RESUMEN
Long non-coding RNAs (lncRNAs) are RNA molecules longer than 200 nucleotides that do not encode proteins. Experimental studies have shown the diversity and importance of lncRNA functions in plants. To expand knowledge about lncRNAs in other species, computational pipelines that allow for standardised data-processing steps in a mode that does not require user control up until the final result were actively developed recently. These advancements enable wider functionality for lncRNA data identification and analysis. In the present work, we propose the ICAnnoLncRNA pipeline for the automatic identification, classification and annotation of plant lncRNAs in assembled transcriptomic sequences. It uses the LncFinder software for the identification of lncRNAs and allows the adjustment of recognition parameters using genomic data for which lncRNA annotation is available. The pipeline allows the prediction of lncRNA candidates, alignment of lncRNA sequences to the reference genome, filtering of erroneous/noise transcripts and probable transposable elements, lncRNA classification by genome location, comparison with sequences from external databases and analysis of lncRNA structural features and expression. We used transcriptomic sequences from 15 maize libraries assembled by Trinity and Hisat2/StringTie to demonstrate the application of the ICAnnoLncRNA pipeline.
Asunto(s)
Perfilación de la Expresión Génica , ARN Largo no Codificante/genética , Transcriptoma , Zea mays/genética , Programas InformáticosRESUMEN
We report a new analytical method that allows the determination of the magnitude of the equilibrium constant of complexation, Kh, of small molecules to C60 fullerene in aqueous solution. The developed method is based on the up-scaled model of C60 fullerene-ligand complexation and contains the full set of equations needed to fit titration datasets arising from different experimental methods (UV-Vis spectroscopy, 1H NMR spectroscopy, diffusion ordered NMR spectroscopy, DLS). The up-scaled model takes into consideration the specificity of C60 fullerene aggregation in aqueous solution and allows the highly dispersed nature of C60 fullerene cluster distribution to be accounted for. It also takes into consideration the complexity of fullerene-ligand dynamic equilibrium in solution, formed by various types of self- and hetero-complexes. These features make the suggested method superior to standard Langmuir-type analysis, the approach used to date for obtaining quantitative information on ligand binding with different nanoparticles.