Eldon Emberly

Factors underlying variable DNA methylation in a human community cohort

Epigenetics is emerging as an attractive mechanism to explain the persistent genomic embedding of early-life experiences. Tightly linked to chromatin, which packages DNA into chromosomes, epigenetic marks primarily serve to regulate the activity of genes. DNA methylation is the most accessible and characterized component of the many chromatin marks that constitute the epigenome, making it an ideal target for epigenetic studies in human populations. Here, using peripheral blood mononuclear cells collected from a community-based cohort stratified for early-life socioeconomic status, we measured DNA methylation in the promoter regions of more than 14,000 human genes. Using this approach, we broadly assessed and characterized epigenetic variation, identified some of the factors that sculpt the epigenome, and determined its functional relation to gene expression. We found that the leukocyte composition of peripheral blood covaried with patterns of DNA methylation at many sites, as did demographic factors, such as sex, age, and ethnicity. Furthermore, psychosocial factors, such as perceived stress, and cortisol output were associated with DNA methylation, as was early-life socioeconomic status. Interestingly, we determined that DNA methylation was strongly correlated to the ex vivo inflammatory response of peripheral blood mononuclear cells to stimulation with microbial products that engage Toll-like receptors. In contrast, our work found limited effects of DNA methylation marks on the expression of associated genes across individuals, suggesting a more complex relationship than anticipated.

Additional annotation enhances potential for biologically-relevant analysis of the Illumina Infinium HumanMethylation450 BeadChip array

BackgroundMeasurement of genome-wide DNA methylation (DNAm) has become an important avenue for investigating potential physiologically-relevant epigenetic changes. Illumina Infinium (Illumina, San Diego, CA, USA) is a commercially available microarray suite used to measure DNAm at many sites throughout the genome. However, it has been suggested that a subset of array probes may give misleading results due to issues related to probe design. To facilitate biologically significant data interpretation, we set out to enhance probe annotation of the newest Infinium array, the HumanMethylation450 BeadChip (450 k), with >485,000 probes covering 99% of Reference Sequence (RefSeq) genes (National Center for Biotechnology Information (NCBI), Bethesda, MD, USA). Annotation that was added or expanded on includes: 1) documented SNPs in the probe target, 2) probe binding specificity, 3) CpG classification of target sites and 4) gene feature classification of target sites.ResultsProbes with documented SNPs at the target CpG (4.3% of probes) were associated with increased within-tissue variation in DNAm. An example of a probe with a SNP at the target CpG demonstrated how sample genotype can confound the measurement of DNAm. Additionally, 8.6% of probes mapped to multiple locations in silico. Measurements from these non-specific probes likely represent a combination of DNAm from multiple genomic sites. The expanded biological annotation demonstrated that based on DNAm, grouping probes by an alternative high-density and intermediate-density CpG island classification provided a distinctive pattern of DNAm. Finally, variable enrichment for differentially methylated probes was noted across CpG classes and gene feature groups, dependant on the tissues that were compared.ConclusionDNAm arrays offer a high-throughput approach for which careful consideration of probe content should be utilized to better understand the biological processes affected. Probes containing SNPs and non-specific probes may affect the assessment of DNAm using the 450 k array. Additionally, probe classification by CpG enrichment classes and to a lesser extent gene feature groups resulted in distinct patterns of DNAm. Thus, we recommend that compromised probes be removed from analyses and that the genomic context of DNAm is considered in studies deciphering the biological meaning of Illumina 450 k array data.

