Evidence map›Paper›PMID 39689042›Full record

ArticleDatabase : the journal of biological databases and curation2024

AthRiboNC: an Arabidopsis database for ncRNAs with coding potential revealed from ribosome profiling.

Yi Shen, Liya Liu, Enyan Liu, Sida Li, Yuriy Orlov, Vladimir Ivanisenko, Ming Chen

Abstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

7 authors.

Yi ShenDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.ORCID 0009-0004-3758-2275
Liya LiuDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.
Enyan LiuDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.
Sida LiDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.
Yuriy OrlovInstitute of Biodesign and Complex Systems Modeling, Sechenov First Moscow State Medical University (Sechenov University), Moscow 119991, Russia.ORCID 0000-0003-0587-1609
Vladimir IvanisenkoInstitute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia.
Ming ChenDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.ORCID 0000-0002-9677-1699

Funding

National Natural Sciences Foundation of China 32070677National Natural Sciences Foundation of China 32070677 32270709National Natural Sciences Foundation of China 32261133526National Natural Sciences Foundation of China 32270709SRTP Program of Zhejiang University Y202204165
6 · The paper itself

Abstract

Non-coding RNAs (ncRNAs) are traditionally considered incapable of encoding proteins, but new evidence suggests that small open reading frames (sORFs) within ncRNAs can actually encode biologically functional small peptides. Despite growing recognition of their importance, a systematic exploration of plant ncRNAs with coding potential has remained largely uncharted territory, especially in the context of their translational activities. By collecting and analyzing Ribo-Seq data from 226 Arabidopsis thaliana samples, we have integrated extensive information on Arabidopsis ncRNAs with coding potential and developed the AthRiboNC database, a novel and dedicated database that consolidates extensive information on ncRNAs with coding potential in Arabidopsis. AthRiboNC covers detailed information on 2743 long non-coding RNAs, 255 microRNAs, and 1871 circular RNA in Arabidopsis, along with 40 162 ORFs identified from these ncRNAs. The database also constructs co-expression networks for ncRNAs with coding potential, revealing correlations and potential biological function interpretations. With a commitment to accessibility and ease-of-use, AthRiboNC features a clear and intuitive interface. We hope that AthRiboNC will serve as a valuable resource for exploring the coding potential of plant ncRNAs. Database URL: https://bis.zju.edu.cn/athribonc.

Indexed as

ArabidopsisOpen Reading FramesRibosomesRNA, UntranslatedDatabases, GeneticDatabases, Nucleic AcidRibosome ProfilingRNA, PlantRNA, PlantRNA, Untranslated

Identifiers

PMID39689042
PMCPMC11651143

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.