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QTL mapping of volatile compound production in Saccharomyces cerevisiae during alcoholic fermentation

Overview of attention for article published in BMC Genomics, March 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

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Title
QTL mapping of volatile compound production in Saccharomyces cerevisiae during alcoholic fermentation
Published in
BMC Genomics, March 2018
DOI 10.1186/s12864-018-4562-8
Pubmed ID
Authors

Matthias Eder, Isabelle Sanchez, Claire Brice, Carole Camarasa, Jean-Luc Legras, Sylvie Dequin

Abstract

The volatile metabolites produced by Saccharomyces cerevisiae during alcoholic fermentation, which are mainly esters, higher alcohols and organic acids, play a vital role in the quality and perception of fermented beverages, such as wine. Although the metabolic pathways and genes behind yeast fermentative aroma formation are well described, little is known about the genetic mechanisms underlying variations between strains in the production of these aroma compounds. To increase our knowledge about the links between genetic variation and volatile production, we performed quantitative trait locus (QTL) mapping using 130 F2-meiotic segregants from two S. cerevisiae wine strains. The segregants were individually genotyped by next-generation sequencing and separately phenotyped during wine fermentation. Using different QTL mapping strategies, we were able to identify 65 QTLs in the genome, including 55 that influence the formation of 30 volatile secondary metabolites, 14 with an effect on sugar consumption and central carbon metabolite production, and 7 influencing fermentation parameters. For ethyl lactate, ethyl octanoate and propanol formation, we discovered 2 interacting QTLs each. Within 9 of the detected regions, we validated the contribution of 13 genes in the observed phenotypic variation by reciprocal hemizygosity analysis. These genes are involved in nitrogen uptake and metabolism (AGP1, ALP1, ILV6, LEU9), central carbon metabolism (HXT3, MAE1), fatty acid synthesis (FAS1) and regulation (AGP2, IXR1, NRG1, RGS2, RGT1, SIR2) and explain variations in the production of characteristic sensorial esters (e.g., 2-phenylethyl acetate, 2-metyhlpropyl acetate and ethyl hexanoate), higher alcohols and fatty acids. The detection of QTLs and their interactions emphasizes the complexity of yeast fermentative aroma formation. The validation of underlying allelic variants increases knowledge about genetic variation impacting metabolic pathways that lead to the synthesis of sensorial important compounds. As a result, this work lays the foundation for tailoring S. cerevisiae strains with optimized volatile metabolite production for fermented beverages and other biotechnological applications.

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The data shown below were collected from the profiles of 9 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 139 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 139 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 26 19%
Researcher 25 18%
Student > Bachelor 21 15%
Student > Master 12 9%
Student > Doctoral Student 9 6%
Other 10 7%
Unknown 36 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 47 34%
Biochemistry, Genetics and Molecular Biology 29 21%
Chemistry 8 6%
Immunology and Microbiology 3 2%
Engineering 3 2%
Other 6 4%
Unknown 43 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 24 October 2021.
All research outputs
#4,756,816
of 23,498,099 outputs
Outputs from BMC Genomics
#1,960
of 10,787 outputs
Outputs of similar age
#91,283
of 332,301 outputs
Outputs of similar age from BMC Genomics
#38
of 188 outputs
Altmetric has tracked 23,498,099 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,787 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 81% 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 332,301 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 72% of its contemporaries.
We're also able to compare this research output to 188 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.