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

Journal Article · · BMC Genomics
 [1];  [2];  [3];  [4];  [5];  [6];  [7];  [8]
  1. Univ. of Southern California, Los Angeles, CA (United States). Quantitative and Computational Biology Program; DOE/OSTI
  2. Univ. of Southern California, Los Angeles, CA (United States). Quantitative and Computational Biology Program
  3. USDA Forest Service, Corvallis, OR (United States). Pacific Northwest Research Station
  4. DNA4 Technologies, LLC, Baltimore, MD (United States)
  5. New Mexico State Univ., Las Cruces, NM (United States). Conservation Genomics Lab.
  6. World Resources Inst., Washington, DC (United States)
  7. National Inst. of Health (NIH), Bethesda, MD (United States). National Library of Medicine. National Center for Biotechnology Information
  8. Univ. of Southern California, Los Angeles, CA (United States). Quantitative and Computational Biology Program; Fudan Univ., Shanghai (China). School of Mathematical Sciences. Centre for Computational Systems Biology

Background: The 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. Results: In this paper, we report the success of an alignment-free genome comparison method, d 2; 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. Conclusions: This 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.

Research Organization:
Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
Grant/Contract Number:
SC0014664
OSTI ID:
1626818
Journal Information:
BMC Genomics, Journal Name: BMC Genomics Journal Issue: 1 Vol. 19; ISSN 1471-2164
Publisher:
SpringerCopyright Statement
Country of Publication:
United States
Language:
English

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