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Eukaryotic Transcriptional and Post-Transcriptional Gene Expression Regulation

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Cover of 'Eukaryotic Transcriptional and Post-Transcriptional Gene Expression Regulation'

Table of Contents

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    Book Overview
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    Chapter 1 Fluorescence Reporter-Based Genome-Wide RNA Interference Screening to Identify Alternative Splicing Regulators.
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    Chapter 2 Tandem Affinity Purification Approach Coupled to Mass Spectrometry to Identify Post-translational Modifications of Histones Associated with Chromatin-Binding Proteins.
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    Chapter 3 Efficient Preparation of High-Complexity ChIP-Seq Profiles from Early Xenopus Embryos.
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    Chapter 4 Eukaryotic Transcriptional and Post-Transcriptional Gene Expression Regulation
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    Chapter 5 Assay for Transposase-Accessible Chromatin with High-Throughput Sequencing (ATAC-Seq) Protocol for Zebrafish Embryos.
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    Chapter 6 Establishment of Time- and Cell-Specific RNAi in Caenorhabditis elegans.
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    Chapter 7 Cell-Penetrating Peptide-Mediated Delivery of Cas9 Protein and Guide RNA for Genome Editing.
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    Chapter 8 Epigenetic Analysis of Endocrine Cell Subtypes from Human Pancreatic Islets.
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    Chapter 9 eIF3 Regulation of Protein Synthesis, Tumorigenesis, and Therapeutic Response.
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    Chapter 10 High-Resolution Gene Expression Profiling of RNA Synthesis, Processing, and Decay by Metabolic Labeling of Newly Transcribed RNA Using 4-Thiouridine.
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    Chapter 11 Accurate Detection of Differential Expression and Splicing Using Low-Level Features.
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    Chapter 12 Profiling Changes in Histone Post-translational Modifications by Top-Down Mass Spectrometry.
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    Chapter 13 Determining if an mRNA is a Substrate of Nonsense-Mediated mRNA Decay in Saccharomyces cerevisiae.
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    Chapter 14 Optimizing In Vitro Pre-mRNA 3' Cleavage Efficiency: Reconstitution from Anion-Exchange Separated HeLa Cleavage Factors and from Adherent HeLa Cell Nuclear Extract.
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    Chapter 15 Eukaryotic Transcriptional and Post-Transcriptional Gene Expression Regulation
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    Chapter 16 Using an Inducible CRISPR-dCas9-KRAB Effector System to Dissect Transcriptional Regulation in Human Embryonic Stem Cells.
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    Chapter 17 In Vitro Assay to Study Histone Ubiquitination During Transcriptional Regulation.
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    Chapter 18 Eukaryotic Transcriptional and Post-Transcriptional Gene Expression Regulation
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    Chapter 19 Large-Scale RNA Interference Screening to Identify Transcriptional Regulators of a Tumor Suppressor Gene.
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    Chapter 20 Transcriptional Analysis-Based Integrative Genomics Approach to Identify Tumor-Promoting Metabolic Genes.
Attention for Chapter 20: Transcriptional Analysis-Based Integrative Genomics Approach to Identify Tumor-Promoting Metabolic Genes.
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Chapter title
Transcriptional Analysis-Based Integrative Genomics Approach to Identify Tumor-Promoting Metabolic Genes.
Chapter number 20
Book title
Eukaryotic Transcriptional and Post-Transcriptional Gene Expression Regulation
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-6518-2_20
Pubmed ID
Book ISBNs
978-1-4939-6516-8, 978-1-4939-6518-2
Authors

Romi Gupta, Narendra Wajapeyee, Gupta, Romi, Wajapeyee, Narendra

Editors

Narendra Wajapeyee, Romi Gupta

Abstract

Metabolic regulation can play key role in normal and pathological states. In particular in cancer cells, alterations in metabolic pathways can drive the growth and survival of cancer cells. Among these alterations, many occur at the transcriptional level leading to the overexpression of metabolic genes. However, not every metabolically upregulated genes may be necessary for tumor growth. Therefore, functional validation approaches are required to distinguish metabolically overexpressed genes that are necessary for tumor growth versus the ones that are not. One of the experimental approaches to do this is to use the approach of RNA interference to systematically survey the transcriptionally upregulated metabolic genes for their requirement in tumor growth. Here, we describe an integrative genomics approach to identify metabolic genes that are necessary for tumor growth. The approach we describe is a general integrative genomics approach that combines bioinformatics-based identification of overexpressed metabolic genes in cancer patient samples and then uses RNAi-based knockdown approach to identify genes that are necessary for tumor growth.

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The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

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Readers by professional status Count As %
Professor 1 100%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 1 100%