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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
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    Chapter 8 Whole Genome Library Construction for Next Generation Sequencing
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    Chapter 9 Whole Exome Library Construction for Next Generation Sequencing
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    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
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    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
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    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 15: Primary Airway Epithelial Cell Gene Editing Using CRISPR-Cas9
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Chapter title
Primary Airway Epithelial Cell Gene Editing Using CRISPR-Cas9
Chapter number 15
Book title
Disease Gene Identification
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7471-9_15
Pubmed ID
Book ISBNs
978-1-4939-7470-2, 978-1-4939-7471-9
Authors

Jamie L. Everman, Cydney Rios, Max A. Seibold

Abstract

The adaptation of the clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR associated endonuclease 9 (CRISPR-Cas9) machinery from prokaryotic organisms has resulted in a gene editing system that is highly versatile, easily constructed, and can be leveraged to generate human cells knocked out (KO) for a specific gene. While standard transfection techniques can be used for the introduction of CRISPR-Cas9 expression cassettes to many cell types, delivery by this method is not efficient in many primary cell types, including primary human airway epithelial cells (AECs). More efficient delivery in AECs can be achieved through lentiviral-mediated transduction, allowing the CRISPR-Cas9 system to be integrated into the genome of the cell, resulting in stable expression of the nuclease machinery and increasing editing rates. In parallel, advancements have been made in the culture, expansion, selection, and differentiation of AECs, which allow the robust generation of a bulk edited AEC population from transduced cells. Applying these methods, we detail here our latest protocol to generate mucociliary epithelial cultures knocked out for a specific gene from donor-isolated primary human basal airway epithelial cells. This protocol includes methods to: (1) design and generate lentivirus which targets a specific gene for KO with CRISPR-Cas9 machinery, (2) efficiently transduce AECs, (3) culture and select for a bulk edited AEC population, (4) molecularly screen AECs for Cas9 cutting and specific sequence edits, and (5) further expand and differentiate edited cells to a mucociliary airway epithelial culture. The AEC knockouts generated using this protocol provide an excellent primary cell model system with which to characterize the function of genes involved in airway dysfunction and disease.

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X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 52 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 17%
Student > Master 6 12%
Researcher 5 10%
Student > Bachelor 4 8%
Professor 2 4%
Other 9 17%
Unknown 17 33%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 19%
Immunology and Microbiology 8 15%
Medicine and Dentistry 5 10%
Agricultural and Biological Sciences 5 10%
Unspecified 2 4%
Other 8 15%
Unknown 14 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 February 2018.
All research outputs
#14,376,243
of 23,023,224 outputs
Outputs from Methods in molecular biology
#4,226
of 13,166 outputs
Outputs of similar age
#240,504
of 442,361 outputs
Outputs of similar age from Methods in molecular biology
#432
of 1,498 outputs
Altmetric has tracked 23,023,224 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,166 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 64% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 442,361 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,498 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.