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Gene-based single nucleotide polymorphism discovery in bovine muscle using next-generation transcriptomic sequencing

Overview of attention for article published in BMC Genomics, May 2013
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Title
Gene-based single nucleotide polymorphism discovery in bovine muscle using next-generation transcriptomic sequencing
Published in
BMC Genomics, May 2013
DOI 10.1186/1471-2164-14-307
Pubmed ID
Authors

Anis Djari, Diane Esquerré, Bernard Weiss, Frédéric Martins, Cédric Meersseman, Mekki Boussaha, Christophe Klopp, Dominique Rocha

Abstract

Genetic information based on molecular markers has increasingly being used in cattle breeding improvement programmes, as a mean to improve conventionally phenotypic selection. Advances in molecular genetics have led to the identification of several genetic markers associated with genes affecting economic traits. Until recently, the identification of the causative genetic variants involved in the phenotypes of interest has remained a difficult task. The advent of novel sequencing technologies now offers a new opportunity for the identification of such variants. Despite sequencing costs plummeting, sequencing whole-genomes or large targeted regions is still too expensive for most laboratories. A transcriptomic-based sequencing approach offers a cheaper alternative to identify a large number of polymorphisms and possibly to discover causative variants. In the present study, we performed a gene-based single nucleotide polymorphism (SNP) discovery analysis in bovine Longissimus thoraci, using RNA-Seq. To our knowledge, this represents the first study done in bovine muscle.

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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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 2 3%
United States 2 3%
Australia 1 1%
United Kingdom 1 1%
France 1 1%
Unknown 69 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 29%
Researcher 15 20%
Student > Master 10 13%
Student > Bachelor 7 9%
Student > Doctoral Student 5 7%
Other 7 9%
Unknown 10 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 45 59%
Biochemistry, Genetics and Molecular Biology 7 9%
Veterinary Science and Veterinary Medicine 6 8%
Medicine and Dentistry 3 4%
Computer Science 1 1%
Other 3 4%
Unknown 11 14%
Attention Score in Context

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 07 May 2013.
All research outputs
#20,192,189
of 22,709,015 outputs
Outputs from BMC Genomics
#9,248
of 10,624 outputs
Outputs of similar age
#168,659
of 193,543 outputs
Outputs of similar age from BMC Genomics
#103
of 115 outputs
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So far Altmetric has tracked 10,624 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 115 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.