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Patterns of variation in cis-regulatory regions: examining evidence of purifying selection

Overview of attention for article published in BMC Genomics, January 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 (79th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

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Title
Patterns of variation in cis-regulatory regions: examining evidence of purifying selection
Published in
BMC Genomics, January 2018
DOI 10.1186/s12864-017-4422-y
Pubmed ID
Authors

Thijessen Naidoo, Per Sjödin, Carina Schlebusch, Mattias Jakobsson

Abstract

With only 2 % of the human genome consisting of protein coding genes, functionality across the rest of the genome has been the subject of much debate. This has gained further impetus in recent years due to a rapidly growing catalogue of genomic elements, based primarily on biochemical signatures (e.g. the ENCODE project). While the assessment of functionality is a complex task, the presence of selection acting on a genomic region is a strong indicator of importance. In this study, we apply population genetic methods to investigate signals overlaying several classes of regulatory elements. We disentangle signals of purifying selection acting directly on regulatory elements from the confounding factors of demography and purifying selection linked to e.g. nearby protein coding regions. We confirm the importance of regulatory regions proximal to coding sequence, while also finding differential levels of selection at distal regions. We note differences in purifying selection among transcription factor families. Signals of constraint at some genomic classes were also strongly dependent on their physical location relative to coding sequence. In addition, levels of selection efficacy across genomic classes differed between African and non-African populations. In order to assign a valid signal of selection to a particular class of genomic sequence, we show that it is crucial to isolate the signal by accounting for the effects of demography and linked-purifying selection. Our study highlights the intricate interplay of factors affecting signals of selection on functional elements.

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The data shown below were collected from the profiles of 14 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 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 22%
Student > Ph. D. Student 4 17%
Student > Master 3 13%
Student > Postgraduate 2 9%
Other 1 4%
Other 3 13%
Unknown 5 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 35%
Agricultural and Biological Sciences 7 30%
Pharmacology, Toxicology and Pharmaceutical Science 1 4%
Mathematics 1 4%
Arts and Humanities 1 4%
Other 0 0%
Unknown 5 22%
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 19 July 2018.
All research outputs
#4,005,582
of 23,018,998 outputs
Outputs from BMC Genomics
#1,613
of 10,697 outputs
Outputs of similar age
#89,290
of 440,577 outputs
Outputs of similar age from BMC Genomics
#34
of 205 outputs
Altmetric has tracked 23,018,998 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 10,697 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 84% 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 440,577 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 79% of its contemporaries.
We're also able to compare this research output to 205 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.