Massive detection of cryptic recessive genetic defects in dairy cattle mining millions of life histories.

ABSTRACT:

Background

Dairy cattle breeds are populations of limited effective size, subject to recurrent outbreaks of recessive defects that are commonly studied using positional cloning. However, this strategy, based on the observation of animals with characteristic features, may overlook a number of conditions, such as immune or metabolic genetic disorders, which may be confused with pathologies of environmental etiology.

Results

We present a data mining framework specifically designed to detect recessive defects in livestock that have been previously missed due to a lack of specific signs, incomplete penetrance, or incomplete linkage disequilibrium. This approach leverages the massive data generated by genomic selection. Its basic principle is to compare the observed and expected n

SUBMITTER: Besnard F 

PROVIDER: S-EPMC11441225 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature