Dadousis Christos, Ablondi Michela, Cipolat-Gotet Claudio, van Kaam Jan-Thijs, Finocchiaro Raffaella, Marusi Maurizio, Cassandro Martino, Sabbioni Alberto, Summer Andrea
Department of Veterinary Science, University of Parma, Parma, Italy.
Associazione Nazionale Allevatori della Razza Frisona Bruna e Jersey Italiana (ANAFIBJ), Cremona, Italy.
Front Vet Sci. 2023 Apr 28;10:1142476. doi: 10.3389/fvets.2023.1142476. eCollection 2023.
The objective of this study was to evaluate the effect of imputation of single nucleotide polymorphisms (SNP) on the estimation of genomic inbreeding coefficients. Imputed genotypes of 68,127 Italian Holstein dairy cows were analyzed. Cows were initially genotyped with two high density (HD) SNP panels, namely the Illumina Infinium BovineHD BeadChip (678 cows; 777,962 SNP) and the Genomic Profiler HD-150K (641 cows; 139,914 SNP), and four medium density (MD): GeneSeek Genomic Profiler 3 (10,679 cows; 26,151 SNP), GeneSeek Genomic Profiler 4 (33,394 cows; 30,113 SNP), GeneSeek MD (12,030 cows; 47,850 SNP) and the Labogena MD (10,705 cows; 41,911 SNP). After imputation, all cows had genomic information on 84,445 SNP. Seven genomic inbreeding estimators were tested: (i) four PLINK v1.9 estimators (F, F), (ii) two genomic relationship matrix (grm) estimators [VanRaden's 1 method, but with observed allele frequencies (F) and VanRaden's 3 method that is allelic free and pedigree dependent (F)], and (iii) a runs of homozygosity (roh) - based estimator (F). Genomic inbreeding coefficients of each SNP panel were compared with genomic inbreeding coefficients derived from the 84,445 imputation SNP. Coefficients of the HD SNP panels were consistent between genotyped-imputed SNP (Pearson correlations ~99%), while variability across SNP panels and estimators was observed in the MD SNP panels, with Labogena MD providing, on average, more consistent estimates. The robustness of Labogena MD, can be partly explained by the fact that 97.85% of the SNP of this panel is included in the 84,445 SNP selected by ANAFIBJ for routine genomic imputations, while this percentage for the other MD SNP panels varied between 55 and 60%. Runs of homozygosity was the most robust estimator. Genomic inbreeding estimates using imputation SNP are influenced by the SNP number of the SNP panel that are included in the imputed SNP, and performance of genomic inbreeding estimators depends on the imputation.
本研究的目的是评估单核苷酸多态性(SNP)插补对基因组近亲繁殖系数估计的影响。分析了68127头意大利荷斯坦奶牛的插补基因型。奶牛最初使用两个高密度(HD)SNP芯片进行基因分型,即Illumina Infinium BovineHD BeadChip(678头奶牛;777962个SNP)和Genomic Profiler HD - 150K(641头奶牛;139914个SNP),以及四个中密度(MD)芯片:GeneSeek Genomic Profiler 3(10679头奶牛;26151个SNP)、GeneSeek Genomic Profiler 4(33394头奶牛;30113个SNP)、GeneSeek MD(12030头奶牛;47850个SNP)和Labogena MD(10705头奶牛;41911个SNP)。插补后,所有奶牛都拥有84445个SNP的基因组信息。测试了七种基因组近亲繁殖估计方法:(i)四种PLINK v1.9估计方法(F、F),(ii)两种基因组关系矩阵(grm)估计方法[VanRaden的方法1,但使用观察到的等位基因频率(F)和VanRaden的方法3,该方法无等位基因且依赖系谱(F)],以及(iii)基于纯合子连续片段(roh)的估计方法(F)。将每个SNP芯片的基因组近亲繁殖系数与从84445个插补SNP得出的基因组近亲繁殖系数进行比较。HD SNP芯片的系数在基因分型 - 插补SNP之间是一致的(Pearson相关性约为99%),而在MD SNP芯片中观察到不同芯片和估计方法之间存在变异性,Labogena MD平均提供了更一致的估计。Labogena MD的稳健性部分可以通过以下事实来解释:该芯片97.85%的SNP包含在ANAFIBJ选择用于常规基因组插补的84445个SNP中,而其他MD SNP芯片的这一比例在55%至60%之间变化。纯合子连续片段是最稳健的估计方法。使用插补SNP的基因组近亲繁殖估计受插补SNP中包含的SNP芯片的SNP数量影响,并且基因组近亲繁殖估计方法的性能取决于插补。