Evidence map›Paper›PMID 32620074›Full record

ArticleBMC genomics2020

TeaCoN: a database of gene co-expression network for tea plant (Camellia sinensis).

Rui Zhang, Yong Ma, Xiaoyi Hu, Ying Chen, Xiaolong He, Ping Wang, Qi Chen, Chi-Tang Ho, Xiaochun Wan, Youhua Zhang and 1 more

Abstract read
In one paragraph

Article in BMC genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

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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

14 citing papers in PubMed.

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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

11 authors.

Rui ZhangSchool of Information and Computer, Anhui Agricultural University, Hefei, China.
Yong MaSchool of Information and Computer, Anhui Agricultural University, Hefei, China.
Xiaoyi HuSchool of Forestry and Landscape Architecture, Anhui Agricultural University, Hefei, China.
Ying ChenState Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, China.
Xiaolong HeSchool of sciences, Anhui Agricultural University, Hefei, China.
Ping WangSchool of sciences, Anhui Agricultural University, Hefei, China.
Qi ChenState Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, China.
Chi-Tang HoFood Science, Rutgers University, New Brunswick, USA.
Xiaochun WanState Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, China.
Youhua ZhangSchool of Information and Computer, Anhui Agricultural University, Hefei, China. zyh163@tom.com.
Shihua ZhangSchool of sciences, Anhui Agricultural University, Hefei, China. lou_biocc@yeah.net.

Funding

National Key Research and Development Program 2017YFD0301303National Natural Science Foundation of China 31270714National Natural Science Foundation of China 31301248
6 · The paper itself

Abstract

backgroundTea plant (Camellia sinensis) is one of the world's most important beverage crops due to its numerous secondary metabolites conferring tea quality and health effects. However, only a small fraction of tea genes (especially for those metabolite-related genes) have been functionally characterized to date. A cohesive bioinformatics platform is thus urgently needed to aid in the functional determination of the remaining genes. DESCRIPTION: TeaCoN, a database of gene co-expression network for tea plant, was established to provide genome-wide associations in gene co-expression to survey gene modules (i.e., co-expressed gene sets) for a function of interest. TeaCoN featured a comprehensive collection of 261 high-quality RNA-Seq experiments that covered a wide range of tea tissues as well as various treatments for tea plant. In the current version of TeaCoN, 31,968 (94% coverage of the genome) tea gene models were documented. Users can retrieve detailed co-expression information for gene(s) of interest in four aspects: 1) co-expressed genes with the corresponding Pearson correlation coefficients (PCC-values) and statistical P-values, 2) gene information (gene ID, description, symbol, alias, chromosomal location, GO and KEGG annotation), 3) expression profile heatmap of co-expressed genes across seven main tea tissues (e.g., leaf, bud, stem, root), and 4) network visualization of co-expressed genes. We also implemented a gene co-expression analysis, BLAST search function, GO and KEGG enrichment analysis, and genome browser to facilitate use of the database.

conclusionThe TeaCoN project can serve as a beneficial platform for candidate gene screening and functional exploration of important agronomical traits in tea plant. TeaCoN is freely available at http://teacon.wchoda.com .

Indexed as

Databases, GeneticGene Expression Regulation, PlantGene Regulatory NetworksCamellia sinensisGene Expression ProfilingGlutamatesRNA-SeqGlutamatestheanineAgronomical traitDatabaseGene co-expression networkGene function determinationTea plant

Identifiers

PMID32620074
PMCPMC7333269

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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.