Project description:Ancient DNA (aDNA) sequencing has enabled reconstruction of speciation, migration, and admixture events for extinct taxa. Outside the permafrost, however, irreversible aDNA post-mortem degradation has so far limited aDNA recovery to the past ~0.5 million years (Ma). Contrarily, multiple analyses suggested the presence of protein residues in Cretaceous fossil remains. Similarly, tandem mass spectrometry (MS) allowed sequencing ~1.5 million year (Ma) old collagen type I (COL1), though with limited phylogenetic use. In the absence of molecular evidence, the speciation of several Early and Middle Pleistocene extinct species remain contentious. In this study, we address the phylogenetic relationships of the Eurasian Pleistocene Rhinocerotidae using a ~1.77 Ma old dental enamel proteome of a Stephanorhinus specimen from the Dmanisi archaeological site in Georgia (South Caucasus). Molecular phylogenetic analyses place the Dmanisi Stephanorhinus as a sister group to the woolly (Coelodonta antiquitatis) and Merck’s rhinoceros (S. kirchbergensis) clade. We show that Coelodonta evolved from an early Stephanorhinus lineage and that the latter includes at least two distinct evolutionary lines. As such, the genus Stephanorhinus is currently paraphyletic and requires systematic revision. We demonstrate that Early Pleistocene dental enamel proteome sequencing overcomes the limits of ancient collagen- and aDNA-based phylogenetic inference. It also provides additional information about the sex and taxonomic assignment of the specimens analysed. Dental enamel, the hardest tissue in vertebrates, is highly abundant in the fossil record. Our findings reveal that palaeoproteomic investigation of this material can push biomolecular investigation further back into the Early Pleistocene.
Project description:Next Generation Sequencing in cancer: a feasibility study in France to assess sample circuit and to perform analyzes within a limited time.
Project description:A functional biodiversity microarray (EcoChip) prototype has been developed to facilitate the analysis of fungal communities in environmental samples with broad functional and phylogenetic coverage and to enable the incorporation of nucleic acid sequence data as they become available from large-scale (next generation) sequencing projects. A dual probe set (DPS) was designed to detect a) functional enzyme transcripts at conserved protein sites and b) phylogenetic barcoding transcripts at ITS regions present in precursor rRNA. Deviating from the concept of GeoChip-type microarrays, the presented EcoChip microarray phylogenetic information was obtained using a dedicated set of barcoding microarray probes, whereas functional gene expression was analyzed by conserved domain-specific probes. By unlinking these two target groups, the shortage of broad sequence information of functional enzyme-coding genes in environmental communities became less important. The novel EcoChip microarray could be successfully applied to identify specific degradation activities in environmental samples at considerably high phylogenetic resolution. Reproducible and unbiased microarray signals could be obtained with chemically labeled total RNA preparations, thus avoiding the use of enzymatic labeling steps. ITS precursor rRNA was detected for the first time in a microarray experiment, which confirms the applicability of the EcoChip concept to selectively quantify the transcriptionally active part of fungal communities at high phylogenetic resolution. In addition, the chosen microarray platform facilitates the conducting of experiments with high sample throughput in almost any molecular biology laboratory. In this study, two independent RNA samples from a pine forest soil were labelled and hybridised to a custom-made EcoChip microarray consisting of about 9000 probes targeting expressed fungals genes and about 5000 probes targeting the precursor-rRNA of different fungal lineages
Project description:ZIKV strains belong to three phylogenetic lineages: East African, West African, and Asian/American. RNA virus genomes exist as populations of genetically-related sequences whose heterogeneity may impact viral fitness, evolution, and virulence. The genetic diversity of representative ZIKVs (N=7) from each lineage was examined using next generation sequencing (NGS) paired with downstream Shannon entropy calculation and single nucleotide variant (SNV) analysis. This comprehensive analysis of ZIKV genetic diversity provides insight into the genetic diversity of ZKIV and repository of SNV positions across lineages.