The publication data currently available has been vetted by Vanderbilt faculty, staff, administrators and trainees. The data itself is retrieved directly from NCBI's PubMed and is automatically updated on a weekly basis to ensure accuracy and completeness.
If you have any questions or comments, please contact us.
Deep sequencing of mammalian DNA methylomes has uncovered a previously unpredicted number of discrete hypomethylated regions in intergenic space (iHMRs). Here, we combined whole-genome bisulfite sequencing data with extensive gene expression and chromatin-state data to define functional classes of iHMRs, and to reconstruct the dynamics of their establishment in a developmental setting. Comparing HMR profiles in embryonic stem and primary blood cells, we show that iHMRs mark an exclusive subset of active DNase hypersensitive sites (DHS), and that both developmentally constitutive and cell-type-specific iHMRs display chromatin states typical of distinct regulatory elements. We also observe that iHMR changes are more predictive of nearby gene activity than the promoter HMR itself, and that expression of noncoding RNAs within the iHMR accompanies full activation and complete demethylation of mature B cell enhancers. Conserved sequence features corresponding to iHMR transcript start sites, including a discernible TATA motif, suggest a conserved, functional role for transcription in these regions. Similarly, we explored both primate-specific and human population variation at iHMRs, finding that while enhancer iHMRs are more variable in sequence and methylation status than any other functional class, conservation of the TATA box is highly predictive of iHMR maintenance, reflecting the impact of sequence plasticity and transcriptional signals on iHMR establishment. Overall, our analysis allowed us to construct a three-step timeline in which (1) intergenic DHS are pre-established in the stem cell, (2) partial demethylation of blood-specific intergenic DHSs occurs in blood progenitors, and (3) complete iHMR formation and transcription coincide with enhancer activation in lymphoid-specified cells.
Mechanisms through which long intergenic noncoding RNAs (ncRNAs) exert regulatory effects on eukaryotic biological processes remain largely elusive. Most studies of these phenomena rely on methods that measure average behaviors in cell populations, lacking resolution to observe the effects of ncRNA transcription on gene expression in a single cell. Here, we combine quantitative single-molecule RNA FISH experiments with yeast genetics and computational modeling to gain mechanistic insights into the regulation of the Saccharomyces cerevisiae protein-coding gene FLO11 by two intergenic ncRNAs, ICR1 and PWR1. Direct detection of FLO11 mRNA and these ncRNAs in thousands of individual cells revealed alternative expression states and provides evidence that ICR1 and PWR1 contribute to FLO11's variegated transcription, resulting in Flo11-dependent phenotypic heterogeneity in clonal cell populations by modulating recruitment of key transcription factors to the FLO11 promoter.
Copyright Â© 2012 Elsevier Inc. All rights reserved.
The recent success of genome-wide association studies has generated a trove of biologically significant variants implicated in human disease. However, many, if not most, of these variants fall in noncoding regions that have traditionally lacked much functional annotation. New data sets and tools allow for a more detailed assessment of potential importance of noncoding genetic variants. An overview of types of regulatory annotation that are currently available, and approaches to analyzing this data are provided with emphasis on usage of the UCSC genome browser.
© 2012 by John Wiley & Sons, Inc.
BACKGROUND - Replication of mammalian genomes requires the activation of thousands of origins which are both spatially and temporally regulated by as yet unknown mechanisms. At the most fundamental level, our knowledge about the distribution pattern of origins in each of the chromosomes, among different cell types, and whether the physiological state of the cells alters this distribution is at present very limited.
