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Harnessing cross-species alignment to discover SNPs and generate a draft genome sequence of a bighorn sheep (Ovis canadensis)

Overview of attention for article published in BMC Genomics, May 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

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2 news outlets
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6 X users
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1 Facebook page

Citations

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19 Dimensions

Readers on

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48 Mendeley
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1 CiteULike
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Title
Harnessing cross-species alignment to discover SNPs and generate a draft genome sequence of a bighorn sheep (Ovis canadensis)
Published in
BMC Genomics, May 2015
DOI 10.1186/s12864-015-1618-x
Pubmed ID
Authors

Joshua M Miller, Stephen S Moore, Paul Stothard, Xiaoping Liao, David W Coltman

Abstract

Whole genome sequences (WGS) have proliferated as sequencing technology continues to improve and costs decline. While many WGS of model or domestic organisms have been produced, a growing number of non-model species are also being sequenced. In the absence of a reference, construction of a genome sequence necessitates de novo assembly which may be beyond the ability of many labs due to the large volumes of raw sequence data and extensive bioinformatics required. In contrast, the presence of a reference WGS allows for alignment which is more tractable than assembly. Recent work has highlighted that the reference need not come from the same species, potentially enabling a wide array of species WGS to be constructed using cross-species alignment. Here we report on the creation a draft WGS from a single bighorn sheep (Ovis canadensis) using alignment to the closely related domestic sheep (Ovis aries). Two sequencing libraries on SOLiD platforms yielded over 865 million reads, and combined alignment to the domestic sheep reference resulted in a nearly complete sequence (95% coverage of the reference) at an average of 12x read depth (104 SD). From this we discovered over 15 million variants and annotated them relative to the domestic sheep reference. We then conducted an enrichment analysis of those SNPs showing fixed differences between the reference and sequenced individual and found significant differences in a number of gene ontology (GO) terms, including those associated with reproduction, muscle properties, and bone deposition. Our results demonstrate that cross-species alignment enables the creation of novel WGS for non-model organisms. The bighorn sheep WGS will provide a resource for future resequencing studies or comparative genomics.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Unknown 47 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 25%
Student > Master 11 23%
Student > Ph. D. Student 5 10%
Professor 3 6%
Student > Postgraduate 3 6%
Other 7 15%
Unknown 7 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 65%
Biochemistry, Genetics and Molecular Biology 4 8%
Computer Science 2 4%
Environmental Science 1 2%
Unknown 10 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 20. 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 23 June 2015.
All research outputs
#1,571,199
of 22,805,349 outputs
Outputs from BMC Genomics
#365
of 10,650 outputs
Outputs of similar age
#21,538
of 266,611 outputs
Outputs of similar age from BMC Genomics
#10
of 251 outputs
Altmetric has tracked 22,805,349 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,650 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 96% 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 266,611 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 91% of its contemporaries.
We're also able to compare this research output to 251 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.