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Characterization of FUS Mutations in Amyotrophic Lateral Sclerosis Using RNA-Seq

Overview of attention for article published in PLOS ONE, April 2013
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Title
Characterization of FUS Mutations in Amyotrophic Lateral Sclerosis Using RNA-Seq
Published in
PLOS ONE, April 2013
DOI 10.1371/journal.pone.0060788
Pubmed ID
Authors

Marka van Blitterswijk, Eric T. Wang, Brad A. Friedman, Pamela J. Keagle, Patrick Lowe, Ashley Lyn Leclerc, Leonard H. van den Berg, David E. Housman, Jan H. Veldink, John E. Landers

Abstract

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease resulting in severe muscle weakness and eventual death by respiratory failure. Although little is known about its pathogenesis, mutations in fused in sarcoma/translated in liposarcoma (FUS) are causative for familial ALS. FUS is a multifunctional protein that is involved in many aspects of RNA processing. To elucidate the role of FUS in ALS, we overexpressed wild-type and two mutant forms of FUS in HEK-293T cells, as well as knocked-down FUS expression. This was followed by RNA-Seq to identify genes which displayed differential expression or altered splicing patterns. Pathway analysis revealed that overexpression of wild-type FUS regulates ribosomal genes, whereas knock-down of FUS additionally affects expression of spliceosome related genes. Furthermore, cells expressing mutant FUS displayed global transcription patterns more similar to cells overexpressing wild-type FUS than to the knock-down condition. This observation suggests that FUS mutants do not contribute to the pathogenesis of ALS through a loss-of-function. Finally, our results demonstrate that the R521G and R522G mutations display differences in their influence on transcription and splicing. Taken together, these results provide additional insights into the function of FUS and how mutations contribute to the development of ALS.

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Geographical breakdown

Country Count As %
United Kingdom 2 3%
United States 2 3%
Unknown 75 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 29%
Researcher 10 13%
Student > Bachelor 9 11%
Student > Doctoral Student 8 10%
Professor 6 8%
Other 16 20%
Unknown 7 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 30 38%
Biochemistry, Genetics and Molecular Biology 14 18%
Neuroscience 10 13%
Medicine and Dentistry 7 9%
Engineering 3 4%
Other 6 8%
Unknown 9 11%