Modelling effects of candidate genes on complex traits as variables over time

Area of Science:

• Animal Genetics
• Dairy Science
• Quantitative Genetics

Background:

• Milk production traits exhibit dynamic changes throughout lactation.
• Previous studies indicated varying additive polygenic effects on milk production over time.
• Understanding genetic determination of milk production requires accounting for temporal variations.

Purpose of the Study:

• To analyze changes in gene effects for milk production traits over time.
• To estimate the potential changes in the magnitude of effects for candidate genes influencing milk production.
• To investigate the temporal dynamics of genetic effects on milk composition and yield.

Main Methods:

• Analysis of daily milk production yields to understand lactation curves.
• Longitudinal modeling of Single Nucleotide Polymorphism (SNP) effects using two independent Holstein-Friesian and Jersey breed datasets.
• Focus on candidate genes including DGAT1, leptin receptor, leptin, and butyrophilin.

Main Results:

• The DGAT1:p.Lys232Ala polymorphism's effect on milk fat and protein content was shown to change during lactation in both breeds.
• Effects of other candidate genes (leptin receptor, leptin, butyrophilin) varied across time but were breed-specific.
• Butyrophilin's effect, potentially missed by time-averaged models, was detected through longitudinal analysis.

Conclusions:

• Longitudinal modeling provides a more precise description of the genetic background of complex traits like milk production.
• Time-averaged models may fail to detect genes with temporally varying effects, such as butyrophilin.
• Accounting for dynamic gene effects is crucial for accurate genetic analysis of milk production traits.