Evidence map›Paper›PMID 32627139›Full record

ArticleMolecular biology reports2020

Deciphering carbohydrate metabolism during wheat grain development via integrated transcriptome and proteome dynamics.

Ayesha Tahir, Jun Kang, Frederic Choulet, Catherine Ravel, Isabelle Romeuf, Fatemeh Rasouli, Asia Nosheen, Gerard Branlard

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Article in Molecular biology reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

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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

8 citing papers in PubMed.

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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

8 authors.

Ayesha TahirDepartment of Biosciences, COMSATS University Islamabad, Islamabad, Pakistan. ayesha.tahir2007@gmail.com.ORCID http://orcid.org/0000-0002-3701-6052
Jun KangSchool of Life Sciences, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin, 300072, China.
Frederic ChouletINRAE, UCA UMR1095 GDEC, Clermont-Ferrand, France.
Catherine RavelINRAE, UCA UMR1095 GDEC, Clermont-Ferrand, France.
Isabelle RomeufDepartment of Biosciences, COMSATS University Islamabad, Islamabad, Pakistan.
Fatemeh RasouliTasmanian Institute of Agriculture, College of Science and Engineering, University of Tasmania, Hobart, Australia.
Asia NosheenDepartment of Biosciences, COMSATS University Islamabad, Islamabad, Pakistan.
Gerard BranlardINRAE, UCA UMR1095 GDEC, Clermont-Ferrand, France. gerard.branlard@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Grain development of Triticum aestivum is being studied extensively using individual OMICS tools. However, integrated transcriptome and proteome studies are limited mainly due to complexity of genome. Current study focused to unravel the transcriptome-proteome coordination of key mechanisms underlying carbohydrate metabolism during whole wheat grain development. Wheat grains were manually dissected to obtain grain tissues for proteomics and transcriptomics analyses. Differentially expressed proteins and transcripts at the 11 stages of grain development were compared. Computational workflow for integration of two datasets related to carbohydrate metabolism was designed. For CM proteins, output peptide sequences of proteomic analyses (via LC-MS/MS) were used as source to search corresponding transcripts. The transcript that turned out with higher number of peptides was selected as bona fide ribonucleotide sequence for respective protein synthesis. More than 90% of hits resulted in successful identification of respective transcripts. Comparative analysis of protein and transcript expression profiles resulted in overall 32% concordance between these two series of data. However, during grain development correlation of two datasets gradually increased up to ~ tenfold from 152 to 655 °Cd and then dropped down. Proteins involved in carbohydrate metabolism were divided in five categories in accordance with their functions. Enzymes involved in starch and sucrose biosynthesis showed the highest correlations between proteome-transcriptome profiles. High percentage of identification and validation of protein-transcript hits highlighted the power of omics data integration approach over existing gene functional annotation tools. We found that correlation of two datasets is highly influenced by stage of grain development. Further, gene regulatory networks would be helpful in unraveling the mechanisms underlying the complex and significant traits such as grain weight and yield.

Indexed as

Carbohydrate MetabolismCarbohydratesChromatography, LiquidEdible GrainGene Expression ProfilingGene Expression Regulation, PlantPlant ProteinsProteomeProteomicsTandem Mass SpectrometryTranscriptomeTriticumCarbohydratesPlant ProteinsProteomeCarbohydrate metabolismGrain developmentGrain proteomeTranscriptomeWheat

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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 Socratic graph.