Using landscape genomics to infer genomic regions involved in environmental adaptation of soybean genebank accessions
| dc.contributor.author | Haupt, Max | |
| dc.contributor.author | Schmid, Karl | |
| dc.date.accessioned | 2025-12-08T12:04:22Z | |
| dc.date.available | 2025-12-08T12:04:22Z | |
| dc.date.issued | 2025 | |
| dc.date.updated | 2025-11-04T13:58:13Z | |
| dc.description.abstract | Background: Understanding how crops adapt to specific environmental conditions is becoming increasingly important in the face of accelerating climate change, but the genetics of local adaptation remains little understood for many crops. Landscape genomics can reveal patterns of genetic variation that indicate adaptive diversification during crop evolution and dispersal. Here, we examine genetic differentiation and association signatures with environmental gradients in soybean ( Glycine max ) germplasm groups from China that were inferred from the USDA Soybean Germplasm Collection ( N = 17, 019 accessions) based on population structure and passport information. Results: We recover genes previously known to be involved in soybean environmental adaptation and report numerous new candidate genes in adaptation signatures implicated by genomic resources such as the genome annotation and gene expression datasets to function in flowering regulation, photoperiodism and stress reaction cascades. Linkage disequilibrium network analysis suggested functional relationships between genomic regions with signatures of genetic differentiation, consistent with a polygenic nature of environmental adaptation. We tested whether haplotypes associated with environmental adaptation in China were present in 843 North American and 160 European soybean cultivars and found that haplotypes in major genes for early maturity have been selected during breeding, but also that a large number of haplotypes exhibiting putative adaptive variation for cold regions at high latitudes are underrepresented in modern cultivars. Conclusions: Our results demonstrate the value of landscape genomics analysis of genebank accessions studying crop environmental adaptation and to inform future research and breeding efforts for improved adaptation of soybean and other crops to future climates. | en |
| dc.description.sponsorship | Open Access funding enabled and organized by Projekt DEAL. | |
| dc.description.sponsorship | Universität Hohenheim (3153) | |
| dc.identifier.uri | https://doi.org/10.1186/s12870-025-07202-5 | |
| dc.identifier.uri | https://hohpublica.uni-hohenheim.de/handle/123456789/18304 | |
| dc.language.iso | eng | |
| dc.rights.license | cc_by | |
| dc.subject | Glycine max | |
| dc.subject | Environmental association mapping | |
| dc.subject | Local adaptation | |
| dc.subject | Landscape genomics | |
| dc.subject | Population structure | |
| dc.subject | Genetic differentiation | |
| dc.subject | Genetic resources | |
| dc.subject | Genebank accessions | |
| dc.subject.ddc | 630 | |
| dc.title | Using landscape genomics to infer genomic regions involved in environmental adaptation of soybean genebank accessions | en |
| dc.type.dini | Article | |
| dcterms.bibliographicCitation | BMC plant biology, 25 (2025), 1175. https://doi.org/10.1186/s12870-025-07202-5. ISSN: 1471-2229 London : BioMed Central | |
| dcterms.bibliographicCitation.articlenumber | 1175 | |
| dcterms.bibliographicCitation.issn | 1471-2229 | |
| dcterms.bibliographicCitation.journaltitle | BMC plant biology | |
| dcterms.bibliographicCitation.originalpublishername | BioMed Central | |
| dcterms.bibliographicCitation.originalpublisherplace | London | |
| dcterms.bibliographicCitation.volume | 25 | |
| local.export.bibtex | @article{Haupt2025, doi = {10.1186/s12870-025-07202-5}, author = {Haupt, Max and Schmid, Karl}, title = {Using landscape genomics to infer genomic regions involved in environmental adaptation of soybean genebank accessions}, journal = {BMC Plant Biology}, year = {2025}, volume = {25}, } | |
| local.subject.sdg | 2 | |
| local.subject.sdg | 9 | |
| local.subject.sdg | 13 | |
| local.title.full | Using landscape genomics to infer genomic regions involved in environmental adaptation of soybean genebank accessions |
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