Genetic Resource Management in Core Collections
Summary
Core collections serve as representative subsets of larger germplasm repositories, enabling efficient conservation, evaluation and utilisation of genetic diversity. By selecting a minimal number of accessions that capture the maximum allelic variation, managers can streamline breeding programmes, reduce maintenance costs and accelerate trait discovery. Modern strategies integrate high‐throughput genotyping, advanced statistical frameworks and computational algorithms to ensure that selected cores maintain both rare alleles and broad genetic structure. Population structure analyses, distance‐based metrics and multi‐objective optimisation each play a role in defining cores tailored to specific goals, whether for association mapping, trait introgression or long‐term ex situ conservation. Recent advances have emphasised scalable methods capable of handling millions of markers, interactive software platforms for user‐driven selection and empirical validation through case studies in crops and fungi. Core collections thus underpin global efforts to safeguard agrobiodiversity, inform breeding decisions and respond rapidly to emerging challenges such as climate change, pest resistance and food security.
Research from Nature Portfolio
No recent Nature Portfolio content available.
Genetic Resource Management in Core Collections publication trend
The graph below shows the total number of articles in genetic resource management in core collections across all publications each year (not limited to Nature Index journals).
Technical terms
Germplasm: Genetic material of plants or microorganisms preserved for breeding and conservation.
Core collection: A strategically chosen subset of germplasm that maximises genetic diversity while minimising redundancy.
Single nucleotide polymorphism (SNP): A genomic position at which a single nucleotide varies among individuals, used as a marker for diversity and association studies.
Population structure: The organisation of genetic variation into subgroups, often revealed by clustering or principal component analyses.
Polymorphism Information Content (PIC): A measure of marker informativeness based on allele frequency, reflecting its utility in diversity studies.
References
- Genetic Diversity Analysis and Core Germplasm Collection Construction of Radish Cultivars Based on Structure Variation Markers. International Journal of Molecular Sciences (2023).
- Establishment and application of a SNP molecular identification system in Grifola frondosa. Frontiers in Microbiology (2024).
- ShinyCore: An R/Shiny program for establishing core collection based on single nucleotide polymorphism data. Plant Methods (2023).
- GenoCore: A simple and fast algorithm for core subset selection from large genotype datasets. PLOS ONE (2017).
- Core Hunter 3: flexible core subset selection. BMC Bioinformatics (2018).
About these summaries
This Nature Research Intelligence Topic summary is created with the cited references and a large language model. We take care to ground generated text with facts, and have systems in place to gain human feedback on the overall quality of the process in line with our AI principles. We strive to create accurate and useful summaries for people unfamiliar with the research topic and that supports this goal. These pages are a beta release and will be updated as we learn how best to help people gain value from a research topic summary.
Turn complex research questions into confident strategic decisions
When you're under pressure to set direction, justify investment, or understand your competitive position, you need more than raw data — you need trusted insights you can act on.
Benchmark your performance against global peers using robust, methodologically sound analysis.
Combine quantitative metrics with qualitative expert insight to uncover strengths, gaps and emerging opportunities.
Gain tailored, decision-ready recommendations aligned to your strategic priorities.
Talk to us to learn more about our data dashboards and bespoke strategy reports.
Grow research skills, confidence and careers with training built for every stage of the research lifecycle.
Developed with Nature Portfolio journal Editors and internationally renowned experts. Discover three ways to learn:
Self-paced, online courses in convenient bite-sized units, covering key skills across scientific writing, publishing, grant writing, data analysis, and more.
Expert trainer-led workshops with hands-on exercises and real-time feedback across core research skills, delivered via interactive group sessions.
Editor-led workshops combining core principles in writing and publishing, personalised 1:1 feedback from Nature Portfolio Editors and hands-on exercises.
Explore course catalogues and workshop agendas, enquire about the options or request institutional pricing.