Evidence map›Paper›PMID 28798764›Full record

ArticleFrontiers in plant science2017

Root Transcriptomic Analysis Revealing the Importance of Energy Metabolism to the Development of Deep Roots in Rice (

Qiaojun Lou, Liang Chen, Hanwei Mei, Kai Xu, Haibin Wei, Fangjun Feng, Tiemei Li, Xiaomeng Pang, Caiping Shi, Lijun Luo and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in plant science, 2017. 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
4.1field-weighted citation impact, top 7% 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, 38 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Qiaojun LouDepartment of Ecology and Evolutionary Biology, School of Life Sciences, Fudan UniversityShanghai, China.
Liang ChenShanghai Agrobiological Gene CenterShanghai, China.
Hanwei MeiShanghai Agrobiological Gene CenterShanghai, China.
Kai XuShanghai Agrobiological Gene CenterShanghai, China.
Haibin WeiShanghai Agrobiological Gene CenterShanghai, China.
Fangjun FengShanghai Agrobiological Gene CenterShanghai, China.
Tiemei LiShanghai Agrobiological Gene CenterShanghai, China.
Xiaomeng PangShanghai Agrobiological Gene CenterShanghai, China.
Caiping ShiShanghai Majorbio Bio-Pharm Technology Co., Ltd.Shanghai, China.
Lijun LuoShanghai Agrobiological Gene CenterShanghai, China.
Yang ZhongDepartment of Ecology and Evolutionary Biology, School of Life Sciences, Fudan UniversityShanghai, China.
Shanghai Agrobiological Gene Center · CNFudan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drought is the most serious abiotic stress limiting rice production, and deep root is the key contributor to drought avoidance. However, the genetic mechanism regulating the development of deep roots is largely unknown. In this study, the transcriptomes of 74 root samples from 37 rice varieties, representing the extreme genotypes of shallow or deep rooting, were surveyed by RNA-seq. The 13,242 differentially expressed genes (DEGs) between deep rooting and shallow rooting varieties (H vs. L) were enriched in the pathway of genetic information processing and metabolism, while the 1,052 DEGs between the deep roots and shallow roots from each of the plants (D vs. S) were significantly enriched in metabolic pathways especially energy metabolism. Ten quantitative trait transcripts (QTTs) were identified and some were involved in energy metabolism. Forty-nine candidate DEGs were confirmed by qRT-PCR and microarray. Through weighted gene co-expression network analysis (WGCNA), we found 18 hub genes. Surprisingly, all these hub genes expressed higher in deep roots than in shallow roots, furthermore half of them functioned in energy metabolism. We also estimated that the ATP production in the deep roots was faster than shallow roots. Our results provided a lot of reliable candidate genes to improve deep rooting, and firstly highlight the importance of energy metabolism to the development of deep roots.

Indexed as

deep rootingenergy metabolismOryza sativa (rice)QTT (quantitative trait transcripts)RDR (ratio of deep roots)transcriptomeWGCNA (weighted gene co-expression network analysis)

Identifiers

PMID28798764
PMCPMC5526896
OpenAlexW2737971420

What OpenQuestion holds

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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.