Systematic Comparison of Constitutive Promoters and the Doxycycline-Inducible Promoter

Constitutive promoters are used routinely to drive ectopic gene expression. Here, we carried out a systematic comparison of eight commonly used constitutive promoters (SV40, CMV, UBC, EF1A, PGK and CAGG for mammalian systems, and COPIA and ACT5C for Drosophila systems). We also included in the comparison the TRE promoter, which can be activated by the rtTA transcriptional activator in a doxycycline-inducible manner. To make our findings representative, we conducted the comparison in a variety of cell types derived from several species. We found that these promoters vary considerably from one another in their strength. Most promoters have fairly consistent strengths across different cell types, but the CMV promoter can vary considerably from cell type to cell type. At maximal induction, the TRE promoter is comparable to a strong constitutive promoter. These results should facilitate more rational choices of promoters in ectopic gene expression studies.</p

Systematic Comparison of Constitutive Promoters and the Doxycycline-Inducible Promoter

Constitutive promoters are used routinely to drive ectopic gene expression. Here, we carried out a systematic comparison of eight commonly used constitutive promoters (SV40, CMV, UBC, EF1A, PGK and CAGG for mammalian systems, and COPIA and ACT5C for Drosophila systems). We also included in the comparison the TRE promoter, which can be activated by the rtTA transcriptional activator in a doxycycline-inducible manner. To make our findings representative, we conducted the comparison in a variety of cell types derived from several species. We found that these promoters vary considerably from one another in their strength. Most promoters have fairly consistent strengths across different cell types, but the CMV promoter can vary considerably from cell type to cell type. At maximal induction, the TRE promoter is comparable to a strong constitutive promoter. These results should facilitate more rational choices of promoters in ectopic gene expression studies

Integrative genetic analysis suggests that skin color modifies the genetic architecture of melanoma

Melanoma is the deadliest form of skin cancer and presents a significant health care burden in many countries. In addition to ultraviolet radiation in sunlight, the main causal factor for melanoma, genetic factors also play an important role in melanoma susceptibility. Although genome-wide association studies have identified many single nucleotide polymorphisms associated with melanoma, little is known about the proportion of disease risk attributable to these loci and their distribution throughout the genome. Here, we investigated the genetic architecture of melanoma in 1,888 cases and 990 controls of European non-Hispanic ancestry. We estimated the overall narrow-sense heritability of melanoma to be 0.18 (P < 0.03), indicating that genetics contributes significantly to the risk of sporadically-occurring melanoma. We then demonstrated that only a small proportion of this risk is attributable to known risk variants, suggesting that much remains unknown of the role of genetics in melanoma. To investigate further the genetic architecture of melanoma, we partitioned the heritability by chromosome, minor allele frequency, and functional annotations. We showed that common genetic variation contributes significantly to melanoma risk, with a risk model defined by a handful of genomic regions rather than many risk loci distributed throughout the genome. We also demonstrated that variants affecting gene expression in skin account for a significant proportion of the heritability, and are enriched among melanoma risk loci. Finally, by incorporating skin color into our analyses, we observed both a shift in significance for melanoma-associated loci and an enrichment of expression quantitative trait loci among melanoma susceptibility variants. These findings suggest that skin color may be an important modifier of melanoma risk. We speculate that incorporating skin color and other non-genetic factors into genetic studies may allow for an improved understanding of melanoma susceptibility and guide future investigations to identify melanoma risk genes

A Single Copy of the Recently Identified Dual Oxidase Maturation Factor (DUOXA) 1 Gene Produces Only Mild Transient Hypothyroidism in a Patient with a Novel Biallelic DUOXA2 Mutation and Monoallelic DUOXA1 Deletion

Transient congenital hypothyroidism in a patient with a single functional DUOXA2 allele indicates that the system can operate with only one functional maturation factor allele

Integrative genetic analysis suggests that skin color modifies the genetic architecture of melanoma

