Project description:In this study transcriptomic data of three life history stages of Orciraptor agilis was generated: 1) Gliding cells in absence of food ('gliding'), 2) Cells attached to the cell wall of its algal prey during perforation ('fattacking'), 3) Cells after acquisition of the algal plastid material ('digesting'). Furthermore, RNA-seq of the algal prey Mougeotia sp. was also performed. A de novo transcriptome assembly of the algal reads was performed in order to identify and substract algal reads of the Orciraptor samples by mapping the Orciraptor reads to the algal transcriptome. After this filtering step the remaining Orciraptor reads from all libraries were pooled for a de novo transcriptome assembly of Orciraptor agilis. This transcriptome was the basis for a comparative transcriptomic study in which transcript expression was compared between the three life history stages.
Project description:De novo peptide sequencing is a fundamental research area in mass spectrometry (MS) based proteomics. However, those methods have often been evaluated using a couple of simple metrics that do not fully reflect their overall performance. Moreover, there has not been an established method to estimate the false discovery rate (FDR) and the significance of de novo peptide-spectrum matches (PSMs). Here we propose NovoBoard, a comprehensive framework to evaluate the performance of de novo peptide sequencing methods. The framework consists of diverse benchmark datasets (including tryptic, nontryptic, immunopeptidomics, and different species), and a standard set of accuracy metrics to evaluate the fragment ions, amino acids, and peptides of the de novo results. More importantly, a new approach is designed to evaluate de novo peptide sequencing methods on target-decoy spectra and to estimate their FDRs. Our results thoroughly reveal the strengths and weaknesses of different de novo peptide sequencing methods, and how their performances depend on specific applications and the types of data. Our FDR estimation also shows that some tools may perform better than the others in distinguishing between de novo PSMs and random matches, and can be used to assess the significance of de novo PSMs.
Project description:Dependent on concise, pre-defined protein sequence databases, traditional search algorithms perform poorly when analyzing mass spectra derived from wholly uncharacterized protein products. Conversely, de novo peptide sequencing algorithms can interpret mass spectra without relying on reference databases. However, such algorithms have been difficult to apply to complex protein mixtures, in part due to a lack of methods for automatically validating de novo sequencing results. Here, we present novel metrics for benchmarking de novo sequencing algorithm performance on large scale proteomics datasets, and present a method for accurately calibrating false discovery rates on de novo results. We also present a novel algorithm (LADS) which leverages experimentally disambiguated fragmentation spectra to boost sequencing accuracy and sensitivity. LADS improves sequencing accuracy on longer peptides relative to other algorithms and improves discriminability of correct and incorrect sequences. Using these advancements, we demonstrate accurate de novo identification of peptide sequences not identifiable using database search-based approaches.
Project description:Precision de novo peptide sequencing using mirror proteases of Ac-LysargiNase and trypsin for large-scale proteomicsPrecision de novo peptide sequencing using mirror proteases of Ac-LysargiNase and trypsin for large-scale proteomics
Project description:We first report the use of next-generation massively parallel sequencing technologies and de novo transcriptome assembly to gain insight into the wide range of transcriptome of Hevea brasiliensis. The output of sequenced data showed that more than 12 million sequence reads with average length of 90nt were generated. Totally 48,768 unigenes (mean size = 488 bp) were assembled through transcriptome de novo assembly, which represent more than 3-fold of all the sequences of Hevea brasiliensis deposited in the GenBank. Assembled sequences were annotated with gene descriptions, gene ontology and clusters of orthologous group terms. Total 37,373 unigenes were successfully annotated and more than 10% of unigenes were aligned to known proteins of Euphorbiaceae. The unigenes contain nearly complete collection of known rubber-synthesis-related genes. Our data provides the most comprehensive sequence resource available for study rubber tree and demonstrates the availability of Illumina sequencing and de novo transcriptome assembly in a species lacking genome information. The transcriptome of latex and leaf in Hevea brasiliensis
Project description:Due to the uperior suppression ability to manipulate plant defense, the invasive spider mite T. evansi has become an ideal model to investigate the plant-herbivores interaction. In this study, we performed de novo transcriptome assembly of T. evansi, and characterize its secreted saliva by transcriptomic sequencing technology and Liquid Chromatography–Mass Spectrometry/Mass Spectrometry (LC–MS/MS) analysis, respectively.
Project description:De novo centromeres originate occasionally from non-centromeric regions of chromosomes, providing an excellent model system to study centromeric chromatin. The maize mini-chromosome Derivative 3-3 contains a de novo centromere, which was derived from a euchromatic site on the short arm of chromosome 9 that lacks traditional centromeric repeat sequences. Our previous study found that the CENH3 binding domain of this de novo centromere is only 288 kb with a high-density gene distribution with low-density of transposons. Here we applied next generation sequencing technology to analyze gene transcription, DNA methylation for this region. Our RNA-seq data revealed that active chromatin is not a barrier for de novo centromere formation. Bisulfite-ChIP-seq results indicate a slightly increased DNA methylation level after de novo centromere formation, reaching the level of a native centromere. These results provide insight into the mechanism of de novo centromere formation and subsequent consequences. RNA-seq was carried out using material from seedling and young leaves between control and Derivative 3-3. Bisulfite-ChIP-seq was carried out with anti-CENH3 antibodies using material from young leaves in Derivative 3-3.
Project description:We combined multi-omics approaches including de novo transcriptome assembly, ribosome profiling and MS-based peptidomics to study the global role of mRNA translation and small ORFs (sORFs) in rice herbicide resistant mutant.