Combined Use of Univariate and Multivariate Approaches to Detect Selection Signatures Associated with Milk or Meat Production in Cattle.

ABSTRACT:

Objectives

The aim of this study was to investigate the genomic structure of the cattle breeds selected for meat and milk production and to identify selection signatures between them.

Methods

A total of 391 animals genotyped at 41,258 SNPs and belonging to nine breeds were considered: Angus (N = 62), Charolais (46), Hereford (31), Limousin (44), and Piedmontese (24), clustered in the Meat group, and Brown Swiss (42), Holstein (63), Jersey (49), and Montbéliarde (30), clustered in the Milk group. The population stratification was analyzed by principal component analysis (PCA), whereas selection signatures were identified by univariate (Wright fixation index, F_ST) and multivariate (canonical discriminant analysis, CDA) approaches. Markers with F_ST values

SUBMITTER: Congiu M 

PROVIDER: S-EPMC11675734 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature