AquaGWAS: A Genome-Wide Association Study Pipeline for Aquatic Animals and Its Application to Reference-Required and Reference-Free Genome-Wide Association Study for Abalone - Deng, Chao; Peng, Wenzhu; Ma, Zhi; Ke, Caihuan; You, Weiwei; Wang, Ying (Frontiers in Marine Science, 2022)
Aquaculture is a rapidly growing industry which brings huge economic benefits. Genome-wide association study is critical for the productivity, sustainability, and product quality of aquaculture species. Current integrated GWAS pipeline either only includes specific limited steps, or requires complex prerequisite environment and configurations. In this study, we developed AquaGWAS, a highly user-friendly Graphic User Interface GWAS pipeline integrated four well-known GWAS models. AquaGWAS is a complete GWAS pipeline from preprocessing, multiple choice of GWAS models, postprocessing to visualizations. AquaGWAS not only offers GUI easy running on Linux, but also automatically generates running command line for HPC or non-GUI server. AquaGWAS is free from installation, configurations, and complicated augments input. AquaGWAS offers whole packages of required reference files for 27 common aquatic species. Furthermore, aiming at the issue that SNP detection is limited by the availability of reference genomic sequence, we make the attempt to detect SNPs in Pacific abalone using classical alignment-based reference-required strategy and kmer-based reference-free strategy combined with downstream AquaGWAS. On 222 resequencing data of Pacific abalone, two strategies detect 221061 and 230213 variants respectively with 180161 common variants. The two strategies emphasized on different variant-situations of capturing variants missed by incomplete or inaccurate reference genomic sequence (kmer-based) and capturing the indel variants having the baseline of genomic sequence (alignment-based). The combination of the two strategies offers a complementary framework to obtain the accurate and complete GWAS analysis for non-model organism species. AquaGWAS is available at https://github.com/Ying-Lab/AquaGWAS .