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Characterization of an EST Database for the Perennial Weed Leafy Spurge: An Important Resource for Weed Biology Research

Published online by Cambridge University Press:  20 January 2017

James V. Anderson ,
David P. Horvath ,
Wun S. Chao ,
Michael E. Foley ,
Alvaro G. Hernandez ,
Jyothi Thimmapuram ,
Lie Liu ,
George L. Gong ,
Mark Band  and
Ryan Kim
...Show all authors
James V. Anderson*
Affiliation:
USDA-ARS, Biosciences Research Laboratory, 1605 Albrecht Boulevard, Fargo, ND 58105
David P. Horvath
Affiliation:
USDA-ARS, Biosciences Research Laboratory, 1605 Albrecht Boulevard, Fargo, ND 58105
Wun S. Chao
Affiliation:
USDA-ARS, Biosciences Research Laboratory, 1605 Albrecht Boulevard, Fargo, ND 58105
Michael E. Foley
Affiliation:
USDA-ARS, Biosciences Research Laboratory, 1605 Albrecht Boulevard, Fargo, ND 58105
Alvaro G. Hernandez
Affiliation:
University of Illinois, W. M. Keck Center for Comparative and Functional Genomics, 1201 West Gregory Drive, Edward R. Madigan Laboratory, Urbana, IL 61801
Jyothi Thimmapuram
Affiliation:
University of Illinois, W. M. Keck Center for Comparative and Functional Genomics, 1201 West Gregory Drive, Edward R. Madigan Laboratory, Urbana, IL 61801
Lie Liu
Affiliation:
University of Illinois, W. M. Keck Center for Comparative and Functional Genomics, 1201 West Gregory Drive, Edward R. Madigan Laboratory, Urbana, IL 61801
George L. Gong
Affiliation:
University of Illinois, W. M. Keck Center for Comparative and Functional Genomics, 1201 West Gregory Drive, Edward R. Madigan Laboratory, Urbana, IL 61801
Mark Band
Affiliation:
University of Illinois, W. M. Keck Center for Comparative and Functional Genomics, 1201 West Gregory Drive, Edward R. Madigan Laboratory, Urbana, IL 61801
Ryan Kim
Affiliation:
University of Illinois, W. M. Keck Center for Comparative and Functional Genomics, 1201 West Gregory Drive, Edward R. Madigan Laboratory, Urbana, IL 61801
Mark A. Mikel
Affiliation:
University of Illinois, Department of Crop Sciences and Roy J. Carver Biotechnology Center, 1206 West Gregory Drive, 2610 Institute for Genomic Biology, Urbana, IL 61801
*
Corresponding author's E-mail: James.Anderson@ars.usda.gov.
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Abstract

Genomics programs in the weed science community have not developed as rapidly as that of other crop, horticultural, forestry, and model plant systems. Development of genomic resources for selected model weeds are expected to enhance our understanding of weed biology, just as they have in other plant systems. In this report, we describe the development, characteristics, and information gained from an expressed sequence tag (EST) database for the perennial weed leafy spurge. ESTs were obtained using a normalized cDNA library prepared from a comprehensive collection of tissues. During the EST characterization process, redundancy was minimized by periodic subtractions of the normalized cDNA library. A sequencing success rate of 88% yielded 45,314 ESTs with an average read length of 671 nucleotides. Using bioinformatic analysis, the leafy spurge EST database was assembled into 23,472 unique sequences representing 19,015 unigenes (10,293 clusters and 8,722 singletons). Blast similarity searches to the GenBank nonredundant protein database identified 18,186 total matches, of which 14,205 were nonredundant. These data indicate that 77.4% of the 23,472 unique sequences and 74.7% of the 19,015 unigenes are similar to other known proteins. Further bioinformatics analysis indicated that 2,950, or 15.5%, of the unigenes have previously not been identified suggesting that some may be novel to leafy spurge. Functional classifications assigned to leafy spurge unique sequences using Munich Information Center for Protein or Gene Ontology were proportional to functional classifications for genes of arabidopsis, with the exception of unclassified or unknowns and transposable elements which were significantly reduced in leafy spurge. Although these EST resources have been developed for the purpose of constructing high-density leafy spurge microarrays, they are already providing valuable information related to sugar metabolism, cell cycle regulation, dormancy, terpenoid secondary metabolism, and flowering.

