Allele frequencies of variants in Ultra Conserved Elements identify selective pressure on transcription factor binding

Ultra-conserved genes or elements (UCGs/UCEs) in the human genome are extreme examples of conservation. We characterized natural variations in 2884 UCEs and UCGs in two distinct populations ; Singaporean Chinese (n=280) and Italian (n=501) by using a pooled sample, targeted capture, sequencing approach. We identify, with high confidence, in these regions the abundance of rare SNVs (MAF<0.5%) of which 75% is not present in dbSNP137. UCEs association studies for complex human traits can use this information to model expected background variation and thus necessary power for association studies. By combining our data with 1000 Genome Project data, we show in three independent datasets that prevalent UCE variants (MAF>5%) are more often found in relatively less-conserved nucleotides within UCEs, compared to rare variants. Moreover, prevalent variants are less likely to overlap transcription factor binding site. Using SNPfold we found no significant influence of RNA secondary structure on UCE conservation. All together, these results suggest UCEs are not under selective pressure as a stretch of DNA but are under differential evolutionary pressure on the single nucleotide level

First somatic mutation of E2F1 in a critical DNA binding residue discovered in well-differentiated papillary mesothelioma of the peritoneum

10.1186/gb-2011-12-9-r96Genome biology129R9

Cancer-related ectopic expression of the bone-related transcription factor RUNX2 in non-osseous metastatic tumor cells is linked to cell proliferation and motility

10.1186/bcr2762Breast Cancer Research125-BCRR

Oncogenic cooperation between SOCS family proteins and EGFR identified using a Drosophila epithelial transformation model

10.1101/gad.192021.112Genes and Development26141602-1611GEDE

Opposing activities of the Ras and Hippo pathways converge on regulation of YAP protein turnover

Cancer genomes accumulate numerous genetic and epigenetic modifications. Yet, human cellular transformation can be accomplished by a few genetically defined elements. These elements activate key pathways required to support replicative immortality and anchorage independent growth, a predictor of tumorigenesis in vivo. Here, we provide evidence that the Hippo tumor suppressor pathway is a key barrier to Ras-mediated cellular transformation. The Hippo pathway targets YAP1 for degradation via the βTrCP-SCF ubiquitin ligase complex. In contrast, the Ras pathway acts oppositely, to promote YAP1 stability through downregulation of the ubiquitin ligase complex substrate recognition factors SOCS5/6. Depletion of SOCS5/6 or upregulation of YAP1 can bypass the requirement for oncogenic Ras in anchorage independent growth in vitro and tumor formation in vivo. Through the YAP1 target, Amphiregulin, Ras activates the endogenous EGFR pathway, which is required for transformation. Thus, the oncogenic activity of Ras(V12) depends on its ability to counteract Hippo pathway activity, creating a positive feedback loop, which depends on stabilization of YAP1

Expression analysis of rare cellular subsets: Direct RT-PCR on limited cell numbers obtained by FACS or soft agar assays

10.2144/000114019BioTechniques544208-211BTNQ

Prevalent and rare variants show distinctive conservation preference.

<p>(<b>A</b>) Distribution of A,T and G,C nucleotides in the UCEs and SNV positions. <b>(B–D</b>) Cumulative distribution plots of phyloP scores of SNVs with different MAFs. Data from three different data sources (<b>B</b>) SG-CHN, (<b>C</b>) ITA and (<b>D</b>) 1 KG are shown. Shaded grey area represents 95% confidence interval (obtained by bootstrapping) of random G/C content corrected UCE positions (blue line). Numbers in the parentheses indicate analyzed positions or SNVs.</p

General characterization of SNVs in the UCEs.

<p>(<b>A</b>) Number of SNVs per mega base (Mb) of UCE sequence per sample. SNVs from three data sources- Singaporean Chinese cohort (SG-CHN), Italian cohort (ITA) and 1000 Genome Project (1 KG) were used. SNVs are discriminated according to their minor allele frequency (MAF). Numbers in the parentheses represent sample size used in this study (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0110692#s2" target="_blank">Materials and Methods</a>). Random set represents random genomic regions that have the same total length as the UCEs set. Y-axis represents SNVs per Mb divided by sample count in the analyzed population. (<b>B–D</b>) Shared and distinct SNVs between SG-CHN, ITA and 1 KG populations. Venn diagrams of (<b>B</b>) all, (<b>C</b>) prevalent (MAF>0.5%) and rare (<b>D</b>) (MAF<0.5%) SNVs from three analyzed population. Numbers in the parentheses indicate analyzed SNVs in the corresponding population.</p

UCEs are enriched for the TFBS.

<p>(<b>A</b>) Box plots represent results of one hundred sets (each set contains one thousand randomly chosen positions). The y-axis indicates actual ENCODE TFBS overlap per one thousand tested positions. Boxes show IQR, notches indicate 95% confidence intervals of the median, whiskers extend to 1.5 times the IQR and open circles show outliers. *** P<2.2×10⁻¹⁶, two- tailed Mann–Whitney test. (<b>B</b>) Prevalent SNV positions are depleted for TFBS. All rare and prevalent SNV positions from the three different populations were analyzed for the ENCODE TFBS overlap. Random UCE set represents randomly chosen UCE positions (G,C content matched) that had the same number of analyzed positions as the rare and prevalent SNVs. Prevalent and rare SNVs overlap with the TFBS overlap is shown as relative to random UCE positions. For the statistical analysis each set (Pearson's Chi-squared test) was individually tested. * P<0.01.</p