Quality assessment of maize assembled genomic islands (MAGIs) and large-scale experimental verification of predicted genes.

Proc Natl Acad Sci U S A

Interdepartmental Genetics Graduate Program, L. H. Baker Center for Bioinformatics and Biological Statistics, Department of Genetics, Development, and Cell Biology, Iowa State University, Ames, IA 50011, USA.

Published: August 2005

Recent sequencing efforts have targeted the gene-rich regions of the maize (Zea mays L.) genome. We report the release of an improved assembly of maize assembled genomic islands (MAGIs). The 114,173 resulting contigs have been subjected to computational and physical quality assessments. Comparisons to the sequences of maize bacterial artificial chromosomes suggest that at least 97% (160 of 165) of MAGIs are correctly assembled. Because the rates at which junction-testing PCR primers for genomic survey sequences (90-92%) amplify genomic DNA are not significantly different from those of control primers ( approximately 91%), we conclude that a very high percentage of genic MAGIs accurately reflect the structure of the maize genome. EST alignments, ab initio gene prediction, and sequence similarity searches of the MAGIs are available at the Iowa State University MAGI web site. This assembly contains 46,688 ab initio predicted genes. The expression of almost half (628 of 1,369) of a sample of the predicted genes that lack expression evidence was validated by RT-PCR. Our analyses suggest that the maize genome contains between approximately 33,000 and approximately 54,000 expressed genes. Approximately 5% (32 of 628) of the maize transcripts discovered do not have detectable paralogs among maize ESTs or detectable homologs from other species in the GenBank NR nucleotide/protein database. Analyses therefore suggest that this assembly of the maize genome contains approximately 350 previously uncharacterized expressed genes. We hypothesize that these "orphans" evolved quickly during maize evolution and/or domestication.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1186025PMC
http://dx.doi.org/10.1073/pnas.0503394102DOI Listing

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