Effects Of Different SNP Panels On The Estimation Accuracy Of GBC Of Ningxiang Pig

Ningxiang pigs are world-renowned for their strong resistance and excellent meat quality.However,they have also faced a series of serious problems,such as a reduction in population,high inbreeding rate of core breeding groups,and loss of genetic diversity,which have seriously affected the sustainable development of Ningxiang pigs.We estimate the Genomic breed composition(GBC)of them using their genome-wide SNP information to deal with these problems.So that we can carry out population genetic analysis and clear the genetic background of Ningxiang pigs.In this way we will be able to protect their genetic diversity and formulate a scientific and sustainable breeding plan.Finally,it will be an efficient technical support to achieve the breeding goals of Ningxiang pigs’ expansion and new breed cultivation.This study takes Ningxiang pigs as the research object.First,We clean and screen the SNP data of the reference groups including Ningxiang pigs to construct a reference panel by the SNP chip data of 10 reference groups;Then,We selecte different density SNPs from the reference Panel to construct SNP Panels by using 3 methods: uniform-distribution method,maximized the Euclidean distance method and random distribution method.Finally,the linear regression method is used to estimate the GBC of Ningxiang pigs with different SNP panels,and the accuracy of the estimation results is evaluated.The main findings are as follows:1.In order to obtain different information content of SNP,according to the density gradient of 500,1K,5K,10 K,and 20 K SNPs,the uniform distribution,the maximum Euclidean distance and the random distribution are used to select SNPs from the 30 K reference SNP Panels.10 SNP Panels by uniform distribution and the maximum Euclidean distance,15 SNP Panels by random distribution were constructed respectively,which are used for subsequent estimation of GBC of Ningxiang pigs.2.In order to verify the accuracy of GBC estimates,first,we estimate the GBC of 129 Ningxiang pigs using the reference panel constructed by 30 K SNP.The results show that the110 Ningxiang pigs from the breeding farm is 100% pure-bred,and the remaining 19 are verified as non-pure-bred Ningxiang pigs.Ningxiang pigs GBC is estimated using the 25 SNP Panels constructed above,and taking the average value of the GBC estimation results of3 iterations of the random distribution method.Then the estimated accuracy of 15 GBC results is evaluated.The evaluation accuracy of GBC estimates of Ningxiang pigs by different SNP Panels shows that the use of 20 K SNP density by maximization Euclidean distance method to construct Panel Ningxiang pigs has the highest GBC estimation accuracy;If paying attention to economic efficiency,the Panel constructed by the 10 K SNP density by maximizing Euclidean distance method can not only ensure the GBC estimation accuracy of Ningxiang pigs(96.36%),but also effectively control the sequencing cost,which is the most economical and efficient.In summary,it is the expansion and extension of the application of chip data to estimate GBC using SNP chip data.If the goal is to focus on further reducing the cost of chip sequencing in pig genome selection,the 10 K SNP Panel selected by the maximum Euclidean distance method in this study can provide a reference for the development of low-density chips.