Genetic effects on milk production traits in dairy cattle might change during lactation. However, most genome-wide association studies (GWAS) for milk production traits assume that genetic effects are constant during lactation. This assumption might lead to missing these quantitative trait loci (QTL) whose effects change during lactation. This study aimed to screen the whole genome specifically for QTL whose effects change during lactation. For this purpose, 4 different GWAS approaches were performed using test-day milk protein content records: (1) separate GWAS for specific lactation stages, (2) GWAS for estimated Wilmink lactation curve parameters, (3) a GWAS using a repeatability model where SNP effects are assumed constant during lactation, and (4) a GWAS for genotype by lactation stage interaction using a repeatability model and accounting for changing genetic effects during lactation. Separate GWAS for specific lactation stages suggested that the detection power greatly differs between lactation stages and that genetic effects of some QTL change during lactation. The GWAS for estimated Wilmink lactation curve parameters detected many chromosomal regions for Wilmink parameter a (protein content level), whereas 2 regions for Wilmink parameter b (decrease in protein content toward nadir) and no regions for Wilmink parameter c (increase in protein content after nadir) were detected. Twenty chromosomal regions were detected with effects on milk protein content; however, there was no evidence that their effects changed during lactation. For 5 chromosomal regions located on chromosomes 3, 9, 10, 14, and 27, significant evidence was observed for a genotype by lactation stage interaction and thus their effects on milk protein content changed during lactation. Three of these 5 regions were only identified using a GWAS for genotype by lactation stage interaction. Our study demonstrated that GWAS for genotype by lactation stage interaction offers new possibilities to identify QTL involved in milk protein content. The performed approaches can be applied to other milk production traits. Identification of QTL whose genetic effects change during lactation will help elucidate the genetic and biological background of milk production.