Evidence map›Paper›PMID 28066479›Full record

ArticleFrontiers in plant science2016

SWATH-MS Quantitative Analysis of Proteins in the Rice Inferior and Superior Spikelets during Grain Filling.

Fu-Yuan Zhu, Mo-Xian Chen, Yu-Wen Su, Xuezhong Xu, Neng-Hui Ye, Yun-Ying Cao, Sheng Lin, Tie-Yuan Liu, Hao-Xuan Li, Guan-Qun Wang and 7 more

Abstract read
In one paragraph

Article in Frontiers in plant science, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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

6 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
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

17 authors.

Fu-Yuan ZhuCollege of Life Sciences, South China Agricultural UniversityGuangzhou, China; State Key Laboratory of Agrobiotechnology, School of Life Sciences, The Chinese University of Hong KongHong Kong, Hong Kong; Shenzhen Research Institute, The Chinese University of Hong KongShenzhen, China.
Mo-Xian ChenState Key Laboratory of Agrobiotechnology, School of Life Sciences, The Chinese University of Hong Kong Hong Kong, Hong Kong.
Yu-Wen SuSchool of Pharmacy, Nanjing Medical University Nanjing, China.
Xuezhong XuCollege of Life Sciences, South China Agricultural University Guangzhou, China.
Neng-Hui YeState Key Laboratory of Agrobiotechnology, School of Life Sciences, The Chinese University of Hong KongHong Kong, Hong Kong; Shenzhen Research Institute, The Chinese University of Hong KongShenzhen, China.
Yun-Ying CaoCollege of Life Sciences, Nantong University Nantong, China.
Sheng LinCollege of Life Sciences, Fujian Agriculture and Forestry University Fuzhou, China.
Tie-Yuan LiuState Key Laboratory of Agrobiotechnology, School of Life Sciences, The Chinese University of Hong Kong Hong Kong, Hong Kong.
Hao-Xuan LiState Key Laboratory of Agrobiotechnology, School of Life Sciences, The Chinese University of Hong Kong Hong Kong, Hong Kong.
Guan-Qun WangState Key Laboratory of Agrobiotechnology, School of Life Sciences, The Chinese University of Hong Kong Hong Kong, Hong Kong.
Yu JinState Key Laboratory of Agrobiotechnology, School of Life Sciences, The Chinese University of Hong Kong Hong Kong, Hong Kong.
Yong-Hai GuThe Rice Research Institute, Guangdong Academy of Agricultural Sciences Guangzhou, China.
Wai-Lung ChanSchool of Biological Science, The University of Hong Kong Hong Kong, China.
Clive LoSchool of Biological Science, The University of Hong Kong Hong Kong, China.
Xinxiang PengCollege of Life Sciences, South China Agricultural University Guangzhou, China.
Guohui ZhuCollege of Life Sciences, South China Agricultural University Guangzhou, China.
Jianhua ZhangState Key Laboratory of Agrobiotechnology, School of Life Sciences, The Chinese University of Hong KongHong Kong, Hong Kong; Shenzhen Research Institute, The Chinese University of Hong KongShenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Modern rice cultivars have large panicle but their yield potential is often not fully achieved due to poor grain-filling of late-flowering inferior spikelets (IS). Our earlier work suggested a broad transcriptional reprogramming during grain filling and showed a difference in gene expression between IS and earlier-flowering superior spikelets (SS). However, the links between the abundances of transcripts and their corresponding proteins are unclear. In this study, a SWATH-MS (sequential window acquisition of all theoretical spectra-mass spectrometry) -based quantitative proteomic analysis has been applied to investigate SS and IS proteomes. A total of 304 proteins of widely differing functionality were observed to be differentially expressed between IS and SS. Detailed gene ontology analysis indicated that several biological processes including photosynthesis, protein metabolism, and energy metabolism are differentially regulated. Further correlation analysis revealed that abundances of most of the differentially expressed proteins are not correlated to the respective transcript levels, indicating that an extra layer of gene regulation which may exist during rice grain filling. Our findings raised an intriguing possibility that these candidate proteins may be crucial in determining the poor grain-filling of IS. Therefore, we hypothesize that the regulation of proteome changes not only occurs at the transcriptional, but also at the post-transcriptional level, during grain filling in rice.

Indexed as

grain fillingpost-transcriptional regulationproteomicsriceSWATH-MS analysis

Identifiers

PMID28066479
PMCPMC5169098

What OpenQuestion holds

Textmetadata
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.