Displaying all 12 publications

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  1. Lim LWK, Chung HH, Chong YL, Lee NK
    Comput Biol Chem, 2018 Jun;74:132-141.
    PMID: 29602043 DOI: 10.1016/j.compbiolchem.2018.03.019
    The race for the discovery of enhancers at a genome-wide scale has been on since the commencement of next generation sequencing decades after the discovery of the first enhancer, SV40. A few enhancer-predicting features such as chromatin feature, histone modifications and sequence feature had been implemented with varying success rates. However, to date, there is no consensus yet on the single enhancer marker that can be employed to ultimately distinguish and uncover enhancers from the enormous genomic regions. Many supervised, unsupervised and semi-supervised computational approaches had emerged to complement and facilitate experimental approaches in enhancer discovery. In this review, we placed our focus on the recently emerged enhancer predictor tools that work on general enhancer features such as sequences, chromatin states and histone modifications, eRNA and of multiple feature approach. Comparisons of their prediction methods and outcomes were done across their functionally similar counterparts. We provide some recommendations and insights for future development of more comprehensive and robust tools.
    Matched MeSH terms: Enhancer Elements, Genetic/genetics*
  2. Hu S, Qian M, Zhang H, Guo Y, Yang J, Zhao X, et al.
    Blood, 2017 06 15;129(24):3264-3268.
    PMID: 28408461 DOI: 10.1182/blood-2017-03-771162
    Matched MeSH terms: Enhancer Elements, Genetic*
  3. Van Ziffle J, Yang W, Chehab FF
    PLoS ONE, 2011;6(2):e17327.
    PMID: 21390308 DOI: 10.1371/journal.pone.0017327
    Progress in the functional studies of human olfactory receptors has been largely hampered by the lack of a reliable experimental model system. Although transgenic approaches in mice could characterize the function of individual olfactory receptors, the presence of over 300 functional genes in the human genome becomes a daunting task. Thus, the characterization of individuals with a genetic susceptibility to altered olfaction coupled with the absence of particular olfactory receptor genes will allow phenotype/genotype correlations and vindicate the function of specific olfactory receptors with their cognate ligands. We characterized a 118 kb β-globin deletion and found that its 3' end breakpoint extends to the neighboring olfactory receptor region downstream of the β-globin gene cluster. This deletion encompasses six contiguous olfactory receptor genes (OR51V1, OR52Z1, OR51A1P, OR52A1, OR52A5, and OR52A4) all of which are expressed in the brain. Topology analysis of the encoded proteins from these olfactory receptor genes revealed that OR52Z1, OR52A1, OR52A5, and OR52A4 are predicted to be functional receptors as they display integral characteristics of G-proteins coupled receptors. Individuals homozygous for the 118 kb β-globin deletion are afflicted with β-thalassemia due to a homozygous deletion of the β-globin gene and have no alleles for the above mentioned olfactory receptors genes. This is the first example of a homozygous deletion of olfactory receptor genes in human. Although altered olfaction remains to be ascertained in these individuals, such a study can be carried out in β-thalassemia patients from Malaysia, Indonesia and the Philippines where this mutation is common. Furthermore, OR52A1 contains a γ-globin enhancer, which was previously shown to confer continuous expression of the fetal γ-globin genes. Thus, the hypothesis that β-thalassemia individuals, who are homozygous for the 118 kb deletion, may also have an exacerbation of their anemia due to the deletion of two copies of the γ-globin enhancer element is worthy of consideration.
    Matched MeSH terms: Enhancer Elements, Genetic/genetics
  4. Lee NK, Fong PK, Abdullah MT
    Biomed Mater Eng, 2014;24(6):3807-14.
    PMID: 25227097 DOI: 10.3233/BME-141210
    Using Genetic Algorithm, this paper presents a modelling method to generate novel logical-based features from DNA sequences enriched with H3K4mel histone signatures. Current histone signature is mostly represented using k-mers content features incapable of representing all the possible complex interactions of various DNA segments. The main contributions are, among others: (a) demonstrating that there are complex interactions among sequence segments in the histone regions; (b) developing a parse tree representation of the logical complex features. The proposed novel feature is compared to the k-mers content features using datasets from the mouse (mm9) genome. Evaluation results show that the new feature improves the prediction performance as shown by f-measure for all datasets tested. Also, it is discovered that tree-based features generated from a single chromosome can be generalized to predict histone marks in other chromosomes not used in the training. These findings have a great impact on feature design considerations for histone signatures as well as other classifier design features.
