Deep insights into Dictyocaulus viviparus transcriptomes provides unique prospects for new drug targets and disease intervention

Cantacessi, Cinzia; Gasser, Robin B.; Strübe, Christina; Schnieder, Thomas; Jex, Aaron R.; Hall, Ross S.; Campbell, Bronwyn E.; Young, Neil D.; Ranganathan, Shoba; Sternberg, Paul W.; Mitreva, Makedonka

doi:10.1016/j.biotechadv.2010.11.005

Cited by 27 publications

(30 citation statements)

References 103 publications

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“…Additional life cycle stages were sequenced and added to available datasets from A. caninum [30], D. viviparus [23], N. americanus [26], and O. dentatum [24] prior to assembly (see Additional file 1: Table S1). Together, these nine species represent a diverse array of parasitic nematodes, in terms of biology as well as phylogeny.…”

Section: Resultsmentioning

confidence: 99%

Identification and characterization of alternative splicing in parasitic nematode transcriptomes

Abubucker¹,

McNulty²,

Rosa³

et al. 2014

Parasites Vectors

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BackgroundAlternative splicing (AS) of mRNA is a vital mechanism for enhancing genomic complexity in eukaryotes. Spliced isoforms of the same gene can have diverse molecular and biological functions and are often differentially expressed across various tissues, times, and conditions. Thus, AS has important implications in the study of parasitic nematodes with complex life cycles. Transcriptomic datasets are available from many species, but data must be revisited with splice-aware assembly protocols to facilitate the study of AS in helminthes.MethodsWe sequenced cDNA from the model worm Caenorhabditis elegans using 454/Roche technology for use as an experimental dataset. Reads were assembled with Newbler software, invoking the cDNA option. Several combinations of parameters were tested and assembled transcripts were verified by comparison with previously reported C. elegans genes and transcript isoforms and with Illumina RNAseq data.ResultsThoughtful adjustment of program parameters increased the percentage of assembled transcripts that matched known C. elegans sequences, decreased mis-assembly rates (i.e., cis- and trans-chimeras), and improved the coverage of the geneset. The optimized protocol was used to update de novo transcriptome assemblies from nine parasitic nematode species, including important pathogens of humans and domestic animals. Our assemblies indicated AS rates in the range of 20-30%, typically with 2-3 transcripts per AS locus, depending on the species. Transcript isoforms from the nine species were translated and searched for similarity to known proteins and functional domains. Some 21 InterPro domains, including several involved in nucleotide and chromatin binding, were statistically correlated with AS genetic loci. In most cases, the Roche/454 data explored in this study are the only sequences available from the species in question; however, the recently published genome of the human hookworm Necator americanus provided an additional opportunity to validate our results.ConclusionsOur optimized assembly parameters facilitated the first survey of AS among parasitic nematodes. The nine transcriptome assemblies, their protein translations, and basic annotations are available from Nematode.net as a resource for the research community. These should be useful for studies of specific genes and gene families of interest as well as for curating draft genome assemblies as they become available.

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Section: Resultsmentioning

confidence: 99%

Identification and characterization of alternative splicing in parasitic nematode transcriptomes

Abubucker¹,

McNulty²,

Rosa³

et al. 2014

Parasites Vectors

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“…Here, NGS data has been assembled with CAP3 alone [14,16] or with MIRA followed by CAP3 [12,18], based on combinations of assemblers performing better in a recent study [10]. However, none of these studies have extensively covered ES protein prediction and further analysis, for identifying therapeutic targets.…”

Section: Introductionmentioning

confidence: 99%

In silico secretome analysis approach for next generation sequencing transcriptomic data

Garg

Ranganathan

2011

BMC Genomics

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BackgroundExcretory/secretory proteins (ESPs) play a major role in parasitic infection as they are present at the host-parasite interface and regulate host immune system. In case of parasitic helminths, transcriptomics has been used extensively to understand the molecular basis of parasitism and for developing novel therapeutic strategies against parasitic infections. However, none of transcriptomic studies have extensively covered ES protein prediction for identifying novel therapeutic targets, especially as parasites adopt non-classical secretion pathways.ResultsWe developed a semi-automated computational approach for prediction and annotation of ES proteins using transcriptomic data from next generation sequencing platforms. For the prediction of non-classically secreted proteins, we have used an improved computational strategy, together with homology matching to a dataset of experimentally determined parasitic helminth ES proteins. We applied this protocol to analyse 454 short reads of parasitic nematode, Strongyloides ratti. From 296231 reads, we derived 28901 contigs, which were translated into 20877 proteins. Based on our improved ES protein prediction pipeline, we identified 2572 ES proteins, of which 407 (1.9%) proteins have classical N-terminal signal peptides, 923 (4.4%) were computationally identified as non-classically secreted while 1516 (7.26%) were identified by homology to experimentally identified parasitic helminth ES proteins. Out of 2572 ES proteins, 2310 (89.8%) ES proteins had homologues in the free-living nematode Caenorhabditis elegans and 2220 (86.3%) in parasitic nematodes. We could functionally annotate 1591 (61.8%) ES proteins with protein families and domains and establish pathway associations for 691 (26.8%) proteins. In addition, we have identified 19 representative ES proteins, which have no homologues in the host organism but homologous to lethal RNAi phenotypes in C. elegans, as potential therapeutic targets.ConclusionWe report a comprehensive approach using freely available computational tools for the secretome analysis of NGS data. This approach has been applied to S. ratti 454 transcriptomic data for in silico excretory/secretory proteins prediction and analysis, providing a foundation for developing new therapeutic solutions for parasitic infections.

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“…In particular, 454 technology was used recently for the rapid de novo sequencing of the transcriptomes of numerous pathogens of humans and animals [33-41], yielding substantial datasets and providing a significant step forward. The development of practical and efficient bioinformatic tools has now become crucial for comprehensive analyses of such datasets.…”

Section: Next-generation Sequencing Technologiesmentioning

confidence: 99%

Major prospects for exploring canine vector borne diseases and novel intervention methods using 'omic technologies

et al. 2011

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Canine vector-borne diseases (CVBDs) are of major socioeconomic importance worldwide. Although many studies have provided insights into CVBDs, there has been limited exploration of fundamental molecular aspects of most pathogens, their vectors, pathogen-host relationships and disease and drug resistance using advanced, 'omic technologies. The aim of the present article is to take a prospective view of the impact that next-generation, 'omics technologies could have, with an emphasis on describing the principles of transcriptomic/genomic sequencing as well as bioinformatic technologies and their implications in both fundamental and applied areas of CVBD research. Tackling key biological questions employing these technologies will provide a 'systems biology' context and could lead to radically new intervention and management strategies against CVBDs.

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Deep insights into Dictyocaulus viviparus transcriptomes provides unique prospects for new drug targets and disease intervention

Cited by 27 publications

References 103 publications

Identification and characterization of alternative splicing in parasitic nematode transcriptomes

Identification and characterization of alternative splicing in parasitic nematode transcriptomes

In silico secretome analysis approach for next generation sequencing transcriptomic data

Major prospects for exploring canine vector borne diseases and novel intervention methods using 'omic technologies

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