Herbarium genomics: plastome sequence assembly from a range of herbarium specimens using an Iterative Organelle Genome Assembly pipeline

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Authors Freek T. Bakker, Di Lei, Jiaying Yu, Setareh Mohammadin, Zhen Wei, Sara van de Kerke, Barbara Gravendeel, Mathijs Nieuwenhuis, Martijn Staats, David E. Alquezar-Planas, Rens Holmer
Journal/Conference Name Biological Journal of the Linnean Society
Paper Category , ,
Paper Abstract Herbarium genomics is proving promising as next-generation sequencing approaches are well suited to deal with the usually fragmented nature of archival DNA. We show that routine assembly of partial plastome sequences from herbarium specimens is feasible, from total DNA extracts and with specimens up to 146 years old. We use genome skimming and an automated assembly pipeline, Iterative Organelle Genome Assembly, that assembles paired-end reads into a series of candidate assemblies, the best one of which is selected based on likelihood estimation. We used 93 specimens from 12 different Angiosperm families, 73 of which were from herbarium material with ages up to 146 years old. For 84 specimens, a sufficient number of paired-end reads were generated (in total 9.4 × 1012 nucleotides), yielding successful plastome assemblies for 74 specimens. Those derived from herbarium specimens have lower fractions of plastome-derived reads compared with those from fresh and silica-gel-dried specimens, but total herbarium assembly lengths are only slightly shorter. Specimens from wet-tropical conditions appear to have a higher number of contigs per assembly and lower N50 values. We find no significant correlation between plastome coverage and nuclear genome size (C value) in our samples, but the range of C values included is limited. Finally, we conclude that routine plastome sequencing from herbarium specimens is feasible and cost-effective (compared with Sanger sequencing or plastome-enrichment approaches), and can be performed with limited sample destruction.
Date of publication 2015
Code Programming Language Python

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