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

Author

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, and Utpal Banerjee

Subjects
g-trace, gene expression, education, stem, cure, Genetics, QH426-470
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.

Published
2019
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2. Spectrum of mutations in monogenic diabetes genes identified from high-throughput DNA sequencing of 6888 individuals

Author

Vikas Bansal, Johann Gassenhuber, Tierney Phillips, Glenn Oliveira, Rebecca Harbaugh, Nikki Villarasa, Eric J. Topol, Thomas Seufferlein, and Bernhard O. Boehm

Subjects
High-throughput sequencing, Monogenic diabetes, Pathogenic variants, Type 2 diabetes, MODY, DNA pooling, Medicine
Abstract

Abstract Background Diagnosis of monogenic as well as atypical forms of diabetes mellitus has important clinical implications for their specific diagnosis, prognosis, and targeted treatment. Single gene mutations that affect beta-cell function represent 1–2% of all cases of diabetes. However, phenotypic heterogeneity and lack of family history of diabetes can limit the diagnosis of monogenic forms of diabetes. Next-generation sequencing technologies provide an excellent opportunity to screen large numbers of individuals with a diagnosis of diabetes for mutations in disease-associated genes. Methods We utilized a targeted sequencing approach using the Illumina HiSeq to perform a case-control sequencing study of 22 monogenic diabetes genes in 4016 individuals with type 2 diabetes (including 1346 individuals diagnosed before the age of 40 years) and 2872 controls. We analyzed protein-coding variants identified from the sequence data and compared the frequencies of pathogenic variants (protein-truncating variants and missense variants) between the cases and controls. Results A total of 40 individuals with diabetes (1.8% of early onset sub-group and 0.6% of adult onset sub-group) were carriers of known pathogenic missense variants in the GCK, HNF1A, HNF4A, ABCC8, and INS genes. In addition, heterozygous protein truncating mutations were detected in the GCK, HNF1A, and HNF1B genes in seven individuals with diabetes. Rare missense mutations in the GCK gene were significantly over-represented in individuals with diabetes (0.5% carrier frequency) compared to controls (0.035%). One individual with early onset diabetes was homozygous for a rare pathogenic missense variant in the WFS1 gene but did not have the additional phenotypes associated with Wolfram syndrome. Conclusion Targeted sequencing of genes linked with monogenic diabetes can identify disease-relevant mutations in individuals diagnosed with type 2 diabetes not suspected of having monogenic forms of the disease. Our data suggests that GCK-MODY frequently masquerades as classical type 2 diabetes. The results confirm that MODY is under-diagnosed, particularly in individuals presenting with early onset diabetes and clinically labeled as type 2 diabetes; thus, sequencing of all monogenic diabetes genes should be routinely considered in such individuals. Genetic information can provide a specific diagnosis, inform disease prognosis and may help to better stratify treatment plans.

Published
2017
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3. Genome-wide association of implantable cardioverter-defibrillator activation with life-threatening arrhythmias.

Author

Sarah S Murray, Erin N Smith, Nikki Villarasa, Tara Nahey, Jeff Lande, Harold Goldberg, Marian Shaw, Lawrence Rosenthal, Brian Ramza, Jamshid Alaeddini, Xinqiang Han, Samir Damani, Orhan Soykan, Robert C Kowal, Eric J Topol, and GAME Investigators

