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Degenerate codon mixing for PCR-based manipulation of highly repetitive sequences

Overview of attention for article published in BMC Research Notes, March 2018
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  • Good Attention Score compared to outputs of the same age and source (65th percentile)

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Title
Degenerate codon mixing for PCR-based manipulation of highly repetitive sequences
Published in
BMC Research Notes, March 2018
DOI 10.1186/s13104-018-3298-5
Pubmed ID
Authors

Dhanushika Ratnayake, Morgan Newman, Michael Lardelli

Abstract

Repeat expansion of polyglutamine tracks leads to a group of inherited human neurodegenerative disorders. Studying such repetitive sequences is required to gain insight into the pathophysiology of these diseases. PCR-based manipulation of repetitive sequences, however, is challenging due to the absence of unique primer binding sites or the generation of non-specific products. We have utilised the degeneracy of the genetic code to generate a polyglutamine sequence with low repeat similarity. This strategy allowed us to use conventional PCR to generate multiple constructs with approximately defined numbers of glutamine repeats. We then used these constructs to measure the in vivo variation in autophagic degradation activity related to the different numbers of glutamine repeats, providing an example of their applicability to study repeat expansion diseases. Our simple and easily generalised method of generating low repetition DNA sequences coding for uniform stretches of amino acid residues provides a strategy for generating particular lengths of polyglutamine tracts using standard PCR and cloning protocols.

X Demographics

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 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 50%
Student > Master 1 17%
Unknown 2 33%
Readers by discipline Count As %
Neuroscience 2 33%
Agricultural and Biological Sciences 1 17%
Nursing and Health Professions 1 17%
Unknown 2 33%
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 29 March 2018.
All research outputs
#13,586,133
of 23,031,582 outputs
Outputs from BMC Research Notes
#1,703
of 4,283 outputs
Outputs of similar age
#170,836
of 330,033 outputs
Outputs of similar age from BMC Research Notes
#30
of 91 outputs
Altmetric has tracked 23,031,582 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,283 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has gotten more attention than average, scoring higher than 57% 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 330,033 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 91 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 65% of its contemporaries.