Other Genetics and Genomics Commons^™

Molecular And Systemic Epigenetic Inheritance: Integrating Development, Genetics, And Evolution, Robert Lickliter, David S. Moore

Pitzer Faculty Publications and Research

Currently, a central problem for theoretical biology is the integration of development with genetics and evolutionary theory. Through the late 20^th century, biologists held that animals resemble their ancestors strictly because of the transgenerational transmission of DNA. This view effectively wrote development out of evolutionary biology. However, many molecular and developmental biologists now understand that phenotypes—anatomical, physiological, and behavioral traits—are not determined by genes (i.e., DNA segments) alone; instead, they emerge epigenetically from developmental processes involving co-acting genetic factors, environmental factors, molecular epigenetic factors, and other non-genetic factors within organisms’ bodies. This insight forces a rethinking of biological inheritance. …

Whole Genome Sequence Analysis Of Apparent Treatment Resistant Hypertension Status In Participants From The Trans-Omics For Precision Medicine Program, Nicole D Armstrong, Vinodh Srinivasasainagendra, Farah Ammous, Themistocles L Assimes, Amber L Beitelshees, Jennifer Brody, Brian E Cade, Yii-Der Ida Chen, Han Chen, Paul S De Vries, James S Floyd, Nora Franceschini, Xiuqing Guo, Jacklyn N Hellwege, John S House, Chii-Min Hwu, Sharon L R Kardia, Ethan M Lange, Leslie A Lange, Caitrin W Mcdonough, May E Montasser, Jeffrey R O'Connell, Megan M Shuey, Xiao Sun, Rikki M Tanner, Zhe Wang, Wei Zhao, April P Carson, Todd L Edwards, Tanika N Kelly, Eimear E Kenny, Charles Kooperberg, Ruth J F Loos, Alanna C Morrison, Alison Motsinger-Reif, Bruce M Psaty, Dabeeru C Rao, Susan Redline, Stephen S Rich, Jerome I Rotter, Jennifer A Smith, Albert V Smith, Marguerite R Irvin, Donna K Arnett

Faculty, Staff and Student Publications

Introduction: Apparent treatment-resistant hypertension (aTRH) is characterized by the use of four or more antihypertensive (AHT) classes to achieve blood pressure (BP) control. In the current study, we conducted single-variant and gene-based analyses of aTRH among individuals from 12 Trans-Omics for Precision Medicine cohorts with whole-genome sequencing data.

Methods: Cases were defined as individuals treated for hypertension (HTN) taking three different AHT classes, with average systolic BP ≥ 140 or diastolic BP ≥ 90 mmHg, or four or more medications regardless of BP (n = 1,705). A normotensive control group was defined as individuals with BP < 140/90 mmHg (n = 22,079), not on AHT medication. A second control group comprised individuals who were treatment responsive on one AHT medication with BP < 140/ 90 mmHg (n = 5,424). Logistic regression with kinship adjustment using the Scalable and Accurate Implementation of Generalized mixed models (SAIGE) was performed, adjusting for age, sex, and genetic ancestry. We assessed variants using SKAT-O in rare-variant analyses. Single-variant and gene-based tests were conducted in a pooled multi-ethnicity stratum, as well as self-reported ethnic/racial strata (European and African American).

Results: One variant in …

Effects Of Depth, Distance To Shore, And Water Velocity On Organismal And Extra-Organismal Environmental Dna Concentrations In A Large River, Dylan Keel

Cal Poly Humboldt theses and projects

Environmental DNA (eDNA) is a sensitive tool for detection of aquatic species and concentrations of eDNA in water samples have been useful for estimating abundance. This study evaluated the effects of depth, distance to shore, and water velocity on the concentration of organismal and extra-organismal eDNA concentrations in the Klamath River, California (basin area ≅ 40,000 km²). At each of six river cross sections 32 water samples were collected, including surface samples and depth samples evenly distributed across the cross section, and eDNA concentrations were determined for the parasite Ceratonova shasta and Chinook salmon, Oncorhynchus tshawytscha, using …

