Project description:<p>Integrative taxonomy is a fundamental part of biodiversity and combines traditional morphology with additional methods such as DNA sequencing or biochemistry. Here, we aim to establish untargeted metabolomics for use in chemotaxonomy. We used three thallose liverwort species <em>Riccia glauca</em>, <em>R. sorocarpa</em> and <em>R. warnstorfii</em> (order Marchantiales, Ricciaceae) with <em>Lunularia cruciata</em> (order Marchantiales, Lunulariacea) as an outgroup. Liquid chromatography high-resolution mass-spectrometry (UPLC/ESI-QTOF-MS) with data-dependent acquisition (DDA-MS) were integrated with DNA marker-based sequencing of the trnL-trnF region and high-resolution bioimaging. Our untargeted chemotaxonomy methodology enables us to distinguish taxa based on chemophenetic markers at different levels of complexity: (1) molecules, (2) compound classes, (3) compound superclasses and (4) molecular descriptors. For the investigated <em>Riccia</em> species, we identified 71 chemophenetic markers at the molecular level, a characteristic composition in 21 compound classes, and 21 molecular descriptors largely indicating electron state, presence of chemical motifs and hydrogen bonds. Our untargeted approach revealed many chemophenetic markers at different complexity levels that can provide more mechanistic insight into phylogenetic delimitation of species within a clade than genetic-based methods coupled with traditional morphology-based information. However, analytical and bioinformatics analysis methods still need to be better integrated to link the chemophenetic information at multiple scales.</p><p><br></p><p>To characterize, classify and name species, taxonomy is a fundamental part of biodiversity research. Integrative taxonomy combines traditional morphology-based methods with additional methods from different disciplines like sequencing. Bioinformatics analysis methods and research data are becoming increasingly important but greater integration is needed to link the information at multiple scales. Here, we present a reference dataset that investigates the principles of integrating metabolomics, sequencing, and phenotypic data into integrative taxonomy.</p>
Project description:We have been studying intersex in male rainbow darter (Etheostoma caeruleum) associated with exposure to sewage effluents. To understand changes in the gene transcriptome associated with intersex it was necessary to have a better understanding of normal annual changes in the transcriptome. The goal of this research is to identify patterns of gene expression associated with the different stages of gonad development during the annual cycle. The studies of molecular pathways involve in ovarian or testis development has been poorly studied. While most studies focus on female ovarian changes, there is a gap in understanding testis development. A customized second generation microarray for rainbow darter (8x15k) was used to identify patterns of gene expression -in terms of mRNA abundance- in male rainbow darter gonads during an annual cycle. Rainbow darter males were collected on field work surveys in May (spawning), August (post-spawning), and October (recrudescence) 2011, and January (developing) and March (pre-spawning) 2012, using a back pack electrofisher from a clean area at the Grand River, ON, Canada.
Project description:Sargassum is one of the most diverse brown algal genus with more than 150 known species, mostly benthic and few pelagic species. They contribute significantly to global primary production and serve as important habitat for wide range of marine organisms. Sargassum vulgare is one of the dominant habitat forming species along Mediterranean coast. Despite their huge ecological importance, it is relatively unknown how they will respond under future global climate change scenario. This work used de novo transcriptome sequencing approach to understand the molecular response of S. vulgare to chronic acidification at the shallow underwater volcanic CO2 vents off Ischia Island, Italy. Keywords: brown algae, Sargassum, de novo transcriptome, ocean acidification, CO2 vents.