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BMC Ecol. 2013 Mar 14;13:8. doi: 10.1186/1472-6785-13-8.

Capturing chloroplast variation for molecular ecology studies: a simple next generation sequencing approach applied to a rainforest tree.

Author information

  • 1National Herbarium of NSW, The Royal Botanic Gardens and Domain Trust, Mrs Macquaries Road, 2000, Sydney, NSW, Australia. hannah.mcpherson@rbgsyd.nsw.gov.au

Abstract

BACKGROUND:

With high quantity and quality data production and low cost, next generation sequencing has the potential to provide new opportunities for plant phylogeographic studies on single and multiple species. Here we present an approach for in silicio chloroplast DNA assembly and single nucleotide polymorphism detection from short-read shotgun sequencing. The approach is simple and effective and can be implemented using standard bioinformatic tools.

RESULTS:

The chloroplast genome of Toona ciliata (Meliaceae), 159,514 base pairs long, was assembled from shotgun sequencing on the Illumina platform using de novo assembly of contigs. To evaluate its practicality, value and quality, we compared the short read assembly with an assembly completed using 454 data obtained after chloroplast DNA isolation. Sanger sequence verifications indicated that the Illumina dataset outperformed the longer read 454 data. Pooling of several individuals during preparation of the shotgun library enabled detection of informative chloroplast SNP markers. Following validation, we used the identified SNPs for a preliminary phylogeographic study of T. ciliata in Australia and to confirm low diversity across the distribution.

CONCLUSIONS:

Our approach provides a simple method for construction of whole chloroplast genomes from shotgun sequencing of whole genomic DNA using short-read data and no available closely related reference genome (e.g. from the same species or genus). The high coverage of Illumina sequence data also renders this method appropriate for multiplexing and SNP discovery and therefore a useful approach for landscape level studies of evolutionary ecology.

PMID:
23497206
[PubMed - indexed for MEDLINE]
PMCID:
PMC3605380
Free PMC Article

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