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Natural variation in non-coding regions underlying phenotypic diversity in budding yeast

Overview of attention for article published in Scientific Reports, February 2016
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (59th percentile)

Mentioned by

twitter
6 tweeters

Citations

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18 Dimensions

Readers on

mendeley
63 Mendeley
Title
Natural variation in non-coding regions underlying phenotypic diversity in budding yeast
Published in
Scientific Reports, February 2016
DOI 10.1038/srep21849
Pubmed ID
Authors

Francisco Salinas, Carl G. de Boer, Valentina Abarca, Verónica García, Mara Cuevas, Sebastian Araos, Luis F. Larrondo, Claudio Martínez, Francisco A. Cubillos

Abstract

Linkage mapping studies in model organisms have typically focused their efforts in polymorphisms within coding regions, ignoring those within regulatory regions that may contribute to gene expression variation. In this context, differences in transcript abundance are frequently proposed as a source of phenotypic diversity between individuals, however, until now, little molecular evidence has been provided. Here, we examined Allele Specific Expression (ASE) in six F1 hybrids from Saccharomyces cerevisiae derived from crosses between representative strains of the four main lineages described in yeast. ASE varied between crosses with levels ranging between 28% and 60%. Part of the variation in expression levels could be explained by differences in transcription factors binding to polymorphic cis-regulations and to differences in trans-activation depending on the allelic form of the TF. Analysis on highly expressed alleles on each background suggested ASN1 as a candidate transcript underlying nitrogen consumption differences between two strains. Further promoter allele swap analysis under fermentation conditions confirmed that coding and non-coding regions explained aspartic and glutamic acid consumption differences, likely due to a polymorphism affecting Uga3 binding. Together, we provide a new catalogue of variants to bridge the gap between genotype and phenotype.

Twitter Demographics

The data shown below were collected from the profiles of 6 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 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Norway 1 2%
Japan 1 2%
Spain 1 2%
Sweden 1 2%
Austria 1 2%
Unknown 56 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 27%
Researcher 14 22%
Student > Master 9 14%
Professor 5 8%
Student > Postgraduate 4 6%
Other 14 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 33 52%
Biochemistry, Genetics and Molecular Biology 24 38%
Unspecified 4 6%
Physics and Astronomy 1 2%
Energy 1 2%
Other 0 0%

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 22 June 2018.
All research outputs
#6,224,944
of 12,319,220 outputs
Outputs from Scientific Reports
#20,994
of 55,212 outputs
Outputs of similar age
#100,753
of 286,948 outputs
Outputs of similar age from Scientific Reports
#1,208
of 3,027 outputs
Altmetric has tracked 12,319,220 research outputs across all sources so far. This one is in the 49th percentile – i.e., 49% of other outputs scored the same or lower than it.
So far Altmetric has tracked 55,212 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.4. This one has gotten more attention than average, scoring higher than 61% 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 286,948 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 64% of its contemporaries.
We're also able to compare this research output to 3,027 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.