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A gene expression microarray for Nicotiana benthamiana based on de novo transcriptome sequence assembly.

ABSTRACT: BACKGROUND:Nicotiana benthamiana has been widely used in laboratories around the world for studying plant-pathogen interactions and posttranscriptional gene expression silencing. Yet the exploration of its transcriptome has lagged behind due to the lack of both adequate sequence information and genome-wide analysis tools, such as DNA microarrays. Despite the increasing use of high-throughput sequencing technologies, the DNA microarrays still remain a popular gene expression tool, because they are cheaper and less demanding regarding bioinformatics skills and computational effort. RESULTS:We designed a gene expression microarray with 103,747 60-mer probes, based on two recently published versions of N. benthamiana transcriptome (v.3 and v.5). Both versions were reconstructed from RNA-Seq data of non-strand-specific pooled-tissue libraries, so we defined the sense strand of the contigs prior to designing the probe. To accomplish this, we combined a homology search against Arabidopsis thaliana proteins and hybridization to a test 244k microarray containing pairs of probes, which represented individual contigs. We identified the sense strand in 106,684 transcriptome contigs and used this information to design an Nb-105k microarray on an Agilent eArray platform. Following hybridization of RNA samples from N. benthamiana roots and leaves we demonstrated that the new microarray had high specificity and sensitivity for detection of differentially expressed transcripts. We also showed that the data generated with the Nb-105k microarray may be used to identify incorrectly assembled contigs in the v.5 transcriptome, by detecting inconsistency in the gene expression profiles, which is indicated using multiple microarray probes that match the same v.5 primary transcripts. CONCLUSIONS:We provided a complete design of an oligonucleotide microarray that may be applied to the research of N. benthamiana transcriptome. This, in turn, will allow the N. benthamiana research community to take full advantage of microarray capabilities for studying gene expression in this plant. Additionally, by defining the sense orientation of over 106,000 contigs, we substantially improved the functional information on the N. benthamiana transcriptome. The simple hybridization-based approach for detecting the sense orientation of computationally assembled sequences can be used for updating the transcriptomes of other non-model organisms, including cases where no significant homology to known proteins exists.

SUBMITTER: Goralski M

PROVIDER: S-EPMC4875705 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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A gene expression microarray for Nicotiana benthamiana based on de novo transcriptome sequence assembly.

Goralski Michal M Sobieszczanska Paula P Obrepalska-Steplowska Aleksandra A Swiercz Aleksandra A Zmienko Agnieszka A Figlerowicz Marek M

Plant methods 20160520

<h4>Background</h4>Nicotiana benthamiana has been widely used in laboratories around the world for studying plant-pathogen interactions and posttranscriptional gene expression silencing. Yet the exploration of its transcriptome has lagged behind due to the lack of both adequate sequence information and genome-wide analysis tools, such as DNA microarrays. Despite the increasing use of high-throughput sequencing technologies, the DNA microarrays still remain a popular gene expression tool, because ...[more]

PMID: 27213006

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Project description:BackgroundNicotiana benthamiana has been widely used for transient gene expression assays and as a model plant in the study of plant-microbe interactions, lipid engineering and RNA silencing pathways. Assembling the sequence of its transcriptome provides information that, in conjunction with the genome sequence, will facilitate gaining insight into the plant's capacity for high-level transient transgene expression, generation of mobile gene silencing signals, and hyper-susceptibility to viral infection.Methodology/resultsRNA-seq libraries from 9 different tissues were deep sequenced and assembled, de novo, into a representation of the transcriptome. The assembly, of 16GB of sequence, yielded 237,340 contigs, clustering into 119,014 transcripts (unigenes). Between 80 and 85% of reads from all tissues could be mapped back to the full transcriptome. Approximately 63% of the unigenes exhibited a match to the Solgenomics tomato predicted proteins database. Approximately 94% of the Solgenomics N. benthamiana unigene set (16,024 sequences) matched our unigene set (119,014 sequences). Using homology searches we identified 31 homologues that are involved in RNAi-associated pathways in Arabidopsis thaliana, and show that they possess the domains characteristic of these proteins. Of these genes, the RNA dependent RNA polymerase gene, Rdr1, is transcribed but has a 72 nt insertion in exon1 that would cause premature termination of translation. Dicer-like 3 (DCL3) appears to lack both the DEAD helicase motif and second dsRNA binding motif, and DCL2 and AGO4b have unexpectedly high levels of transcription.ConclusionsThe assembled and annotated representation of the transcriptome and list of RNAi-associated sequences are accessible at www.benthgenome.com alongside a draft genome assembly. These genomic resources will be very useful for further study of the developmental, metabolic and defense pathways of N. benthamiana and in understanding the mechanisms behind the features which have made it such a well-used model plant.

