Project description:D24, MM418-C1 melanoma and HaCaT cells were treated with 100 µg/mL of the different M. cochinchinensis seed extracts for 48 h prior to RNA collection. Results were presented as the fold change compared to untreated controls ± SEM (n=3), different letters indicated statistical significance at p≤0.05 between different treatments (Analysis by One-way ANOVA with Turkey’s LSD test).
Project description:Profiling of small RNAs identified a total of 359 and 357 conserved; and 490 and 155 novel miRNAs in C. chinense and C. frutescens, respectively. Based on the sequence similarity observed on alignment with already reported plant miRNAs, conserved and novel miRNAs were identified in both the species. The target prediction analysis reveals vital role of miRNAs in regulating genes involved in transcriptions, protein modification, signal transduction and metabolism. Several miRNAs were expressed in a tissue-specific/preferential manner indicating their involvement in tissue/organ development.
Project description:Protein reference databases are a critical part of producing efficient proteomic analyses. However, the method for constructing clean, efficient, and comprehensive protein reference databases is lacking. Existing methods either do not have contamination control procedures, or these methods rely on a three-frame and/or six-frame translation that sharply increases the search space and harms MS results. Herein we propose a framework for constructing a customized comprehensive proteomic reference database (CCPRD) from draft genomes and deep sequencing transcriptomes. Its effectiveness is demonstrated by incorporating the proteomes of nematocysts from endoparasitic cnidarian: myxozoans. By applying customized contamination removal procedures, contaminations in omic data were successfully identified and removed. This is an effective method that does not result in over-decontamination. This can be shown by comparing the CCPRD MS results with an artificially-contaminated database and another database with removed contaminations in genomes and transcriptomes added back. CCPRD outperformed traditional frame-based methods by identifying 35.2%-50.7% more peptides and 35.8%-43.8% more proteins, with a maximum 84.6% in size reduction. A BUSCO analysis showed that the CCPRD maintained a relatively high level of completeness compared to traditional methods. These results confirm the superiority of the CCPRD over existing methods in peptide and protein identification numbers, database size, and completeness. By providing a general framework for generating the reference database, the CCPRD, which does not need a high-quality genome, can potentially be applied to any organisms and significantly contribute to proteomic research.
2020-07-09 | PXD018851 | Pride
Project description:Evaluating genetic diversity in two tropical leguminous trees, Dalbergia cochinchinensis and D. nigrescens, in lowland forests in Cambodia and Thailand using MIG-seq
