Dataset Information

Ameliorated de novo transcriptome assembly using Illumina paired end sequence data with Trinity Assembler.

ABSTRACT: Advent of Next Generation Sequencing has led to possibilities of de novo transcriptome assembly of organisms without availability of complete genome sequence. Among various sequencing platforms available, Illumina is the most widely used platform based on data quality, quantity and cost. Various de novo transcriptome assemblers are also available today for construction of de novo transcriptome. In this study, we aimed at obtaining an ameliorated de novo transcriptome assembly with sequence reads obtained from Illumina platform and assembled using Trinity Assembler. We found that, primary transcriptome assembly obtained as a result of Trinity can be ameliorated on the basis of transcript length, coverage, and depth and protein homology. Our approach to ameliorate is reproducible and could enhance the sensitivity and specificity of the assembled transcriptome which could be critical for validation of the assembled transcripts and for planning various downstream biological assays.

SUBMITTER: Bankar KG

PROVIDER: S-EPMC4583709 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature

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Ameliorated de novo transcriptome assembly using Illumina paired end sequence data with Trinity Assembler.

Bankar Kiran Gopinath KG Todur Vivek Nagaraj VN Shukla Rohit Nandan RN Vasudevan Madavan M

Genomics data 20150715

Advent of Next Generation Sequencing has led to possibilities of de novo transcriptome assembly of organisms without availability of complete genome sequence. Among various sequencing platforms available, Illumina is the most widely used platform based on data quality, quantity and cost. Various de novo transcriptome assemblers are also available today for construction of de novo transcriptome. In this study, we aimed at obtaining an ameliorated de novo transcriptome assembly with sequence reads ...[more]

PMID: 26484285

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Project description:BackgroundThe pine tip moth, Rhyacionia leptotubula (Lepidoptera: Tortricidae) is one of the most destructive forestry pests in Yunnan Province, China. Despite its importance, less is known regarding all aspects of this pest. Understanding the genetic information of it is essential for exploring the specific traits at the molecular level. Thus, we here sequenced the transcriptome of R. leptotubula with high-throughput Illumina sequencing.Methodology/principal findingsIn a single run, more than 60 million sequencing reads were generated. De novo assembling was performed to generate a collection of 46,910 unigenes with mean length of 642 bp. Based on Blastx search with an E-value cut-off of 10(-5), 22,581 unigenes showed significant similarities to known proteins from National Center for Biotechnology Information (NCBI) non-redundant (Nr) protein database. Of these annotated unigenes, 10,360, 6,937 and 13,894 were assigned to Gene Ontology (GO), Clusters of Orthologous Group (COG), and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, respectively. A total of 5,926 unigenes were annotated with domain similarity derived functional information, of which 55 and 39 unigenes respectively encoding the insecticide resistance related enzymes, cytochrome P450 and carboxylesterase. Using the transcriptome data, 47 unigenes belonging to the typical "stress" genes of heat shock protein (Hsp) family were retrieved. Furthermore, 1,450 simple sequence repeats (SSRs) were detected; 3.09% of the unigenes contained SSRs. Large numbers of SSR primer pairs were designed and out of randomly verified primer pairs 80% were successfully yielded amplicons.Conclusions/significanceA large of putative R. leptotubula transcript sequences has been obtained from the deep sequencing, which extensively increases the comprehensive and integrated genomic resources of this pest. This large-scale transcriptome dataset will be an important information platform for promoting our investigation of the molecular mechanisms from various aspects in this species.

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Dataset Information

Ameliorated de novo transcriptome assembly using Illumina paired end sequence data with Trinity Assembler.

Publications

Ameliorated de novo transcriptome assembly using Illumina paired end sequence data with Trinity Assembler.

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