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Molecular Insight Into Mirabilis Rotundifolia (Greene) Standley to Improve Management Decisions

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Molecular Insight Into Mirabilis Rotundifolia (Greene) Standley to Improve Management Decisions Molecular Insight into Mirabilis rotundifolia (Greene) Standley to Improve Management Decisions A Master’s Thesis Presented to the Faculty of the College of Science and Mathematics Colorado State University-Pueblo Pueblo, Colorado In Partial Fulfillment of the Requirements for the Degree of Master of Science in Biology By Sherie A. Caffey Colorado State University-Pueblo May 2016 Dedication I would like to dedicate my work to a number of people, whose support was so important to the completion of this thesis. My parents, brother and sister, grandparents, aunts, uncles, and cousins, and last but not least, Nick. Your love and encouragement means the world. i Acknowledgements I would like to acknowledge my thesis advisor, Dr. Brian Vanden Heuvel for guiding me through my research and writing. His expertise in the field and his advising skills were of great value to my education. I also would like to acknowledge my thesis committee, Dr. Lee Anne Martinez and Dr. Helen Caprioglio for assisting me through this process and developing my knowledge through coursework. I would like to also acknowledge Dr. Dan Caprioglio for assisting me with some of my lab work, and Theresa Jiminez for helping me out in so many ways. ii TABLE OF CONTENTS DEDICATION……………………………………………………………………… i ACKNOWLEDGEMENTS………………………………………………………… ii TABLE OF CONTENTS…………………………………………………………… iii ABSTRACT………………………………………………………………………… iv LIST OF TABLES…………………………………………………………………... v LIST OF FIGURES…………………………………………………………………. vi INTRODUCTION…………………………………………………………………… 1 SIGNIFICANCE…………………………………………………………………….. 19 BACKGROUND…………………………………………………………………….. 27 STATEMENT OF OBJECTIVE…………………………………………………….. 34 MATERIALS AND METHODS……………………………………………………. 36 RESULTS……………………………………………………………………………. 62 DISCUSSION……………………..…………………………………………………. 97 CONCLUSIONS………………………….………………………………………… 108 BIBLIOGRAPHY…………………………………………………………………… 115 APPENDIX A- ITS Sequence Alignment…………………………………………… 121 APPENDIX B- Sample ISSR Gel…………………………………………………… 122 APPENDIX C- ISSR Data Matrix…………………………………………………… 123 APPENDIX D- Conserved ISSR Data Matrix……………………………………….. 151 THESIS DEFENSE SLIDES…………………………………………………………. 158 iii Abstract Mirabilis rotundifolia is a perennial wildflower, endemic to Pueblo and Fremont Counties in Southern Colorado. Due to the limited range of this species it has been listed as “at risk” of becoming endangered by the Department of Defense and local conservation groups. A large proportion of the known populations of M. rotundifolia are located on Ft. Carson Army base, where millions of dollars are spent each year to protect at risk species. Dr. Richard Spellenberg, an expert in the genus Mirabilis, once stated in The Flora of North America that Mirabilis rotundifolia may not be a genetically unique species, but a variant of the more widespread species, Mirabilis albida. It was hypothesized for this study that M. rotundifolia is a genetically unique species, based on phenotype and habitat differences. To analyze the genetic relationship between M. rotundifolia and M. albida, Internal Transcribed Spacer (ITS) sequences, and Inter Simple Sequence Repeat (ISSR) markers were isolated and compared. Other Mirabilis species were also included to get a wider view of the genetic makeup of the whole genus. The results all together did not show evidence that M. rotundifolia is genetically distinct from M. albida. Many of the Mirabilis species shared alleles, which lends evidence to the well-known fact that this genus has complicated genetic relationships between species. In the future, different molecular markers could be used to shed more light on this question. Also, sequencing chloroplast genomes of individuals could give a better look at the relationship between M. rotundifolia and M. albida. iv List of Tables Table 1. Summary of phenotypes of M. linearis, M. albida, and M. rotundifolia ......................... 9 Table 2. The sequences of all PCR primers used in this study ..................................................... 39 Table 3. Information for each individual sampled in this study ................................................... 46 Table 4. The alignment statistics from the ITS sequence alignment for Mirabilis species .......... 66 Table 5. All individuals for which ISSR profiles were obtained .................................................. 68 Table 6. All morphological data collected for each individual in the study. ................................ 75 v List of Figures Figure 1. A large Mirabilis rotundifolia individual found in Pueblo County in the summer of 2015............................................................................................................................................... 20 Figure 2. A large M. albida individual found in El Paso County in the fall of 2014 ................... 20 Figure 3. Mirabilis linearis from a population in Arizona ........................................................... 25 Figure 4. Location of Fort Carson in Southern Colorado ............................................................. 27 Figure 5. Mirabilis rotundifolia on Fort Carson ........................................................................... 29 Figure 6 The complicated relationships in the genus Mirabilis.. .................................................... 8 Figure 7. Common leaf shapes ...................................................................................................... 14 Figure 8. Flow chart for defining species ..................................................................................... 17 Figure 9. Diagram of the ITS region of nrDNA ........................................................................... 36 Figure 10. The theory of the ISSR technique. .............................................................................. 41 Figure 11. The general areas from which all populations orginated............................................. 53 Figure 12. An example of the pictures used to make leaf measurements. .................................... 61 Figure 13. Maximum Likelihood phylogenetic tree constructed from ITS sequence alignment. 64 Figure 14. Maximum Likelihood phenogram constructed using ITS sequence data. .................. 65 Figure 15. Phylogenetic tree constructed from the full data matrix using the distance method. .. 69 Figure 16. Phylogenetic tree constructed from the full data matrix using the parsimony method. ....................................................................................................................................................... 70 Figure 17. Phylogenetic tree constructed from the conserved data matrix using the distance method........................................................................................................................................... 72 Figure 18. Phylogenetic tree constructed from the conserved matrix using the parsimony method........................................................................................................................................... 73 Figure 19. Average leaf areas for all groups in the study. ............................................................ 79 Figure 20. Average hair density of leaves for all groups in the study. ......................................... 80 Figure 21. Distance tree made with full data matrix color coded by hair density level in hairs/mm2. ..................................................................................................................................... 82 Figure 22. Parsimony tree constructed using the full data matrix color coded by hair density .... 83 Figure 23. Distance tree constructed from the conserved data matrix color coded by hair density. ....................................................................................................................................................... 84 vi Figure 24. Parsimony tree constructed from the conserved data matrix color coded by hair density. .......................................................................................................................................... 85 Figure 25. Distance tree constructed from the full data matrix color coded by average leaf area 87 Figure 26. Parsimony tree constructed from the full data matrix color coded by average leaf area ....................................................................................................................................................... 88 Figure 27. Distance tree constructed from the conserved data matrix color coded by leaf area .. 89 Figure 28. Parsimony tree constructed from the conserved data matrix color coded by leaf area 90 Figure 29. Distance tree constructed from the full data matrix and color coded by geographical area. ............................................................................................................................................... 93 Figure 30. Parsimony tree constructed from the full data matrix color coded by geographical area. ............................................................................................................................................... 94 Figure 31. Distance tree constructed from conserved data matrix color coded by geographical area. ............................................................................................................................................... 95 Figure 32. Parsimony tree constructed from conserved data matrix color coded by geographical area. ..............................................................................................................................................
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