    Matched MeSH terms: Enhancer Elements, Genetic/genetics*
  5. Wyszynski A, Hong CC, Lam K, Michailidou K, Lytle C, Yao S, et al.
    Hum. Mol. Genet., 2016 Sep 01;25(17):3863-3876.
    PMID: 27402876 DOI: 10.1093/hmg/ddw223
    Breast cancer is the most diagnosed malignancy and the second leading cause of cancer mortality in females. Previous association studies have identified variants on 2q35 associated with the risk of breast cancer. To identify functional susceptibility loci for breast cancer, we interrogated the 2q35 gene desert for chromatin architecture and functional variation correlated with gene expression. We report a novel intergenic breast cancer risk locus containing an enhancer copy number variation (enCNV; deletion) located approximately 400Kb upstream to IGFBP5, which overlaps an intergenic ERα-bound enhancer that loops to the IGFBP5 promoter. The enCNV is correlated with modified ERα binding and monoallelic-repression of IGFBP5 following oestrogen treatment. We investigated the association of enCNV genotype with breast cancer in 1,182 cases and 1,362 controls, and replicate our findings in an independent set of 62,533 cases and 60,966 controls from 41 case control studies and 11 GWAS. We report a dose-dependent inverse association of 2q35 enCNV genotype (percopy OR = 0.68 95%CI 0.55-0.83, P = 0.0002; replication OR = 0.77 95% CI 0.73-0.82, P = 2.1 × 10(-19)) and identify 13 additional linked variants (r(2 )>( )0.8) in the 20Kb linkage block containing the enCNV (P = 3.2 × 10(-15) - 5.6 × 10(-17)). These associations were independent of previously reported 2q35 variants, rs13387042/rs4442975 and rs16857609, and were stronger for ER-positive than ER-negative disease. Together, these results suggest that 2q35 breast cancer risk loci may be mediating their effect through IGFBP5.
    Matched MeSH terms: Enhancer Elements, Genetic*
  6. Darabi H, McCue K, Beesley J, Michailidou K, Nord S, Kar S, et al.
    Am. J. Hum. Genet., 2015 Jul 02;97(1):22-34.
    PMID: 26073781 DOI: 10.1016/j.ajhg.2015.05.002
    Genome-wide association studies have identified SNPs near ZNF365 at 10q21.2 that are associated with both breast cancer risk and mammographic density. To identify the most likely causal SNPs, we fine mapped the association signal by genotyping 428 SNPs across the region in 89,050 European and 12,893 Asian case and control subjects from the Breast Cancer Association Consortium. We identified four independent sets of correlated, highly trait-associated variants (iCHAVs), three of which were located within ZNF365. The most strongly risk-associated SNP, rs10995201 in iCHAV1, showed clear evidence of association with both estrogen receptor (ER)-positive (OR = 0.85 [0.82-0.88]) and ER-negative (OR = 0.87 [0.82-0.91]) disease, and was also the SNP most strongly associated with percent mammographic density. iCHAV2 (lead SNP, chr10: 64,258,684:D) and iCHAV3 (lead SNP, rs7922449) were also associated with ER-positive (OR = 0.93 [0.91-0.95] and OR = 1.06 [1.03-1.09]) and ER-negative (OR = 0.95 [0.91-0.98] and OR = 1.08 [1.04-1.13]) disease. There was weaker evidence for iCHAV4, located 5' of ADO, associated only with ER-positive breast cancer (OR = 0.93 [0.90-0.96]). We found 12, 17, 18, and 2 candidate causal SNPs for breast cancer in iCHAVs 1-4, respectively. Chromosome conformation capture analysis showed that iCHAV2 interacts with the ZNF365 and NRBF2 (more than 600 kb away) promoters in normal and cancerous breast epithelial cells. Luciferase assays did not identify SNPs that affect transactivation of ZNF365, but identified a protective haplotype in iCHAV2, associated with silencing of the NRBF2 promoter, implicating this gene in the etiology of breast cancer.
    Matched MeSH terms: Enhancer Elements, Genetic/genetics*
  7. Ghoussaini M, French JD, Michailidou K, Nord S, Beesley J, Canisus S, et al.
    Am. J. Hum. Genet., 2016 Oct 06;99(4):903-911.
