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Fast detection of deletion breakpoints using quantitative PCR

Overview of attention for article published in Genetics and Molecular Biology, June 2016
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Title
Fast detection of deletion breakpoints using quantitative PCR
Published in
Genetics and Molecular Biology, June 2016
DOI 10.1590/1678-4685-gmb-2015-0159
Pubmed ID
Authors

Gulshara Abildinova, Zhanara Abdrakhmanova, Helena Tuchinsky, Elimelech Nesher, Albert Pinhasov, Leon Raskin

Abstract

The routine detection of large and medium copy number variants (CNVs) is well established. Hemizygotic deletions or duplications in the large Duchenne muscular dystrophy DMD gene responsible for Duchenne and Becker muscular dystrophies are routinely identified using multiple ligation probe amplification and array-based comparative genomic hybridization. These methods only map deleted or duplicated exons, without providing the exact location of breakpoints. Commonly used methods for the detection of CNV breakpoints include long-range PCR and primer walking, their success being limited by the deletion size, GC content and presence of DNA repeats. Here, we present a strategy for detecting the breakpoints of medium and large CNVs regardless of their size. The hemizygous deletion of exons 45-50 in the DMD gene and the large autosomal heterozygous PARK2 deletion were used to demonstrate the workflow that relies on real-time quantitative PCR to narrow down the deletion region and Sanger sequencing for breakpoint confirmation. The strategy is fast, reliable and cost-efficient, making it amenable to widespread use in genetic laboratories.

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The data shown below were collected from the profile of 1 X user 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 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 7 22%
Student > Ph. D. Student 5 16%
Student > Doctoral Student 3 9%
Researcher 3 9%
Lecturer > Senior Lecturer 2 6%
Other 3 9%
Unknown 9 28%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 22%
Medicine and Dentistry 5 16%
Agricultural and Biological Sciences 4 13%
Engineering 2 6%
Immunology and Microbiology 2 6%
Other 3 9%
Unknown 9 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 28 June 2016.
All research outputs
#18,464,797
of 22,879,161 outputs
Outputs from Genetics and Molecular Biology
#499
of 712 outputs
Outputs of similar age
#247,908
of 326,207 outputs
Outputs of similar age from Genetics and Molecular Biology
#8
of 19 outputs
Altmetric has tracked 22,879,161 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 712 research outputs from this source. They receive a mean Attention Score of 3.1. This one is in the 17th percentile – i.e., 17% of its peers scored the same or lower than it.
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We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.