Genome-wide Association Study Based On The Longitudinal Growth Traits Of Chinese Simmental Beef Cattle

Simmental cattle and their hybrids account for a very large proportion of the beef cattle market in China because of their fast growth rate and high meat yield.Therefore,the regulation mechanism of growth and development of Simmental cattle is one of the research hotspots in beef cattle breeding.A trait whose phenotypic values change over time(lifespan,age,parity,etc.)or other factors(physiological status,environmental conditions,etc.)is called a longitudinal trait.Compared with single data records,longitudinal data can better describe the growth and production rules of livestock and poultry.Therefore,mapping and analysis of functional genes affecting longitudinal traits have great economic value and practical significance for improving the breeding of Simmental cattle.Genome-wide association study(GWAS)is not only an important approach for mapping functional genes of complex traits but also one of the most widely used and effective methods for longitudinal data research.In this study,two-step GWAS and GWAS based on random regression model were used to analyse the longitudinal body weight data of Simmental cattle at four months of age(0,6,12and 18 months).The aim was to locate the SNPs that are significantly associated with the growth and development traits of Simmental cattle and identify candidate genes related to growth and development.The main methods and results of this study are as follows:1.Three growth curve models(Gompertz model,logistic model and Brody model)were used to fit the body weight data of Chinese Simmental cattle at different months of age.The values of parameter A(mature weight)of the three growth curve models were 617.900,551.000 and 1458.000;the values of parameter b(time-scale parameter)were 2.740,9.304 and 0.976;the values of parameter K(maturity rate)were 0.153,0.273 and 0.024,respectively.The goodness of fit R~2 values were 0.954,0.951 and0.951,respectively,indicating that the Gompertz model had the best fitting effect.Therefore,the parameters of the Gompertz model were selected for subsequent analysis.2.The results of the principal component analysis of the experimental population showed that the population was divided into five separate clusters,demonstrating an obvious stratification in the reference population.The majority of individuals are located in the lower right corner,whilst a small number of individuals are distributed in other regions.Therefore,the first three principal components are selected as covariables to eliminate the influence of population stratification on correlation analysis.3.The parameters A,b and K of the Gompertz model were used as phenotypes for single-trait GWAS.For the mature weight trait(A),a total of nine significant SNPs were identified,which were mainly mapped on BTA4,7,10,11,15 and 22 and were near or within PLIN3,BSN,KCNS,etc.For the time-scale parameter(b),a total of 49significant SNPs were identified,which were mainly mapped on BTA1,3,5,9,12,14and 23 and were near or within TMCO1,ANGPTL2,IGF-1,etc.For the maturity rate(K),a total of seven significant SNPs were identified,which were mapped on BTA22and 25 and were near or within GRM7 and SHISA9.4.The parameters A,b and K of the Gompertz model were also used as phenotypes for multi-trait GWAS analysis.A total of 22 significant SNPs were identified,which were mainly mapped on BTA2,3,9,11,14,18,24 and 27 and were near or within CD58,STK3,KAT6A and NBAS.Through GO and KEGG enrichment analysis,135 GO terms and 29 KEGG pathways were enriched,of which 99 GO terms and 12 pathways were significantly enriched(P<0.05).In particular,14 GO terms and seven pathways were associated with growth and development.5.The body weight data of Chinese Simmental cattle at the age of 0,6,12 and 18months were used as the phenotypes of GWAS based on random regression model.A total of 37 significant SNPs were identified,which were mainly mapped on BTA1,2,5,7,11,13,25 and 29,and several candidate genes related to growth and development were identified,such as ICA512,COX6C,RARS,TLK2,MRPL39,PDE1C,SHISA2and ANGPTL4.The conclusions of this study are as follows:1.Some candidate genes related to growth and development were identified by two GWAS methods.These studies provided references for other longitudinal data research and also supported new candidate molecular markers for improving meat production by regulating the growth and development of beef cattle.2.STK3 was found by the two GWAS methods of the two-stage method,and SHISA2,ANGPTL2 and ANGPTL4 were identified by the single-trait GWAS of the two-stage method and the GWAS based on random regression model.Further research should focus on these genes.