Plants (Apr 2020)

The Treasure Vault Can be Opened: Large-Scale Genome Skimming Works Well Using Herbarium and Silica Gel Dried Material

  • Inger Greve Alsos,
  • Sebastien Lavergne,
  • Marie Kristine Føreid Merkel,
  • Marti Boleda,
  • Youri Lammers,
  • Adriana Alberti,
  • Charles Pouchon,
  • France Denoeud,
  • Iva Pitelkova,
  • Mihai Pușcaș,
  • Cristina Roquet,
  • Bogdan-Iuliu Hurdu,
  • Wilfried Thuiller,
  • Niklaus E. Zimmermann,
  • Peter M. Hollingsworth,
  • Eric Coissac

DOI
https://doi.org/10.3390/plants9040432
Journal volume & issue
Vol. 9, no. 4
p. 432

Abstract

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Genome skimming has the potential for generating large data sets for DNA barcoding and wider biodiversity genomic studies, particularly via the assembly and annotation of full chloroplast (cpDNA) and nuclear ribosomal DNA (nrDNA) sequences. We compare the success of genome skims of 2051 herbarium specimens from Norway/Polar regions with 4604 freshly collected, silica gel dried specimens mainly from the European Alps and the Carpathians. Overall, we were able to assemble the full chloroplast genome for 67% of the samples and the full nrDNA cluster for 86%. Average insert length, cover and full cpDNA and rDNA assembly were considerably higher for silica gel dried than herbarium-preserved material. However, complete plastid genomes were still assembled for 54% of herbarium samples compared to 70% of silica dried samples. Moreover, there was comparable recovery of coding genes from both tissue sources (121 for silica gel dried and 118 for herbarium material) and only minor differences in assembly success of standard barcodes between silica dried (89% ITS2, 96% matK and rbcL) and herbarium material (87% ITS2, 98% matK and rbcL). The success rate was > 90% for all three markers in 1034 of 1036 genera in 160 families, and only Boraginaceae worked poorly, with 7 genera failing. Our study shows that large-scale genome skims are feasible and work well across most of the land plant families and genera we tested, independently of material type. It is therefore an efficient method for increasing the availability of plant biodiversity genomic data to support a multitude of downstream applications.

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