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Deconstructing the genetic basis of spent sulphite liquor tolerance using deep sequencing of genome-shuffled yeast

Overview of attention for article published in Biotechnology for Biofuels, March 2015
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3 tweeters

Citations

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17 Dimensions

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38 Mendeley
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Title
Deconstructing the genetic basis of spent sulphite liquor tolerance using deep sequencing of genome-shuffled yeast
Published in
Biotechnology for Biofuels, March 2015
DOI 10.1186/s13068-015-0241-z
Pubmed ID
Authors

Dominic Pinel, David Colatriano, Heng Jiang, Hung Lee, Vincent JJ Martin

Abstract

Identifying the genetic basis of complex microbial phenotypes is currently a major barrier to our understanding of multigenic traits and our ability to rationally design biocatalysts with highly specific attributes for the biotechnology industry. Here, we demonstrate that strain evolution by meiotic recombination-based genome shuffling coupled with deep sequencing can be used to deconstruct complex phenotypes and explore the nature of multigenic traits, while providing concrete targets for strain development. We determined genomic variations found within Saccharomyces cerevisiae previously evolved in our laboratory by genome shuffling for tolerance to spent sulphite liquor. The representation of these variations was backtracked through parental mutant pools and cross-referenced with RNA-seq gene expression analysis to elucidate the importance of single mutations and key biological processes that play a role in our trait of interest. Our findings pinpoint novel genes and biological determinants of lignocellulosic hydrolysate inhibitor tolerance in yeast. These include the following: protein homeostasis constituents, including Ubp7p and Art5p, related to ubiquitin-mediated proteolysis; stress response transcriptional repressor, Nrg1p; and NADPH-dependent glutamate dehydrogenase, Gdh1p. Reverse engineering a prominent mutation in ubiquitin-specific protease gene UBP7 in a laboratory S. cerevisiae strain effectively increased spent sulphite liquor tolerance. This study advances understanding of yeast tolerance mechanisms to inhibitory substrates and biocatalyst design for a biomass-to-biofuel/biochemical industry, while providing insights into the process of mutation accumulation that occurs during genome shuffling.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Indonesia 1 3%
United States 1 3%
Unknown 36 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 21%
Student > Bachelor 5 13%
Student > Ph. D. Student 5 13%
Other 3 8%
Student > Master 3 8%
Other 10 26%
Unknown 4 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 34%
Biochemistry, Genetics and Molecular Biology 10 26%
Engineering 4 11%
Nursing and Health Professions 1 3%
Environmental Science 1 3%
Other 2 5%
Unknown 7 18%

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 16 April 2015.
All research outputs
#12,698,323
of 16,638,522 outputs
Outputs from Biotechnology for Biofuels
#850
of 1,211 outputs
Outputs of similar age
#152,082
of 236,822 outputs
Outputs of similar age from Biotechnology for Biofuels
#1
of 1 outputs
Altmetric has tracked 16,638,522 research outputs across all sources so far. This one is in the 20th percentile – i.e., 20% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,211 research outputs from this source. They receive a mean Attention Score of 4.4. This one is in the 27th percentile – i.e., 27% of its peers scored the same or lower than it.
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We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them