Carolyn Lawrence-Dill

Carolyn Joy Lawrence-Dill (born May 18, 1974) is an American plant biologist. She develops computational systems and tools to help plant science researchers use plant genetics and genomics data for basic biology applications that advance plant breeding.

Carolyn Lawrence-Dill
Born (1974-05-18) May 18, 1974
El Paso, Texas, U.S.
NationalityAmerican
Alma materUniversity of Georgia
Texas Tech University
Hendrix College
Known forPlant science data access and availability; gene function prediction tools and resources; making phenotype descriptions computable, research community-building
Scientific career
FieldsPlant Biology
Bioinformatics
InstitutionsAgricultural Research Service, Iowa State University
Doctoral advisorR. Kelly Dawe & Russell L. Malmberg

Early life and education

Carolyn Joy Lawrence-Dill, née Cogburn, was born in El Paso, Texas. She grew up in Throckmorton, then moved to Cleburne in 1989. She graduated in 1992 from Cleburne High School. Lawrence-Dill earned a B.A. degree in biology from Hendrix College in 1996. She received her M.S. degree in biology in 1997 from Texas Tech University where she worked on cotton physiology, and her Ph.D. degree in botany in 2003 from the University of Georgia. Her doctoral dissertation focused on integrating traditional and computational methods for inferring gene function in plants.[1]

Career

Following her formal education, Lawrence-Dill served for two years as a postdoctoral researcher under the direction of Volker Brendel[2] at Iowa State University.

In the summer of 2005, Lawrence-Dill began work as a research geneticist for the USDA-ARS. She served as the director of MaizeGDB, the maize model organism database through December 2013. In 2014 she joined the faculty of Iowa State University as an associate professor in the Departments of Genetics, Development and Cell Biology and Agronomy. In 2019 she was promoted to the rank of professor.

Research

Lawrence-Dill's research focuses on mapping genomes and gene elements.,[3][4][5][6] predicting protein function,[7][8] inventing new ways to link genes to phenotypic descriptions and images,[9][10] developing ways to compute on phenotypic descriptions,[11][12][13][14] organizing broad datasets for community access and use,[15][16][17] and developing computational tools that enable others to do all of these sorts of analyses directly. Although research and development projects are across the plant kingdom generally, much of her work focuses on maize.

Genomics

Lawrence-Dill has advanced plant scientists' ability to access plant genomics resources by sequencing and assembling genomes, annotating structural elements including genes, regulatory elements and CRISPR sites to genomes, and creating tools that enable researchers to analyze gene expression data.

Phenomics

Lawrence-Dill has advanced plant scientists' ability to compute on phenotype directly via connecting image-based phenotypes to genomics data, crowdsourcing for image-based machine learning, managing information for field and controlled environment high-throughput phenotyping, and computing on phenotypic descriptions.

Leadership and policy

Data sharing

Much of the work Lawrence-Dill has published seeks to advance data sharing to enable researchers to make use of others' findings, as some scientists harbor concerns about data sharing that those who generate materials and data will not derive prominence from downstream use and benefits derived from their own data.[18] However, generally limiting access to data prevents researchers from being able to test whether research results are reproducible. With respect to genomics data and materials, limiting access to digital sequence information (DSI) relevant to specific germplasm can keep researchers from being able to identify biological materials for novel research applications.

Climate and genetic engineering

Lawrence-Dill regularly addresses timely topics like climate change and genetic engineering, advising colleagues to engage in discussions on these topics with colleagues in other disciplines, with policymakers, and with the general public. Her guidance focuses on finding shared values, articulating social, environmental, and economic opportunities, and appealing to a better future rather than negative consequences.

