John M. Olson, University of California, Los Angeles
Cory J. Evans, University of California, Los AngelesFollow
Kathy T. Ngo, University of California, Los Angeles
Hee Jong Kim, University of California, Los Angeles
Joseph Duy Nguyen, University of California, Los Angeles
Kayla G.H. Gurley, University of California, Los Angeles
Truc Ta, University of California, Los Angeles
Vijay Patel, University of California, Los Angeles
Lisa Han, University of California, Los Angeles
Khoa T. Truong-N, University of California, Los Angeles
Letty Liang, University of California, Los Angeles
Maggie K. Chu, University of California, Los Angeles
Hiu Lam, University of California, Los Angeles
Hannah G. Ahn, University of California, Los Angeles
Abhik Kumar Banerjee, University of California, Los Angeles
In Young Choi, University of California, Los Angeles
Ross G. Kelley, University of California, Los Angeles
Naseem Moridzadeh, University of California, Los Angeles
Awais M. Khan, University of California, Los Angeles
Omair Khan, University of California, Los Angeles
Szuyao Lee, University of California, Los Angeles
Elizabeth B. Johnson, University of California, Los Angeles
Annie Tigranyan, University of California, Los Angeles
Jay Wang, University of California, Los Angeles
Anand D. Gandhi, University of California, Los Angeles
Manish M. Padhiar, University of California, Los Angeles
Joseph Hargan Calvopina, University of California, Los Angeles
Kirandeep Sumra, University of California, Los Angeles
Kristy Ou, University of California, Los Angeles
Jessie C. Wu, University of California, Los Angeles
Joseph N. Dickan, University of California, Los Angeles
Sabrena M. Ahmadi, University of California, Los Angeles
Donald N. Allen, University of California, Los Angeles

Document Type

Article

Publication Date

2019

Abstract

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.

Original Publication Citation

Olson JM, et al. Expression-Based Cell Lineage Analysis in Drosophila Through a Course-Based Research Experience for Early Undergraduates. G3 (Bethesda). 2019 Nov 5;9(11):3791-3800.

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