Transcriptional Control in the Segmentation Gene Network of Drosophila

The segmentation gene network of Drosophila consists of maternal and zygotic factors that generate, by transcriptional (cross-) regulation, expression patterns of increasing complexity along the anterior-posterior axis of the embryo. Using known binding site information for maternal and zygotic gap transcription factors, the computer algorithm Ahab recovers known segmentation control elements (modules) with excellent success and predicts many novel modules within the network and genome-wide. We show that novel module predictions are highly enriched in the network and typically clustered proximal to the promoter, not only upstream, but also in intronic space and downstream. When placed upstream of a reporter gene, they consistently drive patterned blastoderm expression, in most cases faithfully producing one or more pattern elements of the endogenous gene. Moreover, we demonstrate for the entire set of known and newly validated modules that Ahabs prediction of binding sites correlates well with the expression patterns produced by the modules, revealing basic rules governing their composition. Specifically, we show that maternal factors consistently act as activators and that gap factors act as repressors, except for the bimodal factor Hunchback. Our data suggest a simple context-dependent rule for its switch from repressive to activating function. Overall, the composition of modules appears well fitted to the spatiotemporal distribution of their positive and negative input factors. Finally, by comparing Ahab predictions with different categories of transcription factor input, we confirm the global regulatory structure of the segmentation gene network, but find odd skipped behaving like a primary pair-rule gene. The study expands our knowledge of the segmentation gene network by increasing the number of experimentally tested modules by 50%. For the first time, the entire set of validated modules is analyzed for binding site composition under a uniform set of criteria, permitting the definition of basic composition rules. The study demonstrates that computational methods are a powerful complement to experimental approaches in the analysis of transcription networks.

The smallest molecular switch.

Ab initio total energy calculations reveal benzene-dithiolate molecules on a gold surface, contacted by a monatomic gold STM tip to have two classes of low-energy conformations with differing symmetries. Lateral motion of the tip or excitation of the molecule cause it to change from one conformation class to the other and to switch between a strongly and a weakly conducting state. Thus, surprisingly, despite their apparent simplicity, these Au/BDT/Au nanowires are shown to be electrically bistable switches, the smallest two-terminal molecular switches to date.

Molecular spintronics: spin-dependent electron transport in molecular wires

Abstract We present a theoretical study of spin-dependent transport through molecular wires bridging ferromagnetic metal nanocontacts. We extend to magnetic systems a recently proposed model that provides a quantitative explanation of the conductance measurements of Reed et al. [Science 278 (1997) 252] on Au break-junctions bridged by self-assembled molecular monolayers (SAMs) of 1,4-benzene–dithiolate (BDT) molecules. Based on our calculations, we predict that spin-valve behavior should be observable in nickel break-junctions bridged by SAMs formed from BDT. We also consider spin transport in systems consisting of a clean ferromagnetic nickel STM tip and SAMs of benzene–thiol molecules on gold and nickel substrates. We find that spin-valve behavior should be possible for the Ni substrate. For the case where the substrate is gold, we show that it should be possible to inject a highly spin-polarized current into the substrate.

Genome-wide mapping of boundary element-associated factor (BEAF) binding sites in Drosophila melanogaster links BEAF to transcription.

ABSTRACT Insulator elements play a role in gene regulation that is potentially linked to nuclear organization. Boundary element-associated factors (BEAFs) 32A and 32B associate with hundreds of sites on Drosophila polytene chromosomes. We hybridized DNA isolated by chromatin immunoprecipitation to genome tiling microarrays to construct a genome-wide map of BEAF binding locations. A distinct difference in the association of 32A and 32B with chromatin was noted. We identified 1,820 BEAF peaks and found that more than 85% were less than 300 bp from transcription start sites. Half are between head-to-head gene pairs. BEAF-associated genes are transcriptionally active as judged by the presence of RNA polymerase II, dimethylated histone H3 K4, and the alternative histone H3.3. Forty percent of these genes are also associated with the polymerase negative elongation factor NELF. Like NELF-associated genes, most BEAF-associated genes are highly expressed. Using quantitative reverse transcription-PCR, we found that the expression levels of most BEAF-associated genes decrease in embryos and cultured cells lacking BEAF. These results provide an unexpected link between BEAF and transcription, suggesting that BEAF plays a role in maintaining most associated promoter regions in an environment that facilitates high transcription levels.

