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Title: GENIC AND REPETITIVE SEQUENCE SIMILARITIES BETWEEN MAIZE CHROMOSOMES

Author
item ODLAND, WADE - UNIVERSITY OF MINNESOTA
item YU, HAOYU - UNIVERSITY OF MINNESOTA
item Rines, Howard
item PHILLIPS, RONALD - UNIVERSITY OF MINNESOTA

Submitted to: Plant and Animal Genome VX Conference Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 10/10/2004
Publication Date: 1/15/2005
Citation: Odland, W., Yu, H., Rines, H.W., Phillips, R. 2005. Genic and repetitive sequence similarities between maize chromosomes [abstract]. Plant and Animal Genome XIII Abstracts. p. 168.

Interpretive Summary:

Technical Abstract: Genomic microarray analysis of the maize genome via oat-maize addition lines (oat lines with a single maize chromosome added) and maize-specific sequences reveal patterns in the chromosomal repetitive compositions. Approximately 85% of the maize genome is repetitive sequence. These repetitive sequences are dispersed throughout the genome, but data presented here show that individual elements are not equally distributed among chromosomes. Forty-two maize-specific probes were designed to 14 of the most abundant repetitive sequences. Microarray analysis, using a reference design, detected the relative abundance of these sequences in DNA from the oat-maize addition lines, each with a different one of the ten maize chromosomes. Two-way analysis of variance (ANOVA) shows significance (p < 0.0001) for both the chromosomal and probe variables. K-means clustering on the relative differences of select repetitive sequences reveals similarities between maize chromosomes. Using the theories of maize as an ancient allo-tetraploid and a modified version of the natural karyotype chromosomal arrangement, a model has been constructed that explains how these chromosomal repetitive compositions evolved during maize's polyploidy state. This model of the maize genome structure has strong implications for detecting differences between sets of identified macro-sytenic regions within the modern maize genome. This material is based upon work supported by the National Science Foundation under Grant No. 0110134.