Evidence map›Paper›PMID 33219668›Full record

ArticleNucleic acids research2021

A network-based comparative framework to study conservation and divergence of proteomes in plant phylogenies.

Junha Shin, Harald Marx, Alicia Richards, Dries Vaneechoutte, Dhileepkumar Jayaraman, Junko Maeda, Sanhita Chakraborty, Michael Sussman, Klaas Vandepoele, Jean-Michel Ané and 2 more

Open access · goldAbstract readComparative Study
In one paragraph

Article in Nucleic acids research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 34% 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

5 citing papers in PubMed, 13 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

12 authors at 3 institutions in 3 countries.

Junha ShinWisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI 53715, USA.
Harald MarxDepartment of Microbiology and Ecosystem Science, University of Vienna, Althanstraße 14, 1090 Vienna, Austria.
Alicia RichardsDepartment of Chemistry, University of Wisconsin-Madison, Madison, WI 53706, USA.
Dries VaneechoutteDepartment of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 927, Ghent, Belgium.
Dhileepkumar JayaramanDepartment of Agronomy, University of Wisconsin-Madison, Madison, WI 53706, USA.
Junko MaedaDepartment of Agronomy, University of Wisconsin-Madison, Madison, WI 53706, USA.
Sanhita ChakrabortyDepartment of Agronomy, University of Wisconsin-Madison, Madison, WI 53706, USA.
Michael SussmanDepartment of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706, USA.
Klaas VandepoeleDepartment of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 927, Ghent, Belgium.
Jean-Michel AnéDepartment of Agronomy, University of Wisconsin-Madison, Madison, WI 53706, USA.
Joshua CoonDepartment of Chemistry, University of Wisconsin-Madison, Madison, WI 53706, USA.
Sushmita RoyWisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI 53715, USA.
University of Wisconsin–Madison · USGhent University · BEUniversity of Vienna · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Comparative functional genomics offers a powerful approach to study species evolution. To date, the majority of these studies have focused on the transcriptome in mammalian and yeast phylogenies. Here, we present a novel multi-species proteomic dataset and a computational pipeline to systematically compare the protein levels across multiple plant species. Globally we find that protein levels diverge according to phylogenetic distance but is more constrained than the mRNA level. Module-level comparative analysis of groups of proteins shows that proteins that are more highly expressed tend to be more conserved. To interpret the evolutionary patterns of conservation and divergence, we develop a novel network-based integrative analysis pipeline that combines publicly available transcriptomic datasets to define co-expression modules. Our analysis pipeline can be used to relate the changes in protein levels to different species-specific phenotypic traits. We present a case study with the rhizobia-legume symbiosis process that supports the role of autophagy in this symbiotic association.

Indexed as

Gene Regulatory NetworksChromatography, LiquidComputational BiologyEvolution, MolecularGene Expression Regulation, PlantGene OntologyGenomicsPhylogenyPlant ProteinsPlantsProteomeProteomicsSpecies SpecificityTandem Mass SpectrometryTranscriptomePlant ProteinsProteome

Identifiers

PMID33219668
PMCPMC7797074
OpenAlexW3098224693

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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.