Automated Author ProfileTing, Nelson
University of Oregon
Ting, Nelson
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: 3.5 (sum of 4 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Immunogenetic data from wild primate populations have been difficult to obtain, due to logistic and methodological constraints. We applied a well-characterized deep sequencing method for MHC I typing, developed for macaques, to a population of wild red colobus to assess the feasibility of identifying MHC I-A/B haplotypes. Ten individuals produced sufficient data from blood and tissue samples to assign haplotypes. Eighty-two sequences were classified as red colobus MHC I alleles distributed across six MHC I loci. Individuals averaged ~13 k reads across six MHC I loci, with 83 % of all alleles representing either MHC I-A or MHC I-B loci. This study not only represents an important advance in the identification and genotyping of MHC in the endangered red colobus but also shows the potential for using this approach in other endangered wild primates.
Authors
- Simons, Noah D. ;
- Ruiz-Lopez, Maria Jose ;
- Chapman, Colin A. ;
- Goldberg, Tony L. ;
- Karl, Julie A. ;
- Wiseman, Roger W. ;
- Bohn, Patrick S. ;
- O'Connor, David H. ;
- Ting, Nelson
A comprehensive understanding of how human disturbance affects tropical forest ecosystems is critical for the mitigation of future losses in global biodiversity. Although many genetic studies of tropical forest fragmentation have been conducted to provide insight into this issue, relatively few have incorporated landscape data to explicitly test the effects of human disturbance on genetic differentiation among populations. In this study, we use a newly developed landscape genetic approach that relies on a genetic algorithm to simultaneously optimize resistance surfaces to investigate the effects of human disturbance in the Udzungwa Mountains of Tanzania, which is an important part of a universally recognized biodiversity hotspot. Our study species is the endangered Udzungwa red colobus monkey (Procolobus gordonorum), which is endemic to the Udzungwa Mountains and a known indicator species that thrives in large and well-protected blocks of old growth forest. Population genetic analyses identified significant population structure among Udzungwa red colobus inhabiting different forest blocks, and Bayesian cluster analyses identified hierarchical structure. Our new method for creating composite landscape resistance models found that the combination of fire density on the landscape and distance to the nearest village best explains the genetic structure observed. These results demonstrate the effects that human activities are having in an area of high global conservation priority and suggest that this ecosystem is in a precarious state. Our study also illustrates the ability of our novel landscape genetic method to detect the impacts of relatively recent landscape features on a long-lived species.
Authors
- Ruiz-Lopez, Maria Jose ;
- Barelli, Claudia ;
- Rovero, Francesco ;
- Hodges, Keith ;
- Roos, Christian ;
- Peterman, William E. ;
- Ting, Nelson
Despite dramatic growth in the field of primate genomics over the past decade, studies of primate population and conservation genomics in the wild have been hampered due to the difficulties inherent in studying non-model organisms and endangered species, such as lack of a reference genome and current challenges in de novo primate genome assembly. Here, we used Restriction-site Associated DNA (RAD) sequencing to develop a population-based SNP panel for the Ugandan red colobus (P. rufomitratus tephrosceles), which is a highly threatened monkey due to habitat loss. We analyzed blood samples from 24 individuals from Kibale National Park (Uganda) using single-end RAD sequencing. We obtained 70,773,857 reads, of which 58,814,906 passed the filtering steps. Using the program STACKS v. 1.11 we identified 113,376 loci, of which 50,558 were polymorphic and had a mean observed heterozygosity of 0.25. These data will be used to study the effects of habitat fragmentation on genomic diversity, dispersal, and disease transmission in this species. Our approach provides a good example of the potential of RAD sequencing in studies of wild primate populations.
Authors
- Ruiz Lopez, Maria Jose ;
- Goldberg, Tony L. ;
- Chapman, Colin A. ;
- Omeja, Patrick A. ;
- Jones, James H. ;
- Switzer, William M. ;
- Etter, Paul D. ;
- Johnson, Eric A. ;
- Ting, Nelson
The emergence of pathogens represents substantial threats to public health, livestock, domesticated animals, and biodiversity. How wild populations respond to emerging pathogens has generated a lot of interest in the last two decades. With the recent advent of high-throughput sequencing technologies it is now possible to develop large transcriptomic resources for non-model organisms, hence allowing new research avenues on the immune responses of hosts from a large taxonomic spectra. We here focused on a wild population of the rostrum dace (Leuciscus burgiladensis) that is infected by Tracheliastes polycolpus, an emerging freshwater ectoparasite copepod. We used next generation Illumina sequencing technology to sequence the transcriptome of eight L. burdigalensis adult individuals collected in natura from the same sampling site. Four individuals were non-infected and four individuals were infected by T. polycolpus. We specifically focused on the spleen, the head kidney and epithelial cells and mucus from the fins, three tissues known to be involved in the immune response of fish. We used the Trinity methodology to reconstruct a de novo full-length transcriptome for L. burdigalensis. The resulting transcriptome will serve as an important broad-scale genomic resource for further studying the response of local population of L. burdigalensis to T. polycolpus pressures.
Authors
- Rey, Olivier ;
- Loot, Géraldine ;
- Bouchez, Olivier ;
- Blanchet, Simon ;
- Ruiz-Lopez, Maria Jose ;
- Ting, Nelson ;
- Etter, Paul D. ;
- Johnson, Eric A. ;
- Goldberg, Tony L. ;
- Chapman, Colin A. ;
- Jones, James H. ;
- Omeja, Patrick A. ;
- Switzer, William M.