Lars Rönnegård

The paper introduces a Bayesian model, BayesRR-RC, to infer the genetic architecture of complex traits and finds that most genetic variance is attributed to non-proximal regulatory and coding regions.

This paper proposes a genomic selection model that incorporates SNP-specific variance predictors, showing improved accuracy compared to traditional methods.

The paper investigates the genetic architecture of long-term selection responses in Virginia chicken lines, identifying multiple loci and genetic mechanisms contributing to body weight variation.