De novo transcriptome assembly of textile hemp from datasets on hypocotyls and adult plants.
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ABSTRACT:
SUBMITTER: Behr M
PROVIDER: S-EPMC6920436 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND:Agaves are succulent monocotyledonous plants native to xeric environments of North America. Because of their adaptations to their environment, including crassulacean acid metabolism (CAM, a water-efficient form of photosynthesis), and existing technologies for ethanol production, agaves have gained attention both as potential lignocellulosic bioenergy feedstocks and models for exploring plant responses to abiotic stress. However, the lack of comprehensive Agave sequence datasets limits the scope of investigations into the molecular-genetic basis of Agave traits. RESULTS:Here, we present comprehensive, high quality de novo transcriptome assemblies of two Agave species, A. tequilana and A. deserti, built from short-read RNA-seq data. Our analyses support completeness and accuracy of the de novo transcriptome assemblies, with each species having a minimum of approximately 35,000 protein-coding genes. Comparison of agave proteomes to those of additional plant species identifies biological functions of gene families displaying sequence divergence in agave species. Additionally, a focus on the transcriptomics of the A. deserti juvenile leaf confirms evolutionary conservation of monocotyledonous leaf physiology and development along the proximal-distal axis. CONCLUSIONS:Our work presents a comprehensive transcriptome resource for two Agave species and provides insight into their biology and physiology. These resources are a foundation for further investigation of agave biology and their improvement for bioenergy development.
| S-EPMC3765226 | biostudies-literature
Project description:Transcriptome data is beneficial to explore molecular mechanisms of extreme adaptations in non- model organisms like mangroves. In this data article, five major datasets and two data sub sets of a salt secreting mangrove, Rhizophora mucronata Lam. were described. A combination of Illumina HiSeq 2500, Trinity, BLAST X, Bowtie 2 and BLAST 2GO was used for RNA Seq, de novo assembly, transcript annotation, gene expression estimation and gene ontology annotation respectively. The RNA Sequence (Read 1 and Read 2) in Sequence Read Archive amounting to 46,366,348 paired end raw reads is the first data set made open for de novo or comparative transcript assembly. Assembled sequences of 93960 gene transcripts constitute the second data set in Transcriptome Shotgun Assembly. The gene/protein annotations to the assembled transcripts give two sub data sets containing 93960 each of GenBank and GenPept entries with comprehensive cDNA and translated protein sequences of genes. Of these, predicted proteins for 87768 coding sequences, mapped to UniProtKB serve as the third data set. The gene expression levels of the annotated transcripts comprise the fourth data set in Gene Expression Omnibus. The fifth data set in Figshare includes 44,028 gene ontology terms extracted for 21,073 confident transcripts. The data sets provide a valuable resource for further analyses including transcriptomic changes in response to environmental stresses.
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Project description:We describe an application of deep sequencing and de novo assembly of short RNA reads to investigate small interfering (si)RNAs mediated immunity in leaf samples from eight tree taxa naturally occurring in Wytham Woods, Oxfordshire, UK. BLAST search for homologues of contigs in the GenBank identified siRNA populations against a number of RNA viruses and a Ty1-copia retrotransposons in these tree species.
2012-06-01 | GSE22079 | GEO
Project description:BACKGROUND:The shift from cross-fertilization to predominant self-fertilization is among the most common evolutionary transitions in the reproductive biology of flowering plants. Increased inbreeding has important consequences for floral morphology, population genetic structure and genome evolution. The transition to selfing is usually characterized by a marked reduction in flower size and the loss of traits involved in pollinator attraction and the avoidance of self-fertilization. Here, we use short-read sequencing to assemble, de novo, the floral transcriptomes of three genotypes of Eichhornia paniculata, including an outcrosser and two genotypes from independently derived selfers, and a single genotype of the sister species E. paradoxa. By sequencing mRNA from tissues sampled at various stages of flower development, our goal was to sequence and assemble the floral transcriptome and identify differential patterns of gene expression. RESULTS:Our 24 Mbp assembly resulted in ~27,000 contigs that averaged ~900 bp in length. All four genotypes had highly correlated gene expression, but the three E. paniculata genotypes were more correlated with one another than each was to E. paradoxa. Our analysis identified 269 genes associated with floral development, 22 of which were differentially expressed in selfing lineages relative to the outcrosser. Many of the differentially expressed genes affect floral traits commonly altered in selfing plants and these represent a set of potential candidate genes for investigating the evolution of the selfing syndrome. CONCLUSIONS:Our study is among the first to demonstrate the use of Illumina short read sequencing for de novo transcriptome assembly in non-model species, and the first to implement this technology for comparing floral transcriptomes in outcrossing and selfing plants.
