scholarly journals Make way for the ‘next generation’: application and prospects for genome-wide, epigenome-specific technologies in endocrine research

2012 ◽  
Vol 49 (1) ◽  
pp. R19-R27 ◽  
Author(s):  
Richard D Emes ◽  
William E Farrell
Keyword(s):  
High Throughput Sequencing ◽  
Cell Types ◽  
Epigenetic Changes ◽  
Disease States ◽  
Base Level ◽  
Genome Wide ◽  
Endocrine Organs ◽  
Life Threatening ◽  
Mechanism Of Interaction ◽  
Genome Level

Epigenetic changes, which target DNA and associated histones, can be described as a pivotal mechanism of interaction between genes and the environment. The field of epigenomics aims to detect and interpret epigenetic modifications at the whole genome level. These approaches have the potential to increase resolution of epigenetic changes to the single base level in multiple disease states or across a population of individuals. Identification and comparison of the epigenomic landscape has challenged our understanding of the regulation of phenotype. Additionally, inclusion of these marks as biomarkers in the early detection or progression monitoring of disease is providing novel avenues for future biomedical research. Cells of the endocrine organs, which include pituitary, thyroid, thymus, pancreas ovary and testes, have been shown to be susceptible to epigenetic alteration, leading to both local and systemic changes often resulting in life-threatening metabolic disease. As with other cell types and populations, endocrine cells are susceptible to tumour development, which in turn may have resulted from aberration of epigenetic control. Techniques including high-throughput sequencing and array-based analysis to investigate these changes have rapidly emerged and are continually evolving. Here, we present a review of these methods and their promise to influence our studies on the epigenome for endocrine research and perhaps to uncover novel therapeutic options in disease states.

scholarly journals Systematic clustering algorithm for chromatin accessibility data and its application to hematopoietic cells

2020 ◽  
Vol 16 (11) ◽  
pp. e1008422
Author(s):  
Azusa Tanaka ◽  
Yasuhiro Ishitsuka ◽  
Hiroki Ohta ◽  
Akihiro Fujimoto ◽  
Jun-ichirou Yasunaga ◽  
...  
Keyword(s):  
Data Reduction ◽  
Clustering Algorithm ◽  
High Throughput Sequencing ◽  
Hematopoietic Cells ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Open Chromatin ◽  
Genome Wide ◽  
Data Reduction Method ◽  
Effective Analysis

The huge amount of data acquired by high-throughput sequencing requires data reduction for effective analysis. Here we give a clustering algorithm for genome-wide open chromatin data using a new data reduction method. This method regards the genome as a string of 1s and 0s based on a set of peaks and calculates the Hamming distances between the strings. This algorithm with the systematically optimized set of peaks enables us to quantitatively evaluate differences between samples of hematopoietic cells and classify cell types, potentially leading to a better understanding of leukemia pathogenesis.

scholarly journals A Comparison of Peak Callers Used for DNase-seq Data

2014 ◽  
Author(s):  
Hashem Koohy ◽  
Thomas Down ◽  
Mikhail Spivakov ◽  
Tim Hubbard
Keyword(s):  
High Throughput Sequencing ◽  
Cell Types ◽  
Regulatory Elements ◽  
Open Chromatin ◽  
Independent Dataset ◽  
Genome Wide ◽  
Binding Data ◽  
Threshold Setting ◽  
Higher Sensitivity

Genome-wide profiling of open chromatin regions using DNase I and high-throughput sequencing (DNase- seq) is an increasingly popular approach for finding and studying regulatory elements. A variety of algorithms have been developed to identify regions of open chromatin from raw sequence-tag data, which has motivated us to assess and compare their performance. In this study, four published, publicly available peak calling algorithms used for DNase-seq data analysis (F-seq, Hotspot, MACS and ZINBA) are assessed at a range of signal thresholds on two published DNase-seq datasets for three cell types. The results were benchmarked against an independent dataset of regulatory regions derived from ENCODE in vivo transcription factor binding data for each particular cell type. The level of overlap between peak regions reported by each algorithm and this ENCODE-derived reference set was used to assess sensitivity and specificity of the algorithms. Our study suggests that F-seq has a slightly higher sensitivity than the next best algorithms. Hotspot and the ChIP-seq oriented method, MACS, both perform competitively when used with their default parameters. However the generic peak finder ZINBA appears to be less sensitive than the other three. We also assess accuracy of each algorithm over a range of signal thresholds. In particular, we show that the accuracy of F-Seq can be considerably improved by using a threshold setting that is different from the default value.

scholarly journals SLIC-CAGE: high-resolution transcription start site mapping using nanogram-levels of total RNA

