Project description:Molecular analysis of population and De Novo transcriptome sequencing of Thai medaka, Oryzias minutillus (Teleostei: Adrianichthyidae)
| PRJNA553068 | ENA
Project description:De Novo transcriptome analysis of Oryzias songkhramensis (Teleostei: Beloniformes)
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 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:The swamp eel or rice field eel (Monopterus albus) taxonomically belongs to the family Synbranchidae of the order Synbranchiformes (Neoteleostei, Teleostei, Vertebrata). It is not only an economically important freshwater fish in aquacultural production, but also an increasingly known model species for biological studies. Understanding molecular mechanisms underlying sex change is a major area of interest. The swamp eel thus offers a powerful system for studying sexual development and adaptive evolution in vertebrates.The whole genome sequencing provides valuable resources for sex control in fish production, species protection through manipulating sex reversal genes, and potentially enabling effective population control and promoting reproduction health in human. High throughput sequencing was employed for three samples,three kind s of sex gonad from swamp eel, testis,ovotestis and ovary, no replicates.
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 report here the use of next-generation massively parallel sequencing technologies and de novo transcriptome assembly to gain insight into the wide range of transcriptome of two Hevea brasiliensis clones (RY8-79 and PR107). The output of sequenced data showed that more than 26 million sequence reads with average length of 90nt were generated in both clones. Totally 51829 unigenes (mean size = 640 bp) were assembled through transcriptome de novo assembly, which represent more than 16-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. Base on limit rule with FDR≤0.001 and |log2 Ratio|≥1, 6726 different expression unigenes (3018 up and 3708 down) were detected as PR107 versus RY8-79. Functional analysis showed mass of categories were reprogrammed between two clones, which relate latex generation and expelling difference between them. As a comparative transcriptome analysis, the results obtained here will greatly expand our understanding of physiological differences among varieties in molecular level and will contribute t The transcriptome of latex in Hevea brasiliensis