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Theor Appl Genet. 2012 Aug;125(3):517-30. doi: 10.1007/s00122-012-1850-6. Epub 2012 Mar 28.

Population structure and linkage disequilibrium in Lupinus albus L. germplasm and its implication for association mapping.

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Department of Plant Sciences, North Dakota State University, Fargo, ND 58108, USA.


White lupin (Lupinus albus L.) has been around since 300 B.C. and is recognized for its ability to grow on poor soils and application as green manure in addition to seed harvest. The seed has very high levels of protein (33-47 %) and oil (6-13 %). It also has many secondary metabolites that are potentially of nutraceutical value to animals and humans. Despite such a great potential, lupins role in modern agriculture began only in the twentieth century. Although a large collection of Lupinus germplasm accessions is available worldwide, rarely have they been genetically characterized. Additionally, scarce genomic resources in terms of recombinant populations and genome information have been generated for L. albus. With the advancement in association mapping methods, the natural populations have the potential to replace the recombinant populations in gene mapping and marker-trait associations. Therefore, we studied the genetic similarity, population structure and marker-trait association in a USDA germplasm collection for their current and future application in this crop improvement. A total of 122 PI (Plant Inventory) lines were screened with 18 AFLP primer pairs that generated 2,277 fragments. A subset of 892 polymorphic markers with MAF >0.05 (minor allele frequency) were used for association mapping. The cluster analysis failed to group accessions on the basis of their passport information, and a weak structure and low linkage disequilibrium (LD) were observed indicating the usefulness of the collection for association mapping. Moreover, we were also able to identify two markers (a p value of 1.53 × 10(-4) and 2.3 × 10(-4)) that explained 22.69 and 20.5 % of seed weight variation determined using R (LR) (2) . The implications of lack of geographic clustering, population structure, low LD and the ability of AFLP to map seed weight trait using association mapping and the usefulness of the PI collections in breeding programs are discussed.

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