    PMID: 27640304 DOI: 10.1016/j.ajhg.2016.07.017
    Genome-wide association studies (GWASs) have revealed increased breast cancer risk associated with multiple genetic variants at 5p12. Here, we report the fine mapping of this locus using data from 104,660 subjects from 50 case-control studies in the Breast Cancer Association Consortium (BCAC). With data for 3,365 genotyped and imputed SNPs across a 1 Mb region (positions 44,394,495-45,364,167; NCBI build 37), we found evidence for at least three independent signals: the strongest signal, consisting of a single SNP rs10941679, was associated with risk of estrogen-receptor-positive (ER(+)) breast cancer (per-g allele OR ER(+) = 1.15; 95% CI 1.13-1.18; p = 8.35 × 10(-30)). After adjustment for rs10941679, we detected signal 2, consisting of 38 SNPs more strongly associated with ER-negative (ER(-)) breast cancer (lead SNP rs6864776: per-a allele OR ER(-) = 1.10; 95% CI 1.05-1.14; p conditional = 1.44 × 10(-12)), and a single signal 3 SNP (rs200229088: per-t allele OR ER(+) = 1.12; 95% CI 1.09-1.15; p conditional = 1.12 × 10(-05)). Expression quantitative trait locus analysis in normal breast tissues and breast tumors showed that the g (risk) allele of rs10941679 was associated with increased expression of FGF10 and MRPS30. Functional assays demonstrated that SNP rs10941679 maps to an enhancer element that physically interacts with the FGF10 and MRPS30 promoter regions in breast cancer cell lines. FGF10 is an oncogene that binds to FGFR2 and is overexpressed in ∼10% of human breast cancers, whereas MRPS30 plays a key role in apoptosis. These data suggest that the strongest signal of association at 5p12 is mediated through coordinated activation of FGF10 and MRPS30, two candidate genes for breast cancer pathogenesis.
    Matched MeSH terms: Enhancer Elements, Genetic/genetics
  8. Syafruddin SE, Rodrigues P, Vojtasova E, Patel SA, Zaini MN, Burge J, et al.
    Nat Commun, 2019 03 11;10(1):1152.
    PMID: 30858363 DOI: 10.1038/s41467-019-09116-x
    Transcriptional networks are critical for the establishment of tissue-specific cellular states in health and disease, including cancer. Yet, the transcriptional circuits that control carcinogenesis remain poorly understood. Here we report that Kruppel like factor 6 (KLF6), a transcription factor of the zinc finger family, regulates lipid homeostasis in clear cell renal cell carcinoma (ccRCC). We show that KLF6 supports the expression of lipid metabolism genes and promotes the expression of PDGFB, which activates mTOR signalling and the downstream lipid metabolism regulators SREBF1 and SREBF2. KLF6 expression is driven by a robust super enhancer that integrates signals from multiple pathways, including the ccRCC-initiating VHL-HIF2A pathway. These results suggest an underlying mechanism for high mTOR activity in ccRCC cells. More generally, the link between super enhancer-driven transcriptional networks and essential metabolic pathways may provide clues to the mechanisms that maintain the stability of cell identity-defining transcriptional programmes in cancer.
    Matched MeSH terms: Enhancer Elements, Genetic/genetics
  9. Tan Y, Neo PC, Najimudin N, Sudesh K, Muhammad TS, Othman AS, et al.
    J. Basic Microbiol., 2010 Apr;50(2):179-89.
    PMID: 20082371 DOI: 10.1002/jobm.200900138
    Pseudomonas sp. USM 4-55 is a locally isolated bacterium that possesses the ability to produce polyhydroxyalkanoates (PHA) consisting of both poly(3-hydroxybutyrate) [P(3HB)] homopolymer and medium-chain length (mcl) monomers (6 to 14 carbon atoms) when sugars or fatty acids are utilized as the sole carbon source. In this study, the P(3HB) biosynthesis operon carrying the phbC(Ps) P(3HB) synthase was successfully cloned and sequenced using a homologous probe. Three open reading frames encoding NADPH-dependent acetoacetyl-coenzyme A reductase (PhbB(Ps)), beta-ketothiolase (PhbA(Ps)) and P(3HB) synthase (PhbC(Ps)) were found in the phb operon. The genetic organization of phb operon showed a putative promoter region, followed by phbB(Ps)-phbA(Ps)-phbC(Ps). phbR(Ps)which encoded a putative transcriptional activator was located in the opposite orientation, upstream of phbBAC(Ps). Heterologous expression of pGEM''ABex harboring phbC(Ps) in Escherichia coli JM109 resulted in P(3HB) accumulation of up to 40% of dry cell weight (DCW).
