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Rice transposable elements: a survey of 73,000 sequence-tagged-connectors - 2001-1988 - News
2001-1988 : Rice transposable elements: a survey of 73,000 sequence-tagged-connectors
Posted by webmaster on 2000/7/31 23:50:00 ( 925 reads )

Mao L, Wood TC, Yu Y, Budiman MA, Tomkins J, Woo S, Sasinowski M, Presting G, Frisch D, Goff S, Dean RA, Wing RA.

Genome Res. 2000 Jul;10(7):982-90.

Clemson University Genomics Institute, South Carolina 29634 USA.

Abstract
As part of an international effort to sequence the rice genome, the Clemson University Genomics Institute is developing a sequence-tagged-connector (STC) framework. This framework includes the generation of deep-coverage BAC libraries from O. sativa ssp. japonica c.v. Nipponbare and the sequencing of both ends of the genomic DNA insert of the BAC clones. Here, we report a survey of the transposable elements (TE) in >73,000 STCs. A total of 6848 STCs were found homologous to regions of known TE sequences (E<10(-5)) by FASTX search of STCs against a set of 1358 TE protein sequences obtained from GenBank. Of these TE-containing STCs (TE-STCs), 88% (6027) are related to retroelements and the remaining are transposase homologs. Nearly all DNA transposons known previously in plants were present in the STCs, including maize Ac/Ds, En/Spm, Mutator, and mariner-like elements. In addition, 2746 STCs were found to contain regions homologous to known miniature inverted-repeat transposable elements (MITEs). The distribution of these MITEs in regions near genes was confirmed by EST comparisons to MITE-containing STCs, and our results showed that the association of MITEs with known EST transcripts varies by MITE type. Unlike the biased distribution of retroelements in maize, we found no evidence for the presence of gene islands when we correlated TE-STCs with a physical map of the CUGI BAC library. These analyses of TEs in nearly 50 Mb of rice genomic DNA provide an interesting and informative preview of the rice genome.

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Attached Files: 982.full.pdf
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A portion of AGI's material is based upon work supported by the National Science Foundation under Grant Number 102620.