In 2016, Lawrence-Dill and sociologist Shawn Dorius began work to better understand where negative public opinions on GMOs and climate change originate. While investigating how GMOs were portrayed in US news coverage, information on Russian interference in the 2016 United States elections emerged, with English language Russian state news from RT and Sputnik being ordered to register as foreign agents. This led the team to look into news reported by RT and Sputnik, where they found their portrayal of GMO topics to be very different from that in US media. Russian state news about GMOs was almost entirely negative, with seemingly intentional mis-associations linking GMOs with controversial, unrelated, and distasteful topics (e.g., topics on abortions of Zika-infected fetuses and the Trans-Pacific Partnership). The team hypothesized that this sort of activity could aim not only to stir up controversy in the US, but that to serve economic interests in Russia given that Russia’s number two industry is agriculture.

While their findings were under peer review, the Des Moines Register released a front-page article[19] describing their findings (February 25, 2018). The researchers released a preprint of the article via the SocArXiv[20] within a day to ensure that detailed materials, methods, and interpretations of the data were fully available. A media frenzy followed with coverage in more than 80 newspapers, online websites, and radio broadcasts, with audio coverage through National Public Radio’s Marketplace (February 28, 2018) and Iowa Public Radio’s River to River (March 2, 2018). There was even a political cartoon released by Greg Kearney,[21] and Bill Gates defended GMOs via a Reddit Ask Me Anything[22] discussion in the midst of the coverage. The peer-reviewed publication[23] was accepted March 11, 2018. Subsequent to media coverage of the GMO-Russia connections, reports of other seemingly unrelated hot topics showed signs of Russian influence with apparent intention to cause discord,[24] with demonstrations of influence campaigns emerging on wide-ranging topics from energy to human rights to international trade.

Scientific community building

Lawrence-Dill has brought together researchers across many communities to coordinate their work. This includes building consensus for standards and nomenclature,[25][26] founding community organizations,[27][28] and encouraging others through mentorship and training opportunities.[29]

Awards

Elected service
  • 2018 International Plant Phenotyping Network[31] Board (3-year term; co-chair)
  • 2018 North American Plant Phenotyping Network[32] Executive Board (2-year term; 2019 chair; founded the 501(c)3)
  • 2016 DivSeek International Network[33] Steering Committee, later Board of Directors (member; 4-year term)
  • 2010 Maize Genetics Executive Committee[34] (5-year term; 2015 chair)

