Using landscape genomics to infer genomic regions involved in environmental adaptation of soybean genebank accessions

dc.contributor.authorHaupt, Max
dc.contributor.authorSchmid, Karl
dc.date.accessioned2025-12-08T12:04:22Z
dc.date.available2025-12-08T12:04:22Z
dc.date.issued2025
dc.date.updated2025-11-04T13:58:13Z
dc.description.abstractBackground: 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.sponsorshipOpen Access funding enabled and organized by Projekt DEAL.
dc.description.sponsorshipUniversität Hohenheim (3153)
dc.identifier.urihttps://doi.org/10.1186/s12870-025-07202-5
dc.identifier.urihttps://hohpublica.uni-hohenheim.de/handle/123456789/18304
dc.language.isoeng
dc.rights.licensecc_by
dc.subjectGlycine max
dc.subjectEnvironmental association mapping
dc.subjectLocal adaptation
dc.subjectLandscape genomics
dc.subjectPopulation structure
dc.subjectGenetic differentiation
dc.subjectGenetic resources
dc.subjectGenebank accessions
dc.subject.ddc630
dc.titleUsing landscape genomics to infer genomic regions involved in environmental adaptation of soybean genebank accessionsen
dc.type.diniArticle
dcterms.bibliographicCitationBMC plant biology, 25 (2025), 1175. https://doi.org/10.1186/s12870-025-07202-5. ISSN: 1471-2229 London : BioMed Central
dcterms.bibliographicCitation.articlenumber1175
dcterms.bibliographicCitation.issn1471-2229
dcterms.bibliographicCitation.journaltitleBMC plant biology
dcterms.bibliographicCitation.originalpublishernameBioMed Central
dcterms.bibliographicCitation.originalpublisherplaceLondon
dcterms.bibliographicCitation.volume25
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.sdg2
local.subject.sdg9
local.subject.sdg13
local.title.fullUsing landscape genomics to infer genomic regions involved in environmental adaptation of soybean genebank accessions

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