Automated Author Profile

Buchalski, Michael R.

California Department of Fish and Wildlife

Current S-Index

1.2

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

0.6

Average Dataset Index per dataset

Total Datasets

2

Total datasets for this author

Average FAIR Score

88.5%

Average FAIR Score per dataset

Total Citations

2

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Data and code from: A multifaceted approach reveals complex genomic mediation of white-nose syndrome resistance in the little brown bat (<em>Myotis lucifugus</em>) (Version: 5)

Novel pathogens have become a major challenge faced by wildlife in the Anthropocene. White-nose syndrome (WNS), a fungal pathogen, has decimated bat populations across North America over the last two decades. Demographic and physiological evidence of resistance in one heavily affected species, Myotis lucifugus, has prompted multiple attempts to delineate the genomic underpinnings, but they show little congruence in their findings. This may be due, in part, to the limitations of the genomic resources utilized and/or analytical approaches employed. Here, we performed high-coverage whole-genome resequencing of M. lucifugus sampled prior to (n = 29) and 10 years after the arrival of WNS (n = 30), aligned to a new reference genome to identify signatures of selection associated with pathogen resistance. Using 41.9 million SNPs, we implemented a combination of hard and soft sweep detection analyses, leading to discovery of 405 genes with robust evidence of selection. Of these, 241 (59.5 %) were associated with enriched gene ontology (GO) terms, many of which were tied to neuron development, organization, and function. Further, approximately half (120) of genes associated with enriched GO terms interact with genes identified by previous studies. Our findings suggest WNS resistance is mediated through highly complex, polygenic mechanisms. Further, we demonstrate there are far more connections among WNS selection study results than previously recognized. We believe that the methods employed by our study illustrate a need for a paradigm shift in non-model selection studies and further highlight the value of genomics as a tool for conservation management.

Authors

  • Capel, Samantha Lucy Rita ;
  • Fraser, Devaughn L. ;
  • Field, Kenneth A. ;
  • Reeder, DeeAnn M. ;
  • Russell, Amy L. ;
  • Sudmant, Peter H. ;
  • Vazquez, Juan Manuel ;
  • Vonhof, Maarten J. ;
  • Lilley, Thomas M. ;
  • Buchalski, Michael R.
0 Citations0 Mentions88% FAIR0.5 Dataset Index
10.5061/dryad.ncjsxkt662026

Data and Code from: A genome assembly of the North American golden eagle, <em>Aquila chrysaetos canadensis</em> (Version: 7)

The golden eagle (Aquila chrysaetos) is an apex predator across its Holarctic range. Although chromosome-level reference genome assemblies are available for two of the six golden eagle subspecies (European and Japanese), current assemblies for the North American subspecies (A. c. canadensis) were generated using short-read sequencing technology, limiting completeness, contiguity, and accuracy. Here we present a chromosome-length de novo genome assembly for A. c. canadensis as part of the California Conservation Genomics Project (CCGP). We used Pacific Biosciences HiFi reads and Omni-C chromatin-proximity sequencing to produce a high-quality assembly consistent with the standard CCGP reference genome protocol. Our assembly spans 1.28 Gbp and comprises 316 scaffolds with a scaffold N50 of 47.3 Mbp, a contig N50 of 47.0 Mbp, and a benchmarking universal single-copy ortholog (BUSCO) completeness score of 97.4%. This reference genome assembly offers a valuable resource for delineating genomic variation and assessing conservation needs in golden eagle populations across California and its North American range more broadly.

Authors

  • Capel, Samantha Lucy Rita ;
  • Fisher, Robert N. ;
  • Escalona, Merly ;
  • Bloom, Peter H. ;
  • Chumchim, Noravit ;
  • Fairbairn, Colin W. ;
  • Nguyen, Oanh H. ;
  • Sahasrabudhe, Ruta M. ;
  • Seligmann, William E. ;
  • Katzner, Todd E. ;
  • Shaffer, H. Bradley ;
  • Buchalski, Michael R.
2 Citations0 Mentions88% FAIR1.2 Dataset Index
10.5061/dryad.2280gb65r2026