Evidence map›Paper›PMID 26504546›Full record

ArticleHorticulture research2014

Construction and validation of a gene co-expression network in grapevine (Vitis vinifera. L.).

Ying-Hai Liang, Bin Cai, Fei Chen, Gang Wang, Min Wang, Yan Zhong, Zong-Ming Max Cheng

Open access · goldAbstract read
In one paragraph

Article in Horticulture research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
5.1field-weighted citation impact, top 5% 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

18 citing papers in PubMed, 39 citations in OpenAlex.

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  5. Modern Approaches for Transcriptome Analyses in Plants.Advances in experimental medicine and biology · 2021
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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

7 authors at 2 institutions in 2 countries.

Ying-Hai LiangCollege of Horticulture, Nanjing Agricultural University , Nanjing 210095, China ; Institute of Pomology, Academy of Agricultural Sciences of Jilin Province , Gong Zhuling 136100, China.
Bin CaiCollege of Horticulture, Nanjing Agricultural University , Nanjing 210095, China.
Fei ChenCollege of Horticulture, Nanjing Agricultural University , Nanjing 210095, China.
Gang WangCollege of Horticulture, Nanjing Agricultural University , Nanjing 210095, China.
Min WangCollege of Horticulture, Nanjing Agricultural University , Nanjing 210095, China.
Yan ZhongCollege of Horticulture, Nanjing Agricultural University , Nanjing 210095, China.
Zong-Ming Max ChengCollege of Horticulture, Nanjing Agricultural University , Nanjing 210095, China ; Department of Plant Sciences, University of Tennessee , Knoxville 37996, TN, USA.
Nanjing Agricultural University · CNInstitute of Pomology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gene co-expression analysis has been widely used for predicting gene functions because genes within modules of a co-expression network may be involved in similar biological processes and exhibit similar biological functions. To detect gene relationships in the grapevine genome, we constructed a grapevine gene co-expression network (GGCN) by compiling a total of 374 publically available grapevine microarray datasets. The GGCN consisted of 557 modules containing a total of 3834 nodes with 13 479 edges. The functions of the subnetwork modules were inferred by Gene ontology (GO) enrichment analysis. In 127 of the 557 modules containing two or more GO terms, 38 modules exhibited the most significantly enriched GO terms, including 'protein catabolism process', 'photosynthesis', 'cell biosynthesis process', 'biosynthesis of plant cell wall', 'stress response' and other important biological processes. The 'response to heat' GO term was highly represented in module 17, which is composed of many heat shock proteins. To further determine the potential functions of genes in module 17, we performed a Pearson correlation coefficient test, analyzed orthologous relationships with Arabidopsis genes and established gene expression correlations with real-time quantitative reverse transcriptase PCR (qRT-PCR). Our results indicated that many genes in module 17 were upregulated during the heat shock and recovery processes and downregulated in response to low temperature. Furthermore, two putative genes, Vit_07s0185g00040 and Vit_02s0025g04060, were highly expressed in response to heat shock and recovery. This study provides insight into GGCN gene modules and offers important references for gene functions and the discovery of new genes at the module level.

Identifiers

PMID26504546
PMCPMC4596334
OpenAlexW2312881896

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.