Evidence map›Paper›PMID 20738856›Full record

ArticleGenome biology2010

Digital expression profiling of novel diatom transcripts provides insight into their biological functions.

Uma Maheswari, Kamel Jabbari, Jean-Louis Petit, Betina M Porcel, Andrew E Allen, Jean-Paul Cadoret, Alessandra De Martino, Marc Heijde, Raymond Kaas, Julie La Roche and 10 more

Abstract read
In one paragraph

Article in Genome biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed.

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  14. 3-Hydroxyisobutyryl-CoA hydrolase involved in isoleucine catabolism regulates triacylglycerol accumulation inPhilosophical transactions of the Royal Society of London. Series B, Biological sciences · 2017
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  17. Proteome response ofAlgal research · 2016
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors.

Uma MaheswariInstitut de Biologie de l'Ecole Normale Supérieure, CNRS UMR 8197 INSERM U1024, Ecole Normale Supérieure, 46 rue d'Ulm, 75005 Paris, France. uma@ebi.ac.uk
Kamel Jabbari
Jean-Louis Petit
Betina M Porcel
Andrew E Allen
Jean-Paul Cadoret
Alessandra De Martino
Marc Heijde
Raymond Kaas
Julie La Roche
Pascal J Lopez
Véronique Martin-Jézéquel
Agnès Meichenin
Thomas Mock
Micaela Schnitzler Parker
Assaf Vardi
E Virginia Armbrust
Jean Weissenbach
Michaël Katinka
Chris Bowler

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiatoms represent the predominant group of eukaryotic phytoplankton in the oceans and are responsible for around 20% of global photosynthesis. Two whole genome sequences are now available. Notwithstanding, our knowledge of diatom biology remains limited because only around half of their genes can be ascribed a function based onhomology-based methods. High throughput tools are needed, therefore, to associate functions with diatom-specific genes.

resultsWe have performed a systematic analysis of 130,000 ESTs derived from Phaeodactylum tricornutum cells grown in 16 different conditions. These include different sources of nitrogen, different concentrations of carbon dioxide, silicate and iron, and abiotic stresses such as low temperature and low salinity. Based on unbiased statistical methods, we have catalogued transcripts with similar expression profiles and identified transcripts differentially expressed in response to specific treatments. Functional annotation of these transcripts provides insights into expression patterns of genes involved in various metabolic and regulatory pathways and into the roles of novel genes with unknown functions. Specific growth conditions could be associated with enhanced gene diversity, known gene product functions, and over-representation of novel transcripts. Comparative analysis of data from the other sequenced diatom, Thalassiosira pseudonana, helped identify several unique diatom genes that are specifically regulated under particular conditions, thus facilitating studies of gene function, genome annotation and the molecular basis of species diversity.

conclusionsThe digital gene expression database represents a new resource for identifying candidate diatom-specific genes involved in processes of major ecological relevance.

Indexed as

Adaptation, PhysiologicalCarbon DioxideDiatomsEnvironmentExpressed Sequence TagsGene Expression ProfilingGene Expression RegulationIronMolecular Sequence DataNitrogenRNA, MessengerSalinitySilicatesTemperatureCarbon DioxideIronNitrogenRNA, MessengerSilicates

Identifiers

PMID20738856
PMCPMC2945787

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Registered trials

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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.