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Large-scale analysis of transcriptional cis-regulatory modules reveals both common features and distinct subclasses

Li, Long, Zhu, Qianqian, He, Xin, Sinha, Saurabh, Halfon, Marc S·2007·Genome Biology

Abstract

Background: Transcriptional cis -regulatory modules (for example, enhancers) play a critical role in regulating gene expression. While many individual regulatory elements have been characterized, they have never been analyzed as a class. Results: We have performed the first such large-scale study of cis -regulatory modules in order to determine whether they have common properties that might aid in their identification and contribute to our understanding of the mechanisms by which they function. A total of 280 individual, experimentally verified cis -regulatory modules from Drosophila were analyzed for a range of sequence-level and functional properties. We report here that regulatory modules do indeed share common properties, among them an elevated GC content, an increased level of interspecific sequence conservation, and a tendency to be transcribed into RNA. However, we find that dense clustering of transcription factor binding sites, especially homotypic clustering, which is commonly believed to be a general characteristic of regulatory modules, is rather a feature that belongs chiefly to a specific subclass. This has important implications for current computational approaches, many of which are biased toward this subset. We explore two new strategies to assess binding site clustering and gauge their performances with respect to their ability to detect all 280 modules and various functionally coherent subsets. Conclusion: Our findings demonstrate that cis -regulatory modules share common features that help to define them as a class and that may lead to new insights into mechanisms of gene regulation. However, these properties alone may not be sufficient to reliably distinguish regulatory from non-regulatory sequences. We also demonstrate that there are distinct subclasses of cis -regulatory modules that are more amenable to in silico detection than others and that these differences must be taken into account when attempting genome-wide regulatory element discovery.

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Crossref · 10.1186/gb-2007-8-6-r101

