Journal Article

Sequencing Angiosperm Plastid Genomes Made Easy: A Complete Set of Universal Primers and a Case Study on the Phylogeny of Saxifragales

Wenpan Dong, Chao Xu, Tao Cheng, Kui Lin and Shiliang Zhou

in Genome Biology and Evolution

Published on behalf of Society for Molecular Biology and Evolution

Volume 5, issue 5, pages 989-997
Published in print January 2013 |
Published online April 2013 | e-ISSN: 1759-6653 | DOI: https://dx.doi.org/10.1093/gbe/evt063

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Plastid genomes are an invaluable resource for plant biological studies. However, the number of completely sequenced plant plastid genomes is still small compared with the vast number of species. To provide an alternative generalized approach, we designed a set of 138 pairs of universal primers for amplifying (termed “short-range PCR”) and sequencing the entire genomes of the angiosperm plastid genomes. The universality of the primers was tested by using species from the basal to asterid angiosperms. The polymerase chain reaction (PCR) success rate was higher than 96%. We sequenced the complete chloroplast genome of Liquidambar formosana as an example using this method and compared it to the genomes independently determined by long-range PCR (from 6.3 kb to 13.3 kb) and next-generation sequencing methods. The three genomes showed that they were completely identical. To test the phylogenetic efficiency of this method, we amplified and sequenced 18 chloroplast regions of 19 Saxifragales and Saxifragales-related taxa, as a case study, to reconstruct the phylogeny of all families of the order. Phylograms based on a combination of our data, together with those from GenBank, clearly indicate three family groups and three single families within the order. This set of universal primers is expected to accelerate the accumulation of angiosperm plastid genomes and to make faster mass data collection of plastid genomes for molecular systematics.

Keywords: plastid genome; universal primers; Saxifragales

Journal Article.  4706 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology ; Evolutionary Biology ; Genetics and Genomics

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