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Published on: January 3, 2025
Pangenomics for Agricultural Breeding: Construction Strategies, Evidence Integration, and Translational Constraints
Jinpeng Shi1, Ying Lu1, Zhengmei Sheng1
1Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China.
Pangenomics advances genetic diversity analysis in agriculture by integrating structural variants and non-reference sequences. This review compares methods for building pangenomes, highlighting their utility and limitations for breeding applications.
Area of Science:
- Genomics
- Bioinformatics
- Agricultural Science
Background:
- Pangenomics offers a comprehensive view of genetic diversity beyond single reference genomes.
- It is crucial for understanding structural variants (SVs), copy number variations (CNVs), and presence/absence variations (PAVs) in agricultural species.
- These variations influence domestication, adaptation, and breeding traits.
Purpose of the Study:
- To review advancements in pangenomics for livestock and crops.
- To compare different technical approaches for pangenome construction and analysis.
- To discuss the application and limitations of pangenome resources in breeding.
Main Methods:
- Summarizing progress in long-read sequencing, telomere-to-telomere (T2T) assembly, and graph-based genome analysis.
- Comparing variant integration, reference-guided iterative graph construction, and reference-free graph construction methods.
- Evaluating methods based on accuracy, scalability, reference bias, and computational demand.
Main Results:
- Pangenome resources facilitate discovery of hidden variants, interpretation of quantitative trait loci (QTL) and genome-wide association studies (GWAS), and environmental adaptation analysis.
- Different pangenome construction strategies yield varying results in terms of accuracy, consistency, and computational requirements.
- Unresolved limitations include graph complexity, pipeline-dependent variant calls, and challenges in functional annotation and cross-study comparability.
Conclusions:
- Pangenome studies are valuable but non-equivalent, with resource-building, method development, and trait-focused studies offering different insights.
- Inconsistencies across studies often reflect differences in sampling, genome complexity, and methodology rather than simple disagreements.
- Further development is needed to overcome current limitations and fully leverage pangenomics for agricultural breeding.
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