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Metabolic Pathway Assignment of Plant Genes based on Phylogenetic Profiling–A Feasibility Study

Overview of attention for article published in Frontiers in Plant Science, October 2017
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Title
Metabolic Pathway Assignment of Plant Genes based on Phylogenetic Profiling–A Feasibility Study
Published in
Frontiers in Plant Science, October 2017
DOI 10.3389/fpls.2017.01831
Pubmed ID
Authors

Sandra Weißenborn, Dirk Walther

Abstract

Despite many developed experimental and computational approaches, functional gene annotation remains challenging. With the rapidly growing number of sequenced genomes, the concept of phylogenetic profiling, which predicts functional links between genes that share a common co-occurrence pattern across different genomes, has gained renewed attention as it promises to annotate gene functions based on presence/absence calls alone. We applied phylogenetic profiling to the problem of metabolic pathway assignments of plant genes with a particular focus on secondary metabolism pathways. We determined phylogenetic profiles for 40,960 metabolic pathway enzyme genes with assigned EC numbers from 24 plant species based on sequence and pathway annotation data from KEGG and Ensembl Plants. For gene sequence family assignments, needed to determine the presence or absence of particular gene functions in the given plant species, we included data of all 39 species available at the Ensembl Plants database and established gene families based on pairwise sequence identities and annotation information. Aside from performing profiling comparisons, we used machine learning approaches to predict pathway associations from phylogenetic profiles alone. Selected metabolic pathways were indeed found to be composed of gene families of greater than expected phylogenetic profile similarity. This was particularly evident for primary metabolism pathways, whereas for secondary pathways, both the available annotation in different species as well as the abstraction of functional association via distinct pathways proved limiting. While phylogenetic profile similarity was generally not found to correlate with gene co-expression, direct physical interactions of proteins were reflected by a significantly increased profile similarity suggesting an application of phylogenetic profiling methods as a filtering step in the identification of protein-protein interactions. This feasibility study highlights the potential and challenges associated with phylogenetic profiling methods for the detection of functional relationships between genes as well as the need to enlarge the set of plant genes with proven secondary metabolism involvement as well as the limitations of distinct pathways as abstractions of relationships between genes.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 24%
Student > Master 7 19%
Student > Bachelor 4 11%
Student > Ph. D. Student 4 11%
Student > Doctoral Student 2 5%
Other 6 16%
Unknown 5 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 38%
Biochemistry, Genetics and Molecular Biology 10 27%
Computer Science 3 8%
Business, Management and Accounting 1 3%
Engineering 1 3%
Other 0 0%
Unknown 8 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 November 2017.
All research outputs
#20,742,744
of 23,344,526 outputs
Outputs from Frontiers in Plant Science
#17,096
of 21,221 outputs
Outputs of similar age
#287,360
of 329,242 outputs
Outputs of similar age from Frontiers in Plant Science
#406
of 489 outputs
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So far Altmetric has tracked 21,221 research outputs from this source. They receive a mean Attention Score of 3.9. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 489 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.