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Your search keyword '"Nikki Villarasa"' showing total 4 results
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4 results on '"Nikki Villarasa"'

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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