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Attention Score in Context
| Title |
Genetic analysis of variation in lifespan using a multiparental advanced intercross Drosophila mapping population
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|---|---|
| Published in |
BMC Genomic Data, August 2016
|
| DOI | 10.1186/s12863-016-0419-9 |
| Pubmed ID | |
| Authors |
Chad A. Highfill, G. Adam Reeves, Stuart J. Macdonald |
| Abstract |
Considerable natural variation for lifespan exists within human and animal populations. Genetically dissecting this variation can elucidate the pathways and genes involved in aging, and help uncover the genetic mechanisms underlying risk for age-related diseases. Studying aging in model systems is attractive due to their relatively short lifespan, and the ability to carry out programmed crosses under environmentally-controlled conditions. Here we investigate the genetic architecture of lifespan using the Drosophila Synthetic Population Resource (DSPR), a multiparental advanced intercross mapping population. We measured lifespan in females from 805 DSPR lines, mapping five QTL (Quantitative Trait Loci) that each contribute 4-5 % to among-line lifespan variation in the DSPR. Each of these QTL co-localizes with the position of at least one QTL mapped in 13 previous studies of lifespan variation in flies. However, given that these studies implicate >90 % of the genome in the control of lifespan, this level of overlap is unsurprising. DSPR QTL intervals harbor 11-155 protein-coding genes, and we used RNAseq on samples of young and old flies to help resolve pathways affecting lifespan, and identify potentially causative loci present within mapped QTL intervals. Broad age-related patterns of expression revealed by these data recapitulate results from previous work. For example, we see an increase in antimicrobial defense gene expression with age, and a decrease in expression of genes involved in the electron transport chain. Several genes within QTL intervals are highlighted by our RNAseq data, such as Relish, a critical immune response gene, that shows increased expression with age, and UQCR-14, a gene involved in mitochondrial electron transport, that has reduced expression in older flies. The five QTL we isolate collectively explain a considerable fraction of the genetic variation for female lifespan in the DSPR, and implicate modest numbers of genes. In several cases the candidate loci we highlight reside in biological pathways already implicated in the control of lifespan variation. Thus, our results provide further evidence that functional genetics tests targeting these genes will be fruitful, lead to the identification of natural sequence variants contributing to lifespan variation, and help uncover the mechanisms of aging. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 33% |
| Unknown | 4 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 67% |
| Scientists | 2 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 3% |
| United States | 1 | 3% |
| Unknown | 35 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 27% |
| Researcher | 10 | 27% |
| Student > Bachelor | 3 | 8% |
| Professor > Associate Professor | 3 | 8% |
| Professor | 2 | 5% |
| Other | 6 | 16% |
| Unknown | 3 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 14 | 38% |
| Biochemistry, Genetics and Molecular Biology | 11 | 30% |
| Engineering | 2 | 5% |
| Neuroscience | 2 | 5% |
| Psychology | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 4 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 23 September 2016.
All research outputs
#14,387,928
of 25,373,627 outputs
Outputs from BMC Genomic Data
#419
of 1,204 outputs
Outputs of similar age
#202,832
of 381,642 outputs
Outputs of similar age from BMC Genomic Data
#10
of 46 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,204 research outputs from this source. They receive a mean Attention Score of 4.3. This one has gotten more attention than average, scoring higher than 64% 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 381,642 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 46 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.