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Non-targeted Metabolomics in Diverse Sorghum Breeding Lines Indicates Primary and Secondary Metabolite Profiles Are Associated with Plant Biomass Accumulation and Photosynthesis

Overview of attention for article published in Frontiers in Plant Science, July 2016
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Title
Non-targeted Metabolomics in Diverse Sorghum Breeding Lines Indicates Primary and Secondary Metabolite Profiles Are Associated with Plant Biomass Accumulation and Photosynthesis
Published in
Frontiers in Plant Science, July 2016
DOI 10.3389/fpls.2016.00953
Pubmed ID
Authors

Marie F. Turner, Adam L. Heuberger, Jay S. Kirkwood, Carl C. Collins, Edward J. Wolfrum, Corey D. Broeckling, Jessica E. Prenni, Courtney E. Jahn

Abstract

Metabolomics is an emerging method to improve our understanding of how genetic diversity affects phenotypic variation in plants. Recent studies have demonstrated that genotype has a major influence on biochemical variation in several types of plant tissues, however, the association between metabolic variation and variation in morphological and physiological traits is largely unknown. Sorghum bicolor (L.) is an important food and fuel crop with extensive genetic and phenotypic variation. Sorghum lines have been bred for differing phenotypes beneficial for production of grain (food), stem sugar (food, fuel), and cellulosic biomass (forage, fuel), and these varying phenotypes are the end products of innate metabolic programming which determines how carbon is allocated during plant growth and development. Further, sorghum has been adapted among highly diverse environments. Because of this geographic and phenotypic variation, the sorghum metabolome is expected to be highly divergent; however, metabolite variation in sorghum has not been characterized. Here, we utilize a phenotypically diverse panel of sorghum breeding lines to identify associations between leaf metabolites and morpho-physiological traits. The panel (11 lines) exhibited significant variation for 21 morpho-physiological traits, as well as broader trends in variation by sorghum type (grain vs. biomass types). Variation was also observed for cell wall constituents (glucan, xylan, lignin, ash). Non-targeted metabolomics analysis of leaf tissue showed that 956 of 1181 metabolites varied among the lines (81%, ANOVA, FDR adjusted p < 0.05). Both univariate and multivariate analyses determined relationships between metabolites and morpho-physiological traits, and 384 metabolites correlated with at least one trait (32%, p < 0.05), including many secondary metabolites such as glycosylated flavonoids and chlorogenic acids. The use of metabolomics to explain relationships between two or more morpho-physiological traits was explored and showed chlorogenic and shikimic acid to be associated with photosynthesis, early plant growth and final biomass measures in sorghum. Taken together, this study demonstrates the integration of metabolomics with morpho-physiological datasets to elucidate links between plant metabolism, growth, and architecture.

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The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 137 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 <1%
United States 1 <1%
Unknown 135 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 33 24%
Researcher 29 21%
Student > Master 13 9%
Student > Bachelor 7 5%
Student > Doctoral Student 5 4%
Other 12 9%
Unknown 38 28%
Readers by discipline Count As %
Agricultural and Biological Sciences 50 36%
Biochemistry, Genetics and Molecular Biology 19 14%
Chemistry 12 9%
Environmental Science 5 4%
Chemical Engineering 1 <1%
Other 7 5%
Unknown 43 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 10 November 2016.
All research outputs
#12,646,591
of 22,880,230 outputs
Outputs from Frontiers in Plant Science
#5,023
of 20,270 outputs
Outputs of similar age
#174,913
of 354,317 outputs
Outputs of similar age from Frontiers in Plant Science
#112
of 515 outputs
Altmetric has tracked 22,880,230 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 20,270 research outputs from this source. They receive a mean Attention Score of 4.0. This one has gotten more attention than average, scoring higher than 74% of its peers.
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 354,317 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.
We're also able to compare this research output to 515 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.