Identification and mapping of disease-resistance QTLs in the eastern oyster, Crassostrea virginica Gmelin
Introduction
The eastern oyster (Crassostrea virginica Gmelin) supports important fishery and aquaculture industries in the United States. The oyster industry is seriously affected by two major diseases: MSX (caused by the parasite Haplosporidium nelsoni) and Dermo (caused by the parasite Perkinsus marinus) (Ford and Tripp, 1996). Each of the two diseases alone may kill 50–90% of the affected oysters. The two diseases, along with over-fishing and habitat destruction, are among the leading causes for the collapse of the oyster fisheries in the mid-Atlantic region (MacKenzie, 1996). They are also hindering efforts in oyster restoration and aquaculture.
Although the two diseases are extremely lethal in the eastern oyster, there is considerable evidence that some oysters are genetically resistant or tolerant to the two diseases. Resistance to MSX has been demonstrated by selective breeding, where survival is greatly improved after five generations of selection (Ford and Haskin, 1987). Moderate resistance to Dermo has also been observed after 4–5 generations of selective breeding (Calvo et al., 2003, Guo et al., 2003). While evidence for genetic determination of disease-resistance is strong, we know little about what and how many genes are involved in determining disease-resistance in the eastern oyster, or their genomic distribution and linkage to other important traits. The identification and mapping of disease-resistance genes or quantitative trait loci (QTLs) may provide valuable information and tools for marker-assisted selection. Marker-assisted selection is particularly useful for the development of disease-resistant oysters because breeding decisions are sometimes made in the absence of disease-exposure (Guo, 2004).
One of the prerequisite for QTL mapping is the availability of a large number of genetic markers. Two types of markers, microsatellites (MS) and amplified fragment length polymorphisms (AFLP), are commonly used for linkage and QTL mapping. MS markers are excellent markers for QTL mapping because of their high levels of polymorphism and co-dominant nature. MS are also expensive to develop and use. In the eastern oyster, only about 25 MS markers are available (Brown et al., 2000, Reece et al., 2004). AFLPs are anonymous and dominant markers that are less transferable and informative than microsatellites, but they can be effectively used in backcrosses as co-dominant markers, and their poor transferability is compensated by the large number of markers that can be quickly developed without prior knowledge of DNA sequences. AFLP markers have been widely used for QTL mapping and breeding in plants (Jin et al., 1998, Goodwin et al., 2003, Bai et al., 1999, Hartl et al., 1999, Altinkut et al., 2003), as well as in aquatic animals (Jackson et al., 1998, Palti et al., 1999, Palti et al., 2001, Palti et al., 2002, Streelman and Kocher, 2002, Shirak et al., 2002, Cnaani et al., 2003). AFLPs have been shown to be effective in linkage mapping in oysters (Yu and Guo, 2003, Li and Guo, 2004).
Another requirement for QTL mapping is availability of reference families where QTLs are well defined and segregating. There is no highly inbred and disease-resistant stock available for making reference crosses in the eastern oyster. On the other hand, high levels of variability in the disease-resistant and wild stocks may provide sufficient segregation of disease-resistance QTLs. Another limitation is that resistance to some diseases (such as MSX) can only be measured by survival. Tissues from susceptible or deceased oysters are not available for genetic analysis. Disease-resistance QTLs can only be identified by markers that show significant frequency shifts after disease-inflicted mortalities. In this study, we tested the feasibility of mapping disease-resistance QTLs in the eastern oyster by screening a large number of AFLP markers before and after disease-inflicted mortalities in two heterozygous families. Our hypothesis is that shifts in frequency after disease-caused mortality are not random, but linked to disease-resistance/susceptibility QTLs on the genetic map. Here we report the identification and mapping of 12 putative disease/mortality-resistance QTLs in the eastern oyster.
Section snippets
Mapping families and strategy
Two families with different genetic backgrounds were used in this study. The first family, NEI-1, is a pair mating between two oysters from the Rutgers disease-resistant strain NEH. NEH is a strain originated from Long Island Sound that has been selected for MSX-resistance since early 1960s and for Dermo-resistance since 1990. NEH has demonstrated strong resistance to MSX and moderate resistance to Dermo (Ford and Haskin, 1987, Guo et al., 2003). While NEH has lost some rare alleles, it has
Mortality in mapping families
The two families had similar patterns of mortality during the studying period but differed somewhat in magnitude (Fig. 1). According to the mortality pattern in Fig. 1, samples collected in September 2000 were chosen as the before-mortality samples, and samples collected in November 2002 were used as the after-mortality samples. There was little mortality during the first year of field deployment. Cumulative field mortality before September 2000 was 4.6% for NEI-1 and 3.1% for DNE-1. By the end
Mapping of putative dermo-resistance QTLs
As far as we can determine, this study represents the first genome scan targeting disease-resistance genes in a mollusc. The number of markers used and the maps developed are adequate for genome wide scan in the eastern oyster. The eastern oyster has an estimated genetic length of 500–650 cM based on chiasmata data (Guo et al., unpublished). The number of markers used for before and after mortality screening, 108 in DNE-1 and 113 in NEI-1, has an expected inter-marker spacing of about 6 cM. The
Acknowledgments
This work is supported by grants from New Jersey Commission on Science and Technology (No. 00-2042-007-20) and NOAA Sea Grant Oyster Disease Research Program (ODRP-29 and R/OD-2003). This is publication IMCS-2005-17 and NJSG-05-614.
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