Gene-Educational Attainment Interactions In A Multi-Population Genome-Wide Meta-Analysis Identify Novel Lipid Loci, Lisa De Las Fuentes, Karen L Schwander, Michael R Brown, Amy R Bentley, Thomas W Winkler, Yun Ju Sung, Patricia B Munroe, Clint L Miller, Hugo Aschard, Stella Aslibekyan, Traci M Bartz, Lawrence F Bielak, Jin Fang Chai, Ching-Yu Cheng, Rajkumar Dorajoo, Mary F Feitosa, Xiuqing Guo, Fernando P Hartwig, Andrea Horimoto, Ivana Kolčić, Elise Lim, Yongmei Liu, Alisa K Manning, Jonathan Marten, Solomon K Musani, Raymond Noordam, Sandosh Padmanabhan, Tuomo Rankinen, Melissa A Richard, Paul M Ridker, Albert V Smith, Dina Vojinovic, Alan B Zonderman, Maris Alver, Mathilde Boissel, Kaare Christensen, Barry I Freedman, Chuan Gao, Franco Giulianini, Sarah E Harris, Meian He, Fang-Chi Hsu, Brigitte Kühnel, Federica Laguzzi, Xiaoyin Li, Leo-Pekka Lyytikäinen, Ilja M Nolte, Alaitz Poveda, Rainer Rauramaa, Muhammad Riaz, Antonietta Robino, Tamar Sofer, Fumihiko Takeuchi, Bamidele O Tayo, Peter J Van Der Most, Niek Verweij, Erin B Ware, Stefan Weiss, Wanqing Wen, Lisa R Yanek, Yiqiang Zhan, Najaf Amin, Dan E Arking, Christie Ballantyne, Eric Boerwinkle, Jennifer A Brody, Ulrich Broeckel, Archie Campbell, Mickaël Canouil, Xiaoran Chai, Yii-Der Ida Chen, Xu Chen, Kumaraswamy Naidu Chitrala, Maria Pina Concas, Ulf De Faire, Renée De Mutsert, H Janaka De Silva, Paul S De Vries, Ahn Do, Jessica D Faul, Virginia Fisher, James S Floyd, Terrence Forrester, Yechiel Friedlander, Giorgia Girotto, C Charles Gu, Göran Hallmans, Sami Heikkinen, Chew-Kiat Heng, Georg Homuth, Steven Hunt, M Arfan Ikram, David R Jacobs, Maryam Kavousi, Chiea Chuen Khor, Tuomas O Kilpeläinen, Woon-Puay Koh, Pirjo Komulainen, Carl D Langefeld, Jingjing Liang, Kiang Liu, Jianjun Liu, Kurt Lohman, Reedik Mägi, Ani W Manichaikul, Colin A Mckenzie, Thomas Meitinger, Yuri Milaneschi, Matthias Nauck, Christopher P Nelson, Jeffrey R O'Connell, Nicholette D Palmer, Alexandre C Pereira, Thomas Perls, Annette Peters, Ozren Polašek, Olli T Raitakari, Kenneth Rice, Treva K Rice, Stephen S Rich, Charumathi Sabanayagam, Pamela J Schreiner, Xiao-Ou Shu, Stephen Sidney, Mario Sims, Jennifer A Smith, John M Starr, Konstantin Strauch, E Shyong Tai, Kent D Taylor, Michael Y Tsai, André G Uitterlinden, Diana Van Heemst, Melanie Waldenberger, Ya-Xing Wang, Wen-Bin Wei, Gregory Wilson, Deng Xuan, Jie Yao, Caizheng Yu, Jian-Min Yuan, Wei Zhao, Diane M Becker, Amélie Bonnefond, Donald W Bowden, Richard S Cooper, Ian J Deary, Jasmin Divers, Tõnu Esko, Paul W Franks, Philippe Froguel, Christian Gieger, Jost B Jonas, Norihiro Kato, Timo A Lakka, Karin Leander, Terho Lehtimäki, Patrik K E Magnusson, Kari E North, Ioanna Ntalla, Brenda Penninx, Nilesh J Samani, Harold Snieder, Beatrice Spedicati, Pim Van Der Harst, Henry Völzke, Lynne E Wagenknecht, David R Weir, Mary K Wojczynski, Tangchun Wu, Wei Zheng, Xiaofeng Zhu, Claude Bouchard, Daniel I Chasman, Michele K Evans, Ervin R Fox, Vilmundur Gudnason, Caroline Hayward, Bernardo L Horta, Sharon L R Kardia, Jose Eduardo Krieger, Dennis O Mook-Kanamori, Patricia A Peyser, Michael M Province, Bruce M Psaty, Igor Rudan, Xueling Sim, Blair H Smith, Rob M Van Dam, Cornelia M Van Duijn, Tien Yin Wong, Donna K Arnett, Dabeeru C Rao, James Gauderman, Ching-Ti Liu, Alanna C Morrison, Jerome I Rotter, Myriam Fornage

Faculty, Staff and Student Publications

Introduction: Educational attainment, widely used in epidemiologic studies as a surrogate for socioeconomic status, is a predictor of cardiovascular health outcomes.

Methods: A two-stage genome-wide meta-analysis of low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and triglyceride (TG) levels was performed while accounting for gene-educational attainment interactions in up to 226,315 individuals from five population groups. We considered two educational attainment variables: “Some College” (yes/no, for any education beyond high school) and “Graduated College” (yes/no, for completing a 4-year college degree). Genome-wide significant (p < 5 × 10−8) and suggestive (p < 1 × 10−6) variants were identified in Stage 1 (in up to 108,784 individuals) through genome-wide analysis, and those variants were followed up in Stage 2 studies (in up to 117,531 individuals).

Results: In combined analysis of Stages 1 and 2, we identified 18 novel lipid loci (nine …