Kabanov Artem, Melnikova Ekaterina, Nikitin Sergey, Somova Maria, Fomenko Oleg, Volkova Valeria, Kostyunina Olga, Karpushkina Tatiana, Martynova Elena, Trebunskikh Elena
L.K. Ernst Federal Research Center for Animal Husbandry, Dubrovitzy Estate, Podolsk District, 142132 Moscow, Russia.
All-Russian Dairy Research Institute, 115093 Moscow, Russia.
Animals (Basel). 2022 Jun 30;12(13):1693. doi: 10.3390/ani12131693.
Changes in the accuracy of the genomic estimates obtained by the ssGBLUP and wssGBLUP methods were evaluated using different reference groups. The weighting procedure's reasonableness of application Pwas considered to improve the accuracy of genomic predictions for meat, fattening and reproduction traits in pigs. Six reference groups were formed to assess the genomic data quantity impact on the accuracy of predicted values (groups of genotyped animals). The datasets included 62,927 records of meat and fattening productivity (fat thickness over 6-7 ribs (BF1, mm)), muscle depth (MD, mm) and precocity up to 100 kg (age, days) and 16,070 observations of reproductive qualities (the number of all born piglets (TNB) and the number of live-born piglets (NBA), according to the results of the first farrowing). The wssGBLUP method has an advantage over ssGBLUP in terms of estimation reliability. When using a small reference group, the difference in the accuracy of ssGBLUP over BLUP AM is from -1.9 to +7.3 percent points, while for wssGBLUP, the change in accuracy varies from +18.2 to +87.3 percent points. Furthermore, the superiority of the wssGBLUP is also maintained for the largest group of genotyped animals: from +4.7 to +15.9 percent points for ssGBLUP and from +21.1 to +90.5 percent points for wssGBLUP. However, for all analyzed traits, the number of markers explaining 5% of genetic variability varied from 71 to 108, and the number of such SNPs varied depending on the size of the reference group (79-88 for BF1, 72-81 for MD, 71-108 for age). The results of the genetic variation distribution have the greatest similarity between groups of about 1000 and about 1500 individuals. Thus, the size of the reference group of more than 1000 individuals gives more stable results for the estimation based on the wssGBLUP method, while using the reference group of 500 individuals can lead to distorted results of GEBV.
使用不同的参考群体评估了通过ssGBLUP和wssGBLUP方法获得的基因组估计准确性的变化。考虑了加权程序应用P的合理性，以提高猪的肉用、育肥和繁殖性状的基因组预测准确性。形成了六个参考群体，以评估基因组数据量对预测值准确性的影响（基因分型动物群体）。数据集包括62927条肉用和育肥生产力记录（第6 - 7肋处脂肪厚度（BF1，毫米））、肌肉深度（MD，毫米）和100千克体重时的早熟性（年龄，天），以及16070条繁殖性状观测值（根据第一胎产仔结果的总产仔数（TNB）和活产仔数（NBA））。在估计可靠性方面，wssGBLUP方法优于ssGBLUP。当使用小参考群体时，ssGBLUP相对于BLUP AM的准确性差异为 - 1.9至 + 7.3个百分点，而对于wssGBLUP，准确性变化范围为 + 18.2至 + 87.3个百分点。此外，对于最大的基因分型动物群体，wssGBLUP的优势也得以保持：ssGBLUP为 + 4.7至 + 15.9个百分点，wssGBLUP为 + 21.1至 + 90.5个百分点。然而，对于所有分析的性状，解释5%遗传变异的标记数量在71至108之间变化，此类单核苷酸多态性（SNP）的数量因参考群体大小而异（BF1为79 - 88，MD为72 - 81，年龄为71 - 108）。基因变异分布结果在约1000和约1500个体的群体之间具有最大的相似性。因此，超过1000个体的参考群体大小基于wssGBLUP方法进行估计时会给出更稳定的结果，而使用500个体的参考群体可能导致基因组估计育种值（GEBV）结果失真。
