↓ Skip to main content

Disease Gene Identification

Overview of attention for book
Cover of 'Disease Gene Identification'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Identification of Disease Susceptibility Alleles in the Next Generation Sequencing Era
  3. Altmetric Badge
    Chapter 2 Induced Pluripotent Stem Cells in Disease Modeling and Gene Identification
  4. Altmetric Badge
    Chapter 3 Development of Targeted Therapies Based on Gene Modification
  5. Altmetric Badge
    Chapter 4 What Can We Learn About Human Disease from the Nematode C. elegans?
  6. Altmetric Badge
    Chapter 5 Microbiome Sequencing Methods for Studying Human Diseases
  7. Altmetric Badge
    Chapter 6 The Emerging Role of Long Noncoding RNAs in Human Disease
  8. Altmetric Badge
    Chapter 7 Identification of Disease-Related Genes Using a Genome-Wide Association Study Approach
  9. Altmetric Badge
    Chapter 8 Whole Genome Library Construction for Next Generation Sequencing
  10. Altmetric Badge
    Chapter 9 Whole Exome Library Construction for Next Generation Sequencing
  11. Altmetric Badge
    Chapter 10 Optimized Methodology for the Generation of RNA-Sequencing Libraries from Low-Input Starting Material: Enabling Analysis of Specialized Cell Types and Clinical Samples
  12. Altmetric Badge
    Chapter 11 Using Fluidigm C1 to Generate Single-Cell Full-Length cDNA Libraries for mRNA Sequencing
  13. Altmetric Badge
    Chapter 12 MiSeq: A Next Generation Sequencing Platform for Genomic Analysis
  14. Altmetric Badge
    Chapter 13 Methods for CpG Methylation Array Profiling Via Bisulfite Conversion
  15. Altmetric Badge
    Chapter 14 miRNA Quantification Method Using Quantitative Polymerase Chain Reaction in Conjunction with C q Method
  16. Altmetric Badge
    Chapter 15 Primary Airway Epithelial Cell Gene Editing Using CRISPR-Cas9
  17. Altmetric Badge
    Chapter 16 RNA Interference to Knock Down Gene Expression
  18. Altmetric Badge
    Chapter 17 Using Luciferase Reporter Assays to Identify Functional Variants at Disease-Associated Loci
  19. Altmetric Badge
    Chapter 18 Physiologic Interpretation of GWAS Signals for Type 2 Diabetes
  20. Altmetric Badge
    Chapter 19 Identification of Genes for Hereditary Hemochromatosis
  21. Altmetric Badge
    Chapter 20 Identification of Driver Mutations in Rare Cancers: The Role of SMARCA4 in Small Cell Carcinoma of the Ovary, Hypercalcemic Type (SCCOHT)
  22. Altmetric Badge
    Chapter 21 The Rise and Fall and Rise of Linkage Analysis as a Technique for Finding and Characterizing Inherited Influences on Disease Expression
Attention for Chapter 13: Methods for CpG Methylation Array Profiling Via Bisulfite Conversion
Altmetric Badge

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
41 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Chapter title
Methods for CpG Methylation Array Profiling Via Bisulfite Conversion
Chapter number 13
Book title
Disease Gene Identification
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7471-9_13
Pubmed ID
Book ISBNs
978-1-4939-7470-2, 978-1-4939-7471-9
Authors

Fatjon Leti, Lorida Llaci, Ivana Malenica, Johanna K. DiStefano

Abstract

DNA methylation is a key factor in epigenetic regulation, and contributes to the pathogenesis of many diseases, including various forms of cancers, and epigenetic events such X inactivation, cellular differentiation and proliferation, and embryonic development. The most conserved epigenetic modification in plants, animals, and fungi is 5-methylcytosine (5mC), which has been well characterized across a diverse range of species. Many technologies have been developed to measure modifications in methylation with respect to biological processes, and the most common method, long considered a gold standard for identifying regions of methylation, is bisulfite conversion. In this technique, DNA is treated with bisulfite, which converts cytosine residues to uracil, but does not affect cytosine residues that have been methylated, such as 5-methylcytosines. Following bisulfite conversion, the only cytosine residues remaining in the DNA, therefore, are those that have been methylated. Subsequent sequencing can then distinguish between unmethylated cytosines, which are displayed as thymines in the resulting amplified sequence of the sense strand, and 5-methylcytosines, which are displayed as cytosines in the resulting amplified sequence of the sense strand, at the single nucleotide level. In this chapter, we describe an array-based protocol for identifying methylated DNA regions. We discuss protocols for DNA quantification, bisulfite conversion, library preparation, and chip assembly, and present an overview of current methods for the analysis of methylation data.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 41 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 8 20%
Student > Master 4 10%
Student > Doctoral Student 3 7%
Researcher 3 7%
Student > Ph. D. Student 3 7%
Other 6 15%
Unknown 14 34%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 24%
Agricultural and Biological Sciences 7 17%
Unspecified 1 2%
Mathematics 1 2%
Nursing and Health Professions 1 2%
Other 3 7%
Unknown 18 44%