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去伪存真——一种利用异地基因库中植物遗传资源的策略。

Separating the wheat from the chaff - a strategy to utilize plant genetic resources from ex situ genebanks.

作者信息

Keilwagen Jens, Kilian Benjamin, Özkan Hakan, Babben Steve, Perovic Dragan, Mayer Klaus F X, Walther Alexander, Poskar C Hart, Ordon Frank, Eversole Kellye, Börner Andreas, Ganal Martin, Knüpffer Helmut, Graner Andreas, Friedel Swetlana

机构信息

1] Molecular Genetics, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466 Seeland OT Gatersleben, Germany [2] Institute for Biosafety in Plant Biotechnology, Julius Kühn-Institut (JKI) - Federal Research Centre for Cultivated Plants, D-06484 Quedlinburg, Germany.

1] Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466 Seeland OT Gatersleben, Germany [2].

出版信息

Sci Rep. 2014 Jun 10;4:5231. doi: 10.1038/srep05231.

Abstract

The need for higher yielding and better-adapted crop plants for feeding the world's rapidly growing population has raised the question of how to systematically utilize large genebank collections with their wide range of largely untouched genetic diversity. Phenotypic data that has been recorded for decades during various rounds of seed multiplication provides a rich source of information. Their usefulness has remained limited though, due to various biases induced by conservation management over time or changing environmental conditions. Here, we present a powerful procedure that permits an unbiased trait-based selection of plant samples based on such phenotypic data. Applying this technique to the wheat collection of one of the largest genebanks worldwide, we identified groups of plant samples displaying contrasting phenotypes for selected traits. As a proof of concept for our discovery pipeline, we resequenced the entire major but conserved flowering time locus Ppd-D1 in just a few such selected wheat samples - and nearly doubled the number of hitherto known alleles.

摘要

为满足全球迅速增长的人口对高产且适应性更强的作物的需求,人们提出了如何系统利用大型基因库中大量尚未开发的广泛遗传多样性的问题。在多轮种子繁殖过程中记录了数十年的表型数据提供了丰富的信息来源。然而,由于长期的保存管理或不断变化的环境条件所导致的各种偏差,这些数据的有用性仍然有限。在此,我们提出了一种强大的方法,该方法允许基于此类表型数据对植物样本进行无偏差的基于性状的选择。将该技术应用于全球最大的基因库之一的小麦收集样本,我们鉴定出了在选定性状上表现出对比表型的植物样本组。作为我们发现流程的概念验证,我们仅对少数此类选定的小麦样本重新测序了整个主要但保守的开花时间基因座Ppd-D1,迄今已知的等位基因数量几乎增加了一倍。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/127f/4050481/de63edf6a688/srep05231-f1.jpg

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