↓ Skip to main content

Are orphan genes protein-coding, prediction artifacts, or non-coding RNAs?

Overview of attention for article published in BMC Bioinformatics, May 2016
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

Mentioned by

twitter
14 X users
facebook
1 Facebook page

Citations

dimensions_citation
46 Dimensions

Readers on

mendeley
81 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Are orphan genes protein-coding, prediction artifacts, or non-coding RNAs?
Published in
BMC Bioinformatics, May 2016
DOI 10.1186/s12859-016-1102-x
Pubmed ID
Authors

Neel Prabh, Christian Rödelsperger

Abstract

Current genome sequencing projects reveal substantial numbers of taxonomically restricted, so called orphan genes that lack homology with genes from other evolutionary lineages. However, it is not clear to what extent orphan genes are real, genomic artifacts, or represent non-coding RNAs. Here, we use a simple set of assumptions to test the nature of orphan genes. First, a sequence that is transcribed is considered a real biological entity. Second, every sequence that is supported by proteome data or shows a depletion of non-synonymous substitutions is a protein-coding gene. Using genomic, transcriptomic and proteomic data for the nematode Pristionchus pacificus, we show that between 4129-7997 (42-81 %) of predicted orphan genes are expressed and 3818-7545 (39-76 %) of orphan genes are under negative selection. In three cases that exhibited strong evolutionary constraint but lacked expression evidence in 14 RNA-seq samples, we could experimentally validate the predicted gene structures. Comparing different data sets to infer selection on orphan gene clusters, we find that the presence of a closely related genome provides the most powerful resource to robustly identify evidence of negative selection. However, even in the absence of other genomic data, the availability of paralogous sequences was enough to show negative selection in 8-10 % of orphan genes. Our study shows that the great majority of previously identified orphan genes in P. pacificus are indeed protein-coding genes. Even though this work represents a case study on a single species, our approach can be transferred to genomic data of other non-model organisms in order to ascertain the protein-coding nature of orphan genes.

X Demographics

X Demographics

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 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Chile 1 1%
Unknown 80 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 30%
Researcher 16 20%
Student > Bachelor 12 15%
Student > Master 10 12%
Student > Doctoral Student 4 5%
Other 5 6%
Unknown 10 12%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 30 37%
Agricultural and Biological Sciences 28 35%
Computer Science 4 5%
Chemistry 2 2%
Immunology and Microbiology 2 2%
Other 4 5%
Unknown 11 14%
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 November 2023.
All research outputs
#4,710,105
of 24,916,485 outputs
Outputs from BMC Bioinformatics
#1,705
of 7,610 outputs
Outputs of similar age
#75,774
of 345,971 outputs
Outputs of similar age from BMC Bioinformatics
#20
of 92 outputs
Altmetric has tracked 24,916,485 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,610 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 76% 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 345,971 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 76% of its contemporaries.
We're also able to compare this research output to 92 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.