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A Whole Mount In Situ Hybridization Method for the Gastropod Mollusc Lymnaea stagnalis
Published on: March 15, 2016
Pyrosequencing-based transcriptomic resources in the pond snail Lymnaea stagnalis, with a focus on genes involved in
Anthony Bouétard1, Céline Noirot, Anne-Laure Besnard
1INRA, UMR0985 INRA-Agrocampus Ouest ESE, Equipe Ecotoxicologie et Qualité des Milieux Aquatiques, 65 rue de Saint-Brieuc, 35042, Rennes cedex, France.
Abstract:
Due to their ability to explore whole genome response to drugs and stressors, omics-based approaches are widely used in toxicology and ecotoxicology, and identified as powerful tools for future ecological risk assessment and environmental monitoring programs. Understanding the long-term effects of contaminants may indeed benefit from the coupling of genomics and eco-evolutionary hypotheses. Next-generation sequencing provides a new way to investigate pollutants impact, by targeting early responses, screening chemicals, and directly quantifying gene expression, even in organisms without reference genome. Lymnaea stagnalis is a freshwater mollusk in which access to genomic resources is critical for many scientific issues, especially in ecotoxicology. We used 454-pyrosequencing to obtain new transcriptomic resources in L. stagnalis and to preliminarily explore gene expression response to a redox-cycling pesticide, diquat. We obtained 151,967 and 128,945 high-quality reads from control and diquat-exposed individuals, respectively. Sequence assembly provided 141,999 contigs, of which 124,387 were singletons. BlastX search revealed significant match for 34.6 % of the contigs (21.2 % protein hits). KEGG annotation showed a predominance of hits with genes involved in energy metabolism and circulatory system, and revealed more than 400 putative genes involved in oxidative stress, cellular/molecular stress and signaling pathways, apoptosis, and metabolism of xenobiotics. Results also suggest that diquat may have a great diversity of molecular effects. Moreover, new genetic markers (putative SNPs) were discovered. We also created a Ensembl-like web-tool for data-mining ( http://genotoul-contigbrowser.toulouse.inra.fr:9095/Lymnaea_stagnalis/index.html ). This resource is expected to be relevant for any genomic approach aimed at understanding the molecular basis of physiological and evolutionary responses to environmental stress in L. stagnalis.
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