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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Genomic landscape of rat strain and substrain variation
|
|---|---|
| Published in |
BMC Genomics, May 2015
|
| DOI | 10.1186/s12864-015-1594-1 |
| Pubmed ID | |
| Authors |
Roel Hermsen, Joep de Ligt, Wim Spee, Francis Blokzijl, Sebastian Schäfer, Eleonora Adami, Sander Boymans, Stephen Flink, Ruben van Boxtel, Robin H van der Weide, Tim Aitman, Norbert Hübner, Marieke Simonis, Boris Tabakoff, Victor Guryev, Edwin Cuppen |
| Abstract |
Since the completion of the rat reference genome in 2003, whole-genome sequencing data from more than 40 rat strains have become available. These data represent the broad range of strains that are used in rat research including commonly used substrains. Currently, this wealth of information cannot be used to its full extent, because the variety of different variant calling algorithms employed by different groups impairs comparison between strains. In addition, all rat whole genome sequencing studies to date used an outdated reference genome for analysis (RGSC3.4 released in 2004). Here we present a comprehensive, multi-sample and uniformly called set of genetic variants in 40 rat strains, including 19 substrains. We reanalyzed all primary data using a recent version of the rat reference assembly (RGSC5.0 released in 2012) and identified over 12 million genomic variants (SNVs, indels and structural variants) among the 40 strains. 28,318 SNVs are specific to individual substrains, which may be explained by introgression from other unsequenced strains and ongoing evolution by genetic drift. Substrain SNVs may have a larger predicted functional impact compared to older shared SNVs. In summary we present a comprehensive catalog of uniformly analyzed genetic variants among 40 widely used rat inbred strains based on the RGSC5.0 assembly. This represents a valuable resource, which will facilitate rat functional genomic research. In line with previous observations, our genome-wide analyses do not show evidence for contribution of multiple ancestral founder rat subspecies to the currently used rat inbred strains, as is the case for mouse. In addition, we find that the degree of substrain variation is highly variable between strains, which is of importance for the correct interpretation of experimental data from different labs. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 2 | 40% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 60% |
| Members of the public | 2 | 40% |
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 Kingdom | 1 | 2% |
| Netherlands | 1 | 2% |
| Unknown | 50 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 27% |
| Researcher | 12 | 23% |
| Student > Master | 6 | 12% |
| Student > Postgraduate | 5 | 10% |
| Professor > Associate Professor | 2 | 4% |
| Other | 5 | 10% |
| Unknown | 8 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 18 | 35% |
| Biochemistry, Genetics and Molecular Biology | 12 | 23% |
| Medicine and Dentistry | 4 | 8% |
| Business, Management and Accounting | 2 | 4% |
| Veterinary Science and Veterinary Medicine | 1 | 2% |
| Other | 5 | 10% |
| Unknown | 10 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 17 May 2015.
All research outputs
#2,673,452
of 22,803,211 outputs
Outputs from BMC Genomics
#915
of 10,649 outputs
Outputs of similar age
#36,112
of 264,554 outputs
Outputs of similar age from BMC Genomics
#27
of 264 outputs
Altmetric has tracked 22,803,211 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,649 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 91% 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 264,554 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 86% of its contemporaries.
We're also able to compare this research output to 264 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.