Expression-Based Cell Lineage Analysis in Drosophila Through a Course-Based Research Experience for Early Undergraduates

• Main Authors: John M. Olson, Cory J. Evans, Kathy T. Ngo, Hee Jong Kim, Joseph Duy Nguyen, Kayla G. H. Gurley, Truc Ta, Vijay Patel, Lisa Han, Khoa T. Truong-N, Letty Liang, Maggie K. Chu, Hiu Lam, Hannah G. Ahn, Abhik Kumar Banerjee, In Young Choi, Ross G. Kelley, Naseem Moridzadeh, Awais M. Khan, Omair Khan, Szuyao Lee, Elizabeth B. Johnson, Annie Tigranyan, Jay Wang, Anand D. Gandhi, Manish M. Padhiar, Joseph Hargan Calvopina, Kirandeep Sumra, Kristy Ou, Jessie C. Wu, Joseph N. Dickan, Sabrena M. Ahmadi, Donald N. Allen, Van Thanh Mai, Saif Ansari, George Yeh, Earl Yoon, Kimberly Gon, John Y. Yu, Johnny He, Jesse M. Zaretsky, Noemi E. Lee, Edward Kuoy, Alexander N. Patananan, Daniel Sitz, PhuongThao Tran, Minh-Tu Do, Samira J. Akhave, Silverio D. Alvarez, Bobby Asem, Neda Asem, Nicole A. Azarian, Arezou Babaesfahani, Ahmad Bahrami, Manjeet Bhamra, Ragini Bhargava, Rakesh Bhatia, Subir Bhatia, Nicholas Bumacod, Jonathan J. Caine, Thomas A. Caldwell, Nicole A. Calica, Elise M. Calonico, Carman Chan, Helen H.-L. Chan, Albert Chang, Chiaen Chang, Daniel Chang, Jennifer S. Chang, Nauman Charania, Jasmine Y. Chen, Kevin Chen, Lu Chen, Yuyu Chen, Derek J. Cheung, Jesse J. Cheung, Jessica J. Chew, Nicole B. Chew, Cheng-An Tony Chien, Alana M. Chin, Chee Jia Chin, Youngho Cho, Man Ting Chou, Ke-Huan K. Chow, Carolyn Chu, Derrick M. Chu, Virginia Chu, Katherine Chuang, Arunit Singh Chugh, Mark R. Cubberly, Michael Guillermo Daniel, Sangita Datta, Raj Dhaliwal, Jenny Dinh, Dhaval Dixit, Emmylou Dowling, Melinda Feng, Christopher M. From, Daisuke Furukawa, Himaja Gaddipati, Lilit Gevorgyan, Zunera Ghaznavi, Tulika Ghosh, Jaskaran Gill, David J. Groves, Kalkidan K. Gurara, Ali R. Haghighi, Alexandra L. Havard, Nasser Heyrani, Tanya Hioe, Kirim Hong, Justin J. Houman, Molly Howland, Elaine L. Hsia, Justin Hsueh, Stacy Hu, Andrew J. Huang, Jasmine C. Huynh, Jenny Huynh, Chris Iwuchukwu, Michael J. Jang, An An Jiang, Simran Kahlon, Pei-Yun Kao, Manpreet Kaur, Matthew G. Keehn, Elizabeth J. Kim, Hannah Kim, Michelle J. Kim, Shawn J. Kim, Aleksandar Kitich, Ross A. Kornberg, Nicholas G. Kouzelos, Jane Kuon, Bryan Lau, Roger K. Lau, Rona Law, Huy D. Le, Rachael Le, Carrou Lee, Christina Lee, Grace E. Lee, Kenny Lee, Michelle J. Lee, Regina V. Lee, Sean H. K. Lee, Sung Kyu Lee, Sung-Ling D. Lee, Yong Jun Lee, Megan J. Leong, David M. Li, Hao Li, Xingfu Liang, Eric Lin, Michelle M. Lin, Peter Lin, Tiffany Lin, Stacey Lu, Serena S. Luong, Jessica S. Ma, Li Ma, Justin N. Maghen, Sravya Mallam, Shivtaj Mann, Jason H. Melehani, Ryan C. Miller, Nitish Mittal, Carmel M. Moazez, Susie Moon, Rameen Moridzadeh, Kaley Ngo, Hanh H. Nguyen, Kambria Nguyen, Thien H. Nguyen, Angela W. Nieh, Isabella Niu, Seo-Kyung Oh, Jessica R. Ong, Randi K. Oyama, Joseph Park, Yaelim A. Park, Kimberly A. Passmore, Ami Patel, Amy A. Patel, Dhruv Patel, Tirth Patel, Katherine E. Peterson, An Huynh Pham, Steven V. Pham, Melissa E. Phuphanich, Neil D. Poria, Alexandra Pourzia, Victoria Ragland, Riki D. Ranat, Cameron M. Rice, David Roh, Solomon