P0670 Refining QTL Regions Affecting Resistance to Parasitic Infection in Yellowtail (Seriola quinqueradiata) by AFLP-based Bulk Segregant Analysis

Junpei Suzuki , Tokyo University of Marine Science and Technology, Tokyo, Japan
Kanako Fuji , Tokyo University of Marine Science and Technology, Tokyo, Japan
Akiyuki Ozaki , National Research Institute of Aquaculture, Fisheries Research Agency, mie, Japan
Kazuo Araki , National Research Institute of Aquaculture, Fisheries Research Agency, mie, Japan
Kazunori Yoshida , Goto Branch of Seikai National Fisheries Research Institute, Fisheries Research Agency, Nagasaki, Japan
Tatsuo Tsuzaki , Goto Branch of Seikai National Fisheries Research Institute, Fisheries Research Agency, Nagasaki, Japan
Nobuaki Okamoto , Tokyo University of Marine Science and Technology, Tokyo, Japan
Takashi Sakamoto , Tokyo University of Marine Science and Technology, Tokyo, Japan
Benedeniasis is a serious disease of yellowtails in mariculture. It is caused by a monogenean parasite, Benedenia seriolae, which attaches to the body surface of yellowtails, leading to the development of secondary infections and a reduction in growth rate. We previously identified two quantitative trait loci (QTLs) for resistance to the parasitic infection on different linkage groups (Squ2 and Squ20) on the yellowtail genetic linkage map. However, the marker density flanking the QTLs was not high enough to identify the responsible genes. In this study, to solve this problem, we performed a bulk segregant analysis combined with an AFLP analysis to increase the marker density in the specific region. We focused on the QTL on Squ2, which showed the largest genetic effect (PVE = 19%). DNA pools obtained from selected offspring from a reference family for linkage mapping allowed us to isolate AFLP fragments that were specifically linked to the QTL region. A total of 256 primer combinations were used and 9 AFLP fragments were identified. Six of these fragments were successfully converted into SCAR markers and mapped to the QTL regions. QTL analysis with the new markers allowed us to narrow down the 95% confidence interval for the QTL on Squ2 from 21.6 cM to 5.5 cM. This strategy will facilitate fine mapping of the QTL and identification of candidate genes and should improve the accuracy of marker-assisted selection.