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An Atlas of Drosophila Genes: Sequences and Molecular Features | UMIACS

Lubliner, S. Core promoter sequence in yeast is a major determinant of expression level. Genome Res. Patwardhan, R. High-resolution analysis of DNA regulatory elements by synthetic saturation mutagenesis. Arnold, C. Science , — Duttke, S.

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Perspectives on unidirectional versus divergent transcription. Cell 60 , — Andersson, R. Human gene promoters are intrinsically bidirectional. Gu, W. Nechaev, S.

Ni, T. A paired-end sequencing strategy to map the complex landscape of transcription initiation. Methods 7 , — Ohler, U. Computational analysis of core promoters in the Drosophila genome. Genome Biol. Saito, K. A regulatory circuit for piwi by the large Maf gene traffic jam in Drosophila. Sienski, G. Transcriptional silencing of transposons by Piwi and maelstrom and its impact on chromatin state and gene expression.

Defining the status of RNA polymerase at promoters. Cell Rep.

Background

Pfeiffer, B. Tools for neuroanatomy and neurogenetics in Drosophila. USA , — Adelman, K. Burke, T. Genes Dev. Lim, C. Zeitlinger, J. RNA polymerase stalling at developmental control genes in the Drosophila melanogaster embryo.


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Genomic regulatory blocks underlie extensive microsynteny conservation in insects. Ponjavic, J. Transcriptional and structural impact of TATA-initiation site spacing in mammalian core promoters. Tibshirani, R. Regression shrinkage and selection via the lasso. B 58 , — Widespread transcription at neuronal activity-regulated enhancers. De Santa, F. PLoS Biol. Lam, M. Enhancer RNAs and regulated transcriptional programs. An atlas of active enhancers across human cell types and tissues. Scruggs, B. Bidirectional transcription arises from two distinct hubs of transcription factor binding and active chromatin.


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  5. Cell 58 , — Hah, N. A rapid, extensive, and transient transcriptional response to estrogen signaling in breast cancer cells. Tomancak, P. Systematic determination of patterns of gene expression during Drosophila embryogenesis. Plot of relationship of individual gene length bp, log scale and codon usage bias ENC for D. A complication arises because under the translational accuracy model, as described above, the strength of selection is proportional to the product of expression level and gene length.

    An Atlas Of Drosophila Genes: Sequences And Molecular Features Hardcover

    If selection is, on the other hand, acting to reduce gene length, how is it possible to see such clear negative correlation in Drosophila and yeast genes between codon usage bias and gene length, but a positive correlation in E. We may have to consider two different sources of selection during translation: accuracy and simple length-dependent energy consumption.

    In the accuracy model, longer genes need to have stronger constraints on codon usage. From the aspect of energy consumption, longer genes are disadvantageous, especially for highly expressed genes. Quantitative data on gene expression levels are not readily available for eukaryotic genes. However, Eyre-Walker 15 compiled data on protein concentration for 46 E. On the other hand, gene length shows a significantly negative correlation with protein concentration A. Eyre-Walker, personal communication. Distribution of ENC for each length category of E. Only complete genes bp or longer were included.

    It is also possible that highly biased genes simply have shorter lengths than weakly biased genes for other functional reasons common to these genes or just by chance. For D. Genes between and bp in length have a bimodal for S. However, a difference in codon bias distribution between short and long genes was not observed in E. Although the mechanisms determining synonymous codon usage appear to be similar in E. This was attributed to the close proximity of adjacent genes in E.

    However, only very weak or no intragenic differences in codon usage bias have been detected in yeast genes A recent study for D. This trend is more pronounced in genes with no introns. Further examination on large data sets may be required. Considering, however, that eukaryotic genes have large intergenic regions and are segmented by introns, it seems that conflicting selection pressure at the start and end regions is not as effective in all eukaryotic genes as in E.

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    On the other hand, Akashi 12 found that codon bias varies among synonymous sites when comparing conserved and non-conserved amino acid positions among Drosophila species. Since conserved amino acids showed higher codon bias than non-conserved amino acids, selection for translational accuracy was postulated as a cause of codon bias. Although Hartl et al. We also found positive correlations when we used only ribosomal protein genes in the yeast and in D. Therefore, selective constraints on codon usage bias appear to be stronger in energetically costly longer genes to ensure efficient translation by minimizing misincorporation and maximizing translational accuracy.

    Selection also constrains gene length to reduce the expense of translation. Gene length is likely to be maximally optimized in the compact genome of E. What we observed in the three organisms is probably the consequence of these different types of selective constraints. Further detailed analyses on other genomes are evidently necessary.

    Depending on the intensity of the selection constraints, it may also be possible to see no correlation between gene length and codon usage bias in other eukaryotic genomes. It will be of great interest to see if the contrasted correlations between prokaryotes and eukaryotes can be seen in other organisms. We thank P. Sharp for his comments on an early version of the manuscript and D. Hartl for helpful discussions.

    Adam Eyre-Walker and anonymous reviewers gave us many critical comments which improved the manuscript significantly.

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