Landauer theory, inelastic scattering, and electron transport in molecular wires

In this paper, we address the topic of inelastic electron scattering in mesoscopic quantum transport. For systems where only elastic scattering is present, Landauer theory provides an adequate description of transport that relates the electronic current to single-particle transmission and reflection probabilities. A formalism proposed recently by Bonc\ifmmode \breve{}\else \u{}\fi{}a and Trugman facilitates the calculation of the one-electron transmission and reflection probabilities for inelastic processes in mesoscopic conductors connected to one-dimensional ideal leads. Building on their work, we have developed a self-consistent procedure for the evaluation of the nonequilibrium electron distributions in ideal leads connecting such mesoscopic conductors to electron reservoirs at finite temperatures and voltages. We evaluate the net electronic current flowing through the mesoscopic device by utilizing these nonequilibrium distributions. Our approach is a generalization of Landauer theory that takes account of the Pauli exclusion principle for the various competing elastic and inelastic processes while satisfying the requirement of particle conservation. As an application we examine the influence of elastic and inelastic scattering on conduction through a two site molecular wire with longitudinal phonons using the Su-Schrieffer-Heeger model of electron-phonon coupling.

Splitting the task: Ubp8 and Ubp10 deubiquitinate different cellular pools of H2BK123

Monoubiquitination of H2BK123 (H2BK123ub), catalyzed by Rad6/Bre1, is a transient histone modification with roles in transcription and is essential for establishing H3K4 and H3K79 trimethylations (H3K4me3 and H3K79me3). Here, we investigated the chromatin network around H2BK123ub by examining its localization and co-occurrence with its dependent marks as well as the transcription elongation mark H3K36me3 across the genome of Saccharomyces cerevisiae. In yeast, H2BK123ub is removed by the deubiquitinases Ubp8 and Ubp10, but their genomic target regions remain to be determined. Genome-wide maps of H2BK123ub in the absence of Ubp8 and Ubp10 revealed their distinct target loci, which were genomic sites enriched for H3K4me3 and H3K79me3, respectively. We propose an extended model of the H2BK123ub cross-talk by integrating existing relationships with the substrate specificities of Ubp8 and Ubp10 reported here.

Concordant and discordant DNA methylation signatures of aging in human blood and brain

BackgroundDNA methylation is an epigenetic mark that balances plasticity with stability. While DNA methylation exhibits tissue specificity, it can also vary with age and potentially environmental exposures. In studies of DNA methylation, samples from specific tissues, especially brain, are frequently limited and so surrogate tissues are often used. As yet, we do not fully understand how DNA methylation profiles of these surrogate tissues relate to the profiles of the central tissue of interest.ResultsWe have adapted principal component analysis to analyze data from the Illumina 450K Human Methylation array using a set of 17 individuals with 3 brain regions and whole blood. All of the top five principal components in our analysis were associated with a variable of interest: principal component 1 (PC1) differentiated brain from blood, PCs 2 and 3 were representative of tissue composition within brain and blood, respectively, and PCs 4 and 5 were associated with age of the individual (PC4 in brain and PC5 in both brain and blood). We validated our age-related PCs in four independent sample sets, including additional brain and blood samples and liver and buccal cells. Gene ontology analysis of all five PCs showed enrichment for processes that inform on the functions of each PC.ConclusionsPrincipal component analysis (PCA) allows simultaneous and independent analysis of tissue composition and other phenotypes of interest. We discovered an epigenetic signature of age that is not associated with cell type composition and required no correction for cellular heterogeneity.

Correlation between sequence hydrophobicity and surface-exposure pattern of database proteins.

Hydrophobicity is thought to be one of the primary forces driving the folding of proteins. On average, hydrophobic residues occur preferentially in the core, whereas polar residues tend to occur at the surface of a folded protein. By analyzing the known protein structures, we quantify the degree to which the hydrophobicity sequence of a protein correlates with its pattern of surface exposure. We have assessed the statistical significance of this correlation for several hydrophobicity scales in the literature, and find that the computed correlations are significant but far from optimal. We show that this less than optimal correlation arises primarily from the large degree of mutations that naturally occurring proteins can tolerate. Lesser effects are due in part to forces other than hydrophobicity, and we quantify this by analyzing the surface‐exposure distributions of all amino acids. Lastly, we show that our database findings are consistent with those found from an off‐lattice hydrophobic–polar model of protein folding.