2018 ◽  
Author(s):  
Nevena Cvetesic ◽  
Harry G. Leitch ◽  
Malgorzata Borkowska ◽  
Ferenc Müller ◽  
Piero Carninci ◽  
...  
Keyword(s):  
Rna Polymerase Ii ◽  
Transcription Initiation ◽  
High Throughput Sequencing ◽  
Core Promoter ◽  
Primordial Germ Cells ◽  
Promoter Sequence ◽  
Cell Types ◽  
Transcription Start ◽  
Total Rna ◽  
Genome Wide

ABSTRACTCap analysis of gene expression (CAGE) is a methodology for genome-wide quantitative mapping of mRNA 5’ends to precisely capture transcription start sites at a single nucleotide resolution. In combination with high-throughput sequencing, CAGE has revolutionized our understanding of rules of transcription initiation, led to discovery of new core promoter sequence features and discovered transcription initiation at enhancers genome-wide. The biggest limitation of CAGE is that even the most recently improved version (nAnT-iCAGE) still requires large amounts of total cellular RNA (5 micrograms), preventing its application to scarce biological samples such as those from early embryonic development or rare cell types. Here, we present SLIC-CAGE, a Super-Low Input Carrier-CAGE approach to capture 5’ends of RNA polymerase II transcripts from as little as 5-10 ng of total RNA. The dramatic increase in sensitivity is achieved by specially designed, selectively degradable carrier RNA. We demonstrate the ability of SLIC-CAGE to generate data for genome-wide promoterome with 1000-fold less material than required by existing CAGE methods by generating a complex, high quality library from mouse embryonic day (E) 11.5 primordial germ cells.

scholarly journals High-throughput sequencing offers new insights into 5-hydroxymethylcytosine

2016 ◽  
Vol 7 (3) ◽  
pp. 169-178 ◽  
Author(s):  
Alina P.S. Pang ◽  
Christopher Sugai ◽  
Alika K. Maunakea
Keyword(s):  
High Throughput Sequencing ◽  
Wide Distribution ◽  
Clinical Applications ◽  
Specific Nature ◽  
Functional Roles ◽  
Disease States ◽  
Tet Proteins ◽  
Genome Wide ◽  
The Brain

AbstractChemical modifications of DNA comprise epigenetic mechanisms that contribute to the maintenance of cellular activities and memory. Although the function of 5-methylcytosine (5-mC) has been extensively studied, little is known about the function(s) of relatively rarer and underappreciated cytosine modifications including 5-hydroxymethylcytosine (5-hmC). The discovery that ten-eleven translocation (Tet) proteins mediate conversion of 5-mC to 5-hmC, and other oxidation derivatives, sparked renewed interest to understand the biological role of 5-hmC. Studies examining total 5-hmC levels revealed the highly dynamic yet tissue-specific nature of this modification, implicating a role in epigenetic regulation and development. Intriguingly, 5-hmC levels are highest during early development and in the brain where abnormal patterns of 5-hmC have been observed in disease conditions. Thus, 5-hmC adds to the growing list of epigenetic modifications with potential utility in clinical applications and warrants further investigation. This review discusses the emerging functional roles of 5-hmC in normal and disease states, focusing primarily on insights provided by recent studies exploring the genome-wide distribution of this modification in mammals.

scholarly journals Genetic analysis of amyotrophic lateral sclerosis identifies contributing pathways and cell types

2021 ◽  
Vol 7 (3) ◽  
pp. eabd9036
Author(s):  
Sara Saez-Atienzar ◽  
Sara Bandres-Ciga ◽  
Rebekah G. Langston ◽  
Jonggeol J. Kim ◽  
Shing Wan Choi ◽  
...  
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Membrane Trafficking ◽  
Molecular Mechanisms ◽  
Cell Types ◽  
Polygenic Risk Score ◽  
Genome Wide ◽  
Genome Wide Data ◽  
Data Driven Approach ◽  
Single Nucleus ◽  
Lateral Sclerosis

Despite the considerable progress in unraveling the genetic causes of amyotrophic lateral sclerosis (ALS), we do not fully understand the molecular mechanisms underlying the disease. We analyzed genome-wide data involving 78,500 individuals using a polygenic risk score approach to identify the biological pathways and cell types involved in ALS. This data-driven approach identified multiple aspects of the biology underlying the disease that resolved into broader themes, namely, neuron projection morphogenesis, membrane trafficking, and signal transduction mediated by ribonucleotides. We also found that genomic risk in ALS maps consistently to GABAergic interneurons and oligodendrocytes, as confirmed in human single-nucleus RNA-seq data. Using two-sample Mendelian randomization, we nominated six differentially expressed genes (ATG16L2, ACSL5, MAP1LC3A, MAPKAPK3, PLXNB2, and SCFD1) within the significant pathways as relevant to ALS. We conclude that the disparate genetic etiologies of this fatal neurological disease converge on a smaller number of final common pathways and cell types.

scholarly journals Advantages of using graph databases to explore chromatin conformation capture experiments

