De novo transcriptome assembly data of the marine bioluminescent dinoflagellate Pyrocystis lunula.
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ABSTRACT:
SUBMITTER: Menghini D
PROVIDER: S-EPMC8267542 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Species within the dinoflagellate genus Dinophysis can produce okadiac acid and dinophysistoxins leading to diarrhetic shellfish poisoning. Since the first report of D. ovum from the Gulf of Mexico in 2008, reports of other Dinophysis species across US have increased. Members of the D. cf. acuminata complex (D. acuminata, D. acuta, D. ovum, D. sacculus) are difficult to differentiate due to their morphological similarities. Dinophysis feeds on and steals the chloroplasts from the ciliate, Mesodinium rubrum, which in turn has fed on and captured the chloroplasts of its prey, the cryptophyte Teleaulax amphioxeia. The objective of this study was to generate de novo transcriptomes for new isolates of these mixotrophic organisms. The transcriptomes obtained will serve as a reference for future experiments to assess the effect of different abiotic and biotic conditions and will also provide a useful resource for screening potential marker genes to differentiate among the closely related species within the D. cf. acuminata-complex. The complete comprehensive detailed workflow and links to obtain the transcriptome data are provided.
| S-EPMC10238436 | biostudies-literature
Project description:BackgroundKarenia brevis is a harmful algal species that blooms in the Gulf of Mexico and produces brevetoxins that cause neurotoxic shellfish poisoning. Elevated brevetoxin levels in K. brevis cells have been measured during laboratory hypo-osmotic stress treatments. To investigate mechanisms underlying K. brevis osmoacclimation and osmoregulation and establish a valuable resource for gene discovery, we assembled reference transcriptomes for three clones: Wilson-CCFWC268, SP3, and SP1 (a low-toxin producing variant). K. brevis transcriptomes were annotated with gene ontology terms and searched for putative transmembrane proteins that may elucidate cellular responses to hypo-osmotic stress. An analysis of single nucleotide polymorphisms among clones was used to characterize genetic divergence.ResultsK. brevis reference transcriptomes were assembled with 58.5 (Wilson), 78.0 (SP1), and 51.4 million (SP3) paired reads. Transcriptomes contained 86,580 (Wilson), 93,668 (SP1), and 84,309 (SP3) predicted transcripts. Approximately 40% of the transcripts were homologous to proteins in the BLAST nr database with an E value ≤ 1.00E-6. Greater than 80% of the highly conserved CEGMA core eukaryotic genes were identified in each transcriptome, which supports assembly completeness. Seven putative voltage-gated Na+ or Ca2+ channels, two aquaporin-like proteins, and twelve putative VATPase subunits were discovered in all clones using multiple bioinformatics approaches. Furthermore, 45% (Wilson) and 43% (SP1 and SP3) of the K. brevis putative peptides > 100 amino acids long produced significant hits to a sequence in the NCBI nr protein database. Of these, 77% (Wilson and SP1) and 73% (SP3) were successfully assigned gene ontology functional terms. The predicted single nucleotide polymorphism (SNP) frequencies between clones were 0.0028 (Wilson to SP1), 0.0030 (Wilson to SP3), and 0.0028 (SP1 to SP3).ConclusionsThe K. brevis transcriptomes assembled here provide a foundational resource for gene discovery and future RNA-seq experiments. The identification of ion channels, VATPases, and aquaporins in all three transcriptomes indicates that K. brevis regulates cellular ion and water concentrations via transmembrane proteins. Additionally, > 40,000 unannotated loci may include potentially novel K. brevis genes. Ultimately, the SNPs identified among the three ecologically diverse clones with different toxin profiles may help to elucidate variations in K. brevis brevetoxin production.
| S-EPMC4203930 | biostudies-literature
Project description:Transcriptome analysis has important applications in many biological fields. However, assembling a transcriptome without a known reference remains a challenging task requiring algorithmic improvements. We present two methods for substantially improving transcriptome de novo assembly. The first method relies on the observation that the use of a single k-mer length by current de novo assemblers is suboptimal to assemble transcriptomes where the sequence coverage of transcripts is highly heterogeneous. We present the Multiple-k method in which various k-mer lengths are used for de novo transcriptome assembly. We demonstrate its good performance by assembling de novo a published next-generation transcriptome sequence data set of Aedes aegypti, using the existing genome to check the accuracy of our method. The second method relies on the use of a reference proteome to improve the de novo assembly. We developed the Scaffolding using Translation Mapping (STM) method that uses mapping against the closest available reference proteome for scaffolding contigs that map onto the same protein. In a controlled experiment using simulated data, we show that the STM method considerably improves the assembly, with few errors. We applied these two methods to assemble the transcriptome of the non-model catfish Loricaria gr. cataphracta. Using the Multiple-k and STM methods, the assembly increases in contiguity and in gene identification, showing that our methods clearly improve quality and can be widely used. The new methods were used to assemble successfully the transcripts of the core set of genes regulating tooth development in vertebrates, while classic de novo assembly failed.
