The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Unlocking the vault: next‐generation museum population genomics
Open accessAbstract
Natural history museum collections provide unique resources for understanding how species respond to environmental change, including the abrupt, anthropogenic climate change of the past century. Ideally, researchers would conduct genome‐scale screening of museum specimens to explore the evolutionary consequences of environmental changes, but to date such analyses have been severely limited by the numerous challenges of working with the highly degraded DNA typical of historic samples. Here, we circumvent these challenges by using custom, multiplexed, exon capture to enrich and sequence ~11 000 exons (~4 Mb) from early 20th‐century museum skins. We used this approach to test for changes in genomic diversity accompanying a climate‐related range retraction in the alpine chipmunks (T amias alpinus) in the high Sierra Nevada area of California, USA. We developed robust bioinformatic pipelines that rigorously detect and filter out base misincorporations in DNA derived from skins, most of which likely resulted from postmortem damage. Furthermore, to accommodate genotyping uncertainties associated with low‐medium coverage data, we applied a recently developed probabilistic method to call single‐nucleotide polymorphisms and estimate allele frequencies and the joint site frequency spectrum. Our results show increased genetic subdivision following range retraction, but no change in overall genetic diversity at either nonsynonymous or synonymous sites. This case study showcases the advantages of integrating emerging genomic and statistical tools in museum collection‐based population genomic applications. Such technical advances greatly enhance the value of museum collections, even where a pre‐existing reference is lacking and points to a broad range of potential applications in evolutionary and conservation biology.
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Cites
The Sequence Alignment/Map format and SAMtools
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Sequencing of 50 Human Exomes Reveals Adaptation to High Altitude
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“…adequate to naively call genotypes for each individual with high confidence by counting alleles, we used a SNP calling and allele frequency estimation method based on genotype likelihoods that uses information from all individuals at all sites simultaneously (Yi et al. 2010; Nielsen et al. 2012).”
BackgroundMethodSelf-citationReliable genotyping of samples with very low DNA quantities using PCR
Taberlet, P. (1996) · Nucleic Acids Research · doi:10.1093/nar/24.16.3189 · Cited by 1,491
Genotype and SNP calling from next-generation sequencing data
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Self-citationPatterns of damage in genomic DNA sequences from a neandertal
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Temporal patterns of nucleotide misincorporations and DNA fragmentation in ancient DNA
Sawyer, S., Krause, J., Guschanski, K., Savolainen, V., & Pääbo, S. (2012) · PLoS ONE · doi:10.1371/journal.pone.0034131 · Cited by 489
Nielsen, R., Korneliussen, T., Albrechtsen, A., Li, Y., & Wang, J. (2012) · PLoS ONE · doi:10.1371/journal.pone.0037558 · Cited by 424 · cited 9×
“A detailed description of the algorithms employed by ANGSD can be found at http://popgen.dk/wiki/index. php/ANGSD and in Nielsen et al. (2012).”
BackgroundMethodInfluentialSelf-citationmapDamage: testing for damage patterns in ancient DNA sequences
Ginolhac, A., Rasmussen, M., Gilbert, M. T. P., Willerslev, E., & Orlando, L. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr347 · Cited by 363
Climate-induced range contraction drives genetic erosion in an alpine mammal
Rubidge, E. M., Patton, J. L., Lim, M., Burton, A. C., Brashares, J. S., & Moritz, C. (2012) · Nature Climate Change · doi:10.1038/nclimate1415 · Cited by 169
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Cited by
Population genomics for wildlife conservation and management
Hohenlohe, P. A., Funk, W. C., & Rajora, O. P. (2021) · Molecular Ecology · doi:10.1111/mec.15720 · Cited by 702
Mining museums for historical DNA: advances and challenges in museomics
Raxworthy, C. J., & Smith, B. T. (2021) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2021.07.009 · Cited by 311
Biological invasions, climate change and genomics
Chown, S. L., Hodgins, K. A., Griffin, P. C., Oakeshott, J. G., Byrne, M., & Hoffmann, A. A. (2015) · Evolutionary Applications · doi:10.1111/eva.12234 · Cited by 284
Quantifying Temporal Genomic Erosion in Endangered Species
Díez-del-Molino, D., Sánchez-Barreiro, F., Barnes, I., Gilbert, M. T. P., & Dalén, L. (2018) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2017.12.002 · Cited by 258
The York Gospels: a 1000-year biological palimpsest
Teasdale, M. D., Fiddyment, S., Vnouček, J., Mattiangeli, V., Speller, C., Binois, A., Carver, M., Dand, C., Newfield, T. P., Webb, C. C., et al. (2017) · Royal Society Open Science · doi:10.1098/rsos.170988 · Cited by 75
Metadata
- Authors
- Bi, K., Linderoth, T., Vanderpool, D., Good, J. M., Nielsen, R., & Moritz, C.
- Venue
- Molecular Ecology
- Publisher
- Wiley
- Published
- 2013-10-07
- Volume
- 22
- Issue
- 24
- Pages
- 6018-6032
- ISSN
- 0962-1083 (ISSN-L)
- 1365-294X
- OpenAlex
- W2167227133
- Cited by
- 381
- References
- 11
- FWCI
- 19.02
- Type
- journal article
- Language
- en
- Open access
- green
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