As part of my thesis, I studied the impact of environmental disturbances, such as chemical pollution and physical modifications of aquatic environments, on the gene expression of fish in the Durance basin. My main objective was to identify biomarkers of exposure and stress to better understand and assess the ecological effects of these disturbances on this river, which is under significant anthropogenic pressure.
To achieve this goal, I developed a specific bioinformatics pipeline to process and analyze the RNA-seq data of the studied species. This bioinformatics work revealed the molecular mechanisms underlying the fish responses to environmental stresses. I was thus able to combine ecotoxicological and bioinformatics approaches to provide precise and innovative answers regarding the impact of these disturbances at a transcriptional level, while integrating the ecological and biological aspects of the study.
To quantify mRNA expression in different fish tissues, we used RNA-seq technology. Three cyprinid species were selected based on their varying sensitivity to pollutants:
Fish were sampled at several stations along the Durance, covering a gradient of exposure to anthropogenic disturbances. Reference stations located in the Suran were also included to compare non-hybridized populations.
RNA Extraction and Preparation:
RNA was extracted from liver tissues and converted into complementary DNA (cDNA) for Illumina sequencing.
RNA-seq Sequencing:
High-throughput sequencing was performed to obtain an overview of gene expression under different environmental conditions.
Bioinformatics Processing:
I developed a specific pipeline, named "Voskhod," for processing RNA-seq data. This pipeline was designed to overcome the challenges related to de novo transcriptome assembly for non-model species. Assembly was carried out with Trinity, followed by sequence alignment against reference databases using BLASTn. This guided approach improved annotation quality by identifying and filtering the most relevant sequences. Subsequently, the data underwent a series of cleaning and filtering processes (FastQC, AdapterRemoval) to ensure sequence quality. Normalization was performed using robust methods such as quantile, TMM, and PoissonSeq, minimizing biases and allowing reliable comparisons between samples.
Differential Analysis:
Differentially expressed genes were identified using rigorous statistical analyses, accounting for biological and technical variations. I used the pipeline to perform multiple comparisons between different environmental conditions and then conducted functional annotation of the genes to interpret the biological processes affected by environmental disturbances. Enrichment analyses were also performed to identify overrepresented biological processes among the differentially expressed genes.
Complementary Studies:
Additional analyses were conducted to assess the combined effects of pollutants (cocktail effect) on gene expression and to compare responses between species. Hybrids were also studied to explore genotype-environment interactions by analyzing how hybridization influences molecular responses to environmental stresses.
Identification of Biomarkers:
Several genes were identified as potential biomarkers of environmental stress, including those involved in responses to aromatic hydrocarbons, heavy metals, and hypoxia.
Response to Hypoxia:
Genes related to the hypoxia response showed significantly elevated expression levels during periods of low flow, particularly in stations affected by dams.
Effect of Organic Pollutants:
Genes from the cytochrome P450 family, associated with hydrocarbon detoxification, exhibited positive regulation in stations downstream of industrial discharges.
Impact of Heavy Metals:
Metallothionein genes were highly expressed in stations impacted by industrial discharges, indicating significant exposure to heavy metals.
Hybrids and Adaptation:
Hybrids between nase and toxostome displayed intermediate expression profiles, suggesting variable adaptation capacities depending on the environments.
The "Voskhod" pipeline was designed to overcome the challenges associated with de novo transcriptome assembly in non-model species. The BLASTn-guided approach improved sequence identification and maximized annotation quality. Additionally, a critical evaluation of RNA-seq data normalization methods was conducted to select the most robust method, minimizing false positives in the identification of differentially expressed genes. I also tested various assembly methodologies, including hybrid assembly, and evaluated their performance on simulated datasets to validate the chosen approach.
The results of this thesis demonstrate that fish gene expression can serve as a sensitive indicator of water quality and environmental disturbances. The development of specialized bioinformatics pipelines and the rigorous analysis of RNA-seq data offer promising prospects for the biomonitoring of aquatic ecosystems. Future research could focus on expanding the study to other species and validating these biomarkers in varied environmental contexts.
The defense of this thesis took place on September 17, 2018, at the University of Aix-Marseille, before a jury composed of recognized experts in ecology and molecular biology. The jury was chaired by Ms. Christine Argillier, Research Director at IRSTEA and specialist in aquatic ecosystems. The thesis reports were prepared by Ms. Céline Brochier-Armanet, Professor at Lyon 1 University and expert in evolutionary biology, and Mr. Joël Grillasca, Professor at the University of Toulon specializing in ecotoxicology.
The jury also included:
The thesis was supervised by Mr. Rémi Chappaz, University Professor at the University of Aix-Marseille, with co-supervision by Mr. André Gilles and Mr. Nicolas Pech. The jury appreciated the quality of the work and validated the thesis during this public defense.
This thesis, supported by EDF, was conducted under the supervision of Rémi Chappaz, with co-supervision by André Gilles and Nicolas Pech. This work involved interdisciplinary collaboration, integrating ecological, biochemical, and bioinformatics approaches for a comprehensive understanding of the environmental impacts on aquatic organisms.