METHODOLOGY/PRINCIPAL FINDINGS - We have used standard λ-exonuclease resistant nascent DNA preparations in the size range of 0.7-1.5 kb obtained from the breast cancer cell line MCF-7 hybridized to a custom tiling array containing 50-60 nt probes evenly distributed among genic and non-genic regions covering about 1% of the human genome. A similar DNA preparation was used for high-throughput DNA sequencing. Array experiments were also performed with DNA obtained from BT-474 and H520 cell lines. By determining the sites showing nascent DNA enrichment, we have localized several thousand origins of DNA replication. Our major findings are: (a) both array and DNA sequencing assay methods produced essentially the same origin distribution profile; (b) origin distribution is largely conserved (>70%) in all cell lines tested; (c) origins are enriched at the 5'ends of expressed genes and at evolutionarily conserved intergenic sequences; and (d) ChIP on chip experiments in MCF-7 showed an enrichment of H3K4Me3 and RNA Polymerase II chromatin binding sites at origins of DNA replication.
CONCLUSIONS/SIGNIFICANCE - Our results suggest that the program for origin activation is largely conserved among different cell types. Also, our work supports recent studies connecting transcription initiation with replication, and in addition suggests that evolutionarily conserved intergenic sequences have the potential to participate in origin selection. Overall, our observations suggest that replication origin selection is a stochastic process significantly dependent upon local accessibility to replication factors.
BACKGROUND AND AIMS - Several genes have been shown to individually affect plasma lipoprotein metabolism in humans. Studies on gene-gene interactions could offer more insight into how genes affect lipid metabolism and may be useful in predicting lipid concentrations. We tested for gene-gene interactions between TaqIB SNP in the cholesterol ester transfer protein (CETP) and three novel single nucleotide polymorphisms (SNPs), namely rs11774572, rs7819412 and rs6995374 for their effect on metabolic syndrome (MetS) components and related traits.
METHODS AND RESULTS - The aforementioned SNPs were genotyped in 1002 subjects who participated in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study. Lipids were measured by standard procedures and lipoprotein subfractions, by proton nuclear magnetic resonance spectroscopy. Polymorphism rs11774572 was significantly associated with MetS (P=0.020), mainly driven by the association of the C allele with lower HDL-C (P=0.043) and higher triglycerides (P=0.049) and insulin (P=0.040) concentrations than TT subjects. A significant interaction between SNPs rs11774572 and CETP-TaqIB SNPs was found for HDL-C concentrations (P=0.006) and for HDL (P=0.008) and LDL particle sizes (P=0.009), small LDL (P=0.004), and VLDL concentrations (P=0.021), in which TT homozygotes displayed higher HDL-C concentrations and for HDL and LDL particle sizes, and lower small LDL and VLDL concentrations than C carriers, if they were CETP B2 allele carriers (P values ranging from <0.001 to 0.001).
CONCLUSIONS - The rs11774572 polymorphism may play a role in the dyslipidemia that characterizes MetS. The interaction between rs11774572 and CETP-TaqIB SNPs on HDL-C concentrations provides some insights into the underlying mechanisms.
Copyright 2009 Elsevier B.V. All rights reserved.
We investigated the single nucleotide polymorphism (SNP) density across the human genome and in different genic categories using two SNP databases: Celera's CgsSNP, which includes SNPs identified by comparing genomic sequences, and Celera's RefSNP, which includes SNPs from a variety of sources and is biased toward disease-associated genes. Based on CgsSNP, the average numbers of SNPs per 10 kb was 8.33, 8.44, and 8.09 in the human genome, in intergenic regions, and in genic regions, respectively. In genic regions, the SNP density in intronic, exonic and adjoining untranslated regions was 8.21, 5.28, and 7.51 SNPs per 10 kb, respectively. The pattern of SNP density based on RefSNP was different from that based on CgsSNP, emphasizing its utility for genotype-phenotype association studies but not for most population genetic studies. The number of SNPs per chromosome was correlated with chromosome length, but the density of SNPs estimated by CgsSNP was not significantly correlated with the GC content of the chromosome. Based on CgsSNP, the ratio of nonsense to missense mutations (0.027), the ratio of missense to silent mutations (1.15), and the ratio of non-synonymous to synonymous mutations (1.18) was less than half of that expected in a human protein coding sequence under the neutral mutation theory, reflecting a role for natural selection, especially purifying selection.