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Article details
Title
Identification of quantitative trait loci for survival in the mutant dynactin p150Glued mouse model of motor neuron disease
Published in
PLOS ONE, September 2022
DOI 10.1371/journal.pone.0274615
Pubmed ID
Authors
Abstract

Amyotrophic lateral sclerosis (ALS) is the most common degenerative motor neuron disorder. Although most cases of ALS are sporadic, 5-10% of cases are familial, with mutations associated with over 40 genes. There is variation of ALS symptoms within families carrying the same mutation; the disease may develop in one sibling and not in another despite the presence of the mutation in both. Although the cause of this phenotypic variation is unknown, it is likely related to genetic modifiers of disease expression. The identification of ALS causing genes has led to the development of transgenic mouse models of motor neuron disease. Similar to families with familial ALS, there are background-dependent differences in disease phenotype in transgenic mouse models of ALS suggesting that, as in human ALS, differences in phenotype may be ascribed to genetic modifiers. These genetic modifiers may not cause ALS rather their expression either exacerbates or ameliorates the effect of the mutant ALS causing genes. We have reported that in both the G93A-hSOD1 and G59S-hDCTN1 mouse models, SJL mice demonstrated a more severe phenotype than C57BL6 mice. From reciprocal intercrosses between G93A-hSOD1 transgenic mice on SJL and C57BL6 strains, we identified a major quantitative trait locus (QTL) on mouse chromosome 17 that results in a significant shift in lifespan. In this study we generated reciprocal intercrosses between transgenic G59S-hDCTN1 mice on SJL and C57BL6 strains and identified survival QTLs on mouse chromosomes 17 and 18. The chromosome 17 survival QTL on G93A-hSOD1 and G59S-hDCTN1 mice partly overlap, suggesting that the genetic modifiers located in this region may be shared by these two ALS models despite the fact that motor neuron degeneration is caused by mutations in different proteins. The overlapping region contains eighty-seven genes with non-synonymous variations predicted to be deleterious and/or damaging. Two genes in this segment, NOTCH3 and Safb/SAFB1, have been associated with motor neuron disease. The identification of genetic modifiers of motor neuron disease, especially those modifiers that are shared by SOD1 and dynactin-1 transgenic mice, may result in the identification of novel targets for therapies that can alter the course of this devastating illness.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 3 33%
Student > Bachelor 1 11%
Researcher 1 11%
Lecturer > Senior Lecturer 1 11%
Unknown 3 33%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 2 22%
Neuroscience 2 22%
Nursing and Health Professions 1 11%
Agricultural and Biological Sciences 1 11%
Unknown 3 33%
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 16 September 2022.
All research outputs
#31,204,628
of 34,386,255 outputs
Outputs from PLOS ONE
#202,091
of 224,596 outputs
Outputs of similar age
#392,489
of 457,333 outputs
Outputs of similar age from PLOS ONE
#2,492
of 2,840 outputs
Altmetric has tracked 34,386,255 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 224,596 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.2. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 457,333 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2,840 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.