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Identification of thyroid hormone receptor binding sites in developing mouse cerebellum.

Gagne R, Green JR, Dong H, Wade MG, Yauk CL - BMC Genomics (2013)

Bottom Line: We found that while the occurrence of the TRE motif is strongly correlated with gene regulation by TH for some genes, other TH-regulated genes do not exhibit an increased density of TRE half-site motifs.Furthermore, we demonstrate that an increase in the rate of occurrence of the half-site motifs does not always indicate the specific location of the TRE within the promoter region.While we have identified 85 putative TREs within these regions, future work will study other mechanisms of action that may mediate the remaining observed TR-binding activity.

View Article: PubMed Central - HTML - PubMed

Affiliation: Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON K1A 0L2, Canada.

ABSTRACT

Background: Thyroid hormones play an essential role in early vertebrate development as well as other key processes. One of its modes of action is to bind to the thyroid hormone receptor (TR) which, in turn, binds to thyroid response elements (TREs) in promoter regions of target genes. The sequence motif for TREs remains largely undefined as does the precise chromosomal location of the TR binding sites. A chromatin immunoprecipitation on microarray (ChIP-chip) experiment was conducted using mouse cerebellum post natal day (PND) 4 and PND15 for the thyroid hormone receptor (TR) beta 1 to map its binding sites on over 5000 gene promoter regions. We have performed a detailed computational analysis of these data.

Results: By analysing a recent spike-in study, the optimal normalization and peak identification approaches were determined for our dataset. Application of these techniques led to the identification of 211 ChIP-chip peaks enriched for TR binding in cerebellum samples. ChIP-PCR validation of 25 peaks led to the identification of 16 true positive TREs. Following a detailed literature review to identify all known mouse TREs, a position weight matrix (PWM) was created representing the classic TRE sequence motif. Various classes of promoter regions were investigated for the presence of this PWM, including permuted sequences, randomly selected promoter sequences, and genes known to be regulated by TH. We found that while the occurrence of the TRE motif is strongly correlated with gene regulation by TH for some genes, other TH-regulated genes do not exhibit an increased density of TRE half-site motifs. Furthermore, we demonstrate that an increase in the rate of occurrence of the half-site motifs does not always indicate the specific location of the TRE within the promoter region. To account for the fact that TR often operates as a dimer, we introduce a novel dual-threshold PWM scanning approach for identifying TREs with a true positive rate of 0.73 and a false positive rate of 0.2. Application of this approach to ChIP-chip peak regions revealed the presence of 85 putative TREs suitable for further in vitro validation.

Conclusions: This study further elucidates TRβ gene regulation in mouse cerebellum, with 211 promoter regions identified to bind to TR. While we have identified 85 putative TREs within these regions, future work will study other mechanisms of action that may mediate the remaining observed TR-binding activity.

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Density of TRE consensus Hexamers for various promoter groups. Sequences in promoter groups a-f were scanned for half sites with a PWM [40] score threshold of 6.0. Probability density functions for the number of TRE half sites observed per 1000 bps are shown for each class of DNA sequence. Estrogen regulated genes (group d) were chosen for this comparison since the characterized motif for their nuclear receptor is highly similar with the exception that the orientation of the motif is a palindrome with a 3 nucleotide spacer. These curves show the density of TRE half sites per 1000 bps for: a. in permutations of random promoter regions (n = 50). b. Randomly selected promoter regions (n = 50). c. promoter region for genes with TH regulated promoter regions (n =28). d. promoter region for genes with estrogen regulated promoter regions (n = 50). e. Regions detected by Splitter (n = 100), and f. validated regions detected by Splitter (n = 36). The results shown by a are random nucleotide permutations of the promoter regions shown in b. On the y-axis, density is the empirical estimate of the underlying probability density function. Regions a-d are 10 kbps in length where regions e,f are in the 300-600 bps range.
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Figure 5: Density of TRE consensus Hexamers for various promoter groups. Sequences in promoter groups a-f were scanned for half sites with a PWM [40] score threshold of 6.0. Probability density functions for the number of TRE half sites observed per 1000 bps are shown for each class of DNA sequence. Estrogen regulated genes (group d) were chosen for this comparison since the characterized motif for their nuclear receptor is highly similar with the exception that the orientation of the motif is a palindrome with a 3 nucleotide spacer. These curves show the density of TRE half sites per 1000 bps for: a. in permutations of random promoter regions (n = 50). b. Randomly selected promoter regions (n = 50). c. promoter region for genes with TH regulated promoter regions (n =28). d. promoter region for genes with estrogen regulated promoter regions (n = 50). e. Regions detected by Splitter (n = 100), and f. validated regions detected by Splitter (n = 36). The results shown by a are random nucleotide permutations of the promoter regions shown in b. On the y-axis, density is the empirical estimate of the underlying probability density function. Regions a-d are 10 kbps in length where regions e,f are in the 300-600 bps range.