Project description:BackgroundNicotiana benthamiana is an allo-tetraploid plant, which can be challenging for de novo transcriptome assemblies due to homeologous and duplicated gene copies. Transcripts generated from such genes can be distinct yet highly similar in sequence, with markedly differing expression levels. This can lead to unassembled, partially assembled or mis-assembled contigs. Due to the different properties of de novo assemblers, no one assembler with any one given parameter space can re-assemble all possible transcripts from a transcriptome.ResultsIn an effort to maximise the diversity and completeness of de novo assembled transcripts, we utilised four de novo transcriptome assemblers, TransAbyss, Trinity, SOAPdenovo-Trans, and Oases, using a range of k-mer sizes and different input RNA-seq read counts. We complemented the parameter space biologically by using RNA from 10 plant tissues. We then combined the output of all assemblies into a large super-set of sequences. Using a method from the EvidentialGene pipeline, the combined assembly was reduced from 9.9 million de novo assembled transcripts to about 235,000 of which about 50,000 were classified as primary. Metrics such as average bit-scores, feature response curves and the ability to distinguish paralogous or homeologous transcripts, indicated that the EvidentialGene processed assembly was of high quality. Of 35 RNA silencing gene transcripts, 34 were identified as assembled to full length, whereas in a previous assembly using only one assembler, 9 of these were partially assembled.ConclusionsTo achieve a high quality transcriptome, it is advantageous to implement and combine the output from as many different de novo assemblers as possible. We have in essence taking the 'best' output from each assembler while minimising sequence redundancy. We have also shown that simultaneous assessment of a variety of metrics, not just focused on contig length, is necessary to gauge the quality of assemblies.

Project description:BackgroundThe ability to generate recombinant drug target proteins is important for drug discovery research as it facilitates the investigation of drug-target-interactions in vitro. To accomplish this, the target's exact protein sequence is required. Public databases, such as Ensembl, UniProt and RefSeq, are extensive protein and nucleotide sequence repositories. However, many sequences for non-human organisms are predicted by computational pipelines and may thus be incomplete or incorrect. This could lead to misinterpreted experimental outcomes due to gaps or errors in orthologous drug target sequences. Transcriptome analysis by RNA-Seq has been established as a standard method for gene expression analysis. Apart from this common application, paired-end RNA-Seq data can also be used to obtain full coverage cDNA sequences via de novo transcriptome assembly.MethodsTo assess whether de novo transcriptome assemblies can be used to determine a protein's sequence by searching the assembly for a known orthologous sequence, we generated 3 × 6 = 18 tissue specific assemblies (three organs: brain, kidney and liver; six species: human, mouse, rat, dog, pig and cynomolgus monkey). These assemblies and the manually curated human protein sequences from UniProtKB/Swiss-Prot were used in a reciprocal BLAST search to identify best matching hits. We automated and generalised our approach and present the a&o-tool, a workflow which exploits de novo assemblies of paired-end RNA-Seq data and orthology information for target sequence validation and refinement across related species. Furthermore, the a&o-tool extracts best hits' sequences from a reciprocal BLAST search, translates them into protein sequences, computes a multiple sequence alignment and quantifies the refinement.ResultsFor the three human assemblies we observed a hit rate greater than 60% with 100% sequence coverage and identity. For assemblies from the other species we observed similar hit rates and coverage with highest identities for cynomolgus monkey.ConclusionsIn summary, we show how to refine protein sequences using RNA-Seq data and sequence information from closely related species. With the a&o-tool we provide a fully automated pipeline to perform refinement including cDNA translation and multiple sequence alignment for visual inspection. The major prerequisite for applying the a&o-tool is high quality sequencing data.

Dataset Information

A gene expression microarray for Nicotiana benthamiana based on de novo transcriptome sequence assembly.

Publications

A gene expression microarray for Nicotiana benthamiana based on de novo transcriptome sequence assembly.

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