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Evidence for evolutionary and nonevolutionary forces shaping the distribution of human genetic variants near transcription start sites.

Scala G, Affinito O, Miele G, Monticelli A, Cocozza S - PLoS ONE (2014)

Bottom Line: We found that, in this 10 kb region, the distribution of variants depends on their frequency and on their localization relative to the TSS.We found a significant relationship between the distribution of rare variants and nucleosome occupancy scores.In conclusion, this study provides a novel and detailed view of the distribution of genomic variants around TSSs, providing insight into the forces that instigate and maintain variability in such critical regions.

View Article: PubMed Central - PubMed

Affiliation: Gruppo Interdipartimentale di Bioinformatica e Biologia Computazionale, Università degli Studi di Napoli "Federico II", Naples, Italy; Dipartimento di Fisica, Università degli Studi di Napoli "Federico II", Naples, Italy; Istituto Nazionale di Fisica Nucleare, Sezione di Napoli, Naples, Italy.

ABSTRACT
The regions surrounding transcription start sites (TSSs) of genes play a critical role in the regulation of gene expression. At the same time, current evidence indicates that these regions are particularly stressed by transcription-related mutagenic phenomena. In this work we performed a genome-wide analysis of the distribution of single nucleotide polymorphisms (SNPs) inside the 10 kb region flanking human TSSs by dividing SNPs into four classes according to their frequency (rare, two intermediate classes, and common). We found that, in this 10 kb region, the distribution of variants depends on their frequency and on their localization relative to the TSS. We found that the distribution of variants is generally different for TSSs located inside or outside of CpG islands. We found a significant relationship between the distribution of rare variants and nucleosome occupancy scores. Furthermore, our analysis suggests that evolutionary (purifying selection) and nonevolutionary (biased gene conversion) forces both play a role in determining the relative SNP frequency around TSSs. Finally, we analyzed the potential pathogenicity of each class of variant using the Combined Annotation Dependent Depletion score. In conclusion, this study provides a novel and detailed view of the distribution of genomic variants around TSSs, providing insight into the forces that instigate and maintain variability in such critical regions.

Show MeSH
Nucleosome density correlation with SNP density values.Pearson correlations between BNP values and BVF values are reported along with corresponding scatter plots for rare, mid1, mid2 and common variants (from left to right) and for the two TSS classes (CGI-TSSs on the top and nCGI-TSSs on the bottom). * indicates statistically significant correlations.
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pone-0114432-g004: Nucleosome density correlation with SNP density values.Pearson correlations between BNP values and BVF values are reported along with corresponding scatter plots for rare, mid1, mid2 and common variants (from left to right) and for the two TSS classes (CGI-TSSs on the top and nCGI-TSSs on the bottom). * indicates statistically significant correlations.

Mentions: For each variant frequency class, we plotted the nucleosome positioning score against the variant density in the same bin and for the same TSS class (Figure 4). For all these plots we have then computed the correlation between the two signals. In CGI-TSSs (upper panel), we found a very strong positive correlation for rarer variants that decreases in higher frequency variant classes. In nCGI-TSSs, a weaker correlation was found. The same analysis was conducted for the other available cell line, K562, with similar results (Figure S3).


Evidence for evolutionary and nonevolutionary forces shaping the distribution of human genetic variants near transcription start sites.

Scala G, Affinito O, Miele G, Monticelli A, Cocozza S - PLoS ONE (2014)

Nucleosome density correlation with SNP density values.Pearson correlations between BNP values and BVF values are reported along with corresponding scatter plots for rare, mid1, mid2 and common variants (from left to right) and for the two TSS classes (CGI-TSSs on the top and nCGI-TSSs on the bottom). * indicates statistically significant correlations.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4256220&req=5

pone-0114432-g004: Nucleosome density correlation with SNP density values.Pearson correlations between BNP values and BVF values are reported along with corresponding scatter plots for rare, mid1, mid2 and common variants (from left to right) and for the two TSS classes (CGI-TSSs on the top and nCGI-TSSs on the bottom). * indicates statistically significant correlations.
Mentions: For each variant frequency class, we plotted the nucleosome positioning score against the variant density in the same bin and for the same TSS class (Figure 4). For all these plots we have then computed the correlation between the two signals. In CGI-TSSs (upper panel), we found a very strong positive correlation for rarer variants that decreases in higher frequency variant classes. In nCGI-TSSs, a weaker correlation was found. The same analysis was conducted for the other available cell line, K562, with similar results (Figure S3).

Bottom Line: We found that, in this 10 kb region, the distribution of variants depends on their frequency and on their localization relative to the TSS.We found a significant relationship between the distribution of rare variants and nucleosome occupancy scores.In conclusion, this study provides a novel and detailed view of the distribution of genomic variants around TSSs, providing insight into the forces that instigate and maintain variability in such critical regions.

View Article: PubMed Central - PubMed

Affiliation: Gruppo Interdipartimentale di Bioinformatica e Biologia Computazionale, Università degli Studi di Napoli "Federico II", Naples, Italy; Dipartimento di Fisica, Università degli Studi di Napoli "Federico II", Naples, Italy; Istituto Nazionale di Fisica Nucleare, Sezione di Napoli, Naples, Italy.

ABSTRACT
The regions surrounding transcription start sites (TSSs) of genes play a critical role in the regulation of gene expression. At the same time, current evidence indicates that these regions are particularly stressed by transcription-related mutagenic phenomena. In this work we performed a genome-wide analysis of the distribution of single nucleotide polymorphisms (SNPs) inside the 10 kb region flanking human TSSs by dividing SNPs into four classes according to their frequency (rare, two intermediate classes, and common). We found that, in this 10 kb region, the distribution of variants depends on their frequency and on their localization relative to the TSS. We found that the distribution of variants is generally different for TSSs located inside or outside of CpG islands. We found a significant relationship between the distribution of rare variants and nucleosome occupancy scores. Furthermore, our analysis suggests that evolutionary (purifying selection) and nonevolutionary (biased gene conversion) forces both play a role in determining the relative SNP frequency around TSSs. Finally, we analyzed the potential pathogenicity of each class of variant using the Combined Annotation Dependent Depletion score. In conclusion, this study provides a novel and detailed view of the distribution of genomic variants around TSSs, providing insight into the forces that instigate and maintain variability in such critical regions.

Show MeSH