Subjects
Medicine, Science
Abstract

To identify genetic factors that would be predictive of individuals who require an implantable cardioverter-defibrillator (ICD), we conducted a genome-wide association study among individuals with an ICD who experienced a life-threatening arrhythmia (LTA; cases) vs. those who did not over at least a 3-year period (controls).Most individuals that receive implantable cardioverter-defibrillators never experience a life-threatening arrhythmia. Genetic factors may help identify who is most at risk.Patients with an ICD and extended follow-up were recruited from 34 clinical sites with the goal of oversampling those who had experienced LTA, with a cumulative 607 cases and 297 controls included in the analysis. A total of 1,006 Caucasian patients were enrolled during a time period of 13 months. Arrhythmia status of 904 patients could be confirmed and their genomic data were included in the analysis. In this cohort, there were 704 males, 200 females, and the average age was 73.3 years. We genotyped DNA samples using the Illumina Human660 W Genotyping BeadChip and tested for association between genotype at common variants and the phenotype of having an LTA.We did not find any associations reaching genome-wide significance, with the strongest association at chromosome 13, rs11856574 at P = 5×10⁻⁶. Loci previously implicated in phenotypes such as QT interval (measure of the time between the start of the Q wave and the end of the T wave as measured by electrocardiogram) were not found to be significantly associated with having an LTA. Although powered to detect such associations, we did not find common genetic variants of large effect associated with having a LTA in those of European descent. This indicates that common gene variants cannot be used at this time to guide ICD risk-stratification.ClinicalTrials.gov NCT00664807.

Published
2012
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4. Discovery-based science education: functional genomic dissection in Drosophila by undergraduate researchers.

Author

Jiong Chen, Gerald B Call, Elsa Beyer, Chris Bui, Albert Cespedes, Amy Chan, Jenny Chan, Stacy Chan, Akanksha Chhabra, Peter Dang, Artemis Deravanesian, Brenda Hermogeno, James Jen, Eunha Kim, Eric Lee, Gemma Lewis, Jamie Marshall, Kirsten Regalia, Farnaz Shadpour, Aram Shemmassian, Kristin Spivey, Maggie Wells, Joy Wu, Yuki Yamauchi, Amir Yavari, Anna Abrams, Amanda Abramson, Latiffe Amado, Jenny Anderson, Keenan Bashour, Elena Bibikova, Allen Bookatz, Sarah Brewer, Natalie Buu, Stephanie Calvillo, Joseph Cao, Aileen Chang, Daniel Chang, Yuli Chang, Yibing Chen, Joo Choi, Jeyling Chou, Sumit Datta, Ardy Davarifar, Poonam Desai, Jordan Fabrikant, Shahbaz Farnad, Katherine Fu, Eddie Garcia, Nick Garrone, Srpouhi Gasparyan, Phyllis Gayda, Chad Goffstein, Courtney Gonzalez, Mariam Guirguis, Ryan Hassid, Aria Hong, Julie Hong, Lindsay Hovestreydt, Charles Hu, Farid Jamshidian, Katrin Kahen, Linda Kao, Melissa Kelley, Thomas Kho, Sarah Kim, Yein Kim, Brian Kirkpatrick, Emil Kohan, Robert Kwak, Adam Langenbacher, Santino Laxamana, Chris Lee, Janet Lee, So-Youn Lee, To Hang S Lee, Toni Lee, Sheila Lezcano, Henry Lin, Peter Lin, Julie Luu, Thanh Luu, Will Marrs, Erin Marsh, Sarah Min, Tanya Minasian, Amit Misra, Miles Morimoto, Yasaman Moshfegh, Jessica Murray, Cynthia Nguyen, Kha Nguyen, Ernesto Nodado, Amanda O'Donahue, Ndidi Onugha, Nneka Orjiakor, Bhavin Padhiar, Mara Pavel-Dinu, Alex Pavlenko, Edwin Paz, Sarah Phaklides, Lephong Pham, Preethi Poulose, Russell Powell, Aya Pusic, Divi Ramola, Meghann Ribbens, Bassel Rifai, Desiree Rosselli, Manyak Saakyan, Pamela Saarikoski, Miriam Segura, Ramnik Singh, Vivek Singh, Emily Skinner, Daniel Solomin, Kosha Soneji, Erika Stageberg, Marina Stavchanskiy, Leena Tekchandani, Leo Thai, Jayantha Thiyanaratnam, Maurine Tong, Aneet Toor, Steve Tovar, Kelly Trangsrud, Wah-Yung Tsang, Marc Uemura, Mary Unkovic, Emily Vollmer, Emily Weiss, Damien Wood, Sophia Wu, Winston Wu, Qing Xu, Kevin Yackle, Will Yarosh, Laura Yee, George Yen, Grant Alkin, Sheryllene Go, Devon M Huff, Helena Minye, Eric Paul, Nikki Villarasa, Allison Milchanowski, and Utpal Banerjee

