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1 September 2009 Evolution of Weediness and Invasiveness: Charting the Course for Weed Genomics
C. Neal Stewart, Patrick J. Tranel, David P. Horvath, James V. Anderson, Loren H. Rieseberg, James H. Westwood, Carol A. Mallory-Smith, Maria L. Zapiola, Katrina M. Dlugosch
Author Affiliations +
Abstract

The genetic basis of weedy and invasive traits and their evolution remain poorly understood, but genomic approaches offer tremendous promise for elucidating these important features of weed biology. However, the genomic tools and resources available for weed research are currently meager compared with those available for many crops. Because genomic methodologies are becoming increasingly accessible and less expensive, the time is ripe for weed scientists to incorporate these methods into their research programs. One example is next-generation sequencing technology, which has the advantage of enhancing the sequencing output from the transcriptome of a weedy plant at a reduced cost. Successful implementation of these approaches will require collaborative efforts that focus resources on common goals and bring together expertise in weed science, molecular biology, plant physiology, and bioinformatics. We outline how these large-scale genomic programs can aid both our understanding of the biology of weedy and invasive plants and our success at managing these species in agriculture. The judicious selection of species for developing weed genomics programs is needed, and we offer up choices, but no Arabidopsis-like model species exists in the world of weeds. We outline the roadmap for creating a powerful synergy of weed science and genomics, given well-placed effort and resources.

C. Neal Stewart, Patrick J. Tranel, David P. Horvath, James V. Anderson, Loren H. Rieseberg, James H. Westwood, Carol A. Mallory-Smith, Maria L. Zapiola, and Katrina M. Dlugosch "Evolution of Weediness and Invasiveness: Charting the Course for Weed Genomics," Weed Science 57(5), 451-462, (1 September 2009). https://doi.org/10.1614/WS-09-011.1
Received: 14 January 2009; Accepted: 1 April 2009; Published: 1 September 2009
KEYWORDS
bioinformatics
DNA sequencing
gene expression
genetic transformation
genomics
systems biology
weed biology
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