Keywords

Leafy spurge, Euphorbia esula L. EPHESarabidopsis, Arabidopsis thaliana (L.) HeynhExpressed sequence taggenomicsleafy spurgeperennial weeds
Type
Weed Biology and Ecology
Information
Weed Science , Volume 55 , Issue 3 , June 2007 , pp. 193 - 203
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

Aharoni, A., Keizer, L. C. P., and Bouwmeester, H. J. et al. 2000. Identification of the SAAT gene involved in strawberry flavor biogenesis by use of DNA microarrays. Plant Cell. 12:647–661.CrossRefGoogle ScholarPubMed
Ali, S., Holloway, B., and Taylor, W. C. 2000. Normalization of cereal endosperm EST libraries for structural and functional genomic analysis. Plant Mol. Biol. Rep. 18:123–132.CrossRefGoogle Scholar
Altschul, S. F., Gish, W., Miller, W., Myers, E. W., and Lipman, D. J. 1990. Basic local alignment search tool. J. Mol. Biol. 215:403–410.CrossRefGoogle ScholarPubMed
Anderson, J. V. and Davis, D. G. 2004. Abiotic stress alters transcript profiles and activity of enzymes involved in glutathione-metabolism in Euphorbia esula . Physiol. Plant. 120:421–433.CrossRefGoogle Scholar
Anderson, J. V., Delseny, M., and Fregene, M. A. et al. 2004. An EST resource for cassava and other species of Euphorbiaceae. Plant Mol. Biol. 56:527–539.CrossRefGoogle ScholarPubMed
Anderson, J. V., Gesch, R. W., Jia, Y., Chao, W. S., and Horvath, D. P. 2005. Seasonal shifts in dormancy status, carbohydrate metabolism, and related gene expression in crown buds of leafy spurge. Plant Cell Environ. 28:1567–1578.CrossRefGoogle Scholar
Anderson, J. V. and Horvath, D. P. 2001. Random sequencing of cDNAs and identification of mRNAs. Weed Sci. 49:590–597.CrossRefGoogle Scholar
Arabidopsis Genome Initiative, The 2000. Analysis of the genome sequence of the flowering plant Arabidopsis thaliana . Nature. 408:796–815.CrossRefGoogle Scholar
Asamizu, E., Nakamura, Y., Sato, S., and Tabata, S. 2000a. Generation of 7137 non-redundant expressed sequence tags from a legume, Lotus japonicus . DNA Res. 7:127–130.CrossRefGoogle ScholarPubMed
Asamizu, E., Nakamura, Y., Sato, S., and Tabata, S. 2000b. Large scale analysis of cDNA in Arabidopsis thaliana: Generation of 12,028 non-redundant expressed sequence tags from normalized and size-selected cDNA libraries. DNA Res. 7 (3):175–180.CrossRefGoogle Scholar
Bangsund, D. A., Leistritz, F. L., and Leitch, J. A. 1999. Assessing economic impacts of biological control of weeds: The case of leafy spurge in northern Great Plains of the United States. J. Environ. Manag. 56:35–43.CrossRefGoogle Scholar
Basu, C., Halfhill, M. D., Mueller, T. C., and Stewart, C. N. 2004. Weed genomics: New tools to understand weed biology. Trends Plant Sci. 9:391–398.CrossRefGoogle ScholarPubMed
Benson, D. A., Karsch-Mizrach, I., Lipman, D. J., Ostell, J., and Wheeler, D. L. 2005. GenBank: Update. Nucleic Acids Res. 33:D34–D38.CrossRefGoogle Scholar
Boguski, M. S., Lowe, T. M. J., and Tolstoshev, C. M. 1993. dbEST-database for “expressed sequence tags,”. Nat. Genet. 4:332–333.CrossRefGoogle ScholarPubMed
Böhlenius, H., Huang, T., Charbonnel-Campaa, L., Brunner, A. M., Jansson, S., Strauss, S. H., and Nilsson, O. 2006. CO/FT regulatory module controls timing of flowering and seasonal growth cessation in trees. Science. 312:1040–1043.CrossRefGoogle ScholarPubMed
Bonaldo, M. F., Lennon, G., and Soares, M. B. 1996. Normalization and subtraction: Two approaches to facilitate gene discovery. Genome Res. 6:791–806.CrossRefGoogle ScholarPubMed
Cadman, C. S. C., Toorop, P. E., Hilhorst, H. W. M., and Finch-Savage, W. E. 2006. Gene expression profiles of arabidopsis Cvi seeds during dormancy cycling indicate a common underlying dormancy control mechanism. Plant J. 46:805–822.CrossRefGoogle ScholarPubMed
Chang, S., Puryer, J., and Cairney, J. 1993. A simple and efficient method for isolating RNA from pine trees. Plant Mol. Biol. Rep. 11:113–116.CrossRefGoogle Scholar