Subjects
Biology (General), QH301-705.5
Published
2005
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5. Spectrum of mutations in monogenic diabetes genes identified from high-throughput DNA sequencing of 6888 individuals

Author

Nikki Villarasa, Tierney Phillips, Bernhard O. Boehm, Johann Gassenhuber, Eric J. Topol, Vikas Bansal, Rebecca Harbaugh, Thomas Seufferlein, Glenn Oliveira, and Lee Kong Chian School of Medicine (LKCMedicine)

Subjects
Male, 0301 basic medicine, endocrine system diseases, DNA Mutational Analysis, lcsh:Medicine, Type 2 diabetes, Medical and Health Sciences, Cohort Studies, 0302 clinical medicine, Monogenic Diabetes, 2.1 Biological and endogenous factors, Missense mutation, Gene panel testing, Aetiology, Genetics, screening and diagnosis, High-throughput sequencing, biology, Diabetes, High-Throughput Nucleotide Sequencing, Pathogenic variants, General Medicine, Prognosis, HNF1B, HNF1A, High-throughput Sequencing, Detection, Phenotype, MODY, Targeted sequencing, Female, Sequence Analysis, Type 2, Biotechnology, 4.2 Evaluation of markers and technologies, Adult, Wolfram syndrome, Mutation, Missense, 030209 endocrinology & metabolism, Genome sequencing, ABCC8, Maturity-onset diabetes of the young, 03 medical and health sciences, Monogenic diabetes, Clinical Research, General & Internal Medicine, Diabetes mellitus, Type 2 diabetes mellitus, Diabetes Mellitus, medicine, Humans, Genetic Testing, Metabolic and endocrine, Genetic heterogeneity, business.industry, lcsh:R, Sequence Analysis, DNA, DNA, medicine.disease, 4.1 Discovery and preclinical testing of markers and technologies, 030104 developmental biology, Diabetes Mellitus, Type 2, Case-Control Studies, Mutation, Commentary, biology.protein, DNA pooling, Missense, business
Abstract

Background Diagnosis of monogenic as well as atypical forms of diabetes mellitus has important clinical implications for their specific diagnosis, prognosis, and targeted treatment. Single gene mutations that affect beta-cell function represent 1–2% of all cases of diabetes. However, phenotypic heterogeneity and lack of family history of diabetes can limit the diagnosis of monogenic forms of diabetes. Next-generation sequencing technologies provide an excellent opportunity to screen large numbers of individuals with a diagnosis of diabetes for mutations in disease-associated genes. Methods We utilized a targeted sequencing approach using the Illumina HiSeq to perform a case-control sequencing study of 22 monogenic diabetes genes in 4016 individuals with type 2 diabetes (including 1346 individuals diagnosed before the age of 40 years) and 2872 controls. We analyzed protein-coding variants identified from the sequence data and compared the frequencies of pathogenic variants (protein-truncating variants and missense variants) between the cases and controls. Results A total of 40 individuals with diabetes (1.8% of early onset sub-group and 0.6% of adult onset sub-group) were carriers of known pathogenic missense variants in the GCK, HNF1A, HNF4A, ABCC8, and INS genes. In addition, heterozygous protein truncating mutations were detected in the GCK, HNF1A, and HNF1B genes in seven individuals with diabetes. Rare missense mutations in the GCK gene were significantly over-represented in individuals with diabetes (0.5% carrier frequency) compared to controls (0.035%). One individual with early onset diabetes was homozygous for a rare pathogenic missense variant in the WFS1 gene but did not have the additional phenotypes associated with Wolfram syndrome. Conclusion Targeted sequencing of genes linked with monogenic diabetes can identify disease-relevant mutations in individuals diagnosed with type 2 diabetes not suspected of having monogenic forms of the disease. Our data suggests that GCK-MODY frequently masquerades as classical type 2 diabetes. The results confirm that MODY is under-diagnosed, particularly in individuals presenting with early onset diabetes and clinically labeled as type 2 diabetes; thus, sequencing of all monogenic diabetes genes should be routinely considered in such individuals. Genetic information can provide a specific diagnosis, inform disease prognosis and may help to better stratify treatment plans.

