ReviewFrontiers in genetics2015
Assembly, Assessment, and Availability of De novo Generated Eukaryotic Transcriptomes.
Review in Frontiers in genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
29 citing papers in PubMed, 1 synthesis or guideline pooled it.
- FACE facts hold for multiple generations; Evidence from natural COGlobal change biology · 2019Pooled it
- First insight into metal binding proteins from the de novo transcriptome of acanthocephalan parasite Dentitruncus truttae.Scientific reports · 2025Article
- RNA sequencing least shrew (Frontiers in genetics · 2023Article
- Evolutionary diversification of the autophagy-related ubiquitin-like conjugation systems.Autophagy · 2022Article
- Stress response gene family expansions correlate with invasive potential in teleost fish.The Journal of experimental biology · 2022Article
- A Comprehensive Guide to Potato Transcriptome Assembly.Methods in molecular biology (Clifton, N.J.) · 2021Article
- Modern Approaches for Transcriptome Analyses in Plants.Advances in experimental medicine and biology · 2021Article
- Repositories for Taxonomic Data: Where We Are and What is Missing.Systematic biology · 2020Review
- Article
- Multi-model seascape genomics identifies distinct environmental drivers of selection among sympatric marine species.BMC evolutionary biology · 2020Article
- Comparative Analysis of Strategies forHigh-throughput · 2019Article
- Didelphis albiventris: an overview of unprecedented transcriptome sequencing of the white-eared opossum.BMC genomics · 2019Article
- Improving in-silico normalization using read weights.Scientific reports · 2019Article
- Iso-Seq Allows Genome-Independent Transcriptome Profiling of Grape Berry Development.G3 (Bethesda, Md.) · 2019Article
- Multi-tissue transcriptomes of caecilian amphibians highlight incomplete knowledge of vertebrate gene families.DNA research : an international journal for rapid publication of reports on genes and genomes · 2019Article
- De novo assembly of Agave sisalana transcriptome in response to drought stress provides insight into the tolerance mechanisms.Scientific reports · 2019Article
- Article
- Comprehensive Stress-Based De Novo Transcriptome Assembly and Annotation of Guar (International journal of genomics · 2019Article
- In silico read normalization using set multi-cover optimization.Bioinformatics (Oxford, England) · 2018Article
- Assessment of an Organ-SpecificG3 (Bethesda, Md.) · 2018Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
De novo assembly of a complete transcriptome without the need for a guiding reference genome is attractive, particularly where the cost and complexity of generating a eukaryote genome is prohibitive. The transcriptome should not however be seen as just a quick and cheap alternative to building a complete genome. Transcriptomics allows the understanding and comparison of spatial and temporal samples within an organism, and allows surveying of multiple individuals or closely related species. De novo assembly in theory allows the building of a complete transcriptome without any prior knowledge of the genome. It also allows the discovery of alternate splice forms of coding RNAs and also non-coding RNAs, which are often missed by proteomic approaches, or are incompletely annotated in genome studies. The limitations of the method are that the generation of a truly complete assembly is unlikely, and so we require some methods for the assessment of the quality and appropriateness of a generated transcriptome. Whilst no single consensus pipeline or tool is agreed as optimal, various algorithms, and easy to use software do exist making transcriptome generation a more common approach. With this expansion of data, questions still exist relating to how do we make these datasets fully discoverable, comparable and most useful to understand complex biological systems?
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.