Abstract: This study aimed to explore a suitable method for assessing the genetic relationships of indigenous beef breeds in China, based on a systematic comparative analysis of different computational methods for determining kinship. This study focused on 10 local beef cattle breeds, such as Chaidamu cattle, and utilized the resampling method to generate simulated data for these local breeds. Based on this, the study utilized PCA clustering results as a reference and systematically compared different evaluation methods, including predictive error variance, generalized coefficient of determination, predictive error correlation coefficient, and the degree of linkage consistency between SNPs and QTLs, to classify the genetic relationships of these local breeds. Additionally, the study explored the influence of genetic factors on different methods of assessing kinship. The PCA analysis showed that the 10 indigenous beef cattle breeds could be classified into 3 major categories, northern cattle breeds (Chaidamu cattle, Xizang cattle, Mongolian cattle and Yanhuang cattle), southern cattle breeds (Wenshan cattle, Nandan cattle and Leiqiong cattle) and southwestern cattle breeds (Pingwu cattle, Liangshan cattle and Zhaotong cattle). The classification results were consistent with the geographical distribution of the above breeds. Compared with the PCA results, the correlation of persistence of LD phase affinity assessment method was consistent with the PCA clustering results, and the method was able to quantify the relationship using Pearson correlation coefficient relationships with better accuracy. The 3 methods, PEVD, CD and r, were susceptible to the influence of the error variance of the estimated breeding values of the traits when assessing the relationship compared to the above methods, resulting in errors in the assessment results of the relationship. The analysis of factors affecting the assessment results revealed that the PEVD, CD and r methods were susceptible to the influence of the heritability of the assessed traits compared to the PCA and LD phase consistent assessment methods, and the assessment results were less stable. On the other hand, the PCA and LD phase consistent assessment methods are more stable and quantitative in assessing relatedness among breeds because they rely only on genomic data and are not affected by heritability and have better reliability. Therefore, the results based on LD phase consistent assessment method can accurately and quantitatively assess the relationship between breeds and the assessment results are more stable.

Key words: multi-breed genomic selection, relationship, indigenous beef cattle breed, high-density SNP chip, linkage disequilibrium