Published
2017

6. Genomewide Clonal Analysis of Lethal Mutations in the Drosophila melanogaster Eye: Comparison of the X Chromosome and Autosomes

Author

Christopher Lee, Thanh Luu, Maurine Tong, Cheryl Chan, Thomas Walsh, Mabel Chin, Jiong Chen, Jacob Makshanoff, Diane Vo, Yuli Chang, John M. Olson, Tony Hung, Yuki Yamauchi, Manyak Saakyan, Renata P. Lerner, Elizabeth Evers, Latiffe Amado, Nick Garrone, Carol Salame, Jesse M. Zaretsky, Eric Paul, Winston Wu, Trinh Tran, David Kohanchi, James Z. Hui, Neetika Srivastava, Allison M. Yabroff, Aria Hong, Daniel Solomin, Preethi Poulose, Brian Kirkpatrick, Katherine Wu, Eunha Kim, Abbas Anwar, Diane Tan, Nneka Orjiakor, Utpal Banerjee, Lindsay Hovestreydt, Riju Gupta, Michael Hsieh, Jian-ya Lin, Jennifer Leighn. Sta.Ana, Alex Pavlenko, Ardy Davarifar, Stephanie S. Latterman, Shekhar S. Pai, Qing Xu, Phyllis Gayda, Amir Yavari, Allen Bookatz, Kathy T. Ngo, Paul D. Picard, Srpouhi Gasparyan, ToHang S. Lee, Emily Skinner, Sanjit Datta, Jennifer D. Trinh, Sarah Brewer, Courtney Gonzalez, Matteo Pellegrini, Desiree Rosselli, Gerald B. Call, Gemma Lewis, Kosha Soneji, Quynh-Minh Tran, Amy W. Ku, Farzin Farshidi, Cynthia Nguyen, Vivek Singh, Tanya Minasian, Mara Pavel-Dinu, Chad Goffstein, Bryon C. Lim, So-Youn Lee, Stephanie S. Lauw, Long H. Nguyen, Kevin Yackle, Will Yarosh, Santino Laxamana, Chelsea E. Taber, Sarah Kim, Tiffany Liu, Stacy Chan, Armonde Baghdanian, Kelly Trangsrud, Robert Kwak, Gelsey L. Goodstein, Farnaz Shadpour, Mariam Guirguis, Wah-Yung Tsang, Jayantha Thiyanaratnam, Edwin Paz, Chloe Knudsen-Robbins, Tatiana Moroz, Arlene J. Formanes, Mei L. Iao, Latifat Alli, Shawn S. Badal, Kathleen Lin, PhuongThao Tran, Jamie L. Marshall, Regan S. Wong, Akanksha Chhabra, Ran X. Zhu, Amanda Abramson, Sarah Min, Amit Misra, Vanessa Soma, Blake E. Haas, Eddie Garcia, Ndidi Onugha, Divi Ramola, Ya-Whey Wu, Bogdana Kovshilovskaya, Crystal P. Y. Lui, Kai C. Lei, Jeyling Chou, Yasaman Moshfegh, Sohrab Sidhu, Mark E. L. Landig, Michael G. Yeranosian, James S. Yu, Laura Yee, Lydia S-H. Kim, Katrina Fischer, Angela Y. Kim, Junia J. Song, Melissa M. Kelley, Sheila Lezcano, Jingwen