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Mendeley readers
Attention Score in Context
| Title |
Diversity and regulatory impact of copy number variation in the primate Macaca fascicularis
|
|---|---|
| Published in |
BMC Genomics, February 2017
|
| DOI | 10.1186/s12864-017-3531-y |
| Pubmed ID | |
| Authors |
Andreas R. Gschwind, Anjali Singh, Ulrich Certa, Alexandre Reymond, Tobias Heckel |
| Abstract |
Copy number variations (CNVs) are a significant source of genetic diversity and commonly found in mammalian genomes. We have generated a genome-wide CNV map for Cynomolgus monkeys (Macaca fascicularis). This crab-eating macaque is the closest animal model to humans that is used in biomedical research. We show that Cynomolgus monkey CNVs are in general much smaller in size than gene loci and are specific to the population of origin. Genome-wide expression data from five vitally important organs demonstrates that CNVs in close proximity to transcription start sites associate strongly with expression changes. Among these eQTL genes we find an overrepresentation of genes involved in metabolism, receptor activity, and transcription. These results provide evidence that CNVs shape tissue transcriptomes in monkey populations, potentially offering an adaptive advantage. We suggest that this genetic diversity should be taken into account when using Cynomolgus macaques as models. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 18 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 28% |
| Student > Master | 4 | 22% |
| Student > Ph. D. Student | 3 | 17% |
| Professor | 1 | 6% |
| Student > Bachelor | 1 | 6% |
| Other | 2 | 11% |
| Unknown | 2 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 7 | 39% |
| Agricultural and Biological Sciences | 6 | 33% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 6% |
| Economics, Econometrics and Finance | 1 | 6% |
| Chemistry | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 2 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 December 2017.
All research outputs
#18,552,700
of 22,977,819 outputs
Outputs from BMC Genomics
#8,219
of 10,686 outputs
Outputs of similar age
#312,201
of 422,776 outputs
Outputs of similar age from BMC Genomics
#165
of 235 outputs
Altmetric has tracked 22,977,819 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,686 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 12th percentile – i.e., 12% of its peers scored the same or lower than it.
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We're also able to compare this research output to 235 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.