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Polygenic analysis and targeted improvement of the complex trait of high acetic acid tolerance in the yeast Saccharomyces cerevisiae

Overview of attention for article published in Biotechnology for Biofuels and Bioproducts, January 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

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2 X users
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3 patents

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Title
Polygenic analysis and targeted improvement of the complex trait of high acetic acid tolerance in the yeast Saccharomyces cerevisiae
Published in
Biotechnology for Biofuels and Bioproducts, January 2016
DOI 10.1186/s13068-015-0421-x
Pubmed ID
Authors

Jean-Paul Meijnen, Paola Randazzo, María R. Foulquié-Moreno, Joost van den Brink, Paul Vandecruys, Marija Stojiljkovic, Françoise Dumortier, Polona Zalar, Teun Boekhout, Nina Gunde-Cimerman, Janez Kokošar, Miha Štajdohar, Tomaž Curk, Uroš Petrovič, Johan M. Thevelein

Abstract

Acetic acid is one of the major inhibitors in lignocellulose hydrolysates used for the production of second-generation bioethanol. Although several genes have been identified in laboratory yeast strains that are required for tolerance to acetic acid, the genetic basis of the high acetic acid tolerance naturally present in some Saccharomyces cerevisiae strains is unknown. Identification of its polygenic basis may allow improvement of acetic acid tolerance in yeast strains used for second-generation bioethanol production by precise genome editing, minimizing the risk of negatively affecting other industrially important properties of the yeast. Haploid segregants of a strain with unusually high acetic acid tolerance and a reference industrial strain were used as superior and inferior parent strain, respectively. After crossing of the parent strains, QTL mapping using the SNP variant frequency determined by pooled-segregant whole-genome sequence analysis revealed two major QTLs. All F1 segregants were then submitted to multiple rounds of random inbreeding and the superior F7 segregants were submitted to the same analysis, further refined by sequencing of individual segregants and bioinformatics analysis taking into account the relative acetic acid tolerance of the segregants. This resulted in disappearance in the QTL mapping with the F7 segregants of a major F1 QTL, in which we identified HAA1, a known regulator of high acetic acid tolerance, as a true causative allele. Novel genes determining high acetic acid tolerance, GLO1, DOT5, CUP2, and a previously identified component, VMA7, were identified as causative alleles in the second major F1 QTL and in three newly appearing F7 QTLs, respectively. The superior HAA1 allele contained a unique single point mutation that significantly improved acetic acid tolerance under industrially relevant conditions when inserted into an industrial yeast strain for second-generation bioethanol production. This work reveals the polygenic basis of high acetic acid tolerance in S. cerevisiae in unprecedented detail. It also shows for the first time that a single strain can harbor different sets of causative genes able to establish the same polygenic trait. The superior alleles identified can be used successfully for improvement of acetic acid tolerance in industrial yeast strains.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 153 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 <1%
Thailand 1 <1%
Belgium 1 <1%
Unknown 150 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 30 20%
Researcher 26 17%
Student > Master 24 16%
Student > Bachelor 19 12%
Student > Doctoral Student 11 7%
Other 19 12%
Unknown 24 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 53 35%
Biochemistry, Genetics and Molecular Biology 40 26%
Chemical Engineering 6 4%
Engineering 5 3%
Immunology and Microbiology 4 3%
Other 9 6%
Unknown 36 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 21 March 2019.
All research outputs
#4,369,982
of 25,374,647 outputs
Outputs from Biotechnology for Biofuels and Bioproducts
#252
of 1,578 outputs
Outputs of similar age
#70,228
of 400,126 outputs
Outputs of similar age from Biotechnology for Biofuels and Bioproducts
#7
of 58 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,578 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done well, scoring higher than 83% 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 400,126 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 58 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.