2021 ◽  
Vol 22 (S2) ◽  
Author(s):  
Daniele D’Agostino ◽  
Pietro Liò ◽  
Marco Aldinucci ◽  
Ivan Merelli
Keyword(s):  
Web Application ◽  
High Throughput Sequencing ◽  
Cell Types ◽  
Graph Database ◽  
Graph Databases ◽  
Sources Of Information ◽  
Chromosome Conformation ◽  
Wide Scale ◽  
User Friendly ◽  
Different Cell Types

Abstract Background High-throughput sequencing Chromosome Conformation Capture (Hi-C) allows the study of DNA interactions and 3D chromosome folding at the genome-wide scale. Usually, these data are represented as matrices describing the binary contacts among the different chromosome regions. On the other hand, a graph-based representation can be advantageous to describe the complex topology achieved by the DNA in the nucleus of eukaryotic cells. Methods Here we discuss the use of a graph database for storing and analysing data achieved by performing Hi-C experiments. The main issue is the size of the produced data and, working with a graph-based representation, the consequent necessity of adequately managing a large number of edges (contacts) connecting nodes (genes), which represents the sources of information. For this, currently available graph visualisation tools and libraries fall short with Hi-C data. The use of graph databases, instead, supports both the analysis and the visualisation of the spatial pattern present in Hi-C data, in particular for comparing different experiments or for re-mapping omics data in a space-aware context efficiently. In particular, the possibility of describing graphs through statistical indicators and, even more, the capability of correlating them through statistical distributions allows highlighting similarities and differences among different Hi-C experiments, in different cell conditions or different cell types. Results These concepts have been implemented in NeoHiC, an open-source and user-friendly web application for the progressive visualisation and analysis of Hi-C networks based on the use of the Neo4j graph database (version 3.5). Conclusion With the accumulation of more experiments, the tool will provide invaluable support to compare neighbours of genes across experiments and conditions, helping in highlighting changes in functional domains and identifying new co-organised genomic compartments.

scholarly journals Emerging Roles for Browning of White Adipose Tissue in Prostate Cancer Malignant Behaviour

2021 ◽  
Vol 22 (11) ◽  
pp. 5560
Author(s):  
Alejandro Álvarez-Artime ◽  
Belén García-Soler ◽  
Rosa María Sainz ◽  
Juan Carlos Mayo
Keyword(s):  
Prostate Cancer ◽  
Adipose Tissue ◽  
White Adipose Tissue ◽  
Tumor Development ◽  
Cell Types ◽  
Protective Role ◽  
Bioactive Molecules ◽  
Brown Adipose ◽  
Endocrine Organs

In addition to its well-known role as an energy repository, adipose tissue is one of the largest endocrine organs in the organism due to its ability to synthesize and release different bioactive molecules. Two main types of adipose tissue have been described, namely white adipose tissue (WAT) with a classical energy storage function, and brown adipose tissue (BAT) with thermogenic activity. The prostate, an exocrine gland present in the reproductive system of most mammals, is surrounded by periprostatic adipose tissue (PPAT) that contributes to maintaining glandular homeostasis in conjunction with other cell types of the microenvironment. In pathological conditions such as the development and progression of prostate cancer, adipose tissue plays a key role through paracrine and endocrine signaling. In this context, the role of WAT has been thoroughly studied. However, the influence of BAT on prostate tumor development and progression is unclear and has received much less attention. This review tries to bring an update on the role of different factors released by WAT which may participate in the initiation, progression and metastasis, as well as to compile the available information on BAT to discuss and open a new field of knowledge about the possible protective role of BAT in prostate cancer.

scholarly journals Differential Effects of Toll-Like Receptor Activation and Differential Mediation by MAP Kinases of Immune Responses in Microglial Cells

2021 ◽  
Author(s):  
Jaedeok Kwon ◽  
Christos Arsenis ◽  
Maria Suessmilch ◽  
Alison McColl ◽  
Jonathan Cavanagh ◽  
...  
Keyword(s):  
Map Kinase ◽  
Microglial Activation ◽  
Map Kinases ◽  
Mrna Level ◽  
Cell Types ◽  
Receptor Activation ◽  
Microglial Cells ◽  
Toll Like Receptor ◽  
Disease States ◽  
Nitrite Production