| S-EPMC2945192 | biostudies-literature
Project description:High-throughput RNA-seq technology has provided an unprecedented opportunity to reveal the very complex structures of transcriptomes. However, it is an important and highly challenging task to assemble vast amounts of short RNA-seq reads into transcriptomes with alternative splicing isoforms. In this study, we present a novel de novo assembler, BinPacker, by modeling the transcriptome assembly problem as tracking a set of trajectories of items with their sizes representing coverage of their corresponding isoforms by solving a series of bin-packing problems. This approach, which subtly integrates coverage information into the procedure, has two exclusive features: 1) only splicing junctions are involved in the assembling procedure; 2) massive pell-mell reads are assembled seemingly by moving a comb along junction edges on a splicing graph. Being tested on both real and simulated RNA-seq datasets, it outperforms almost all the existing de novo assemblers on all the tested datasets, and even outperforms those ab initio assemblers on the real dog dataset. In addition, it runs substantially faster and requires less memory space than most of the assemblers. BinPacker is published under GNU GENERAL PUBLIC LICENSE and the source is available from: http://sourceforge.net/projects/transcriptomeassembly/files/BinPacker_1.0.tar.gz/download. Quick installation version is available from: http://sourceforge.net/projects/transcriptomeassembly/files/BinPacker_binary.tar.gz/download.
| S-EPMC4760927 | biostudies-literature
Project description:We present a new de novo transcriptome assembler, Bridger, which takes advantage of techniques employed in Cufflinks to overcome limitations of the existing de novo assemblers. When tested on dog, human, and mouse RNA-seq data, Bridger assembled more full-length reference transcripts while reporting considerably fewer candidate transcripts, hence greatly reducing false positive transcripts in comparison with the state-of-the-art assemblers. It runs substantially faster and requires much less memory space than most assemblers. More interestingly, Bridger reaches a comparable level of sensitivity and accuracy with Cufflinks. Bridger is available at https://sourceforge.net/projects/rnaseqassembly/files/?source=navbar.
| S-EPMC4342890 | biostudies-literature
Project description:The blue-winged teal (Spatula discors) is a recreationally and ecologically important dabbling duck species in North America. Transcriptomic data of this species can be used in public and animal health studies given its role as a natural reservoir host for avian influenza, which can be a zoonotic disease of high concern. Ileum and bursa of Fabricius tissues were sampled from six captive raised blue-winged teals, four of the six who were experimentally infected with low-pathogenic avian influenza virus H5N9. RNAseq data were generated from extracted total mRNA from each tissue and pooled to create a de novo assembly of the transcriptome using Trinity. A total of 571,105 transcripts were identified at 449,956 unique unigenes that have been functionally annotated. This transcriptome will be useful for future blue-winged teal gene expression research, especially in hypothesis driven differential expression studies to determine the driving forces of avian influenza host-pathogen interactions, spatial distribution, and transmission.
| S-EPMC7115110 | biostudies-literature
Project description:BackgroundRapid advances in next-generation sequencing methods have provided new opportunities for transcriptome sequencing (RNA-Seq). The unprecedented sequencing depth provided by RNA-Seq makes it a powerful and cost-efficient method for transcriptome study, and it has been widely used in model organisms and non-model organisms to identify and quantify RNA. For non-model organisms lacking well-defined genomes, de novo assembly is typically required for downstream RNA-Seq analyses, including SNP discovery and identification of genes differentially expressed by phenotypes. Although RNA-Seq has been successfully used to sequence many non-model organisms, the results of de novo assembly from short reads can still be improved by using recent bioinformatic developments.ResultsIn this study, we used 212.6 million pair-end reads, which accounted for 16.2 Gb, to assemble the hexaploid wheat transcriptome. Two state-of-the-art assemblers, Trinity and Trans-ABySS, which use the single and multiple k-mer methods, respectively, were used, and the whole de novo assembly process was divided into the following four steps: pre-assembly, merging different samples, removal of redundancy and scaffolding. We documented every detail of these steps and how these steps influenced assembly performance to gain insight into transcriptome assembly from short reads. After optimization, the assembled transcripts were comparable to Sanger-derived ESTs in terms of both continuity and accuracy. We also provided considerable new wheat transcript data to the community.ConclusionsIt is feasible to assemble the hexaploid wheat transcriptome from short reads. Special attention should be paid to dealing with multiple samples to balance the spectrum of expression levels and redundancy. To obtain an accurate overview of RNA profiling, removal of redundancy may be crucial in de novo assembly.
