Enhancers regulate progression of development in mammalian cells

Estimating the activity of transcription factors by the effect on their target genes

Motivation: Understanding regulation of transcription is central for elucidating cellular regulation. Several statistical and mechanistic models have come up the last couple of years explaining gene transcription levels using information of potential transcriptional regulators as transcription factors (TFs) and information from epigenetic modifications. The activity of TFs is often inferred by their transcription levels, promoter binding and epigenetic effects. However, in principle, these methods do not take hard-to-measure influences such as post-transcriptional modifications into account.

Results: For TFs, we present a novel concept circumventing this problem. We estimate the regulatory activity of TFs using their cumulative effects on their target genes. We established our model using expression data of 59 cell lines from the National Cancer Institute. The trained model was applied to an independent expression dataset of melanoma cells yielding excellent expression predictions and elucidated regulation of melanogenesis.

Availability and implementation: Using mixed-integer linear programming, we implemented a switch-like optimization enabling a constrained but optimal selection of TFs and optimal model selection estimating their effects. The method is generic and can also be applied to further regulators of transcription.

Contact:rainer.koenig@uni-jena.de

Supplementary information:Supplementary data are available at Bioinformatics online.

Characterizing protein interactions employing a genome-wide siRNA cellular phenotyping screen

Characterizing the activating and inhibiting effect of protein-protein interactions (PPI) is fundamental to gain insight into the complex signaling system of a human cell. A plethora of methods has been suggested to infer PPI from data on a large scale, but none of them is able to characterize the effect of this interaction. Here, we present a novel computational development that employs mitotic phenotypes of a genome-wide RNAi knockdown screen and enables identifying the activating and inhibiting effects of PPIs. Exemplarily, we applied our technique to a knockdown screen of HeLa cells cultivated at standard conditions. Using a machine learning approach, we obtained high accuracy (82% AUC of the receiver operating characteristics) by cross-validation using 6,870 known activating and inhibiting PPIs as gold standard. We predicted de novo unknown activating and inhibiting effects for 1,954 PPIs in HeLa cells covering the ten major signaling pathways of the Kyoto Encyclopedia of Genes and Genomes, and made these predictions publicly available in a database. We finally demonstrate that the predicted effects can be used to cluster knockdown genes of similar biological processes in coherent subgroups. The characterization of the activating or inhibiting effect of individual PPIs opens up new perspectives for the interpretation of large datasets of PPIs and thus considerably increases the value of PPIs as an integrated resource for studying the detailed function of signaling pathways of the cellular system of interest.

Mathematical models which aim to describe cellular signaling start from constructing an interaction network of effectors, mediators and their effected target proteins. Several developments came up making it easier to put these links together. Besides tediously assembling knowledge from textbooks and research articles, experimental high-throughput methods were established like Yeast-2-Hybrid assays or Fluorescence Emission Resonance Transfer. However, these methods do not elucidate the effect of such interactions. We aimed inferring if an interaction in a specific cellular context is rather activating or inhibiting. We used cellular phenotypes of a genome-wide RNAi knockdown screen of live cells to identify such activating and inhibiting effects of protein interactions. The rationale behind it is that activating protein interactions should lead to similar phenotypes when their respective genes are knocked down, whereas an inhibiting protein interaction should lead to dissimilar phenotypes. Exemplarily, we applied our method to a phenotype screen of perturbed HeLa cells. Our predictions effectively reproduced textbook relationships between proteins or domains when comparing the predicted effects with pairs of effectors, receptors, kinases, phosphatases and of general signalling modules. The presented computational approach is generic and may enable elucidating the effects of studied interactions also of other cellular systems under more specific conditions.

Childhood bone mineral content is associated with methylation status of the RXRA promoter at birth

Maternal vitamin D deficiency has been associated with reduced offspring bone mineral accrual. Retinoid-X receptor-alpha (RXRA) is an essential cofactor in the action of 1,25-dihydroxyvitamin D (1,25[OH]2 -vitamin D), and RXRA methylation in umbilical cord DNA has been associated with later offspring adiposity. We tested the hypothesis that RXRA methylation in umbilical cord DNA collected at birth is associated with offspring skeletal development, assessed by dual-energy X-ray absorptiometry, in a population-based mother-offspring cohort (Southampton Women's Survey). Relationships between maternal plasma 25-hydroxyvitamin D (25[OH]-vitamin D) concentrations and cord RXRA methylation were also investigated. In 230 children aged 4 years, a higher percent methylation at four of six RXRA CpG sites measured was correlated with lower offspring bone mineral content (BMC) corrected for body size (β = -2.1 to -3.4 g/SD, p = 0.002 to 0.047). In a second independent cohort (n = 64), similar negative associations at two of these CpG sites, but positive associations at the two remaining sites, were observed; however, none of the relationships in this replication cohort achieved statistical significance. The maternal free 25(OH)-vitamin D index was negatively associated with methylation at one of these RXRA CpG sites (β = -3.3 SD/unit, p = 0.03). Thus, perinatal epigenetic marking at the RXRA promoter region in umbilical cord was inversely associated with offspring size-corrected BMC in childhood. The potential mechanistic and functional significance of this finding remains a subject for further investigation.

