Title |
Genomic value prediction for quantitative traits under the epistatic model
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Published in |
BMC Genomic Data, January 2011
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DOI | 10.1186/1471-2156-12-15 |
Pubmed ID | |
Authors |
Zhiqiu Hu, Yongguang Li, Xiaohui Song, Yingpeng Han, Xiaodong Cai, Shizhong Xu, Wenbin Li |
Abstract |
Most quantitative traits are controlled by multiple quantitative trait loci (QTL). The contribution of each locus may be negligible but the collective contribution of all loci is usually significant. Genome selection that uses markers of the entire genome to predict the genomic values of individual plants or animals can be more efficient than selection on phenotypic values and pedigree information alone for genetic improvement. When a quantitative trait is contributed by epistatic effects, using all markers (main effects) and marker pairs (epistatic effects) to predict the genomic values of plants can achieve the maximum efficiency for genetic improvement. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United States | 2 | 2% |
Brazil | 2 | 2% |
Argentina | 1 | 1% |
France | 1 | 1% |
Unknown | 78 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 21 | 25% |
Researcher | 20 | 24% |
Student > Doctoral Student | 6 | 7% |
Professor | 6 | 7% |
Other | 5 | 6% |
Other | 14 | 17% |
Unknown | 12 | 14% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 55 | 65% |
Biochemistry, Genetics and Molecular Biology | 4 | 5% |
Mathematics | 2 | 2% |
Environmental Science | 2 | 2% |
Computer Science | 2 | 2% |
Other | 3 | 4% |
Unknown | 16 | 19% |