Abstract

To speed up the progress of marker-assisted selection (MAS) in cattle breeding, the dual-specificity tyrosine phosphorylation-regulated kinase 2 (DYRK2), cadherin 2 (CDH2), and kinesin family member 1A (KIF1A) genes were chosen based on our pervious genome-wide association study (GWAS) analysis results. DYRK2 is a kinase that may participate in cell growth and/or development; it shows phosphorylation activity toward serine, threonine, and tyrosine fragments of proteins, and it is different from other protein kinases. The CDH2 gene encodes a classic cadherin, which is a member of the cadherin superfamily. The protein encoded by KIF1A is a member of the kinesin family and plays a role in the transportation of membrane organelles along axon microtubules. We detected insertion/deletion (InDel) variation in these three candidate genes in 438 individual cattle (Xinjiang Brown cattle and Wagyu Luxi crossbreed cattle). Only DYRK2-P3-11 bp was polymorphic and genotyped. The polymorphism information content of DYRK2-P3-11 bp was 0.336. Correlation analyses showed that InDel polymorphism was significantly associated with six different milk traits. These findings may aid future analyses of InDel genotypes in cattle breeds, and speed up the progress of MAS in cattle breeding.

Highlights

  • We listed the frequency of population parameters for this InDel and found that the I allele (0.690) of dual-specificity tyrosine phosphorylation-regulated kinase 2 (DYRK2)-P3-11 bp was more frequent than the D (0.310) allele (Table 2)

  • We studied the correlation between this Xinjiang Brown cattle (XJBC) DYRK2 InDel and milk traits

  • The InDel locus showed a significant relationship with milk traits (Table 3), such as 305 d milk yield (305M) (P < 0.05), protein yield (PY) (P < 0.05) in the fourth parity, and fat yield (FY) (P < 0.05) in the sixth parity

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Summary

Introduction

XJBC are an improved breed of local Chinese yellow cattle, which is obtained by crossing Chinese yellow with Brown Swiss cattle, Alatuowu cattle, and Kostroma cattle (Lin et al, 2010; Li et al, 2018). To have better milk production, genetic variation between cattle varieties and between major genes could be appropriately used to establish breeding programs Many of the potential genes affecting milk traits have not been fully confirmed (Lai et al, 2016; Mota et al, 2017). To solve this problem, GWAS analyses have been used to screen large livestock populations

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