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首页> 外文期刊>Journal of Bioinformatics and Computational Biology >AN OPTIMIZATION METHOD FOR THE IDENTIFICATION OF MINIMAL SETS OF DISCRIMINATING GENE MARKERS: APPLICATION TO CULTIVAR IDENTIFICATION IN WHEAT
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AN OPTIMIZATION METHOD FOR THE IDENTIFICATION OF MINIMAL SETS OF DISCRIMINATING GENE MARKERS: APPLICATION TO CULTIVAR IDENTIFICATION IN WHEAT

机译：识别基因标记最小集的一种优化方法：在小麦品种识别中的应用

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摘要

A potentially large number of molecular markers are available for identifying genotypes in various species. For wheat, cultivar identity is an important determinant for end-use segregation and for payment of end-point royalties and grower premiums. A number of dominant DNA markers, that give either a positive or negative response, have been developed previously for wheat cultivar identification. This paper gives a method for identifying minimal marker sets for a given cultivar group, for example those grown in a specific geographical zone. It is based on an integer linear programming formulation of the problem, and can find all minimal marker sets for the group if required. The paper then describes the production of two software packages, GGDS and GGIP, that incorporate this methodology. Various practical issues are also discussed. These packages enable the rapid selection of minimal marker sets for the efficient discrimination of any sample set where the marker responses of the samples are known. They are already being used by the Australian wheat industry.
机译：潜在的大量分子标记可用于鉴定各种物种的基因型。对于小麦而言，品种身份是最终用途隔离以及支付终端使用费和种植者溢价的重要决定因素。先前已经开发出许多给出阳性或阴性反应的显性DNA标记，用于小麦品种鉴定。本文提供了一种用于识别给定品种组（例如在特定地理区域内生长的品种）的最小标记集的方法。它基于问题的整数线性规划公式，并且可以根据需要找到该组的所有最小标记集。然后，本文描述了采用此方法的两个软件包GGDS和GGIP的制作。还讨论了各种实际问题。这些软件包可以快速选择最小的标记集，以有效地区分已知标记响应的任何样本集。它们已经被澳大利亚的小麦行业使用。

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