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Inherent signals in sequencing-based Chromatin-ImmunoPrecipitation control libraries.

Vega VB, Cheung E, Palanisamy N, Sung WK - PLoS ONE (2009)

Bottom Line: The growth of sequencing-based Chromatin Immuno-Precipitation studies call for a more in-depth understanding of the nature of the technology and of the resultant data to reduce false positives and false negatives.We found that copy number plays a major influence in both ChIP-enriched as well as control libraries.Next, significantly tag-rich 5 kbp regions were identified and they were associated with various genomic landmarks.

View Article: PubMed Central - PubMed

Affiliation: Computational and Mathematical Biology Group, Genome Institute of Singapore, Singapore, Singapore.

ABSTRACT

Background: The growth of sequencing-based Chromatin Immuno-Precipitation studies call for a more in-depth understanding of the nature of the technology and of the resultant data to reduce false positives and false negatives. Control libraries are typically constructed to complement such studies in order to mitigate the effect of systematic biases that might be present in the data. In this study, we explored multiple control libraries to obtain better understanding of what they truly represent.

Methodology: First, we analyzed the genome-wide profiles of various sequencing-based libraries at a low resolution of 1 Mbp, and compared them with each other as well as against aCGH data. We found that copy number plays a major influence in both ChIP-enriched as well as control libraries. Following that, we inspected the repeat regions to assess the extent of mapping bias. Next, significantly tag-rich 5 kbp regions were identified and they were associated with various genomic landmarks. For instance, we discovered that gene boundaries were surprisingly enriched with sequenced tags. Further, profiles between different cell types were noticeably distinct although the cell types were somewhat related and similar.

Conclusions: We found that control libraries bear traces of systematic biases. The biases can be attributed to genomic copy number, inherent sequencing bias, plausible mapping ambiguity, and cell-type specific chromatin structure. Our results suggest careful analysis of control libraries can reveal promising biological insights.

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Related in: MedlinePlus

Expression levels of genes were correlated with tag density in WCEseq libraries.Density profiles (50 bp average) of tags (combined sense- and antisense-mapped) around TSS and TES of highly expressed (red) and lowly expressed (green) genes.
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pone-0005241-g005: Expression levels of genes were correlated with tag density in WCEseq libraries.Density profiles (50 bp average) of tags (combined sense- and antisense-mapped) around TSS and TES of highly expressed (red) and lowly expressed (green) genes.

Mentions: Using the accompanying expression data in [8], genes were grouped into high expressing and low expressing. We found that high-expressing genes exhibited a more pronounced profile of tag density around gene boundaries (Fig. 5), while low-expressing genes exhibited a more subdued contour, closer to genomic background. Overall, the TSS of high-expressing genes was populated by approximately four times more tags than the TSS of low-expressing genes, while regions around the TES of high-expressing genes contained ∼30% more tags than those of low-expressing genes.


Inherent signals in sequencing-based Chromatin-ImmunoPrecipitation control libraries.

Vega VB, Cheung E, Palanisamy N, Sung WK - PLoS ONE (2009)

Expression levels of genes were correlated with tag density in WCEseq libraries.Density profiles (50 bp average) of tags (combined sense- and antisense-mapped) around TSS and TES of highly expressed (red) and lowly expressed (green) genes.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2666154&req=5

pone-0005241-g005: Expression levels of genes were correlated with tag density in WCEseq libraries.Density profiles (50 bp average) of tags (combined sense- and antisense-mapped) around TSS and TES of highly expressed (red) and lowly expressed (green) genes.
Mentions: Using the accompanying expression data in [8], genes were grouped into high expressing and low expressing. We found that high-expressing genes exhibited a more pronounced profile of tag density around gene boundaries (Fig. 5), while low-expressing genes exhibited a more subdued contour, closer to genomic background. Overall, the TSS of high-expressing genes was populated by approximately four times more tags than the TSS of low-expressing genes, while regions around the TES of high-expressing genes contained ∼30% more tags than those of low-expressing genes.

Bottom Line: The growth of sequencing-based Chromatin Immuno-Precipitation studies call for a more in-depth understanding of the nature of the technology and of the resultant data to reduce false positives and false negatives.We found that copy number plays a major influence in both ChIP-enriched as well as control libraries.Next, significantly tag-rich 5 kbp regions were identified and they were associated with various genomic landmarks.

View Article: PubMed Central - PubMed

Affiliation: Computational and Mathematical Biology Group, Genome Institute of Singapore, Singapore, Singapore.

ABSTRACT

Background: The growth of sequencing-based Chromatin Immuno-Precipitation studies call for a more in-depth understanding of the nature of the technology and of the resultant data to reduce false positives and false negatives. Control libraries are typically constructed to complement such studies in order to mitigate the effect of systematic biases that might be present in the data. In this study, we explored multiple control libraries to obtain better understanding of what they truly represent.

Methodology: First, we analyzed the genome-wide profiles of various sequencing-based libraries at a low resolution of 1 Mbp, and compared them with each other as well as against aCGH data. We found that copy number plays a major influence in both ChIP-enriched as well as control libraries. Following that, we inspected the repeat regions to assess the extent of mapping bias. Next, significantly tag-rich 5 kbp regions were identified and they were associated with various genomic landmarks. For instance, we discovered that gene boundaries were surprisingly enriched with sequenced tags. Further, profiles between different cell types were noticeably distinct although the cell types were somewhat related and similar.

Conclusions: We found that control libraries bear traces of systematic biases. The biases can be attributed to genomic copy number, inherent sequencing bias, plausible mapping ambiguity, and cell-type specific chromatin structure. Our results suggest careful analysis of control libraries can reveal promising biological insights.

Show MeSH
Related in: MedlinePlus