| S-EPMC3128866 | 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:We describe an application of deep sequencing and de novo assembly of short RNA reads to investigate small interfering (si)RNAs mediated immunity in leaf samples from eight tree taxa naturally occurring in Wytham Woods, Oxfordshire, UK. BLAST search for homologues of contigs in the GenBank identified siRNA populations against a number of RNA viruses and a Ty1-copia retrotransposons in these tree species. Small RNA sequencing and de novo assembly
2012-06-01 | E-GEOD-22079 | biostudies-arrayexpress
Project description:Apricot (Prunus armeniaca) belonging to the Prunus species is a popular kind of stone fruit tree. Apricot is native to Armenia and is currently cultivated in many countries with climates adaptable for apricot growth. In general, fresh fruits as well as dried apricot are produced. However, the information associated with genes and genetic markers for apricot is very limited. In this study, we carried out de novo transcriptome assembly for two selected apricot cultivars referred to as Harcot and Ungarische Beste, which are commercially important apricot cultivars in the world, using next generation sequencing. We obtained a total of 9.31 GB and 8.88 GB raw data from Harcot and Ungarische Beste (NCBI accession numbers: SRX1186946 and SRX1186893), respectively. De novo transcriptome assembly using Trinity identified 147,501 and 152,235 transcripts for Harcot and Ungarische Beste, respectively. Next, we identified 113,565 and 126,444 proteins from Harcot and Ungarische Beste using the TransDecoder program. We performed BLASTP against an NCBI non-redundant (nr) dataset to annotate identified proteins. Taken together, we provide transcriptomes of two different apricot cultivars by RNA-Seq.
| S-EPMC4664767 | biostudies-literature
Project description:Correct quantification of transcript expression is essential to understand the functional elements in different physiological conditions. For the organisms without the reference transcriptome, de novo transcriptome assembly must be carried out prior to quantification. However, a large number of erroneous contigs produced by the assemblers might result in unreliable estimation. In this regard, this study investigates how assembly quality affects the performance of quantification based on de novo transcriptome assembly. We examined the over-extended and incomplete contigs, and demonstrated that assembly completeness has a strong impact on the estimation of contig abundance. Then we investigated the behavior of the quantifiers with respect to sequence ambiguity which might be originally presented in the transcriptome or accidentally produced by assemblers. The results suggested that the quantifiers often over-estimate the expression of family-collapse contigs and under-estimate the expression of duplicated contigs. For organisms without reference transcriptome, it remains challenging to detect the inaccurate estimation on family-collapse contigs. On the contrary, we observed that the situation of under-estimation on duplicated contigs can be warned through analyzing the read proportion of estimated abundance (RPEA) of contigs in the connected component inferenced by the quantifiers. In addition, we suggest that the estimated quantification results on the connected component level have better accuracy over sequence level quantification. The analytic results conducted in this study provides valuable insights for future development of transcriptome assembly and quantification.
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Project description:Cucurbita pepo (squash, pumpkin, gourd), a worldwide-cultivated vegetable of American origin, is extremely variable in fruit characteristics. However, the information associated with genes and genetic markers for pumpkin is very limited. In order to identify new genes and to develop genetic markers, we performed a transcriptome analysis (RNA-Seq) of two contrasting pumpkin cultivars. Leaves and female flowers of cultivars, 'Big Moose' with large round fruits and 'Munchkin' with small round fruits, were harvested for total RNA extraction. We obtained a total of 6 GB (Big Moose; http://www.ncbi.nlm.nih.gov/Traces/sra/?run=SRR3056882) and 5 GB (Munchkin; http://www.ncbi.nlm.nih.gov/Traces/sra/?run=SRR3056883) sequence data (NCBI SRA database SRX1502732 and SRX1502735, respectively), which correspond to 18,055,786 and 14,824,292 150-base reads. After quality assessment, the clean sequences where 17,995,932 and 14,774,486 respectively. The numbers of total transcripts for 'Big Moose' and 'Munchkin' were 84,727 and 68,051, respectively. TransDecoder identified possible coding regions in assembled transcripts. This study provides transcriptome data for two contrasting pumpkin cultivars, which might be useful for genetic marker development and comparative transcriptome analyses.
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