Tan, Vincent Luong, Jennifer J. Zhou, Christopher N.H. Bui, Jenny Chan, Sophia D. Jin, Natalie Buu, Emily Weiss, Amanda O'Donahue, Christian Sanchez, Andrew Folick, Nkau X. V. Yang, Christie Sun, Lephong Pham, Stephanie Calvillo, Charles Hu, Yein Kim, Aileen Chang, George Yen, Joy Wu, Poonam Desai, Linda Kao, Emily G. Travis, Mary Unkovic, Damien Wood, Miriam Segura, Marc Uemura, Henry Lin, Maggie Wells, Miles Morimoto, Sumit Datta, Kha Nguyen, Jessica Wickland, Christina C. Seifert, Leo Thai, Bhavin Padhiar, Hei J. Chan, Yibing Chen, Abhishek Shah, Julie Hong, Cheng R. Huang, Sara A. Baumann, Xibin A. Cheng, Russell Powell, Shawn J. Cokus, Sonia Arevalo, Anna L. Abrams, Mark Engeln, Minh-Tu Do, Joseph Cao, JiEun Lee, Brenda Hermogeno, Bassel Rifai, Preethika S Ekanayake, Alison S. Teruya, Carlyn Crisostomo, Lesley L. Leung, Toni Lee, Megan King, Amy Chan, William R. Marrs, Ryan Hassid, Elena Bibikova, Adam D. Langenbacher, Francie Diep, Jun Gong, Joann S. Lee, Manish Pandya, Emil Kohan, Daniel S. Lee, Jenny Anderson, Kristin Spivey, Devon M Huff, Yulee Kim, Thomas Kho, Alma Rangel, Janet Lee, Aneet Toor, Pamela Saarikoski, Nikki Villarasa, Julie Luu, Vivian N. Becerra, Yara A. Mikhaeil, Shahbaz Farnad, Vida Chitsazzadeh, Q. Angela Fang, Ju An, Leena Tekchandani, Tharani Prasad, Elsa Beyer, Christopher M. Allen, Fleurette Chong, Eric Lee, Meghann Ribbens, Sherrylene Go, Amrita K. Cheema, Jordan Fabrikant, Michael Safaee, An-Chi Mei, Peter Lin, Jessica Murray, Nina Sanchez, Katherine Fu, Sacha L. Prashad, Artemis Deravanesian, Erin Marsh, Robyn Tikia, Raymond W. Kung, Sarah Phaklides, Oganes H. Shilgevorkyan, Peter Dang, Aadit R. Patel, Erika Stageberg, Helena Minye, Alexander N. Patananan, Albert Cespedes, Kasey Topp, Vicky Hahm, Keenan Bashour, Joo Choi, Daniel Chang, Majid Moarefi, William Kim, Farid Jamshidian, Inderroop Singh, Aileen E. Chang, Miguel Meza, Edward Kuoy, Danny Ayoub, Aya Pusic, Daniel Sitz, Marina Stavchanskiy, Sophia Wu, Emily Vollmer, Angela Delosreyes, James Jen, Ernesto Nodado, Aram Shemmassian, Kirsten Regalia, Ramnik Singh, Arthur H. Baghdanian, Steve Tovar, H-C. Angela Liu, and Katrin Kahen