Chao, W.S. and J.V. Anderson 2004. Euphorbia esula . In:. Crop Protection Compendium, 2004 ed. Wallingford, UK CAB International.Google Scholar
Chao, W. S., Horvath, D. P., Anderson, J. V., and Foley, M. P. 2005. Potential model weeds to study genomics, ecology, and physiology in the 21st century. Weed Science. 53:929–937.CrossRefGoogle Scholar
Chao, W. S., Serpe, M. D., Anderson, J. V., Gesch, R. W., and Horvath, D. P. 2006. Sugars, hormones, and environment affect the dormancy status in underground adventitious buds of leafy spurge (Euphorbia esula L.). Weed Sci. 54:59–68.CrossRefGoogle Scholar
Coupland, R. T., Selleck, G. W., and Alex, J. F. 1955. Distribution of vegetative buds on the underground parts of leafy spurge (Euphorbia esula L.). Can. J. Agric. Sci. 35:161–167.Google Scholar
Ewing, B. and Green, P. 1998. Base-calling of automated sequencer traces using phred. II. Error probabilities. Genome Res. 8:186–194.CrossRefGoogle ScholarPubMed
Ewing, B., Hillier, L., Wendl, M. C., and Green, P. 1998. Base-calling of automated sequencer traces using phred. I. Accuracy assessment. Genome Res. 8:175–185.CrossRefGoogle ScholarPubMed
Garcia-Hernandez, M., Berardini, T. Z., and Chen, G. et al. 2002. TAIR: A resource for integrated arabidopsis data. Funct. Integr. Genomics. 2:239–253.CrossRefGoogle Scholar
Gene Ontology Consortium 2004. The gene ontology (GO) database and informatics resource. Nucleic Acids Res. 32:D258–D261.CrossRefGoogle Scholar
Gutierrez, R. A., Ewing, R. M., Cherry, J. M., and Green, P. J. 2002. Identification of unstable transcripts in arabidopsis by cDNA microarray analysis: Rapid decay is associated with a group of touch and specific clock-controlled genes. Proc. Natl. Acad. Sci. USA. 99 (17):11513–11518.CrossRefGoogle ScholarPubMed
Horvath, D. P., Anderson, J. V., Soto, M., and Chao, W. S. 2006. Transcriptome analysis of leafy spurge (Euphorbia esula L.) crown buds during shifts in well-defined phases of dormancy. Weed Sci. 54:821–827.CrossRefGoogle Scholar
Horvath, D. P., Chao, W. S., and Anderson, J. V. 2002. Molecular analysis of signals controlling dormancy and growth in underground adventitious buds of leafy spurge (Euphorbia esula L.). Plant Physiol. 128:1439–1446.CrossRefGoogle Scholar
Horvath, D. P., Schaffer, R., West, M., and Wisman, E. 2003. Arabidopsis microarrays identify conserved and differentially-expressed genes involved in shoot growth and development from distantly related plant species. Plant J. 34:125–134.CrossRefGoogle ScholarPubMed
Horvath, D. P., Soto, M., Jia, Y., Chao, W. S., and Anderson, J. V. 2005. Transcriptome analysis of paradormancy release in root buds of leafy spurge (Euphorbia esula). Weed Sci. 53:795–801.CrossRefGoogle Scholar
Huang, H. and Madan, A. 1999. CAP3: A DNA sequence assembly program. Genome Res. 9:868–877.CrossRefGoogle ScholarPubMed
International Rice Genome Sequencing Project 2005. The map-based sequence of the rice genome. Nature. 436:793–800.CrossRefGoogle Scholar
Kloosterman, B., Vorst, O., Hall, R. D., Visser, R. G. F., and Bachem, C. W. 2005. Tuber on a chip: Differential gene expression during potato tuber development. Plant Biotech. J. 3:505–519.CrossRefGoogle ScholarPubMed
Kumar, C. G., LeDuc, R., Gong, G., Roinishivili, L., Lewin, H. A., and Liu, L. 2004. ESTIMA, a tool for EST management in a multi-project environment. BMC Bioinf. 5:176.CrossRefGoogle Scholar
Lee, J. M., Williams, M. E., Tingey, S. V., and Rafalski, J. A. 2002. DNA array profiling of gene expression changes during maize embryo development. Funct. Integr. Genomics. 2:13–27.CrossRefGoogle ScholarPubMed
Leitch, J. A., Leistritz, F. L., and Bangsund, D. A. 1996. Economic effect of leafy spurge in the upper Great Plains: Methods, models, and results. Impact Assess. 14:419–433.CrossRefGoogle Scholar
