The field of association mapping studies has recently received major attention for genetic studies of quantitative traits in many important aquatic species. Access to next generation sequencing technologies, high phenotypic data and a variety of sophisticated statistical tools have enabled association mapping studies in aquatic species to be successful in identifying gene loci controlling quantitative traits. Due to the importance of association mapping method in mapping studies of the quantitative traits, the present project was prepared to explain the association mapping method and its use in rainbow trout breeding and also to perform a meta-analysis of these QTL to identify regions of the rainbow trout genome that are consistently associated with growth traits. To identify Meta-QTL (MQTL), a QTL database was developed from 1400 QTL targeted at growth traits. This project also provides some information about statistical software packages used in association mapping and then the opportunities and challenges of association mapping and post-genome wide association studies at the whole genome level discussed. For QTL mapped relative to a single marker, nucleotide sequence of the marker was retrieved from the relevant marker database. For QTL mapped relative to two flanking markers, sequences for both flanking markers were retrieved from the database. The positions of individual QTL were projected onto a consensus genetic map based on the presence of common molecular markers and a 95% confidence interval (CI) was calculated for each QTL. After positioning the individual QTL, the software ‘Biomercator v2.1’ was used to predict the location and CI of MQTL based on maximum likelihood. In total, 854 QTL were reported for 80 growth traits. This included 280 for average daily gain (ADG), 16 for body weight (BW), 9 for Condition factor (CF) and 7 for fork length (FL) trait QTL in rainbow trout genome. In total, 27 QTLs were detected on four linkage groups for the studied traits. That from 2 to 23/8% of the phenotypic variation (LOD) were justified. Most QTLs were detected on 13 linkage groups. In this study, for the body height traits not detected a QTL. Results revealed the existence of co-localized QTLs for studied traits, which enhance the efficiency of marker-assisted selection and developing rainbow trout breeding programs.