<div><p>Melanoma is the deadliest form of skin cancer and presents a significant health care burden in many countries. In addition to ultraviolet radiation in sunlight, the main causal factor for melanoma, genetic factors also play an important role in melanoma susceptibility. Although genome-wide association studies have identified many single nucleotide polymorphisms associated with melanoma, little is known about the proportion of disease risk attributable to these loci and their distribution throughout the genome. Here, we investigated the genetic architecture of melanoma in 1,888 cases and 990 controls of European non-Hispanic ancestry. We estimated the overall narrow-sense heritability of melanoma to be 0.18 (<i>P</i> < 0.03), indicating that genetics contributes significantly to the risk of sporadically-occurring melanoma. We then demonstrated that only a small proportion of this risk is attributable to known risk variants, suggesting that much remains unknown of the role of genetics in melanoma. To investigate further the genetic architecture of melanoma, we partitioned the heritability by chromosome, minor allele frequency, and functional annotations. We showed that common genetic variation contributes significantly to melanoma risk, with a risk model defined by a handful of genomic regions rather than many risk loci distributed throughout the genome. We also demonstrated that variants affecting gene expression in skin account for a significant proportion of the heritability, and are enriched among melanoma risk loci. Finally, by incorporating skin color into our analyses, we observed both a shift in significance for melanoma-associated loci and an enrichment of expression quantitative trait loci among melanoma susceptibility variants. These findings suggest that skin color may be an important modifier of melanoma risk. We speculate that incorporating skin color and other non-genetic factors into genetic studies may allow for an improved understanding of melanoma susceptibility and guide future investigations to identify melanoma risk genes.</p></div

Melanoma heritability stratified by chromosome.

<p>Heritability estimates for each chromosome are plotted against chromosome length. The solid line is the regression of heritability on chromosome length and the dashed lines represent the 95% confidence intervals for the slope of the regression line. Chromosomes 6, 9, 11 and 16 are outside the 95% confidence interval and have higher heritability estimates than that expected based on chromosome length.</p

eQTL enrichment in the melanoma GWAS dataset becomes more significant upon conditioning on skin color.

<p>The distributions of the number of skin cis-eQTLs (at two different p-value thresholds: p < 0.01 and p < 0.001) in the permuted 1,000 GWAS datasets, generated by shuffling case-control status each time, are shown in the histograms. In each permuted dataset, the number of eQTLs are determined among the top 2,000 (top panel) or top 1,000 (bottom panel) associations. The solid black circle is the actual eQTL count among the melanoma-associated SNPs. The p-values correspond to empirical p-values, calculated as the proportion of permuted GWAS datasets in which the eQTL count exceeds the actual observed count among the top associations. <b>Panel (A)</b> displays results of the analysis without conditioning on skin color. Enrichment of eQTLs among the top 1,000 melanoma associated SNPs is statistically significant (<i>P</i> < 0.05), while enrichment among the top 2,000 SNPs fails to reach statistical significance but is highly suggestive. <b>Panel (B)</b> displays results of the analysis in which skin color is included as a covariate in the analysis. Upon conditioning on skin color, enrichment of eQTLs among the top melanoma-associated SNPs becomes more pronounced and is statistically significant at all thresholds tested.</p

The <i>CDKN2A</i> region surpasses the genome-wide significance threshold whereas the <i>MC1R</i> and <i>HERC2/OCA2</i> loci do not upon conditioning on skin color in the melanoma etiology GWAS.

<p>Manhattan plot of the p-values for the association between imputed SNPs and melanoma using skin color as a covariate. The x-axis shows the chromosomal positions whereas the y-axis shows the–log₁₀ p-values of the SNPs. The p-values were obtained by logistic regression analysis including age, sex, skin color and the first two PCs from the PCA of GWAS (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0185730#pone.0185730.s003" target="_blank">S3 Fig</a>) as covariates. The red horizontal line is the widely used genome-wide significance threshold (p = 5 x 10⁻⁸) that was estimated by correcting independent common variants, which is roughly 1,000,000. The blue horizontal line is the suggestive significance threshold (p = 1 x 10⁻⁵). The <i>CDKN2A</i> region on chromosome 9 (black) reaches genome-wide significance upon the inclusion of skin color as a covariate in the analysis while the pigmentation loci <i>MC1R</i> (chromosome 16) and <i>HERC2/OCA2</i> (chromosome 15) are no longer significant.</p