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Single molecule real time sequencing in ADTKD-MUC1 allows complete assembly of the VNTR and exact positioning of causative mutations

Overview of attention for article published in Scientific Reports, March 2018
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  • Good Attention Score compared to outputs of the same age (67th percentile)
  • Good Attention Score compared to outputs of the same age and source (65th percentile)

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Title
Single molecule real time sequencing in ADTKD-MUC1 allows complete assembly of the VNTR and exact positioning of causative mutations
Published in
Scientific Reports, March 2018
DOI 10.1038/s41598-018-22428-0
Pubmed ID
Authors

Andrea Wenzel, Janine Altmueller, Arif B. Ekici, Bernt Popp, Kurt Stueber, Holger Thiele, Alois Pannes, Simon Staubach, Eduardo Salido, Peter Nuernberg, Richard Reinhardt, André Reis, Patrick Rump, Franz-Georg Hanisch, Matthias T. F. Wolf, Michael Wiesener, Bruno Huettel, Bodo B. Beck

Abstract

Recently, the Mucin-1 (MUC1) gene has been identified as a causal gene of autosomal dominant tubulointerstitial kidney disease (ADTKD). Most causative mutations are buried within a GC-rich 60 basepair variable number of tandem repeat (VNTR), which escapes identification by massive parallel sequencing methods due to the complexity of the VNTR. We established long read single molecule real time sequencing (SMRT) targeted to the MUC1-VNTR as an alternative strategy to the snapshot assay. Our approach allows complete VNTR assembly, thereby enabling the detection of all variants residing within the VNTR and simultaneous determination of VNTR length. We present high resolution data on the VNTR architecture for a cohort of snapshot positive (n = 9) and negative (n = 7) ADTKD families. By SMRT sequencing we could confirm the diagnosis in all previously tested cases, reconstruct both VNTR alleles and determine the exact position of the causative variant in eight of nine families. This study demonstrates that precise positioning of the causative mutation(s) and identification of other coding and noncoding sequence variants in ADTKD-MUC1 is feasible. SMRT sequencing could provide a powerful tool to uncover potential factors encoded within the VNTR that associate with intra- and interfamilial phenotype variability of MUC1 related kidney disease.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 59 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 15%
Student > Master 8 14%
Researcher 8 14%
Student > Doctoral Student 5 8%
Other 3 5%
Other 8 14%
Unknown 18 31%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 14 24%
Medicine and Dentistry 12 20%
Agricultural and Biological Sciences 7 12%
Computer Science 2 3%
Pharmacology, Toxicology and Pharmaceutical Science 2 3%
Other 3 5%
Unknown 19 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 13 February 2021.
All research outputs
#6,087,813
of 23,102,082 outputs
Outputs from Scientific Reports
#40,867
of 124,878 outputs
Outputs of similar age
#107,188
of 332,781 outputs
Outputs of similar age from Scientific Reports
#1,302
of 3,784 outputs
Altmetric has tracked 23,102,082 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 124,878 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.3. This one has gotten more attention than average, scoring higher than 67% 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 332,781 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.
We're also able to compare this research output to 3,784 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.