Alignment-free genome comparison enables accurate geographic sourcing of white oak DNA

Kujin Tang,Fengzhu Sun,John L Spouge,Richard Cronn,Brook G Milligan,David L Erickson,Jie Ren,Meaghan Parker-Forney

doi:10.1186/s12864-018-5253-1

Abstract

BackgroundThe application of genomic data and bioinformatics for the identification of restricted or illegally-sourced natural products is urgently needed. The taxonomic identity and geographic provenance of raw and processed materials have implications in sustainable-use commercial practices, and relevance to the enforcement of laws that regulate or restrict illegally harvested materials, such as timber. Improvements in genomics make it possible to capture and sequence partial-to-complete genomes from challenging tissues, such as wood and wood products.ResultsIn this paper, we report the success of an alignment-free genome comparison method, {d}_2^{ast }, that differentiates different geographic sources of white oak (Quercus) species with a high level of accuracy with very small amount of genomic data. The method is robust to sequencing errors, different sequencing laboratories and sequencing platforms.ConclusionsThis method offers an approach based on genome-scale data, rather than panels of pre-selected markers for specific taxa. The method provides a generalizable platform for the identification and sourcing of materials using a unified next generation sequencing and analysis framework.

Highlights

The application of genomic data and bioinformatics for the identification of restricted or illegally-sourced natural products is urgently needed
Using next generation sequencing (NGS) data from 92 white oaks from North America (NA), Europe (EU), and Asia (AS), we show that for each sample the two most similar white oak trees according to the dÃ2 dissimilarity measure are from the same geographic provenance based on small sequencing quantities (e.g., 50 Mbp)
Genomic dissimilarity analyses based on dÃ2 resolve oak geographic origins We used six alignment-free distance/dissimilarity measures (Manhattan, Euclid, d2 [26], CVTree [16], dÃ2 and ds2 [17,18,19]) based on the relative frequencies of k-mers to calculate pairwise distances of white oak tree samples based on DNA samples of 50, 100 and 300 Mbp

Summary

Introduction

The application of genomic data and bioinformatics for the identification of restricted or illegally-sourced natural products is urgently needed. To mitigate trafficking of illegally-sourced wood, the United States (2008), European Union (2010) and Australia (2012) adopted regulations that prohibit the import, export, transport, purchase or sale of illegally harvested timber and plant products. These regulations can impose civil and criminal penalties on buyers and suppliers of wood products who fail to adopt “due care” controls. A key component of due care is that wood or wood products entering or exiting the U.S must declare the scientific name and geographic source of the wood Despite this requirement, mislabeling and document falsification are widespread because few methods are available to validate these declarations [4]

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Conclusion