This paper presents the current stage of the development of EA-MOSGWA – a tool for identifying causal genes in Genome Wide Association Studies (GWAS). The main goal of GWAS is to identify chromosomal regions which are associated with a particular disease (e.g. diabetes, cancer) or with some quantitative trait (e.g height or blood pressure). To this end hundreds of thousands of Single Nucleotide Polymorphisms (SNP) are genotyped. One is then interested to identify as many SNPs as possible which are associated with the trait in question, while at the same time minimizing the number of false detections.

The software package MOSGWA allows to detect SNPs via variable selection using the criterion mBIC2, a modified version of the Schwarz Bayesian Information Criterion. MOSGWA tries to minimize mBIC2 using some stepwise selection methods, whereas EA-MOSGWA applies some advanced evolutionary algorithms to achieve the same goal. We present results from an extensive simulation study where we compare the performance of EA-MOSGWA when using different parameter settings. We also consider using a clustering procedure to relax the multiple testing correction in mBIC2. Finally we compare results from EA-MOSGWA with the original stepwise search from MOSGWA, and show that the newly proposed algorithm has good properties in terms of minimizing the mBIC2 criterion, as well as in minimizing the misclassification rate of detected SNPs.

Conservation of genetic resources by semen cryopreservation is essential for biodiversity conservation and storage of rare poultry breeds. Despite the widespread use of this method not all individuals presentia similar capacity for semen to be used after defrosting. The aim of the current study was to identify SNP markers and linked candidate genes potentially associated with rooster (Gallus gallus) sperm motility after cryopreservation. Genome-wide association studies were performed using 33 roosters from four breeds genotyped using Illumina Chicken 60K SNP BeadChip Calculations were performed using PLINK and EMMAX software. Significant SNP associations rs15557972 (p<1.36E-07) on chromosome 10 in the LOXL1 gene and rs15751385 (p<6.10E-06) on chromosome 6 in the intron of the ENSGALG00000052127 gene were identified. These findings associated with sperm motility SNPs will help to develop strategies for the selection of valuable individuals and the efficient conservation of the gene pool.