Evidence map›Paper›PMID 29220485›Full record

ArticleGigaScience2018

funRiceGenes dataset for comprehensive understanding and application of rice functional genes.

Wen Yao, Guangwei Li, Yiming Yu, Yidan Ouyang

Abstract read
In one paragraph

Article in GigaScience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed, 1 pooled it
–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

62 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  14. Improving yield-related traits by editing the promoter of the heading date gene Ehd1 in rice.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023
    Article
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  18. Mining genes regulating root system architecture in maize based on data integration analysis.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023
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2 more citing papers are in PubMed but not listed here.

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

4 authors.

Wen YaoNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, China.
Guangwei LiNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, China.
Yiming YuNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, China.
Yidan OuyangNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: As a main staple food, rice is also a model plant for functional genomic studies of monocots. Decoding of every DNA element of the rice genome is essential for genetic improvement to address increasing food demands. The past 15 years have witnessed extraordinary advances in rice functional genomics. Systematic characterization and proper deposition of every rice gene are vital for both functional studies and crop genetic improvement. Findings: We built a comprehensive and accurate dataset of ∼2800 functionally characterized rice genes and ∼5000 members of different gene families by integrating data from available databases and reviewing every publication on rice functional genomic studies. The dataset accounts for 19.2% of the 39 045 annotated protein-coding rice genes, which provides the most exhaustive archive for investigating the functions of rice genes. We also constructed 214 gene interaction networks based on 1841 connections between 1310 genes. The largest network with 762 genes indicated that pleiotropic genes linked different biological pathways. Increasing degree of conservation of the flowering pathway was observed among more closely related plants, implying substantial value of rice genes for future dissection of flowering regulation in other crops. All data are deposited in the funRiceGenes database (https://funricegenes.github.io/). Functionality for advanced search and continuous updating of the database are provided by a Shiny application (http://funricegenes.ncpgr.cn/). Conclusions: The funRiceGenes dataset would enable further exploring of the crosslink between gene functions and natural variations in rice, which can also facilitate breeding design to improve target agronomic traits of rice.

Indexed as

Gene Expression Regulation, PlantGene Regulatory NetworksGenes, PlantSoftwareChromosome MappingDatabases, GeneticDatasets as TopicFlowersGenetic PleiotropyOryzaPhenotypePlant BreedingQuantitative Trait Locifunctional genomicsgenetic improvementinteraction networkOryza sativa (rice)

Identifiers

PMID29220485
PMCPMC5765555

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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.