Mentions: As described above, TREs are composed of 2 hexamers or half sites. We investigated whether the density of hexamers could help identify genomic regions containing TREs. We hypothesised that a higher density of hexamers in a genomic region would indicate a higher probability of finding a TRE. A position weight matrix (PWM) model was built using all previously reported half sites (Table 2) to represent the classic TRE hexamer sequence motif. Briefly, a PWM compiles information content (log odd values) for each nucleotide position using existing information on known binding sequences for the protein of interest. Scores for DNA sequences of interest can then be calculated by respectively summing the PWM matrix values for each position. The presence and abundance of TRE hexamers was determined for various different types of genomic DNA sequences. The DNA regions examined included: (A) permutations of random promoter regions (-8 kb to +2 kb of transcription start site); (B) randomly selected promoter regions (without permutation); (C) promoter regions for genes that are known to be regulated by TH (see Methods); (D) promoter regions for genes that are regulated by estrogen; (E) regions corresponding to the peaks detected by Splitter; and (F) Splitter detected regions validated through ChIP-PCR to be truly TR-binding. Estrogen regulated genes were included in this comparison since the characterized motif for this nuclear receptor is highly similar to TREs, with the exception that the orientation of the motif is a palindrome with a 3 nucleotide spacer [21]. Figure 5 shows the distribution of TRE hexamer frequency (per Kbp) within each class of promoter sequence. The analysis revealed that permuted promoter regions contain significantly (p < 0.0001) fewer half sites than non-permutated promoter regions (Figure 5a vs. b). The data suggest a nucleotide position importance for promoter sequence composition, since permutations of identical sequences show a much lower number of hexamers. Interestingly, the promoters of established TH-regulated and estrogen-regulated genes (Figure 5 groups c & d) appear to exhibit bi-modal distributions, where one mode behaves similarly to the random promoters (Figure 5 group b) and another mode has half-site frequencies well above what one would expect by chance. We therefore conclude that, while the occurrence of the TRE motif is strongly correlated with gene regulation by TH for some genes, other TH-regulated genes do not exhibit an increased density of TRE half-site motifs. Figure 5 (groups e & f) shows the distribution of half sites in Splitter predicted and Splitter validated regions. The distribution of TRE motifs across these regions is broader and half site frequency is much higher than for randomly selected promoter regions (p < 0.0001). The broader distribution of these regions indicates higher variability in the number of hexamers for these classes of sequence. It is interesting to note that the Splitter peak regions are also significantly enriched for TRE motifs when compared to the promoter regions of previously reported TH-regulated genes (p < 0.003). However, it should be noted that these Splitter peak regions are much smaller (300-600 bp) than the 10 kb scanned for the other promoter sequence classes examined, which may lead to an apparent concentration of TRE half sites. That is, the concentration of TRE half sites may be ‘diluted’ when examining an entire promoter region vs. the subsequence that ChIP-chip indicates is TR-binding.