Liu, L., Roinishvili, L., Pan, X., Liu, Z., and Kumar, C. 2000. GPMS A Web based Genome Project Management System. Pages 62–67. in. Proceeding of the 4th World Multi-conference on Systematics, Cybernectics, and Informatics SCI2000.Google Scholar
Marshall, E. 2004. Getting the noise out of gene arrays. Science. 306:630–631.CrossRefGoogle ScholarPubMed
McGinnis, S. and Madden, T. L. 2004. BLAST: At the core of a powerful and diverse set of sequence analysis tools. Nucleic Acid Res. 32:W20–W25.CrossRefGoogle ScholarPubMed
Mewes, H. W., Frishman, D., and Güldener, U. et al. 2002. MIPS: A database for genomes and protein sequences. Nucleic Acids Res. 30:31–34.CrossRefGoogle ScholarPubMed
Ohlrogge, J. and Benning, C. 2000. Unravelling plant metabolism by EST analysis. Curr. Opin. Plant Biol. 3:224–228.CrossRefGoogle ScholarPubMed
Oztur, Z. N., Talame, V., Deyholos, M., Michalowski, C. B., Galbraith, D. W., Gozukirmizi, N., Tuberosa, R., and Bohnert, H. J. 2002. Monitoring large-scale changes in transcript abundance in drought- and salt-stressed barley. Plant Mol. Biol. 48:551–573.CrossRefGoogle ScholarPubMed
Potokina, E., Sreenivasulu, N., Altschmied, L., Michalek, W., and Graner, A. 2002. Differential gene expression during seed germination in barley (Hordeum vulgare L.). Funct. Integr. Genomics. 2:28–39.CrossRefGoogle ScholarPubMed
Quackenbush, R. C., Cho, J., and Lee, D. et al. 2001. The TIGR Gene Indices: Analysis of gene transcript sequences in highly sampled eukaryotic species. Nucleic Acids Res. 29:159–164.CrossRefGoogle ScholarPubMed
Reymond, P., Weber, H., Damond, M., and Farmer, E. E. 2000. Differential gene expression in response to mechanical wounding and insect feeding in arabidopsis. Plant Cell. 12:707–719.CrossRefGoogle ScholarPubMed
Richmond, T. and Somerville, S. 2000. Chasing the dream: Plant EST microarrays. Curr. Opin. Plant Biol. 3:108–116.CrossRefGoogle ScholarPubMed
Schena, M., Shalon, D., Davis, R. W., and Brown, P. O. 1995. Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science. 270:467–470.CrossRefGoogle ScholarPubMed
Schoof, H., Zaccaria, P., Gundlach, H., Lemcke, K., Rudd, S., Kolesov, G., Arnold, R., Mewes, H. W., and Mayer, K. F. X. 2002. MIPS Arabidopsis thaliana database (MAtDB): An integrated biological knowledge resource based on the first complete plant genome. Nucleic Acids Res. 30: 91–93.CrossRefGoogle ScholarPubMed
Schrader, J., Moyle, R., Bhalerao, R., Hertzberg, M., Lundeberg, J., Nilsson, P., and Bhalerao, R. P. 2004. Cambial meristem dormancy in trees involves extensive remodeling of the transcriptome. Plant J. 40:173–187.CrossRefGoogle ScholarPubMed
Smit, A. F., Hubley, R., and Green, P. 1996–2004. RepeatMasker Open-3.0. http://www.repeatmasker.org.Google Scholar
Soares, M. B., Bonaldo, M. F., Jelene, P., Su, L., Lawton, L., and Efstratiadis, F. 1994. Construction and characterization of a normalized cDNA library. Proc. Natl. Acad. Sci. USA. 91:9228–9232.CrossRefGoogle ScholarPubMed
Sonju, R. and Horvath, D. P. 2005. Cloning and expression of Krp genes from adventitious buds of the perennial weed leafy spurge. Pages 31. in. 2005 Midwest American Society of Plant Biology Sectional Meeting. Donald Danforth Plant Science Center, St. Louis, MO. July 18–19. [Abstract].Google Scholar
van Hal, N. L. W., Vorst, O., van Houwelingen, A. M. M. L., Kok, E. J., Peijnenburg, A., Aharoni, A., van Tunen, A. J., and Keijer, J. 2000. The application of microarrays in gene expression analysis. J. Biotech. 78:271–280.CrossRefGoogle ScholarPubMed
Wheeler, D. L., Church, D. M., and Edgar, R. et al. 2004. Database resources of the National Center for Biotechnology Information: Update. Nucleic Acids Res. 32:D35–D40.CrossRefGoogle ScholarPubMed
Zhu, T., Budworth, P., and Chen, W. et al. 2003. Transcriptional control of nutrient partitioning during rice grain filling. Plant Biotech. J. 1:59–70.CrossRefGoogle ScholarPubMed