CmLunCruc20
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB59341 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Lunularia cruciata (crescent-cup liverwort), genomic and transcriptomic data
| PRJEB57425 | ENA
Project description:Purpose: The recent publication of the fungal mutualist R. irregularis genome facilitated transcriptomic studies. We here wanted to understand the large host range of this fungus, throught its gene regulation in divergent plants Methods: mRNA from Medicago truncatula (legume), Brachypodium distachyon (grass) and Lunularia cruciata (liverwort) in association with R. irregularis were sequenced. Reads were mapped on the genome assembly with the software CLC workbench. Fungal gene expression in the different plants was compared to extra radical hyphae as a control. Results: 529, 486 and 523 R. irregularis gene were highly overexpressed (fold change >5 ; FDR <0,05 and experimental value > l10l) in M. truncatula, B. distachyon and L. cruciata, respectively. Among those genes, 262 were induced in all hosts. qPCR validation on 32 genes supported these results in an extended set of hosts (Zea mays spp parviglumis, Pisum sativum, Marchantia paleacea).
2017-09-29 | GSE67926 | GEO
Project description:Lunularia cruciata isolate:LC1 Genome sequencing and assembly
| PRJNA701193 | ENA
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>
2026-01-30 | MTBLS4668 | MetaboLights
Project description:Cruciata laevipes (crosswort) genome assembly, daCruLaev1
| PRJEB70271 | ENA
Project description:Cruciata laevipes (crosswort) genome assembly, daCruLaev1, alternate haplotype
| PRJEB70272 | ENA
Project description:Teleiodes luculella (crescent groundling) genome assembly, ilTelLucu1
| PRJEB59316 | ENA
Project description:Trisateles emortualis (olive crescent) genome assembly, ilTriEmor1
| PRJEB56843 | ENA