| dc.contributor.author | Chikara, Shireen | |
| dc.description.abstract | Iron deficiency results in iron deficiency chlorosis (IDC) in soybean grown in the
north central regions of the United States. Soybean plants display a variety of symptoms,
ranging from slight yellowing of the leaves to interveinal chlorosis, and sometimes IDC is
followed by stunted growth. In severe cases IDC may even lead to cell death. The
objective of this project was to employ a whole genome association mapping approach to
uncover the genomic regions associated with the iron deficiency trait in soybean. Golden
gate assay technology was applied to expedite the screening of 1,536 single nucleotide
polymorphisms in two different sets of soybean populations belonging to the year 2005 and
2006. The two soybean populations were screened for IDC at multiple locations in
replicated field trials.
The experiment only considered marker loci with a minor allele frequency greater
than 0.1. Probability-probability plot helped in selecting the appropriate general linear
models, which controlled for only population structure, and mixed linear models, which
controlled for both the population structure and the ancestry. For the 2005 population, three
statistical approaches (PCA, PCA+K and PCA+K*) identified twelve marker/trait
associations, and for the 2006 population, five statistical models (Q, PCA, Q+K, Q+K * and
PCA+K*) resulted in the discovery of twenty-two such associations. Although none of the
markers significantly associated with JDC was common to both the populations under
study, similar regions of significance were observed between the two years. When the
phenotypic and the genotypic data of the two populations were combined, 10 markers were significantly (pFDR < 0.01) associated with the IDC trait using the PCA and PCA+K*
statistical models. Out of the 10 markers, six selected markers showed a significant
phenotypic mean difference for the tolerant and susceptible alleles. A detailed analysis
revealed that using a smaller set of combinations from these six markers can effectively
identify IDC tolerant genotypes. The next step would be to verify the reproducibility of the
selected set of marker combinations in another set of populations. | en_US |
| dc.publisher | North Dakota State University | en_US |
| dc.rights | NDSU policy 190.6.2 | en_US |
| dc.title | Genome-wide Scan for Loci Affecting Iron Deficieny Chlorosis in Soybean. | en_US |
| dc.type | Thesis | en_US |
| dc.date.accessioned | 2024-03-28T23:38:58Z | |
| dc.date.available | 2024-03-28T23:38:58Z | |
| dc.date.issued | 2010 | |
| dc.identifier.uri | https://hdl.handle.net/10365/33762 | |
| dc.subject.lcsh | Soybean -- Disease and pest resistance -- Genetic aspects. | en_US |
| dc.subject.lcsh | Chlorosis (Plants). | en_US |
| dc.subject.lcsh | Soybean -- Diseases and pests. | en_US |
| dc.rights.uri | https://www.ndsu.edu/fileadmin/policy/190.pdf | en_US |
| ndsu.degree | Master of Science (MS) | en_US |
| ndsu.college | Interdisciplinary Studies | en_US |
| ndsu.department | Genomics, Phenomics, and Bioinformatics | en_US |
| ndsu.program | Genomics and Bioinformatics | en_US |
| ndsu.advisor | McClean, Phillip E. | |
