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Gene stacking of multiple traits for high yield of fermentable sugars in plant biomass

Overview of attention for article published in Biotechnology for Biofuels and Bioproducts, January 2018
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Title
Gene stacking of multiple traits for high yield of fermentable sugars in plant biomass
Published in
Biotechnology for Biofuels and Bioproducts, January 2018
DOI 10.1186/s13068-017-1007-6
Pubmed ID
Authors

Aude Aznar, Camille Chalvin, Patrick M. Shih, Michael Maimann, Berit Ebert, Devon S. Birdseye, Dominique Loqué, Henrik V. Scheller

Abstract

Second-generation biofuels produced from biomass can help to decrease dependency on fossil fuels, bringing about many economic and environmental benefits. To make biomass more suitable for biorefinery use, we need a better understanding of plant cell wall biosynthesis. Increasing the ratio of C6 to C5 sugars in the cell wall and decreasing the lignin content are two important targets in engineering of plants that are more suitable for downstream processing for second-generation biofuel production. We have studied the basic mechanisms of cell wall biosynthesis and identified genes involved in biosynthesis of pectic galactan, including the GALS1 galactan synthase and the UDP-galactose/UDP-rhamnose transporter URGT1. We have engineered plants with a more suitable biomass composition by applying these findings, in conjunction with synthetic biology and gene stacking tools. Plants were engineered to have up to fourfold more pectic galactan in stems by overexpressing GALS1, URGT1, and UGE2, a UDP-glucose epimerase. Furthermore, the increased galactan trait was engineered into plants that were already engineered to have low xylan content by restricting xylan biosynthesis to vessels where this polysaccharide is essential. Finally, the high galactan and low xylan traits were stacked with the low lignin trait obtained by expressing the QsuB gene encoding dehydroshikimate dehydratase in lignifying cells. The results show that approaches to increasing C6 sugar content, decreasing xylan, and reducing lignin content can be combined in an additive manner. Thus, the engineered lines obtained by this trait-stacking approach have substantially improved properties from the perspective of biofuel production, and they do not show any obvious negative growth effects. The approach used in this study can be readily transferred to bioenergy crop plants.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 49 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 18%
Student > Master 6 12%
Student > Bachelor 5 10%
Researcher 5 10%
Unspecified 4 8%
Other 7 14%
Unknown 13 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 22%
Agricultural and Biological Sciences 11 22%
Unspecified 4 8%
Engineering 2 4%
Nursing and Health Professions 1 2%
Other 6 12%
Unknown 14 29%
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 15 March 2018.
All research outputs
#19,951,180
of 25,382,440 outputs
Outputs from Biotechnology for Biofuels and Bioproducts
#1,254
of 1,578 outputs
Outputs of similar age
#326,639
of 450,867 outputs
Outputs of similar age from Biotechnology for Biofuels and Bioproducts
#31
of 49 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,578 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 18th percentile – i.e., 18% 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 450,867 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 49 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.