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Establishment of Chinese soybean Glycine max core collections with agronomic traits and SSR markers
Authors:Lixia Wang  Yuan Guan  Rongxia Guan  Yinghui Li  Yansong Ma  Zhimin Dong  Xian Liu  Haiyan Zhang  Yueqiang Zhang  Zhangxiong Liu  Ruzhen Chang  Haiming Xu  Linhai Li  Fanyun Lin  Weijiang Luan  Zhe Yan  Xuecheng Ning  Li Zhu  Yanhua Cui  Rihua Piao  Yan Liu  Pengying Chen  Lijuan Qiu
Institution:(1) Institute of Crop Science, National Key Facility of Crop Gene Resource and Genetic Improvement, Key Lab of Crop Germplasm & Biotechnology (MOA), Chinese Academy of Agricultural Sciences, 100081 Beijing, China;(2) Xinjiang Agricultural University, 830046 Urumqi, China;(3) Department of agronomy, Jilin Agricultural University, 130118 Changchun, China;(4) Department of Agronomy, Liaoning Agricultural University, 110161 Shenyang, China;(5) Northeast Agricultural University, 150030 Haerbin, China;(6) Department of Agronomy, College of Agriculture and Biotechnology, Zhejiang University, 310029 Hangzhou, China;(7) Northwest Science and Technology, University of Agriculture & Forestry, Yangling, 712100 Shannxi, China;(8) College of Agriculture Northwest Sci-Tech, University Agriculture and Forestry, Shanxi Yanglin, 712100 Shannxi, China;(9) Department of Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, AR, 72701, U.S.A.
Abstract:It is very important to efficiently study and use genetic diversity resources in crop breeding and sustainable agriculture. In this study, different sampling methods and sample sizes were compared in order to optimize the strategies for building a rationally sized core collection of Chinese soybean (Glycine max). The diversity in the core collection captured more than 70% of that in the pre-core collection, no matter what sampling methods were used, at a sampling proportion of 1%. Core collections established with both simple sequence repeat (SSR) marker data and agronomic traits were more representative than those chosen on an independent basis. An optimal sampling method for a soybean core collection was determined, in which strategy ‘S’ (allocating accessions to clusters according to the proportion of square root of the original sample size within each ecotype) was used based on SSR and agronomic data. Curve estimation was used to estimate the allelic richness of the entire Chinese soybean germplasm and a minimum sample size for a core collection, on which a sampling proportion of about 2% was determined to be optimal for a core collection. Further analysis on the core collection with fourteen agronomic traits and allelic constitution at 60 SSR loci suggested that it highly represented the entire collections both on genetic structure and diversity distribution. This core collection would provide an effective platform in proper exploitation of soybean germplasm resources for the study of complex traits and discovering important novel traits for crop genetic development.
Keywords:Glycine max                Germplasm  Breeding  Landrace
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