Evidence map›Paper›PMID 35247985›Full record

ArticleBMC genomics2022

Label-free quantitative proteomics of maize roots from different root zones provides insight into proteins associated with enhance water uptake.

Junqiao Song, Daowen Lu, Yongfeng Niu, Haichao Sun, Pan Zhang, Wenheng Dong, Yongjiang Li, Yingying Zhang, Lianyong Lu, Qi Men and 3 more

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
1.5field-weighted citation impact, top 17% 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

0 citing papers in PubMed, 9 citations in OpenAlex.

No citing paper in PubMed yet.

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

13 authors at 2 institutions in 1 country.

Junqiao Song *College of Agronomy, Henan University of Science and Technology, Luoyang, China.
Daowen Lu *Maize Research Institute, Anyang Academy of Agricultural Sciences, Anyang, China.
Yongfeng NiuMaize Research Institute, Anyang Academy of Agricultural Sciences, Anyang, China.
Haichao SunMaize Research Institute, Anyang Academy of Agricultural Sciences, Anyang, China.
Pan ZhangMaize Research Institute, Anyang Academy of Agricultural Sciences, Anyang, China.
Wenheng DongMaize Research Institute, Anyang Academy of Agricultural Sciences, Anyang, China.
Yongjiang LiMaize Research Institute, Anyang Academy of Agricultural Sciences, Anyang, China.
Yingying ZhangMaize Research Institute, Anyang Academy of Agricultural Sciences, Anyang, China.
Lianyong LuMaize Research Institute, Anyang Academy of Agricultural Sciences, Anyang, China.
Qi MenHebei Runnong Water Saving Technology Co., Ltd., Tangshan, China.
Xiaohui ZhangMaize Research Institute, Anyang Academy of Agricultural Sciences, Anyang, China.
Pengxun RenCollege of Agronomy, Henan University of Science and Technology, Luoyang, China.
Chuankui ChenMaize Research Institute, Anyang Academy of Agricultural Sciences, Anyang, China. cck_aaas@163.com.
Anyang Academy of Agricultural Sciences · CNHenan University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMaize is one of the most important food crops worldwide. Roots play important role in maize productivity through water and nutrient uptake from the soil. Improving maize root traits for efficient water uptake will help to optimize irrigation and contribute to sustainable maize production. Therefore, we investigated the protein profiles of maize cv. Anyu308 root system divided into Upper root zone (UR), Middle root (MR), and Lower root (LR), by label free quantitative shotgun proteomic approach (LFQ). The aim of our study was to identify proteins and mechanisms associated with enhanced water uptake in different maize root zones under automatic irrigation system.

resultsAt field capacity, MR had the highest water uptake than the UR and LR. We identified a total of 489 differentially abundant proteins (DAPs) by pairwise comparison of MR, LR, and UR. Cluster analysis of DAPs revealed MR and UR had similar protein abundance patterns different from LR. More proteins were differentially abundant in MR/UR compared to LR/MR and LR/UR. Comparisons of protein profiles indicate that the DAPs in MR increased in abundance, compared to UR and LR which had more downregulated DAPs. The abundance patterns, functional category, and pathway enrichment analyses highlight chromatin structure and dynamics, ribosomal structures, polysaccharide metabolism, energy metabolism and transport, induction of water channels, inorganic ion transport, intracellular trafficking, and vesicular transport, and posttranslational modification as primary biological processes related to enhanced root water uptake in maize. Specifically, the abundance of histones, ribosomal proteins, and aquaporins, including mitochondrion electron transport proteins and the TCA cycle, underpinned MR's enhanced water uptake. Furthermore, proteins involved in folding and vascular transport supported the radial transport of solute across cell membranes in UR and MR. Parallel reaction monitoring analysis was used to confirmed profile of the DAPs obtained by LFQ-based proteomics.

conclusionThe list of differentially abundant proteins identified in MR are interesting candidates for further elucidation of their role in enhanced water uptake in maize root. Overall, the current results provided an insight into the mechanisms of maize root water uptake.

Indexed as

ProteomicsZea maysPlant ProteinsPlant RootsStress, PhysiologicalWaterPlant ProteinsWaterField capacityLabel-free proteomicsMaizeRoots, irrigationRoot zonesSoil layersWater uptake

Identifiers

PMID35247985
PMCPMC8898408
OpenAlexW4220887063

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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.