TAILIEUCHUNG - Báo cáo sinh học: "Accuracy of breeding values of 'unrelated' individuals predicted by dense SNP genotyping"

Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học quốc tế đề tài: Accuracy of breeding values of 'unrelated' individuals predicted by dense SNP genotyping | Genetics Selection Evolution BioMed Central Research Accuracy of breeding values of unrelated individuals predicted by dense SNP genotyping Theo HE Meuwissen Address Department of Animal and Aquacultural Sciences Norwegian University of Life Sciences Box 1432 Ảs Norway Email Theo HE Meuwissen - Open Access Published II June 2009 Received 29 May 2009 Genetics Selection Evolution 2009 41 35 doi 1297-9686-41 -35 Accepted 11 June 2009 This article is available from http content 41 1 35 2009 Meuwissen licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract Background Recent developments in SNP discovery and high throughput genotyping technology have made the use of high-density SNP markers to predict breeding values feasible. This involves estimation of the SNP effects in a training data set and use of these estimates to evaluate the breeding values of other evaluation individuals. Simulation studies have shown that these predictions of breeding values can be accurate when training and evaluation individuals are closely related. However many general applications of genomic selection require the prediction of breeding values of unrelated individuals . individuals from the same population but not particularly closely related to the training individuals. Methods Accuracy of selection was investigated by computer simulation of small populations. Using scaling arguments the results were extended to different populations training data sets and genome sizes and different trait heritabilities. Results Prediction of breeding values of unrelated individuals required a substantially higher marker density and number of training records than when prediction individuals were offspring of .

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