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Hybridization ddRAD-sequencing for population genomics of nonmodel plants using highly degraded historical specimen DNA

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Lang,  PLM
Department Molecular Biology, Max Planck Institute for Developmental Biology, Max Planck Society;

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Weiß,  CL
Department Molecular Biology, Max Planck Institute for Developmental Biology, Max Planck Society;

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Kersten,  S
Department Molecular Biology, Max Planck Institute for Developmental Biology, Max Planck Society;

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Latorre,  SM
Department Molecular Biology, Max Planck Institute for Developmental Biology, Max Planck Society;

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Burbano,  HA
Department Molecular Biology, Max Planck Institute for Developmental Biology, Max Planck Society;

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Citation

Lang, P., Weiß, C., Kersten, S., Latorre, S., Nagel, S., Nickel, B., et al. (2020). Hybridization ddRAD-sequencing for population genomics of nonmodel plants using highly degraded historical specimen DNA. Molecular Ecology Resources, 20(5), 1228-1247. doi:10.1111/1755-0998.13168.


Cite as: https://hdl.handle.net/21.11116/0000-000A-5D23-7
Abstract
Abstract Species’ responses at the genetic level are key to understanding the long-term consequences of anthropogenic global change. Herbaria document such responses, and, with contemporary sampling, provide high-resolution time-series of plant evolutionary change. Characterizing genetic diversity is straightforward for model species with small genomes and a reference sequence. For nonmodel species—with small or large genomes—diversity is traditionally assessed using restriction-enzyme-based sequencing. However, age-related DNA damage and fragmentation preclude the use of this approach for ancient herbarium DNA. Here, we combine reduced-representation sequencing and hybridization-capture to overcome this challenge and efficiently compare contemporary and historical specimens. Specifically, we describe how homemade DNA baits can be produced from reduced-representation libraries of fresh samples, and used to efficiently enrich historical libraries for the same fraction of the genome to produce compatible sets of sequence data from both types of material. Applying this approach to both Arabidopsis thaliana and the nonmodel plant Cardamine bulbifera, we discovered polymorphisms de novo in an unbiased, reference-free manner. We show that the recovered genetic variation recapitulates known genetic diversity in A. thaliana, and recovers geographical origin in both species and over time, independent of bait diversity. Hence, our method enables fast, cost-efficient, large-scale integration of contemporary and historical specimens for assessment of genome-wide genetic trends over time, independent of genome size and presence of a reference genome.