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Core collections have proven to be a valuable asset in aiding management as well as enhancing access to crop diversity present in huge germplasm collections held in genebanks. Initially these were generated based on passport and phenotypic data using several randomised hierarchical sampling methods to capture the largest amount of diversity in a limited number of accessions. With the availability of large-scale molecular marker data, especially SNPs generated by high-throughput techniques, there are several alternative optimization-based algorithms available that can leverage this information for core development. Here we illustrate the construction of core sets from such data using a few such software implementations such as PowerCore, Core Hunter 3, coreCollection and ShinyCore.

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Methods for the Construction of Core Collections Using SNP Markers

  • 实验方案

  • 发表日期：

    2026年

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  • J. Aravind,
  • Ankit Saroha,
  • Dhammaprakash Pandhari Wankhede

摘要

Core collections have proven to be a valuable asset in aiding management as well as enhancing access to crop diversity present in huge germplasm collections held in genebanks. Initially these were generated based on passport and phenotypic data using several randomised hierarchical sampling methods to capture the largest amount of diversity in a limited number of accessions. With the availability of large-scale molecular marker data, especially SNPs generated by high-throughput techniques, there are several alternative optimization-based algorithms available that can leverage this information for core development. Here we illustrate the construction of core sets from such data using a few such software implementations such as PowerCore, Core Hunter 3, coreCollection and ShinyCore.