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

Muhammad Javed Iqbal, Sujan Mamidi, Rubina Ahsan, Shahryar F. Kianian, Clarice J. Coyne, Anwar A. Hamama, Satya S. Narina, Harbans L. Bhardwaj

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

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 RLR2. 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.

Original languageEnglish (US)
Pages (from-to)517-530
Number of pages14
JournalTheoretical and Applied Genetics
Volume125
Issue number3
DOIs
StatePublished - Aug 2012

Bibliographical note

Funding Information:
This project was supported by USDA-NIFA-1890 Institutions Capacity Building Grants Program funds allocated to Virginia State University (H. L. Bhardwaj as PI/PD). The AFLP lab work was done at Institute for Advanced Learning and Research, Danville, VA by MJI and RA. Contribution of Virginia State University, Agricultural Research Station Journal Article Series Number 284. The use of any trade names or vendors does not imply approval to the exclusion of other products or vendors that may also be suitable.

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