    Matched MeSH terms: Enhancer Elements, Genetic
  10. Kar SP, Beesley J, Amin Al Olama A, Michailidou K, Tyrer J, Kote-Jarai Z, et al.
    Cancer Discov, 2016 09;6(9):1052-67.
    PMID: 27432226 DOI: 10.1158/2159-8290.CD-15-1227
    Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10(-8) seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type-specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10(-5) in the three-cancer meta-analysis.

    SIGNIFICANCE: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932.

    Matched MeSH terms: Enhancer Elements, Genetic
  11. Orr N, Dudbridge F, Dryden N, Maguire S, Novo D, Perrakis E, et al.
    Hum. Mol. Genet., 2015 May 15;24(10):2966-84.
    PMID: 25652398 DOI: 10.1093/hmg/ddv035
    We recently identified a novel susceptibility variant, rs865686, for estrogen-receptor positive breast cancer at 9q31.2. Here, we report a fine-mapping analysis of the 9q31.2 susceptibility locus using 43 160 cases and 42 600 controls of European ancestry ascertained from 52 studies and a further 5795 cases and 6624 controls of Asian ancestry from nine studies. Single nucleotide polymorphism (SNP) rs676256 was most strongly associated with risk in Europeans (odds ratios [OR] = 0.90 [0.88-0.92]; P-value = 1.58 × 10(-25)). This SNP is one of a cluster of highly correlated variants, including rs865686, that spans ∼14.5 kb. We identified two additional independent association signals demarcated by SNPs rs10816625 (OR = 1.12 [1.08-1.17]; P-value = 7.89 × 10(-09)) and rs13294895 (OR = 1.09 [1.06-1.12]; P-value = 2.97 × 10(-11)). SNP rs10816625, but not rs13294895, was also associated with risk of breast cancer in Asian individuals (OR = 1.12 [1.06-1.18]; P-value = 2.77 × 10(-05)). Functional genomic annotation using data derived from breast cancer cell-line models indicates that these SNPs localise to putative enhancer elements that bind known drivers of hormone-dependent breast cancer, including ER-α, FOXA1 and GATA-3. In vitro analyses indicate that rs10816625 and rs13294895 have allele-specific effects on enhancer activity and suggest chromatin interactions with the KLF4 gene locus. These results demonstrate the power of dense genotyping in large studies to identify independent susceptibility variants. Analysis of associations using subjects with different ancestry, combined with bioinformatic and genomic characterisation, can provide strong evidence for the likely causative alleles and their functional basis.
    Matched MeSH terms: Enhancer Elements, Genetic
  12. Zeng C, Guo X, Long J, Kuchenbaecker KB, Droit A, Michailidou K, et al.
    Breast Cancer Res., 2016 06 21;18(1):64.
    PMID: 27459855 DOI: 10.1186/s13058-016-0718-0
    BACKGROUND: Multiple recent genome-wide association studies (GWAS) have identified a single nucleotide polymorphism (SNP), rs10771399, at 12p11 that is associated with breast cancer risk.

    METHOD: We performed a fine-scale mapping study of a 700 kb region including 441 genotyped and more than 1300 imputed genetic variants in 48,155 cases and 43,612 controls of European descent, 6269 cases and 6624 controls of East Asian descent and 1116 cases and 932 controls of African descent in the Breast Cancer Association Consortium (BCAC; http://bcac.ccge.medschl.cam.ac.uk/ ), and in 15,252 BRCA1 mutation carriers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Stepwise regression analyses were performed to identify independent association signals. Data from the Encyclopedia of DNA Elements project (ENCODE) and the Cancer Genome Atlas (TCGA) were used for functional annotation.

    RESULTS: Analysis of data from European descendants found evidence for four independent association signals at 12p11, represented by rs7297051 (odds ratio (OR) = 1.09, 95 % confidence interval (CI) = 1.06-1.12; P = 3 × 10(-9)), rs805510 (OR = 1.08, 95 % CI = 1.04-1.12, P = 2 × 10(-5)), and rs1871152 (OR = 1.04, 95 % CI = 1.02-1.06; P = 2 × 10(-4)) identified in the general populations, and rs113824616 (P = 7 × 10(-5)) identified in the meta-analysis of BCAC ER-negative cases and BRCA1 mutation carriers. SNPs rs7297051, rs805510 and rs113824616 were also associated with breast cancer risk at P 

    Matched MeSH terms: Enhancer Elements, Genetic
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