Title |
Fine mapping of complex traits in non-model species: using next generation sequencing and advanced intercross lines in Japanese quail
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Published in |
BMC Genomics, October 2012
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DOI | 10.1186/1471-2164-13-551 |
Pubmed ID | |
Authors |
Laure Frésard, Sophie Leroux, Patrice Dehais, Bertrand Servin, Hélène Gilbert, Olivier Bouchez, Christophe Klopp, Cédric Cabau, Florence Vignoles, Katia Feve, Amélie Ricros, David Gourichon, Christian Diot, Sabine Richard, Christine Leterrier, Catherine Beaumont, Alain Vignal, Francis Minvielle, Frédérique Pitel |
Abstract |
As for other non-model species, genetic analyses in quail will benefit greatly from a higher marker density, now attainable thanks to the evolution of sequencing and genotyping technologies. Our objective was to obtain the first genome wide panel of Japanese quail SNP (Single Nucleotide Polymorphism) and to use it for the fine mapping of a QTL for a fear-related behaviour, namely tonic immobility, previously localized on Coturnix japonica chromosome 1. To this aim, two reduced representations of the genome were analysed through high-throughput 454 sequencing: AFLP (Amplified Fragment Length Polymorphism) fragments as representatives of genomic DNA, and EST (Expressed Sequence Tag) as representatives of the transcriptome. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United Kingdom | 1 | 25% |
Unknown | 3 | 75% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 50% |
Scientists | 1 | 25% |
Practitioners (doctors, other healthcare professionals) | 1 | 25% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Brazil | 2 | 4% |
Portugal | 1 | 2% |
France | 1 | 2% |
Netherlands | 1 | 2% |
Australia | 1 | 2% |
Ireland | 1 | 2% |
Unknown | 49 | 88% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 20 | 36% |
Other | 6 | 11% |
Student > Master | 6 | 11% |
Student > Ph. D. Student | 5 | 9% |
Professor > Associate Professor | 4 | 7% |
Other | 9 | 16% |
Unknown | 6 | 11% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 37 | 66% |
Biochemistry, Genetics and Molecular Biology | 3 | 5% |
Veterinary Science and Veterinary Medicine | 2 | 4% |
Environmental Science | 1 | 2% |
Computer Science | 1 | 2% |
Other | 3 | 5% |
Unknown | 9 | 16% |