Evidence map›Paper›PMID 32934280›Full record

ArticleScientific reports2020

Analysis of rice nuclear-localized seed-expressed proteins and their database (RSNP-DB).

Priyanka Deveshwar, Shivam Sharma, Ankita Prusty, Neha Sinha, Sajad Majeed Zargar, Divya Karwal, Vishal Parashar, Sanjeev Singh, Akhilesh Kumar Tyagi

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.1field-weighted citation impact, top 55% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. LocalizationFrontiers in cellular and infection microbiology · 2023
    Article
  3. Article
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

9 authors at 2 institutions in 1 country.

Priyanka DeveshwarInterdisciplinary Centre for Plant Genomics and Department of Plant Molecular Biology, University of Delhi, South Campus, New Delhi, India.
Shivam SharmaInterdisciplinary Centre for Plant Genomics and Department of Plant Molecular Biology, University of Delhi, South Campus, New Delhi, India.
Ankita PrustyInterdisciplinary Centre for Plant Genomics and Department of Plant Molecular Biology, University of Delhi, South Campus, New Delhi, India.
Neha SinhaInterdisciplinary Centre for Plant Genomics and Department of Plant Molecular Biology, University of Delhi, South Campus, New Delhi, India.
Sajad Majeed ZargarInterdisciplinary Centre for Plant Genomics and Department of Plant Molecular Biology, University of Delhi, South Campus, New Delhi, India.
Divya KarwalInstitute of Informatics and Communications, University of Delhi, South Campus, New Delhi, India.
Vishal ParasharInstitute of Informatics and Communications, University of Delhi, South Campus, New Delhi, India.
Sanjeev SinghInstitute of Informatics and Communications, University of Delhi, South Campus, New Delhi, India.
Akhilesh Kumar TyagiInterdisciplinary Centre for Plant Genomics and Department of Plant Molecular Biology, University of Delhi, South Campus, New Delhi, India. akhilesh@genomeindia.org.
University of Delhi · INSher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nuclear proteins are primarily regulatory factors governing gene expression. Multiple factors determine the localization of a protein in the nucleus. An upright identification of nuclear proteins is way far from accuracy. We have attempted to combine information from subcellular prediction tools, experimental evidence, and nuclear proteome data to identify a reliable list of seed-expressed nuclear proteins in rice. Depending upon the number of prediction tools calling a protein nuclear, we could sort 19,441 seed expressed proteins into five categories. Of which, half of the seed-expressed proteins were called nuclear by at least one out of four prediction tools. Further, gene ontology (GO) enrichment and transcription factor composition analysis showed that 6116 seed-expressed proteins could be called nuclear with a greater assertion. Localization evidence from experimental data was available for 1360 proteins. Their analysis showed that a 92.04% accuracy of a nuclear call is valid for proteins predicted nuclear by at least three tools. Distribution of nuclear localization signals and nuclear export signals showed that the majority of category four members were nuclear resident proteins, whereas other categories have a low fraction of nuclear resident proteins and significantly higher constitution of shuttling proteins. We compiled all the above information for the seed-expressed genes in the form of a searchable database named Rice Seed Nuclear Protein DataBase (RSNP-DB) https://pmb.du.ac.in/rsnpdb . This information will be useful for comprehending the role of seed nuclear proteome in rice.

Indexed as

Databases, ProteinCell NucleusNuclear ProteinsOryzaPlant ProteinsProteomeSeedsNuclear ProteinsPlant ProteinsProteome

Identifiers

PMID32934280
PMCPMC7492263
OpenAlexW3087322040

What OpenQuestion holds

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LicenceCC BY
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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.