Rojhani, Lili Sadri, Agafe Saguros, Zainab Saifee, Manjot Sandhu, Brooke Scruggs, Lisa M. Scully, Vanessa Shih, Brian A. Shin, Tamir Sholklapper, Harnek Singh, Sumedha Singh, Sondra L. Snyder, Katelyn F. Sobotka, Sae Ho Song, Siddharth Sukumar, Halley C. Sullivan, Mark Sy, Hande Tan, Sara K. Taylor, Shivani K. Thaker, Tulsi Thakore, Gregory E. Tong, Jacinda N. Tran, Jonathan Tran, Tuan D. Tran, Vivi Tran, Cindy L. Trang, Hung G. Trinh, Peter Trinh, Han-Ching H. Tseng, Ted T. Uotani, Akram V. Uraizee, Kent K. T. Vu, Kevin K. T. Vu, Komal Wadhwani, Paluk K. Walia, Rebecca S. Wang, Shuo Wang, Stephanie J. Wang, Danica D. Wiredja, Andrew L. Wong, Daniel Wu, Xi Xue, Griselda Yanez, Yung-Hsuan Yang, Zhong Ye, Victor W. Yee, Cynthia Yeh, Yue Zhao, Xin Zheng, Anke Ziegenbalg, Jon Alkali, Ida Azizkhanian, Akash Bhakta, Luke Berry, Ryen Castillo, Sonja Darwish, Holly Dickinson, Ritika Dutta, Rahul Kumar Ghosh, Riley Guerin, Jonathan Hofman, Garrick Iwamoto, Sarah Kang, Andrew Kim, Brian Kim, Hanwool Kim, Kristine Kim, Suji Kim, Julie Ko, Michael Koenig, Alejandro LaRiviere, Clifton Lee, Jiwon Lee, Brandon Lung, Max Mittelman, Mark Murata, Yujin Park, Daniel Rothberg, Ben Sprung-Keyser, Kunal Thaker, Vivian Yip, Paul Picard, Francie Diep, Nikki Villarasa, Volker Hartenstein, Casey Shapiro, Marc Levis-Fitzgerald, Leslie Jaworski, David Loppato, Ira E. Clark, Utpal Banerjee
• Format: Article
• Language: English
• Published: Oxford University Press 2019-11-01
• Series: G3: Genes, Genomes, Genetics
• Subjects: g-trace; gene expression; education; stem; cure
• Online Access: http://g3journal.org/lookup/doi/10.1534/g3.119.400541
• ISSN: 2160-1836

A variety of genetic techniques have been devised to determine cell lineage relationships during tissue development. Some of these systems monitor cell lineages spatially and/or temporally without regard to gene expression by the cells, whereas others correlate gene expression with the lineage under study. The GAL4 Technique for Real-time and Clonal Expression (G-TRACE) system allows for rapid, fluorescent protein-based visualization of both current and past GAL4 expression patterns and is therefore amenable to genome-wide expression-based lineage screens. Here we describe the results from such a screen, performed by undergraduate students of the University of California, Los Angeles (UCLA) Undergraduate Research Consortium for Functional Genomics (URCFG) and high school summer scholars as part of a discovery-based education program. The results of the screen, which reveal novel expression-based lineage patterns within the brain, the imaginal disc epithelia, and the hematopoietic lymph gland, have been compiled into the G-TRACE Expression Database (GED), an online resource for use by the Drosophila research community. The impact of this discovery-based research experience on student learning gains was assessed independently and shown to be greater than that of similar programs conducted elsewhere. Furthermore, students participating in the URCFG showed considerably higher STEM retention rates than UCLA STEM students that did not participate in the URCFG, as well as STEM students nationwide.