Subjects
Genetics Education, Genetics, Mutation, Genes, Essential, X Chromosome, Autosome, Genome, Insect, Genes, Insect, Biology, Eye, biology.organism_classification, medicine.disease_cause, Clonal analysis, Clone Cells, Drosophila melanogaster, medicine, Eye development, Animals, Genes, Lethal, Drosophila (subgenus), Gene, X chromosome
Abstract

Using a large consortium of undergraduate students in an organized program at the University of California, Los Angeles (UCLA), we have undertaken a functional genomic screen in the Drosophila eye. In addition to the educational value of discovery-based learning, this article presents the first comprehensive genomewide analysis of essential genes involved in eye development. The data reveal the surprising result that the X chromosome has almost twice the frequency of essential genes involved in eye development as that found on the autosomes.

Published
2007
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7. Evidence for the role of EPHX2 gene variants in anorexia nervosa

Author

Nicholas J. Schork, Vikas Bansal, D. B. Woodside, Erin N. Smith, K. Plotnicov, Katherine A. Halmi, Sathanur R. Srinivasan, Pierre J. Magistretti, Cynthia M. Bulik, Janet Treasure, Thomas Phillips, Manfred M. Fichter, Gerald S. Berenson, A. A. Scott-Van Zeeland, L. Galvez, Nathan E. Wineinger, M. La Via, Phillip H. Pham, Harry Brandt, Pamela K. Keel, Eric J. Topol, Vikas Duvvuri, Lisa R. Lilenfeld, Guangfa Zhang, Alessandro Rotondo, Scott J. Crow, Kelly L. Klump, Andrew W. Bergen, Sarah S. Murray, Wade H. Berrettini, Andrew R. Carson, Sybil L. Crawford, Burcu F. Darst, S. Levy, Pei-an Betty Shih, Craig Johnson, Ondrej Libiger, Ali Torkamani, Michael Strober, Cinnamon S. Bloss, Wai Chen, Rebecca L. Tisch, Nikki Villarasa, Walter H. Kaye, Allan S. Kaplan, James E. Mitchell, and Ryan Tewhey

Subjects
Male, Candidate gene, Anorexia Nervosa, Eating Disorders, Medical and Health Sciences, Body Mass Index, Cohort Studies, 2.1 Biological and endogenous factors, hyperlipidemia, Longitudinal Studies, Aetiology, 2. Zero hunger, Genetics, Psychiatry, Epoxide Hydrolases, Single Nucleotide, sequencing, Biological Sciences, Middle Aged, 3. Good health, Anorexia, Psychiatry and Mental health, Eating disorders, Mental Health, Cholesterol, Anorexia nervosa (differential diagnoses), Female, Original Article, Adult, Psychometrics, European Continental Ancestry Group, Biology, Polymorphism, Single Nucleotide, White People, Cellular and Molecular Neuroscience, Young Adult, Clinical Research, Genetic variation, medicine, genomics, Humans, Genetic Predisposition to Disease, pooling, Polymorphism, Molecular Biology, Genotyping, Gene, Nutrition, Whites, Human Genome, Psychology and Cognitive Sciences, Case-control study, Genetic Variation, medicine.disease, EPHX2, Case-Control Studies, Body mass index
Abstract

Anorexia nervosa (AN) and related eating disorders are complex, multifactorial neuropsychiatric conditions with likely rare and common genetic and environmental determinants. To identify genetic variants associated with AN, we pursued a series of sequencing and genotyping studies focusing on the coding regions and upstream sequence of 152 candidate genes in a total of 1205 AN cases and 1948 controls. We identified individual variant associations in the Estrogen Receptor-ß (ESR2) gene, as well as a set of rare and common variants in the Epoxide Hydrolase 2 (EPHX2) gene, in an initial sequencing study of 261 early-onset severe AN cases and 73 controls (P=0.0004). The association of EPHX2 variants was further delineated in: (1) a pooling-based replication study involving an additional 500 AN patients and 500 controls (replication set P=0.00000016); (2) single-locus studies in a cohort of 386 previously genotyped broadly defined AN cases and 295 female population controls from the Bogalusa Heart Study (BHS) and a cohort of 58 individuals with self-reported eating disturbances and 851 controls (combined smallest single locus P