References
  1. Archived 2020-10-17 at the Wayback Machine Dissertation Carolyn Joy Lawrence: A combined bioinformatic/molecular-based approach to understanding molecular motors in plants - website of the Library of the University of Georgia
  2. Brendel, Volker. "Volker Brendel, Professor of Biology". Department of Biology, Indiana University.
  3. Andorf, Carson M.; Kopylov, Mykhailo; Dobbs, Drena; Koch, Karen E.; Stroupe, M. Elizabeth; Lawrence, Carolyn J.; Bass, Hank W. (December 2014). "G-Quadruplex (G4) Motifs in the Maize (Zea mays L.) Genome Are Enriched at Specific Locations in Thousands of Genes Coupled to Energy Status, Hypoxia, Low Sugar, and Nutrient Deprivation". Journal of Genetics and Genomics. 41 (12): 627–647. doi:10.1016/j.jgg.2014.10.004. PMID 25527104.
  4. Law, MeiYee; Childs, Kevin L.; Campbell, Michael S.; Stein, Joshua C.; Olson, Andrew J.; Holt, Carson; Panchy, Nicholas; Lei, Jikai; Jiao, Dian; Andorf, Carson M.; Lawrence, Carolyn J.; Ware, Doreen; Shiu, Shin-Han; Sun, Yanni; Jiang, Ning; Yandell, Mark (1 January 2015). "Automated Update, Revision, and Quality Control of the Maize Genome Annotations Using MAKER-P Improves the B73 RefGen_v3 Gene Models and Identifies New Genes". Plant Physiology. 167 (1): 25–39. doi:10.1104/pp.114.245027. PMC 4280997. PMID 25384563.
  5. Campbell, Michael S.; Law, MeiYee; Holt, Carson; Stein, Joshua C.; Moghe, Gaurav D.; Hufnagel, David E.; Lei, Jikai; Achawanantakun, Rujira; Jiao, Dian; Lawrence, Carolyn J.; Ware, Doreen; Shiu, Shin-Han; Childs, Kevin L.; Sun, Yanni; Jiang, Ning; Yandell, Mark (1 February 2014). "MAKER-P: A Tool Kit for the Rapid Creation, Management, and Quality Control of Plant Genome Annotations". Plant Physiology. 164 (2): 513–524. doi:10.1104/pp.113.230144. PMC 3912085. PMID 24306534. S2CID 11525262.
  6. Manchanda, Nancy; Portwood, John L.; Woodhouse, Margaret R.; Seetharam, Arun S.; Lawrence-Dill, Carolyn J.; Andorf, Carson M.; Hufford, Matthew B. (2 March 2020). "GenomeQC: a quality assessment tool for genome assemblies and gene structure annotations". BMC Genomics. 21 (1): 193. doi:10.1186/s12864-020-6568-2. PMC 7053122. PMID 32122303.
  7. Wimalanathan, Kokulapalan; Lawrence-Dill, Carolyn J. (18 October 2019). "Gene Ontology Meta Annotator for Plants". doi:10.1101/809988. S2CID 208587945. Cite journal requires |journal= (help)
  8. Wimalanathan, Kokulapalan; Friedberg, Iddo; Andorf, Carson M.; Lawrence-Dill, Carolyn J. (April 2018). "Maize GO Annotation-Methods, Evaluation, and Review (maize-GAMER)". Plant Direct. 2 (4): e00052. doi:10.1002/pld3.52. PMC 6508527. PMID 31245718. S2CID 90386060.
  9. Cho, Kyoung Tak; Portwood, John L.; Gardiner, Jack M.; Harper, Lisa C.; Lawrence-Dill, Carolyn J.; Friedberg, Iddo; Andorf, Carson M. (28 August 2019). "MaizeDIG: Maize Database of Images and Genomes". Frontiers in Plant Science. 10: 1050. doi:10.3389/fpls.2019.01050. PMC 6724615. PMID 31555312.
  10. Zhou, Naihui; Siegel, Zachary D.; Zarecor, Scott; Lee, Nigel; Campbell, Darwin A.; Andorf, Carson M.; Nettleton, Dan; Lawrence-Dill, Carolyn J.; Ganapathysubramanian, Baskar; Kelly, Jonathan W.; Friedberg, Iddo (30 July 2018). "Crowdsourcing image analysis for plant phenomics to generate ground truth data for machine learning". PLOS Computational Biology. 14 (7): e1006337. Bibcode:2018PLSCB..14E6337Z. doi:10.1371/journal.pcbi.1006337. PMC 6085066. PMID 30059508. S2CID 51881800.
