↓ Skip to main content

PNAS

Article Metrics

Achieving diverse and monoallelic olfactory receptor selection through dual-objective optimization design

Overview of attention for article published in Proceedings of the National Academy of Sciences of the United States of America, May 2016
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
24 news outlets
blogs
3 blogs
twitter
11 tweeters
wikipedia
1 Wikipedia page
googleplus
3 Google+ users

Citations

dimensions_citation
20 Dimensions

Readers on

mendeley
52 Mendeley
citeulike
1 CiteULike
Title
Achieving diverse and monoallelic olfactory receptor selection through dual-objective optimization design
Published in
Proceedings of the National Academy of Sciences of the United States of America, May 2016
DOI 10.1073/pnas.1601722113
Pubmed ID
Authors

Xiao-Jun Tian, Hang Zhang, Jens Sannerud, Jianhua Xing

Abstract

Multiple-objective optimization is common in biological systems. In the mammalian olfactory system, each sensory neuron stochastically expresses only one out of up to thousands of olfactory receptor (OR) gene alleles; at the organism level, the types of expressed ORs need to be maximized. Existing models focus only on monoallele activation, and cannot explain recent observations in mutants, especially the reduced global diversity of expressed ORs in G9a/GLP knockouts. In this work we integrated existing information on OR expression, and constructed a comprehensive model that has all its components based on physical interactions. Analyzing the model reveals an evolutionarily optimized three-layer regulation mechanism, which includes zonal segregation, epigenetic barrier crossing coupled to a negative feedback loop that mechanistically differs from previous theoretical proposals, and a previously unidentified enhancer competition step. This model not only recapitulates monoallelic OR expression, but also elucidates how the olfactory system maximizes and maintains the diversity of OR expression, and has multiple predictions validated by existing experimental results. Through making an analogy to a physical system with thermally activated barrier crossing and comparative reverse engineering analyses, the study reveals that the olfactory receptor selection system is optimally designed, and particularly underscores cooperativity and synergy as a general design principle for multiobjective optimization in biology.

Twitter Demographics

The data shown below were collected from the profiles of 11 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 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
United Kingdom 1 2%
Unknown 49 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 35%
Researcher 14 27%
Student > Doctoral Student 4 8%
Professor > Associate Professor 3 6%
Student > Master 2 4%
Other 7 13%
Unknown 4 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 31%
Biochemistry, Genetics and Molecular Biology 9 17%
Neuroscience 9 17%
Physics and Astronomy 7 13%
Psychology 3 6%
Other 5 10%
Unknown 3 6%

Attention Score in Context

This research output has an Altmetric Attention Score of 218. 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 30 October 2020.
All research outputs
#90,955
of 17,083,063 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#2,089
of 88,706 outputs
Outputs of similar age
#1,356
of 239,760 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#33
of 934 outputs
Altmetric has tracked 17,083,063 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 88,706 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 30.3. This one has done particularly well, scoring higher than 97% 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 239,760 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 934 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.