کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4499590 | 1319037 | 2006 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Genome-wide analysis of mammalian DNA segment fusion/fission
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
علوم کشاورزی و بیولوژیک (عمومی)
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چکیده انگلیسی
As a powerful tool for gene function prediction, gene fusion has been widely studied in prokaryotes and certain groups of eukaryotes, but it has been little applied in studies of mammalian genomes. With the first fully sequenced mammalian genomes (human, mouse, rat) now available, we defined and collected a set of fusion/fission event-linked segments (FFLS) based on structured organized genomic alignment. The statistics of the sequence features highlighted the FFLSs against their random context. We found that there are three groups of FFLSs with different component pairs (i.e. gene-gene, gene-noncoding and noncoding-noncoding) in all three mammalian genomes. The proteins encoded by the components of FFLSs in the first group shown a strong tendency to interact with each other. The segmental components in the last two groups which did not contain any protein-coding genes, were found not only to be transcribed to some level, but also more conserved than the random background. Thus, these segments are possibly carrying certain biologically functional elements. We propose that FFLS may be a potential tool for prediction and analysis of function and functional interaction of genetic elements, including both genes and noncoding elements, in mammalian genomes. The full list of the FFLSs in the genomes of the three mammals is available as supporting information at doi:10.1016/j.jtbi.2005.09.016.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Theoretical Biology - Volume 240, Issue 2, 21 May 2006, Pages 200-208
Journal: Journal of Theoretical Biology - Volume 240, Issue 2, 21 May 2006, Pages 200-208
نویسندگان
Zhihua Zhang, Hong Sun, Yong Zhang, Yi Zhao, Baochen Shi, Shiwei Sun, Hongchao Lu, Dongbo Bu, Lunjiang Ling, Runsheng Chen,