(5): 1168-1173.
[27]
BJELLAND D W, WEIGEL K A, VUKASINOVIC N, et al. Evaluation of inbreeding depression in Holstein cattle using whole-genome SNP markers and alternative measures of genomic inbreeding[J]. J Dairy Sci, 2013, 96(7): 4697-4706.
[28]
ZILKO J P, HARLEY D, HANSEN B, et al. Accounting for cryptic population substructure enhances detection of inbreeding depression with genomic inbreeding coefficients: an example from a critically endangered marsupial[J]. Mol Ecol, 2020, 29(16): 2978-2993.
[29]
MAKANJUOLA B O, MALTECCA C, MIGLIOR F, et al. Effect of recent and ancient inbreeding on production and fertility traits in Canadian Holsteins[J]. BMC Genomics, 2020, 21(1): 605.
[30]
NISKANEN A K, BILLING A M, HOLAND H, et al. Consistent scaling of inbreeding depression in space and time in a house sparrow metapopulation[J]. Proc Natl Acad Sci U S A, 2020, 117(25): 14584-14592.
[31]
GASCOIN-LACHAMBRE G, BUFFAT C, REBOURCET R, et al. Cullins in human intra-uterine growth restriction: expressional and epigenetic alterations[J]. Placenta, 2010, 31(2): 151-157.
[32]
TSUNEMATSU R, NISHIYAMA M, KOTOSHIBA S, et al. Fbxw8 is essential for Cul1-Cul7 complex formation and for placental development[J]. Mol Cell Biol, 2006, 26(16): 6157-6169.
[33]
OKADA Y, UESHIN Y, ISOTANI A, et al. Complementation of placental defects and embryonic lethality by trophoblast-specific lentiviral gene transfer[J]. Nat Biotechnol, 2007, 25(2): 233-237.
[34]
BLITEK A, SZYMANSKA M. Expression and role of peroxisome proliferator-activated receptors in the porcine early placenta trophoblast[J]. Domest Anim Endocrinol, 2019, 67: 42-53.
[35]
DING H J, ZHANG Y Y, LIU L, et al. Activation of peroxisome proliferator activator receptor delta in mouse impacts lipid composition and placental development at early stage of gestation[J]. Biol Reprod, 2014, 91(3): 57.
[36]
RINCÓN J A A, GINDRI P C, MION B, et al. Early embryonic development of bovine oocytes challenged with LPS in vitro or in vivo[J]. Reproduction, 2019, 158(5): 453-463.
[37]
NIRINGIYUMUKIZA J D, CAI H C, XIANG W P. Prostaglandin E2 involvement in mammalian female fertility: ovulation, fertilization, embryo development and early implantation[J]. Reprod Biol Endocrinol, 2018, 16(1): 43.
[38]
ZAMAH A M, HSIEH M, CHEN J, et al. Human oocyte maturation is dependent on LH-stimulated accumulation of the epidermal growth factor-like growth factor, amphiregulin[J]. Hum Reprod, 2010, 25(10): 2569-2578.

(编辑   郭云雁)