AbstractMicroglial activation is believed to play a role in many psychiatric and neurodegenerative diseases. Based largely on evidence from other cell types, it is widely thought that MAP kinase (ERK, JNK and p38) signalling pathways contribute strongly to microglial activation following immune stimuli acting on toll-like receptor (TLR) 3 or TLR4. We report here that exposure of SimA9 mouse microglial cell line to immune mimetics stimulating TLR4 (lipopolysaccharide—LPS) or TLR7/8 (resiquimod/R848), results in marked MAP kinase activation, followed by induction of nitric oxide synthase, and various cytokines/chemokines. However, in contrast to TLR4 or TLR7/8 stimulation, very few effects of TLR3 stimulation by poly-inosine/cytidine (polyI:C) were detected. Induction of chemokines/cytokines at the mRNA level by LPS and resiquimod were, in general, only marginally affected by MAP kinase inhibition, and expression of TNF, Ccl2 and Ccl5 mRNAs, along with nitrite production, were enhanced by p38 inhibition in a stimulus-specific manner. Selective JNK inhibition enhanced Ccl2 and Ccl5 release. Many distinct responses to stimulation of TLR4 and TLR7 were observed, with JNK mediating TNF protein induction by the latter but not the former, and suppressing Ccl5 release by the former but not the latter. These data reveal complex modulation by MAP kinases of microglial responses to immune challenge, including a dampening of some responses. They demonstrate that abnormal levels of JNK or p38 signalling in microglial cells will perturb their profile of cytokine and chemokine release, potentially contributing to abnormal inflammatory patterns in CNS disease states.

scholarly journals AKT Alters Genome-Wide Estrogen Receptor α Binding and Impacts Estrogen Signaling in Breast Cancer

2008 ◽  
Vol 28 (24) ◽  
pp. 7487-7503 ◽  
Author(s):  
Poornima Bhat-Nakshatri ◽  
Guohua Wang ◽  
Hitesh Appaiah ◽  
Nikhil Luktuke ◽  
Jason S. Carroll ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Estrogen Receptor ◽  
Binding Sites ◽  
Transforming Growth Factor ◽  
Cell Types ◽  
Estrogen Receptor Α ◽  
Estrogen Signaling ◽  
Primary Tumors ◽  
Genome Wide ◽  
Extracellular Signal

ABSTRACT Estrogen regulates several biological processes through estrogen receptor α (ERα) and ERβ. ERα-estrogen signaling is additionally controlled by extracellular signal activated kinases such as AKT. In this study, we analyzed the effect of AKT on genome-wide ERα binding in MCF-7 breast cancer cells. Parental and AKT-overexpressing cells displayed 4,349 and 4,359 ERα binding sites, respectively, with ∼60% overlap. In both cell types, ∼40% of estrogen-regulated genes associate with ERα binding sites; a similar percentage of estrogen-regulated genes are differentially expressed in two cell types. Based on pathway analysis, these differentially estrogen-regulated genes are linked to transforming growth factor β (TGF-β), NF-κB, and E2F pathways. Consistent with this, the two cell types responded differently to TGF-β treatment: parental cells, but not AKT-overexpressing cells, required estrogen to overcome growth inhibition. Combining the ERα DNA-binding pattern with gene expression data from primary tumors revealed specific effects of AKT on ERα binding and estrogen-regulated expression of genes that define prognostic subgroups and tamoxifen sensitivity of ERα-positive breast cancer. These results suggest a unique role of AKT in modulating estrogen signaling in ERα-positive breast cancers and highlights how extracellular signal activated kinases can change the landscape of transcription factor binding to the genome.

scholarly journals Genome-wide miRNA analysis and integrated network for flavonoid biosynthesis in Osmanthus fragrans

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yong Shi ◽  
Heng Xia ◽  
Xiaoting Cheng ◽  
Libin Zhang
Keyword(s):  
Secondary Metabolites ◽  
High Throughput Sequencing ◽  
Target Genes ◽  
Expression Profiles ◽  
Flavonoid Biosynthesis ◽  
Integrated Network ◽  
Osmanthus Fragrans ◽  
Flavonoid Synthesis ◽  
Genome Wide

AbstractBackgroundOsmanthus fragransis an important economical plant containing multiple secondary metabolites including flavonoids and anthocyanins. During the past years, the roles of miRNAs in regulating the biosynthesis of secondary metabolites in plants have been widely investigated. However, few studies on miRNA expression profiles and the potential roles in regulating flavonoid biosynthesis have been reported inO. fragrans.ResultsIn this study, we used high-throughput sequencing technology to analyze the expression profiles of miRNAs in leaf and flower tissues ofO. fragrans. As a result, 106 conserved miRNAs distributed in 47 families and 88 novel miRNAs were identified. Further analysis showed there were 133 miRNAs differentially expressed in leaves and flowers. Additionally, the potential target genes of miRNAs as well as the related metabolic pathways were predicted. In the end, flavonoid content was measured in flower and leaf tissues and potential role of miR858 in regulating flavonoid synthesis was illustrated inO. fragrans.ConclusionsThis study not only provided the genome-wide miRNA profiles in the flower and leaf tissue ofO. fragrans, but also investigated the potential regulatory role of miR858a in flavonoid synthesis inO. fragrans. The results specifically indicated the connection of miRNAs to the regulation of secondary metabolite biosynthesis in non-model economical plant.

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