Identification of thyroid hormone receptor binding sites in developing mouse cerebellum.

Gagne R, Green JR, Dong H, Wade MG, Yauk CL - BMC Genomics (2013)

Density of TRE consensus Hexamers for various promoter groups. Sequences in promoter groups a-f were scanned for half sites with a PWM [40] score threshold of 6.0. Probability density functions for the number of TRE half sites observed per 1000 bps are shown for each class of DNA sequence. Estrogen regulated genes (group d) were chosen for this comparison since the characterized motif for their nuclear receptor is highly similar with the exception that the orientation of the motif is a palindrome with a 3 nucleotide spacer. These curves show the density of TRE half sites per 1000 bps for: a. in permutations of random promoter regions (n = 50). b. Randomly selected promoter regions (n = 50). c. promoter region for genes with TH regulated promoter regions (n =28). d. promoter region for genes with estrogen regulated promoter regions (n = 50). e. Regions detected by Splitter (n = 100), and f. validated regions detected by Splitter (n = 36). The results shown by a are random nucleotide permutations of the promoter regions shown in b. On the y-axis, density is the empirical estimate of the underlying probability density function. Regions a-d are 10 kbps in length where regions e,f are in the 300-600 bps range.
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Figure 5: Density of TRE consensus Hexamers for various promoter groups. Sequences in promoter groups a-f were scanned for half sites with a PWM [40] score threshold of 6.0. Probability density functions for the number of TRE half sites observed per 1000 bps are shown for each class of DNA sequence. Estrogen regulated genes (group d) were chosen for this comparison since the characterized motif for their nuclear receptor is highly similar with the exception that the orientation of the motif is a palindrome with a 3 nucleotide spacer. These curves show the density of TRE half sites per 1000 bps for: a. in permutations of random promoter regions (n = 50). b. Randomly selected promoter regions (n = 50). c. promoter region for genes with TH regulated promoter regions (n =28). d. promoter region for genes with estrogen regulated promoter regions (n = 50). e. Regions detected by Splitter (n = 100), and f. validated regions detected by Splitter (n = 36). The results shown by a are random nucleotide permutations of the promoter regions shown in b. On the y-axis, density is the empirical estimate of the underlying probability density function. Regions a-d are 10 kbps in length where regions e,f are in the 300-600 bps range.
Mentions: As described above, TREs are composed of 2 hexamers or half sites. We investigated whether the density of hexamers could help identify genomic regions containing TREs. We hypothesised that a higher density of hexamers in a genomic region would indicate a higher probability of finding a TRE. A position weight matrix (PWM) model was built using all previously reported half sites (Table 2) to represent the classic TRE hexamer sequence motif. Briefly, a PWM compiles information content (log odd values) for each nucleotide position using existing information on known binding sequences for the protein of interest. Scores for DNA sequences of interest can then be calculated by respectively summing the PWM matrix values for each position. The presence and abundance of TRE hexamers was determined for various different types of genomic DNA sequences. The DNA regions examined included: (A) permutations of random promoter regions (-8 kb to +2 kb of transcription start site); (B) randomly selected promoter regions (without permutation); (C) promoter regions for genes that are known to be regulated by TH (see Methods); (D) promoter regions for genes that are regulated by estrogen; (E) regions corresponding to the peaks detected by Splitter; and (F) Splitter detected regions validated through ChIP-PCR to be truly TR-binding. Estrogen regulated genes were included in this comparison since the characterized motif for this nuclear receptor is highly similar to TREs, with the exception that the orientation of the motif is a palindrome with a 3 nucleotide spacer [21]. Figure 5 shows the distribution of TRE hexamer frequency (per Kbp) within each class of promoter sequence. The analysis revealed that permuted promoter regions contain significantly (p < 0.0001) fewer half sites than non-permutated promoter regions (Figure 5a vs. b). The data suggest a nucleotide position importance for promoter sequence composition, since permutations of identical sequences show a much lower number of hexamers. Interestingly, the promoters of established TH-regulated and estrogen-regulated genes (Figure 5 groups c & d) appear to exhibit bi-modal distributions, where one mode behaves similarly to the random promoters (Figure 5 group b) and another mode has half-site frequencies well above what one would expect by chance. We therefore conclude that, while the occurrence of the TRE motif is strongly correlated with gene regulation by TH for some genes, other TH-regulated genes do not exhibit an increased density of TRE half-site motifs. Figure 5 (groups e & f) shows the distribution of half sites in Splitter predicted and Splitter validated regions. The distribution of TRE motifs across these regions is broader and half site frequency is much higher than for randomly selected promoter regions (p < 0.0001). The broader distribution of these regions indicates higher variability in the number of hexamers for these classes of sequence. It is interesting to note that the Splitter peak regions are also significantly enriched for TRE motifs when compared to the promoter regions of previously reported TH-regulated genes (p < 0.003). However, it should be noted that these Splitter peak regions are much smaller (300-600 bp) than the 10 kb scanned for the other promoter sequence classes examined, which may lead to an apparent concentration of TRE half sites. That is, the concentration of TRE half sites may be ‘diluted’ when examining an entire promoter region vs. the subsequence that ChIP-chip indicates is TR-binding.