  11. Oellrich, Anika; Walls, Ramona L; Cannon, Ethalinda; Cannon, Steven B; Cooper, Laurel; Gardiner, Jack; Gkoutos, Georgios V; Harper, Lisa; He, Mingze; Hoehndorf, Robert; Jaiswal, Pankaj; Kalberer, Scott R; Lloyd, John P; Meinke, David; Menda, Naama; Moore, Laura; Nelson, Rex T; Pujar, Anuradha; Lawrence, Carolyn J; Huala, Eva (2015). "An ontology approach to comparative phenomics in plants". Plant Methods. 11 (1): 10. doi:10.1186/s13007-015-0053-y. PMC 4359497. PMID 25774204. S2CID 18382593.
  12. Braun, Ian; Lawrence-Dill, Carolyn (2018). "Computational Classification of Phenologs Across Biological Diversity" (PDF). Proceedings of the 9th International Conference on Biological Ontology: 2. Archived (PDF) from the original on 2019-01-14. Retrieved 2020-10-16.
  13. Braun, Ian R.; Lawrence-Dill, Carolyn J. (10 January 2020). "Automated Methods Enable Direct Computation on Phenotypic Descriptions for Novel Candidate Gene Prediction". Frontiers in Plant Science. 10: 1629. doi:10.3389/fpls.2019.01629. ISSN 1664-462X. PMC 6965352. PMID 31998331. S2CID 210117404.
  14. Braun, Ian R.; Yanarella, Colleen F.; Lawrence-Dill, Carolyn J. (20 May 2020). "Computing on Phenotypic Descriptions for Candidate Gene Discovery and Crop Improvement". Plant Phenomics. 2020: 1–4. doi:10.34133/2020/1963251.
  15. AlKhalifah, Naser; Campbell, Darwin A.; Falcon, Celeste M.; Gardiner, Jack M.; Miller, Nathan D.; Romay, Maria Cinta; Walls, Ramona; Walton, Renee; Yeh, Cheng-Ting; Bohn, Martin; Bubert, Jessica; Buckler, Edward S.; Ciampitti, Ignacio; Flint-Garcia, Sherry; Gore, Michael A.; Graham, Christopher; Hirsch, Candice; Holland, James B.; Hooker, David; Kaeppler, Shawn; Knoll, Joseph; Lauter, Nick; Lee, Elizabeth C.; Lorenz, Aaron; Lynch, Jonathan P.; Moose, Stephen P.; Murray, Seth C.; Nelson, Rebecca; Rocheford, Torbert; Rodriguez, Oscar; Schnable, James C.; Scully, Brian; Smith, Margaret; Springer, Nathan; Thomison, Peter; Tuinstra, Mitchell; Wisser, Randall J.; Xu, Wenwei; Ertl, David; Schnable, Patrick S.; De Leon, Natalia; Spalding, Edgar P.; Edwards, Jode; Lawrence-Dill, Carolyn J. (December 2018). "Maize Genomes to Fields: 2014 and 2015 field season genotype, phenotype, environment, and inbred ear image datasets". BMC Research Notes. 11 (1): 452. doi:10.1186/s13104-018-3508-1. PMC 6038255. PMID 29986751.
  16. Lawrence, C. J. (1 January 2004). "MaizeGDB, the community database for maize genetics and genomics". Nucleic Acids Research. 32 (90001): 393D–397. doi:10.1093/nar/gkh011. PMC 308746. PMID 14681441.
  17. Duvick, J.; Fu, A.; Muppirala, U.; Sabharwal, M.; Wilkerson, M. D.; Lawrence, C. J.; Lushbough, C.; Brendel, V. (23 December 2007). "PlantGDB: a resource for comparative plant genomics". Nucleic Acids Research. 36 (Database): D959–D965. doi:10.1093/nar/gkm1041. PMC 2238959. PMID 18063570. S2CID 10046054.
  18. Longo, Dan L.; Drazen, Jeffrey M. (20 January 2016). "Data Sharing". New England Journal of Medicine. 374 (3): 276–277. doi:10.1056/NEJMe1516564. PMID 26789876.
  19. Eller, Donnelle. "Anti-GMO articles tied to Russian sites, ISU research shows". Des Moines Register. Archived from the original on 17 October 2020. Retrieved 15 October 2020.
  20. Dorius, Shawn F; Lawrence-Dill, Carolyn J (27 February 2018). "Sowing the seeds of skepticism: Russian state news and anti-GMO sentiment". doi:10.31235/osf.io/26ubf. PMID 29561212. Archived from the original on 2 May 2019. Retrieved 17 October 2020. Cite journal requires |journal= (help)