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Figures

Figure 1 GC content of the REDfly analysis CRMs as well as coding, intronic, and intergenic sequences.
Figure 1 GC content of the REDfly analysis CRMs as well as coding, intronic, and intergenic sequences.CC BY · PubMed Central
Figure 2 Correlations between CRM length and GC content (column 1) and degree of sequence conservation with seven Drosophila species. Values given are the Spearman correlation coefficients. Black bars indicate CRM sequences, gray bars indicate size-matched randomly drawn non-coding sequence. Asterisks signify that the correlation is statistically significant (Bonferroni-adjusted P < 0.05). Dsim, D. simulans; Dyak, D. yakuba; Dere, D. erecta; Dana, D. ananassae; Dpse, D. pseudoobscura; Dvir, D. virilis; Dmoj, D. mojavensis.
Figure 2 Correlations between CRM length and GC content (column 1) and degree of sequence conservation with seven Drosophila species. Values given are the Spearman correlation coefficients. Black bars indicate CRM sequences, gray bars indicate size-matched randomly drawn non-coding sequence. Asterisks signify that the correlation is statistically significant (Bonferroni-adjusted P < 0.05). Dsim, D. simulans; Dyak, D. yakuba; Dere, D. erecta; Dana, D. ananassae; Dpse, D. pseudoobscura; Dvir, D. virilis; Dmoj, D. mojavensis.CC BY · PubMed Central
Figure 3 Sequence conservation properties of the REDfly analysis CRMs. (a) Average fraction of aligned bases between D. melanogaster and each of the other species for the CRMs (blue), CRM flanking sequences (green; ± 1 kb to each side of the CRM; see text), coding regions (orange; based on 2,000 genes; see Materials and methods), and size-matched randomly selected non-coding sequences (red). Dashed lines indicate the 20% and 80% percentile values for the CRMs and random sequences. Also indicated are the 'differences' in conservation between CRMs and random non-coding sequences (black) and between coding sequences and random non-coding sequences (pink). Species abbreviations are as given in the legend to Figure 3. A similar graph showing the fraction of aligned 'identical' bases is given in Figure S3-1 in Additional data file 3. (b) Histogram of the conservation fraction for CRMs (black bars) and random non-coding sequences (white bars) for D. melanogaster aligned with D. pseudoobscura. Histograms for the other species are shown in Figure S3-2 in Additional data file 3. (c) Median conserved block density for each of the species aligned to D. melanogaster. Blocks are defined as ungapped regions of seven or more nucleotides with ≥75% identity. Shown are block densities for CRMs (blue), CRM flanking regions (green), and size-matched randomly selected non-coding sequences (red). (d) Histogram of the distribution of conserved block density for CRMs (black bars) and random non-coding sequences (white bars) for D. melanogaster aligned with D. pseudoobscura. Histograms for the other species are shown in Figure S3-3 in Additional data file 3.
Figure 3 Sequence conservation properties of the REDfly analysis CRMs. (a) Average fraction of aligned bases between D. melanogaster and each of the other species for the CRMs (blue), CRM flanking sequences (green; ± 1 kb to each side of the CRM; see text), coding regions (orange; based on 2,000 genes; see Materials and methods), and size-matched randomly selected non-coding sequences (red). Dashed lines indicate the 20% and 80% percentile values for the CRMs and random sequences. Also indicated are the 'differences' in conservation between CRMs and random non-coding sequences (black) and between coding sequences and random non-coding sequences (pink). Species abbreviations are as given in the legend to Figure 3. A similar graph showing the fraction of aligned 'identical' bases is given in Figure S3-1 in Additional data file 3. (b) Histogram of the conservation fraction for CRMs (black bars) and random non-coding sequences (white bars) for D. melanogaster aligned with D. pseudoobscura. Histograms for the other species are shown in Figure S3-2 in Additional data file 3. (c) Median conserved block density for each of the species aligned to D. melanogaster. Blocks are defined as ungapped regions of seven or more nucleotides with ≥75% identity. Shown are block densities for CRMs (blue), CRM flanking regions (green), and size-matched randomly selected non-coding sequences (red). (d) Histogram of the distribution of conserved block density for CRMs (black bars) and random non-coding sequences (white bars) for D. melanogaster aligned with D. pseudoobscura. Histograms for the other species are shown in Figure S3-3 in Additional data file 3.CC BY · PubMed Central
Figure 4 Results from the FTT-Z test. Boxplots indicate the median (heavy bar) and first and third quartiles of the data (boxed area). Details are provided in the text.
Figure 4 Results from the FTT-Z test. Boxplots indicate the median (heavy bar) and first and third quartiles of the data (boxed area). Details are provided in the text.CC BY · PubMed Central
Figure 5 YMF scores for the REDfly analysis CRMs. (a) Histograms of percentage of CRMs for given P value ranges (YMF scores). The histogram for all 280 REDfly analysis CRMs is shown in blue ('CRMs'), for randomly selected non-coding sequences in green ('Random'), and for the random expectation ('Uniform') in red. (b) Cumulative histograms of YMF scores for tissue- and stage-specific CRM subsets. The entire REDfly analysis set is shown in blue and the expected uniform distribution in red. Solid green lines indicate the blastoderm CRMs, while dashed green lines represent the non-blastoderm CRMs; orange solid and dashed lines show the embryo and non-embryo CRM subsets, respectively. Note that all subsets show significant deviation from the expected uniform distribution. (c) Specificity/sensitivity curves for CRM prediction using YMF. Three sets of curves are shown, representing three different assumptions as to the number of CRMs present in the randomly selected background sequences: 25% CRMs (red), 50% CRMs (blue), and 75% CRMs (green). Solid lines indicate curves for the entire 280 REDfly analysis CRMs, while dashed lines show the blastoderm CRM subset. The black dashed line represents the curve for randomly selected sequences, shown for 50% background CRMs only. For each category, the random expectation is equal to the assumed number of CRMs in the background.
Figure 5 YMF scores for the REDfly analysis CRMs. (a) Histograms of percentage of CRMs for given P value ranges (YMF scores). The histogram for all 280 REDfly analysis CRMs is shown in blue ('CRMs'), for randomly selected non-coding sequences in green ('Random'), and for the random expectation ('Uniform') in red. (b) Cumulative histograms of YMF scores for tissue- and stage-specific CRM subsets. The entire REDfly analysis set is shown in blue and the expected uniform distribution in red. Solid green lines indicate the blastoderm CRMs, while dashed green lines represent the non-blastoderm CRMs; orange solid and dashed lines show the embryo and non-embryo CRM subsets, respectively. Note that all subsets show significant deviation from the expected uniform distribution. (c) Specificity/sensitivity curves for CRM prediction using YMF. Three sets of curves are shown, representing three different assumptions as to the number of CRMs present in the randomly selected background sequences: 25% CRMs (red), 50% CRMs (blue), and 75% CRMs (green). Solid lines indicate curves for the entire 280 REDfly analysis CRMs, while dashed lines show the blastoderm CRM subset. The black dashed line represents the curve for randomly selected sequences, shown for 50% background CRMs only. For each category, the random expectation is equal to the assumed number of CRMs in the background.CC BY · PubMed Central

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Metadata

Authors
Li, L., Zhu, Q., He, X., Sinha, S., & Halfon, M. S.
Venue
Genome Biology
Published
2007-06-05
Volume
8
Issue
6
ISSN
1474-760X
Cited by
69
References
99
Language
en
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Li, L., Zhu, Q., He, X., Sinha, S., & Halfon, M. S. (2007). Large-scale analysis of transcriptional cis-regulatory modules reveals both common features and distinct subclasses. Genome Biology. https://doi.org/10.1186/gb-2007-8-6-r101

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