18S rRNA sequencing Dark Earth
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB10851 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR1016680.fastq.gz | Fastqsanger.gz | |||
| ERR1016690.fastq.gz | Fastqsanger.gz | |||
| ERR1016681.fastq.gz | Fastqsanger.gz | |||
| ERR1016691.fastq.gz | Fastqsanger.gz | |||
| ERR1016682.fastq.gz | Fastqsanger.gz |
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Project description:Nematodes are the most abundant and diverse animals on the planet but lack representation in biodiversity research. This presents a problem for studying nematode diversity, particularly when molecular tools (i.e., barcoding and metabarcoding) rely on well-populated and curated reference databases, which are absent for nematodes. To improve molecular identification and the assessment of nematode diversity, we created and curated an 18S rRNA database specific to nematodes (18S-NemaBase) using sequences sourced from the most recent publicly available 18S rRNA SILVA v138 database. As part of the curation process, taxonomic strings were standardized to contain a fixed number of taxonomic ranks relevant to nematology and updated for the most recent accepted nematode classifications. In addition, apparent erroneous sequences were removed. To test the efficacy and accuracy of 18S-NemaBase, we compared it to an older but also curated SILVA v111 and the newest SILVA v138 by assigning taxonomies and analyzing the diversity of a nematode dataset from the Western Nebraska Sandhills. We showed that 18S-NemaBase provided more accurate taxonomic assignments and diversity assessments than either version of SILVA, with a much easier workflow and no need for manual corrections. Additionally, observed diversity further improved when 18S-NemaBase was supplemented with reference sequences from nematodes present in the study site. Although the 18S-NemaBase is a step in the right direction, a concerted effort to increase the number of high-quality, accessible, full-length nematode reference sequences is more important now than ever.
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Project description:Quantification of fungal dark matter using qPCR
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Project description:Purpose: The goals of this study is to compare the transcriptome (RNA-seq) modulations in Saccharomyces cerevisiae exposed to two rare earth elements. Lanthanum and ytterbium were used as representative of light and heavy rare earth elements, respectively. Methods: mRNA were sequenced from Saccharomyces cerevisiae exposed to two different rare earth elements. Lanthanum and ytterbium were used as representative of light and heavy rare earth elements respectively. The transcriptome of S. cerevisiae was analysed after being exposed for one hour to the EC10 (Effective concentration 10 %) and the EC50 (Effective concentration 50 %) of lanthanum (50 and 160 µM) and ytterbium (6 and 8 µM). The sequence reads were trimmed using Trimmomativ v0.36.1 and FastQC v0.67 used for quality check. Reads passing the quality check were mapped on the reference genome (S288C R64-2-1 of 2015-01-31 from https://www.yeastgenome.org/) of S. cerevisiae using TopHat v2.1.1. Reads that were mapped on the reference genome were quantified using HTSeq-count v0.6.1p1. Finally, differential gene expression analysis between treatments was carried out using DESeq2 v1.14.1. Differentially expressed genes between conditions were obtained and expressed as log2-fold change with adjusted p-values calculated via a Benjamini-Hochberg test. A cut-off adjusted p-value of < 0.01 was applied. Results: The transcription of genes related to several crucial pathways was modulated in response to both REEs, such as oxidative-reduction processes, DNA replication, and carbohydrate metabolism. REE-specific responses involving the cell wall and the pheromone signalling pathways were highlighted, while these were not reported for other metals. REE exposure also modified the expression and abundance of several ion transport systems, for which strong discrepancies were observed between the two contrasted REEs. Conclusions: Our results demonstrate the discrepancies in yeast response to different rare earth elements (light vs heavy rare earth elements). This results are valuable to prioritize key genes and proteins involved in REE detoxification mechanisms that would deserve further characterisation to better understand the REE toxicity on the environment and human health.
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