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      Development of a core collection for ramie by heuristic search based on SSR markers

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          There are more than 2000 ramie germplasms in the National Ramie Germplasm Nursery affiliated with the Institute of Bast Fiber Crops, Chinese Academy of Agricultural Science, China. As it is difficult to perform effective conservation, management, evaluation, and utilization of redundant genetic resources, it is necessary to construct a core collection by using molecular markers. In this study, a core collection of ramie consisting of 22 germplasms was constructed from 108 accessions by heuristic search based on 21 Simple Sequence Repeat (SSR) marker combinations. The results showed that there is a poor relationship between the core collection and the geographic distribution. The number of amplification bands for the core collection was the same as that for the entire collection. Shannon's index for three of the SSR primers (14%) and Nei's index for nine of the SSR primers (19%) were lower in the core collection than in the entire collection. The true core collection had wider genetic diversity compared with the random core collection. Collectively, the core collection constructed in this study is reliable and represents the genetic diversity of all the 108 accessions.

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          Most cited references 134

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          PowerCore: a program applying the advanced M strategy with a heuristic search for establishing core sets.

          Core sets are necessary to ensure that access to useful alleles or characteristics retained in genebanks is guaranteed. We have successfully developed a computational tool named 'PowerCore' that aims to support the development of core sets by reducing the redundancy of useful alleles and thus enhancing their richness. The program, using a new approach completely different from any other previous methodologies, selects entries of core sets by the advanced M (maximization) strategy implemented through a modified heuristic algorithm. The developed core set has been validated to retain all characteristics for qualitative traits and all classes for quantitative ones. PowerCore effectively selected the accessions with higher diversity representing the entire coverage of variables and gave a 100% reproducible list of entries whenever repeated. PowerCore software uses the .NET Framework Version 1.1 environment which is freely available for the MS Windows platform. The files can be downloaded from The distribution of the package includes executable programs, sample data and a user manual.
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            A worldwide bread wheat core collection arrayed in a 384-well plate.

            Bread wheat (Triticum aestivum), one of the world's major crops, is genetically very diverse. In order to select a representative sample of the worldwide wheat diversity, 3,942 accessions originating from 73 countries were analysed with a set of 38 genomic simple sequence repeat (SSR) markers. The number of alleles at each locus ranged from 7 to 45 with an average of 23.9 alleles per locus. The 908 alleles detected were used together with passport data to select increasingly large sub-samples that maximised both the number of observed alleles at SSR loci and the number of geographical origins. A final core of 372 accessions (372CC) was selected with this M strategy. All the different geographical areas and more than 98% of the allelic diversity at the 38 polymorphic loci were represented in this core. The method used to build the core was validated, by using a second set of independent markers [44 expressed sequence tag (EST)-SSR markers] on a larger sample of 744 accessions: 96.74% of the alleles observed at these loci had already been captured in the 372CC. So maximizing the diversity with a first set of markers also maximised the diversity at a second independent set of locus. To relate the genetic structure of wheat germplasm to its geographical origins, the two sets of markers were used to compute a dissimilarity matrix between geographical groups. Current worldwide wheat diversity is clearly divided according to wheat's European and Asian origins, whereas the diversity within each geographical group might be the result of the combined effects of adaptation of an initial germplasm to different environmental conditions and specific breeding practices. Seeds from each accession of the 372CC were multiplied and are now available to the scientific community. The genomic DNA of the 372CC, which can be entirely contained in a 384-deep-well storage plate, will be a useful tool for future studies of wheat genetic diversity.
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              Microsatellite marker-mediated analysis of the EMBRAPA Rice Core Collection genetic diversity.

              The objectives of this study were to determine the genetic structure of 242 accessions from the EMBRAPA Rice Core Collection (ERiCC), to create a mini-core collection and to develop a multiplex panel of fluorescent labeled simple sequence repeats (SSRs). Eighty-six SSRs were used to identify 1,066 alleles, with an average number of 12.4 alleles/locus and average polymorphism information content (PIC)/locus of 0.75. A model-based clustering method recognized the structure of the accessions on two levels, according to their cultivation system and origin. The most divergent subgroup identified was the worldwide lowland accessions, with the highest values for gene diversity (0.75), average Rogers distance modified by Wright (0.80), average number of alleles/locus (11.7) and private alleles (132). A mini-core was assembled with the most divergent 24 lowland and upland accessions. This mini-core displayed an average distance of 0.86, an average number of alleles/locus of 8.4 and an average PIC/locus of 0.8. From the 86 SSRs, 24 were selected to compose six multiplex panels in order to optimize the process of rice genotyping. This set of markers distinguished all 242 accessions, and showed an average PIC of 0.80 and an average number of alleles/locus of 15.4, higher than the entire set of 86 SSRs. Since the heterogeneity found in lines and cultivars of ERiCC was higher than expected, it is necessary to analyze pooled DNA samples to get a better estimate of genetic variability. The SSR characterization of ERiCC clearly indicates that there is high genetic variability in rice accessions stored in genebanks worldwide which can be promptly explored by rice pre-breeding programs.

                Author and article information

                Biotechnol Biotechnol Equip
                Biotechnol. Biotechnol. Equip
                Biotechnology, Biotechnological Equipment
                Taylor & Francis
                3 September 2014
                3 November 2014
                : 28
                : 5
                : 798-804
                [ a ]Chinese Academy of Agricultural Sciences, Institute of Bast Fiber Crops, Key Laboratory of Stem-fiber Biomass and Engineering Microbiology (Ministry of Agriculture) , Changsha, Hunan, P. R. China
                [ b ]Department of Basic Medicine, Yiyang Medical School, Yiyang, Hunan, P. R. China
                [ c ]Department of Plant Nutrition, China Agricultural University, Beijing, P. R. China
                Author notes
                [* ]Corresponding author. Email: chenjianhua@
                © 2014 The Author(s). Published by Taylor & Francis.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The moral rights of the named author(s) have been asserted.

                Page count
                Figures: 0, Tables: 6, References: 40, Pages: 7
                This study was financially supported by the National Natural Science Foundation of China (Youth Program) [grant number 30900913]; Hunan Provincial Natural Science Foundation of China [grant number 13JJ4116]; Science and Technology Funds Program of CAAS (2009).
                Article; Agriculture and Environmental Biotechnology

                core collection, ramie, ssr


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