Bottom Line: We found that while the occurrence of the TRE motif is strongly correlated with gene regulation by TH for some genes, other TH-regulated genes do not exhibit an increased density of TRE half-site motifs.Furthermore, we demonstrate that an increase in the rate of occurrence of the half-site motifs does not always indicate the specific location of the TRE within the promoter region.While we have identified 85 putative TREs within these regions, future work will study other mechanisms of action that may mediate the remaining observed TR-binding activity.

View Article: PubMed Central - HTML - PubMed

Affiliation: Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON K1A 0L2, Canada.

ABSTRACT

Background: Thyroid hormones play an essential role in early vertebrate development as well as other key processes. One of its modes of action is to bind to the thyroid hormone receptor (TR) which, in turn, binds to thyroid response elements (TREs) in promoter regions of target genes. The sequence motif for TREs remains largely undefined as does the precise chromosomal location of the TR binding sites. A chromatin immunoprecipitation on microarray (ChIP-chip) experiment was conducted using mouse cerebellum post natal day (PND) 4 and PND15 for the thyroid hormone receptor (TR) beta 1 to map its binding sites on over 5000 gene promoter regions. We have performed a detailed computational analysis of these data.

Results: By analysing a recent spike-in study, the optimal normalization and peak identification approaches were determined for our dataset. Application of these techniques led to the identification of 211 ChIP-chip peaks enriched for TR binding in cerebellum samples. ChIP-PCR validation of 25 peaks led to the identification of 16 true positive TREs. Following a detailed literature review to identify all known mouse TREs, a position weight matrix (PWM) was created representing the classic TRE sequence motif. Various classes of promoter regions were investigated for the presence of this PWM, including permuted sequences, randomly selected promoter sequences, and genes known to be regulated by TH. We found that while the occurrence of the TRE motif is strongly correlated with gene regulation by TH for some genes, other TH-regulated genes do not exhibit an increased density of TRE half-site motifs. Furthermore, we demonstrate that an increase in the rate of occurrence of the half-site motifs does not always indicate the specific location of the TRE within the promoter region. To account for the fact that TR often operates as a dimer, we introduce a novel dual-threshold PWM scanning approach for identifying TREs with a true positive rate of 0.73 and a false positive rate of 0.2. Application of this approach to ChIP-chip peak regions revealed the presence of 85 putative TREs suitable for further in vitro validation.

Conclusions: This study further elucidates TRβ gene regulation in mouse cerebellum, with 211 promoter regions identified to bind to TR. While we have identified 85 putative TREs within these regions, future work will study other mechanisms of action that may mediate the remaining observed TR-binding activity.

Show MeSH