CCAT: Combinatorial Code Analysis Tool for transcriptional regulation

Combinatorial interplay among transcription factors (TFs) is an important mechanism by which transcriptional regulatory specificity is achieved. However, despite the increasing number of TFs for which either binding specificities or genome-wide occupancy data are known, knowledge about cooperativity between TFs remains limited. To address this, we developed a computational framework for predicting genome-wide co-binding between TFs (CCAT, Combinatorial Code Analysis Tool), and applied it to Drosophila melanogaster to uncover cooperativity among TFs during embryo development. Using publicly available TF binding specificity data and DNaseI chromatin accessibility data, we first predicted genome-wide binding sites for 324 TFs across five stages of D. melanogaster embryo development. We then applied CCAT in each of these developmental stages, and identified from 19 to 58 pairs of TFs in each stage whose predicted binding sites are significantly co-localized. We found that nearby binding sites for pairs of TFs predicted to cooperate were enriched in regions bound in relevant ChIP experiments, and were more evolutionarily conserved than other pairs. Further, we found that TFs tend to be co-localized with other TFs in a dynamic manner across developmental stages. All generated data as well as source code for our front-to-end pipeline are available at http://cat.princeton.edu.

Sp1 trans-activates and is required for maximal aldosterone induction of the αENaC gene in collecting duct cells

The epithelial Na+ channel (ENaC) in the distal nephron constitutes the rate-limiting step for renal sodium reabsorption. Aldosterone increases tubular sodium absorption in large part by increasing αENaC transcription in collecting duct principal cells. We previously reported that Af9 binds to +78/+92 of αENaC and recruits Dot1a to repress basal and aldosterone-sensitive αENaC transcription in mouse inner medullary collecting duct (mIMCD)3 cells. Despite this epigenetic repression, basal αENaC transcription is still evident and physiologically necessary, indicating basal operation of positive regulators. In the present study, we identified Sp1 as one such regulator. Gel shift and antibody competition assays using a +208/+240 probe revealed DNA-Sp1-containing complexes in mIMCD3 cells. Mutation of the +222/+229 element abrogated Sp1 binding in vitro and in promoter-reporter constructs stably expressed in mIMCD3 cells. Compared with the wild-type promoter, an αENaC promoter-luciferase construct with +222/+229 mutations exhibited much lower activity and impaired trans-activation in Sp1 overexpression experiments. Conversely, Sp1 knockdown inhibited endogenous αENaC mRNA and the activity of the wild-type αENaC promoter but not the mutated construct. Aldosterone triggered Sp1 recruitment to the αENaC promoter, which was required for maximal induction of αENaC promoter activity and was blocked by spironolactone. Sequential chromatin immunoprecipitation assays and functional tests of +78/+92 and +222/+229 αENaC promoter mutants indicated that while Sp1, Dot1a, and Af9 co-occupy the αENaC promoter, the Sp1 effects are functionally independent from Dot1a and Af9. In summary, Sp1 binding to a cis-element at +222/+229 represents the first identified constitutive driver of αENaC transcription, and it contributes to maximal aldosterone trans-activation of αENaC.

The genomic signature of trait-associated variants

BACKGROUND

Genome-wide association studies have identified thousands of SNP variants associated with hundreds of phenotypes. For most associations the causal variants and the molecular mechanisms underlying pathogenesis remain unknown. Exploration of the underlying functional annotations of trait-associated loci has thrown some light on their potential roles in pathogenesis. However, there are some shortcomings of the methods used to date, which may undermine efforts to prioritize variants for further analyses. Here, we introduce and apply novel methods to rigorously identify annotation classes showing enrichment or depletion of trait-associated variants taking into account the underlying associations due to co-location of different functional annotations and linkage disequilibrium.

RESULTS

We assessed enrichment and depletion of variants in publicly available annotation classes such as genic regions, regulatory features, measures of conservation, and patterns of histone modifications. We used logistic regression to build a multivariate model that identified the most influential functional annotations for trait-association status of genome-wide significant variants. SNPs associated with all of the enriched annotations were 8 times more likely to be trait-associated variants than SNPs annotated with none of them. Annotations associated with chromatin state together with prior knowledge of the existence of a local expression QTL (eQTL) were the most important factors in the final logistic regression model. Surprisingly, despite the widespread use of evolutionary conservation to prioritize variants for study we find only modest enrichment of trait-associated SNPs in conserved regions.

CONCLUSION

We established odds ratios of functional annotations that are more likely to contain significantly trait-associated SNPs, for the purpose of prioritizing GWAS hits for further studies. Additionally, we estimated the relative and combined influence of the different genomic annotations, which may facilitate future prioritization methods by adding substantial information.

Evaluation of methylation status of the eNOS promoter at birth in relation to childhood bone mineral content

Our previous work has shown associations between childhood adiposity and perinatal methylation status of several genes in umbilical cord tissue, including endothelial nitric oxide synthase (eNOS). There is increasing evidence that eNOS is important in bone metabolism; we therefore related the methylation status of the eNOS gene promoter in stored umbilical cord to childhood bone size and density in a group of 9-year-old children. We used Sequenom MassARRAY to assess the methylation status of two CpGs in the eNOS promoter, identified from our previous study, in stored umbilical cords of 66 children who formed part of a Southampton birth cohort and who had measurements of bone size and density at age 9 years (Lunar DPXL DXA instrument). Percentage methylation varied greatly between subjects. For one of the two CpGs, eNOS chr7:150315553 + , after taking account of age and sex, there were strong positive associations between methylation status and the child's whole-body bone area (r = 0.28, P = 0.02), bone mineral content (r = 0.34, P = 0.005), and areal bone mineral density (r = 0.34, P = 0.005) at age 9 years. These associations were independent of previously documented maternal determinants of offspring bone mass. Our findings suggest an association between methylation status at birth of a specific CpG within the eNOS promoter and bone mineral content in childhood. This supports a role for eNOS in bone growth and metabolism and implies that its contribution may at least in part occur during early skeletal development.