Published
2013

8. Discovery-based science education: functional genomic dissection in Drosophila by undergraduate researchers

Author

Kristin Spivey, Aneet Toor, Gerald B. Call, Brenda Hermogeno, Pamela Saarikoski, Qing Xu, Sheryllene Go, Vivek Singh, Brian Kirkpatrick, Bhavin Padhiar, Aram Shemmassian, Ramnik Singh, Steve Tovar, Sophia Wu, James Jen, Katrin Kahen, Courtney Gonzalez, Grant Alkin, Bassel Rifai, Poonam Desai, Damien Wood, Robert Kwak, Mariam Guirguis, Jayantha Thiyanaratnam, Preethi Poulose, Yuli Chang, Maggie Wells, Jamie L. Marshall, Aya Pusic, Marina Stavchanskiy, Thomas Kho, Nick Garrone, Jeyling Chou, Stephanie Calvillo, Charles Hu, Emily Vollmer, Winston Wu, Henry Lin, Sumit Datta, Leo Thai, Sheila Lezcano, Devon M Huff, Santino Laxamana, Meghann Ribbens, Mara Pavel-Dinu, Yein Kim, Yibing Chen, Eunha Kim, Nneka Orjiakor, Sarah Kim, Allison Milchanowski, Edwin Paz, Manyak Saakyan, Erin Marsh, Linda Kao, Russell Powell, Christopher N.H. Bui, Nikki Villarasa, Joy Wu, Eric Paul, Artemis Deravanesian, Aria Hong, Kha Nguyen, Akanksha Chhabra, Leena Tekchandani, Toni Lee, Utpal Banerjee, William R. Marrs, Elena Bibikova, Eric Lee, Lindsay Hovestreydt, Anna L. Abrams, Jordan Fabrikant, Joseph Cao, Chad Goffstein, So-Youn Lee, Daniel Chang, Will Yarosh, Peter Lin, Kosha Soneji, Christopher Lee, Thanh Luu, Katherine Fu, Maurine Tong, Amanda O'Donahue, Amanda Abramson, Desiree Rosselli, Gemma Lewis, Farid Jamshidian, George Yen, Jiong Chen, Amir Yavari, Yasaman Moshfegh, Amit Misra, Lephong Pham, Ernesto Nodado, Tanya Minasian, Ryan Hassid, Erika Stageberg, Stacy Chan, Cynthia Nguyen, Yuki Yamauchi, Marc Uemura, Janet Lee, Helena Minye, Aileen Chang, Alex Pavlenko, Kelly Trangsrud, Phyllis Gayda, Miles Morimoto, Kirsten Regalia, Jenny Chan, Ardy Davarifar, Shahbaz Farnad, Peter Dang, Daniel Solomin, Laura Yee, Jenny Anderson, Albert Cespedes, To Hang S Lee, Julie Luu, Jessica Murray, Allen Bookatz, Keenan Bashour, Joo Choi, Adam D. Langenbacher, Emil Kohan, Amy M. Chan, Sarah Min, Melissa M. Kelley, Miriam Segura, Elsa Beyer, Sarah Phaklides, Natalie Buu, Emily Weiss, Mary Unkovic, Julie Hong, Emily Skinner, Farnaz Shadpour, Wah-Yung Tsang, Eddie Garcia, Divi Ramola, Latiffe Amado, Srpouhi Gasparyan, Sarah Brewer, Kevin Yackle, and Ndidi Onugha

Subjects
Discovery science, Genetics, General Immunology and Microbiology, QH301-705.5, General Neuroscience, Genomics, In vivo analysis, Biology, Development, Genetics/Genomics/Gene Therapy, Data science, Science education, Genome, General Biochemistry, Genetics and Molecular Biology, Community Page, ComputingMilieux_COMPUTERSANDEDUCATION, Identification (biology), Drosophila, Biology (General), General Agricultural and Biological Sciences, Curriculum, Functional genomics
Abstract

The excitement of scientific research and discovery cannot be fully conveyed by didactic lectures alone. Several recent initiatives and proposals, therefore, have supported a more participatory, discovery-based instruction for undergraduate science education [1,2]. In functional genomics, we have found an ideal platform to simultaneously benefit students and contribute to scientific discovery. The sequencing of eukaryotic genomes has facilitated the identification of complete sets of genes in humans and model genetic organisms. This has allowed many forms of high-throughput analyses of transcriptional profiles, protein interactions, structural motifs, and even genome-wide knock-downs in cell lines or in selected organisms. However, one of the best tools to provide functional information about gene action— obtaining in vivo evidence about the phenotype resulting from heritable loss of function—is difficult and less amenable to high-throughput research. We were able to achieve a large-scale in vivo analysis with a significant number of undergraduate students at UCLA, called the UCLA Undergraduate Consortium for Functional Genomics. This work, a practical manifestation of policy positions proposing discoverybased education, is described in summary form here (and in Box 1) and in detail online at http://www.bruinfly.ucla.edu. This effort combines professional-quality research with a strategy for research-based undergraduate education.

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