  21. Kearney, G. M. "Drawing Attention". Archived from the original on 17 October 2020. Retrieved 15 October 2020.
  22. Gates, Bill. "r/IAmA - Comment by u/thisisbillgates on "I'm Bill Gates, co-chair of the Bill & Melinda Gates Foundation. Ask Me Anything."". reddit.
  23. Dorius, Shawn F.; Lawrence-Dill, Carolyn J. (3 April 2018). "Sowing the seeds of skepticism: Russian state news and anti-GMO sentiment". GM Crops & Food. 9 (2): 53–58. doi:10.1080/21645698.2018.1454192. PMC 6277062. PMID 29561212. S2CID 4051135.
  24. Timberg, Craig; Romm, Tony. "These provocative images show Russian trolls sought to inflame debate over climate change, fracking and Dakota pipeline". Washington Post. Retrieved 20 October 2020.
  25. Gray, John; Bevan, Michael; Brutnell, Thomas; Buell, C. Robin; Cone, Karen; Hake, Sarah; Jackson, David; Kellogg, Elizabeth; Lawrence, Carolyn; McCouch, Susan; Mockler, Todd; Moose, Stephen; Paterson, Andrew; Peterson, Thomas; Rokshar, Daniel; Souza, Glaucia Mendes; Springer, Nathan; Stein, Nils; Timmermans, Marja; Wang, Guo-Liang; Grotewold, Erich (January 2009). "A Recommendation for Naming Transcription Factor Proteins in the Grasses". Plant Physiology. 149 (1): 4–6. doi:10.1104/pp.108.128504. PMC 2613739. PMID 19126689.
  26. Lawrence, Carolyn J.; Dawe, R. Kelly; Christie, Karen R.; Cleveland, Don W.; Dawson, Scott C.; Endow, Sharyn A.; Goldstein, Lawrence S.B.; Goodson, Holly V.; Hirokawa, Nobutaka; Howard, Jonathon; Malmberg, Russell L.; McIntosh, J. Richard; Miki, Harukata; Mitchison, Timothy J.; Okada, Yasushi; Reddy, Anireddy S.N.; Saxton, William M.; Schliwa, Manfred; Scholey, Jonathan M.; Vale, Ronald D.; Walczak, Claire E.; Wordeman, Linda (11 October 2004). "A standardized kinesin nomenclature". Journal of Cell Biology. 167 (1): 19–22. doi:10.1083/jcb.200408113. PMC 2041940. PMID 15479732. S2CID 30027277.
  27. Carroll, April Agee; Clarke, Jennifer; Fahlgren, Noah; Gehan, Malia A.; Lawrence‐Dill, Carolyn J.; Lorence, Argelia (January 2019). "NAPPN: Who We Are, Where We Are Going, and Why You Should Join Us!". The Plant Phenome Journal. 2 (1): 1–4. doi:10.2135/tppj2018.08.0006. S2CID 186567373.
  28. Lawrence‐Dill, Carolyn J.; Schnable, Patrick S.; Springer, Nathan M. (July 2019). "Idea Factory: the Maize Genomes to Fields Initiative". Crop Science. 59 (4): 1406–1410. doi:10.2135/cropsci2019.02.0071.
  29. Lawrence-Dill, Carolyn; Heindel, Theodore; Schnable, Patrick; Strong, Stephanie; Wittrock, Jill; Losch, Mary; Dickerson, Julie (16 May 2018). "Transdisciplinary Graduate Training in Predictive Plant Phenomics". Agronomy. 8 (5): 73. doi:10.3390/agronomy8050073.
  30. "Women of Achievement". ywca. Archived from the original on 2020-10-17. Retrieved 2020-10-15.
  31. "IPPN Home". www.plant-phenotyping.org. Archived from the original on 2020-10-01. Retrieved 2020-10-15.
  32. "North American Plant Phenotyping Network". nappn.plant-phenotyping.org. Archived from the original on 2020-06-12. Retrieved 2020-10-15.
  33. "DivSeek International Network - A Global Community Driven Not-for-Profit Organization". DivSeek Intl. Archived from the original on 2020-10-17. Retrieved 2020-10-15.
  34. "Maize Genetics Executive Committee". maizegdb.org. Archived from the original on 2020-05-13. Retrieved 2020-10-15.

Websites

Podcasts

Seminars
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