Comparative transcriptome and gene co-expression network analysis identifies key candidate genes associated with resistance to summer mortality in the Pacific oyster (Crassostrea gigas)

Abstract

The global oyster industry is severely hampered by frequent outbreaks of summer massive mortalities. Selective breeding of disease-resistant broodstock is considered as a key strategy to address this problem, and marker-assisted selection programs would help develop oyster lines that are resistance to summer mortality. However, there is currently a need to identify candidate genes associated with disease resistance and to develop molecular markers based on these genes. To identify candidate genes associated with summer mortality resistance, we selected three most resistant and three most susceptible oyster families and compared their basal transcriptomes. A total of 59 families were tested in two sites, and there were significant differences in summer survival among families of different genetic backgrounds. Principal component analysis showed that there was significant clustering of different resistant families, suggesting that the molecular mechanisms underlying the development of resistance characteristics in different resistant families may be similar. Interestingly, transcriptome results showed that the highly expressed genes in resistant families were mainly associated with innate immunity, especially some pattern recognition receptors, including C-type lectins, fibrinogen-related proteins and scavenger receptors. Some transient receptor potential family genes showed differential expression in the both resistant and susceptible families, which may be related to the thermal tolerance of oysters. Notably, some genes related to antioxidant responses and detoxification were highly expressed in resistant families, such as glutathione S-transferase and Cytochrome P450, suggesting that oysters with summer mortality resistance may have greater antioxidant and detoxification capacities. In addition, weighted gene co-expression network analysis (WGCNA) identified three modules that were significantly positively associated with summer survival. The network map of key modules allows us to identify a series of hub genes, such as PEAR1, MCT12, RPL23, TRPM2, MFAP4, TLN1, SCARF1, GAL9 and ACOD. Overall, our study provides new insight into summer mortality resistance by employing comparative transcriptome and WGCNA, and the genes identified in this study should be further investigated for use in marker-assisted selection breeding programs.