Evidence map›Paper›PMID 17586815›Full record

ArticleNucleic acids research2007

Combined experimental and computational approach to identify non-protein-coding RNAs in the deep-branching eukaryote Giardia intestinalis.

Xiaowei Sylvia Chen, Timofey S Rozhdestvensky, Lesley J Collins, Jürgen Schmitz, David Penny

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.1field-weighted citation impact, top 13% of its field
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

17 citing papers in PubMed, 29 citations in OpenAlex.

  1. Exploration ofParasitology · 2024
    Review
  2. Utilization of Small RNA Genes to DistinguishThe American journal of tropical medicine and hygiene · 2019
    Article
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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

5 authors at 2 institutions in 3 countries.

Xiaowei Sylvia ChenAllan Wilson Centre, IMBS, Massey University, Palmerston North, New Zealand.
Timofey S Rozhdestvensky
Lesley J Collins
Jürgen Schmitz
David Penny
Massey University · NZAllan Wilson Centre · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-protein-coding RNAs represent a large proportion of transcribed sequences in eukaryotes. These RNAs often function in large RNA-protein complexes, which are catalysts in various RNA-processing pathways. As RNA processing has become an increasingly important area of research, numerous non-messenger RNAs have been uncovered in all the model eukaryotic organisms. However, knowledge on RNA processing in deep-branching eukaryotes is still limited. This study focuses on the identification of non-protein-coding RNAs from the diplomonad parasite Giardia intestinalis, showing that a combined experimental and computational search strategy is a fast method of screening reduced or compact genomes. The analysis of our Giardia cDNA library has uncovered 31 novel candidates, including C/D-box and H/ACA box snoRNAs, as well as an unusual transcript of RNase P, and double-stranded RNAs. Subsequent computational analysis has revealed additional putative C/D-box snoRNAs. Our results will lead towards a future understanding of RNA metabolism in the deep-branching eukaryote Giardia, as more ncRNAs are characterized.

Indexed as

AnimalsComputational BiologyDNA, ComplementaryGene LibraryGiardia lambliaRepetitive Sequences, Nucleic AcidRibonuclease PRNA, ProtozoanRNA, Small NucleolarRNA, UntranslatedSequence Analysis, RNADNA, ComplementaryRibonuclease PRNA, ProtozoanRNA, Small NucleolarRNA, Untranslated

Identifiers

PMID17586815
PMCPMC1950533
OpenAlexW2150628289

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.