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Systems Genetic Validation of the SNP-Metabolite Association in Rice Via Metabolite-Pathway-Based Phenome-Wide Association Scans

Overview of attention for article published in Frontiers in Plant Science, November 2015
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Title
Systems Genetic Validation of the SNP-Metabolite Association in Rice Via Metabolite-Pathway-Based Phenome-Wide Association Scans
Published in
Frontiers in Plant Science, November 2015
DOI 10.3389/fpls.2015.01027
Pubmed ID
Authors

Yaping Lu, Yemao Liu, Xiaohui Niu, Qingyong Yang, Xuehai Hu, Hong-Yu Zhang, Jingbo Xia

Abstract

In the post-GWAS (Genome-Wide Association Scan) era, the interpretation of GWAS results is crucial to screen for highly relevant phenotype-genotype association pairs. Based on the single genotype-phenotype association test and a pathway enrichment analysis, we propose a Metabolite-pathway-based Phenome-Wide Association Scan (M-PheWAS) to analyze the key metabolite-SNP pairs in rice and determine the regulatory relationship by assessing similarities in the changes of enzymes and downstream products in a pathway. Two SNPs, sf0315305925 and sf0315308337, were selected using this approach, and their molecular function and regulatory relationship with Enzyme EC:5.5.1.6 and with flavonoids, a significant downstream regulatory metabolite product, were demonstrated. Moreover, a total of 105 crucial SNPs were screened using M-PheWAS, which may be important for metabolite associations.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Israel 1 4%
Turkey 1 4%
France 1 4%
Belgium 1 4%
Unknown 22 85%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 19%
Researcher 5 19%
Student > Master 4 15%
Student > Bachelor 3 12%
Professor 1 4%
Other 3 12%
Unknown 5 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 10 38%
Biochemistry, Genetics and Molecular Biology 6 23%
Engineering 2 8%
Computer Science 1 4%
Mathematics 1 4%
Other 0 0%
Unknown 6 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 27 November 2015.
All research outputs
#15,965,023
of 23,775,451 outputs
Outputs from Frontiers in Plant Science
#11,498
of 21,845 outputs
Outputs of similar age
#231,367
of 391,527 outputs
Outputs of similar age from Frontiers in Plant Science
#195
of 417 outputs
Altmetric has tracked 23,775,451 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 21,845 research outputs from this source. They receive a mean Attention Score of 3.9. This one is in the 46th percentile – i.e., 46% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 391,527 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 417 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.