The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Practical low‐coverage genomewide sequencing of hundreds of individually barcoded samples for population and evolutionary genomics in nonmodel species
Abstract
Today most population genomic studies of nonmodel organisms either sequence a subset of the genome deeply in each individual or sequence pools of unlabelled individuals. With a step‐by‐step workflow, we illustrate how low‐coverage whole‐genome sequencing of hundreds of individually barcoded samples is now a practical alternative strategy for obtaining genomewide data on a population scale. We used a highly efficient protocol to generate high‐quality libraries for ~6.5 USD from each of 876 Atlantic silversides (a teleost fish with a genome size ~730 Mb) that we sequenced to 1–4× genome coverage. In the absence of a reference genome, we developed a bioinformatic pipeline for mapping the genomic reads to a de novo assembled reference transcriptome. This provides an ‘in silico’ method for exome capture that avoids the complexities and expenses of using wet chemistry for target isolation. Using novel tools for analysis of low‐coverage data, we extracted population allele frequencies, individual genotype likelihoods and polymorphism data for 2 504 335 SNP s across the exome for the 876 fish. To illustrate the use of the resulting data, we present a preliminary analysis of geographical patterns in the exome data and a comparison of complete mitochondrial genome sequences for each individual (constructed from the low‐coverage data) that show population colonization patterns along the US east coast. With a total cost per sample of less than 50 USD (including sequencing) and ability to prepare 96 libraries in only 5 h, our approach adds a viable new option to the population genomics toolbox.
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Cites
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Magoč, T., & Salzberg, S. L. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr507 · Cited by 15,366
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Wang, Z., Gerstein, M., & Snyder, M. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2484 · Cited by 13,174
Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration
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A fast, lock-free approach for efficient parallel counting of occurrences of k -mers
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ANGSD: Analysis of Next Generation Sequencing Data
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Genotype and SNP calling from next-generation sequencing data
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Inexpensive Multiplexed Library Preparation for Megabase-Sized Genomes
Baym, M., Kryazhimskiy, S., Lieberman, T. D., Chung, H., Desai, M. M., & Kishony, R. (2015) · PLOS ONE · doi:10.1371/journal.pone.0128036 · Cited by 685
Cited by
A beginner's guide to low‐coverage whole genome sequencing for population genomics
Lou, R. N., Jacobs, A., Wilder, A. P., & Therkildsen, N. O. (2021) · Molecular Ecology · doi:10.1111/mec.16077 · Cited by 334
Self-citationA demonstration of conservation genomics for threatened species management
Wright, B. R., Farquharson, K. A., McLennan, E. A., Belov, K., Hogg, C. J., & Grueber, C. E. (2020) · Molecular Ecology Resources · doi:10.1111/1755-0998.13211 · Cited by 69
Metadata
- Authors
- Therkildsen, N. O., & Palumbi, S. R.
- Venue
- Molecular Ecology Resources
- Publisher
- Wiley
- Published
- 2016-08-29
- Volume
- 17
- Issue
- 2
- Pages
- 194-208
- ISSN
- 1755-098X (ISSN-L)
- 1755-0998
- OpenAlex
- W2478924953
- Cited by
- 173
- References
- 7
- FWCI
- 4.66
- Type
- journal article
- Language
- en
- Open access
- closed
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