Automated Author ProfileRobertson, Shaun
University of GlasgowUniversity of Nottingham
Robertson, Shaun
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 2.2 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Understanding how wild immune variation covaries with other traits can reveal how costs and trade-offs shape immune evolution in the wild. Divergent life history strategies may increase or alleviate immune costs, helping shape immune variation in a consistent, testable way. Contrasting hypotheses suggest that shorter life histories may alleviate costs by offsetting them against increased mortality; or increase the effect of costs if immune responses are traded off against development or reproduction. We investigated the evolutionary relationship between life history and immune responses within an island radiation of three-spined stickleback, with discrete populations of varying life histories and parasitism. We sampled two short-lived, two long-lived and an anadromous population using qPCR to quantify current immune profile and RAD-seq data to study the distribution of immune variants within our assay genes and across the genome. Short-lived populations exhibited significantly increased expression of all assay genes, which was accompanied by a strong association with population-level variation in local alleles and divergence in a gene that may be involved in complement pathways. In addition, divergence around the eda gene in anadromous fish is likely associated with increased inflammation. A wider analysis of 15 populations across the island revealed that immune genes across the genome show evidence of having diverged alongside life history strategies. Parasitism and reproductive investment were also important sources of variation for expression, highlighting the caution required when assaying immune responses in the wild. These results provide strong, gene-based support for current hypotheses linking life history and immune variation across multiple populations of a vertebrate model.
Authors
- Whiting, James R. ;
- Magalhaes, Isabel S. ;
- Singkam, Abdul R. ;
- Robertson, Shaun ;
- D'Agostino, Daniele ;
- Bradley, Janette E. ;
- MacColl, Andrew D.C. ;
- MacColl, Andrew D. C.