Evidence map›Paper›PMID 26911482›Full record

ArticleBMC genomics2016

Analysis of weighted co-regulatory networks in maize provides insights into new genes and regulatory mechanisms related to inositol phosphate metabolism.

Shaojun Zhang, Wenzhu Yang, Qianqian Zhao, Xiaojin Zhou, Ling Jiang, Shuai Ma, Xiaoqing Liu, Ye Li, Chunyi Zhang, Yunliu Fan and 1 more

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
8.2field-weighted citation impact, top 4% 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

16 citing papers in PubMed, 27 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 2 countries.

Shaojun ZhangBiotechnology Research Institute, Chinese Academy of Agricultural Sciences, 100081, Beijing, China. connshaojun.zhang@hotmail.com.
Wenzhu YangBiotechnology Research Institute, Chinese Academy of Agricultural Sciences, 100081, Beijing, China. yangwenzhu@caas.cn.
Qianqian ZhaoBiotechnology Research Institute, Chinese Academy of Agricultural Sciences, 100081, Beijing, China. zhaoqianqian@yeah.net.
Xiaojin ZhouBiotechnology Research Institute, Chinese Academy of Agricultural Sciences, 100081, Beijing, China. zhouxiaojin@caas.cn.
Ling JiangBiotechnology Research Institute, Chinese Academy of Agricultural Sciences, 100081, Beijing, China. jiangling@caas.cn.
Shuai MaBiotechnology Research Institute, Chinese Academy of Agricultural Sciences, 100081, Beijing, China. mscclg@163.com.
Xiaoqing LiuBiotechnology Research Institute, Chinese Academy of Agricultural Sciences, 100081, Beijing, China. qing0225@126.com.
Ye LiBiotechnology Research Institute, Chinese Academy of Agricultural Sciences, 100081, Beijing, China. liye20086@163.com.
Chunyi ZhangBiotechnology Research Institute, Chinese Academy of Agricultural Sciences, 100081, Beijing, China. zhangchunyi@caas.cn.
Yunliu FanBiotechnology Research Institute, Chinese Academy of Agricultural Sciences, 100081, Beijing, China. fanyunliu@caas.cn.
Rumei ChenBiotechnology Research Institute, Chinese Academy of Agricultural Sciences, 100081, Beijing, China. chenrumei@caas.cn.
Chinese Academy of Agricultural Sciences · CNBiotechnology Research Institute · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundD-myo-inositol phosphates (IPs) are a series of phosphate esters. Myo-inositol hexakisphosphate (phytic acid, IP6) is the most abundant IP and has negative effects on animal and human nutrition. IPs play important roles in plant development, stress responses, and signal transduction. However, the metabolic pathways and possible regulatory mechanisms of IPs in maize are unclear. In this study, the B73 (high in phytic acid) and Qi319 (low in phytic acid) lines were selected for RNA-Seq analysis from 427 inbred lines based on a screening of IP levels. By integrating the metabolite data with the RNA-Seq data at three different kernel developmental stages (12, 21 and 30 days after pollination), co-regulatory networks were constructed to explore IP metabolism and its interactions with other pathways.

resultsDifferentially expressed gene analyses showed that the expression of MIPS and ITPK was related to differences in IP metabolism in Qi319 and B73. Moreover, WRKY and ethylene-responsive transcription factors (TFs) were common among the differentially expressed TFs, and are likely to be involved in the regulation of IP metabolism. Six co-regulatory networks were constructed, and three were chosen for further analysis. Based on network analyses, we proposed that the GA pathway interacts with the IP pathway through the ubiquitination pathway, and that Ca(2+) signaling functions as a bridge between IPs and other pathways. IP pools were found to be transported by specific ATP-binding cassette (ABC) transporters. Finally, three candidate genes (Mf3, DH2 and CB5) were identified and validated using Arabidopsis lines with mutations in orthologous genes or RNA interference (RNAi)-transgenic maize lines. Some mutant or RNAi lines exhibited seeds with a low-phytic-acid phenotype, indicating perturbation of IP metabolism. Mf3 likely encodes an enzyme involved in IP synthesis, DH2 encodes a transporter responsible for IP transport across organs and CB5 encodes a transporter involved in IP co-transport into vesicles.

conclusionsThis study provides new insights into IP metabolism and regulation, and facilitates our development of a better understanding of the functions of IPs and how they interact with other pathways involved in plant development and stress responses. Three new genes were discovered and preliminarily validated, thereby increasing our knowledge of IP metabolism.

Indexed as

Gene Expression Regulation, PlantGenes, PlantAlternative SplicingArabidopsisGene Regulatory NetworksInositol PhosphatesMicroRNAsPhenotypePhytic AcidPlants, Genetically ModifiedRNA, PlantSeedsSequence Analysis, RNATranscription FactorsTranscriptomeZea maysInositol PhosphatesMicroRNAsPhytic AcidRNA, PlantTranscription Factors

Identifiers

PMID26911482
PMCPMC4765147
OpenAlexW2285170096

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.