| S-EPMC3485621 | biostudies-literature
Project description:The shrimp Palaemon serratus is a coastal decapod crustacean with a high commercial value. It is harvested for human consumption. In this study, we used Illumina sequencing technology (HiSeq 2000) to sequence, assemble and annotate the transcriptome of P. serratus. RNA was isolated from muscle of adults individuals and, from a pool of larvae. A total number of 4 cDNA libraries were constructed, using the TruSeq RNA Sample Preparation Kit v2. The raw data in this study was deposited in NCBI SRA database with study accession number of SRP090769. The obtained data were subjected to de novo transcriptome assembly using Trinity software, and coding regions were predicted by TransDecoder. We used Blastp and Sma3s to annotate the identified proteins. The transcriptome data could provide some insight into the understanding of genes involved in the larval development and metamorphosis. SPECIFICATIONS:[Table: see text].
| S-EPMC5200869 | biostudies-literature
Project description:MotivationDe novo transcriptome assembly is an integral part for many RNA-seq workflows. Common applications include sequencing of non-model organisms, cancer or meta transcriptomes. Most de novo transcriptome assemblers use the de Bruijn graph (DBG) as the underlying data structure. The quality of the assemblies produced by such assemblers is highly influenced by the exact word length k As such no single kmer value leads to optimal results. Instead, DBGs over different kmer values are built and the assemblies are merged to improve sensitivity. However, no studies have investigated thoroughly the problem of automatically learning at which kmer value to stop the assembly. Instead a suboptimal selection of kmer values is often used in practice.ResultsHere we investigate the contribution of a single kmer value in a multi-kmer based assembly approach. We find that a comparative clustering of related assemblies can be used to estimate the importance of an additional kmer assembly. Using a model fit based algorithm we predict the kmer value at which no further assemblies are necessary. Our approach is tested with different de novo assemblers for datasets with different coverage values and read lengths. Further, we suggest a simple post processing step that significantly improves the quality of multi-kmer assemblies.ConclusionWe provide an automatic method for limiting the number of kmer values without a significant loss in assembly quality but with savings in assembly time. This is a step forward to making multi-kmer methods more reliable and easier to use.Availability and implementationA general implementation of our approach can be found under: https://github.com/SchulzLab/KREATIONSupplementary information: Supplementary data are available at Bioinformatics online.Contactmschulz@mmci.uni-saarland.de.
| S-EPMC4892416 | biostudies-literature
Project description:For vertebrate organisms where a reference genome is not available, de novo transcriptome assembly enables a cost effective insight into the identification of tissue specific or differentially expressed genes and variation of the coding part of the genome. However, since there are a number of different tools and parameters that can be used to reconstruct transcripts, it is difficult to determine an optimal method. Here we suggest a pipeline based on (1) assessing the performance of three different assembly tools (2) using both single and multiple k-mer (MK) approaches (3) examining the influence of the number of reads used in the assembly (4) merging assemblies from different tools. We use an example dataset from the vertebrate Anas platyrhynchos domestica (Pekin duck). We find that taking a subset of data enables a robust assembly to be produced by multiple methods without the need for very high memory capacity. The use of reads mapped back to transcripts (RMBT) and CEGMA (Core Eukaryotic Genes Mapping Approach) provides useful metrics to determine the completeness of assembly obtained. For this dataset the use of MK in the assembly generated a more complete assembly as measured by greater number of RMBT and CEGMA score. Merged single k-mer assemblies are generally smaller but consist of longer transcripts, suggesting an assembly consisting of fewer fragmented transcripts. We suggest that the use of a subset of reads during assembly allows the relatively rapid investigation of assembly characteristics and can guide the user to the most appropriate transcriptome for particular downstream use. Transcriptomes generated by the compared assembly methods and the final merged assembly are freely available for download at http://dx.doi.org/10.6084/m9.figshare.1032613.
| S-EPMC4070175 | biostudies-literature