Genomic Courses

GENETICS 335 – Genomes in a Modern World

The ability to sequence genomes rapidly has transformed our understanding of the evolution of species and human history, our approaches to improve health and medicine, as well as how we tackle global environmental challenges, and increasingly impacts our modern world. Explore the interdisciplinary connections between genetics- and genomics-based research and important current questions related to ethics, history, and public policy.

Fall & Spring, 3 credits.

Pre-requisites: GENETICS 234.

AN SCI 366 – Concepts in Genomics

Basic overview of the latest concepts in genomics, including genome organization, the importance of genome annotation, the use of genomic testing in plant and animal breeding, the potential of genomic prediction on human medicine, and the latest advances in omics integration.

Offered every Fall, 3 credits. Instructor: Francisco Peñagaricano

Pre-requisites: none.

BIOCHEMISTRY 375 – Introductory Biotechnology: From Farm to Pharma

Biotechnology is changing how we grow food, fight disease, and understand life itself. This course introduces you to the science behind those changes — from genetically engineered crops to modern medicines. You don’t need any college biology or chemistry to take this class. We’ll start with the basics (DNA, genes, and proteins) and build up to real-world examples of how biotechnology is used today.

Fall, 1 credit. Instructor: Michael Sussman

Pre-requisites: none.

GENETICS 375 – Quantitative Methods in Genetics 

Specialized subject matter of current interest to undergraduate students.

Fall, 1-4 credits. Instructor: Steven Schrodi

Pre-requisites: none.

ZOOLOGY 415 – Genetics of Human History

Covers a range of topics related to human genetics and evolution. Explores questions about what genetic differences between humans tell us about our species’ evolutionary and demographic history, and conversely, how our history has shaped the genetic diversity of people living today. At a time of rapidly increasing ability to sequence huge numbers of genomes such questions play a central role in understanding how genetics impacts individuals’ disease risks, how to interpret reported ancestry and family history from direct-to-consumer genotyping kits, and how genetics can (or importantly, cannot) inform descriptions of human diversity and concepts of race. Includes topics of diversity and inclusion in genomics studies, with a focus on the application and limits of results obtained from one group to our understanding of other groups.

Spring, 3 credits. Instructor: Aaron Ragsdale

Pre-requisites: BIOLOGY/ZOOLOGY 101 and 102, BIOLOGY/BOTANY/ZOOLOGY 152, or BIOCORE 381.

PATH 501 – Topics in Environmental Viral Pathogen Surveillance

Explore the methods for environmental pathogen surveillance used in research and public health. Includes an advanced discussion of molecular genetics, genomics, and sequencing technologies. Explores the implications for public health and pandemic preparedness.

Spring, 3 credits. Instructor: Heidi Horn

Pre-requisites: ZOOLOGY/BOTANY 101 and 102 or ZOOLOGY/BOTANY/BIOLOGY 152 and GENETICS 466 or 468, BIOCORE 383, or graduate/professional standing.

GENETICS 548 – The Genomic Revolution

Profound advances are now possible thanks to genomic data and analysis. Introduces the structure, function, and evolution of genomes. It also outlines the realized and prospective benefits of genomic technology for human health, agriculture, and conservation.

Fall, 3 credits. Instructors: Nicole Perna, Bret Payseur

Pre-requisites: GENETICS 466, 468, or BIOCORE 587.

BOTANY/PL PATH 563 – Phylogenetic Analysis of Molecular Data

Theory and practice of phylogenetic inference from DNA sequence data.

Spring, 3 credits. Instructor: Claudia Solis-Lemus

Pre-requisites: BIOLOGY/BOTANY/ZOOLOGY 151, BIOLOGY/BOTANY 130, BIOLOGY/ZOOLOGY 101, or BIOCORE 381 and STAT 240, 301, 324, or 371 or graduate/professional standing.

GENETICS 564 – Genomics and Proteomics

The basic principles of genomics, proteomics and bioinformatics will be taught through a semester-long project of the students choosing. Creative problem solving in science skills will be learned through a variety of active-learning techniques that include: reading of primary literature, group presentations, peer review, bioinformatic lab exercises, science communication skills (writing & visualization), and creating a website. Emphasis will be placed upon how to effectively communicate science (written, oral and written). Topics include: genomic sequencing, phylogeny, domain analysis, transcriptomics, CRISPR screens, chemical genomics, quantitative proteomics and protein networks. Capstone course.

Spring, 3 credits. Instructor: Ahna Skop

Pre-requisites: GENETICS 466, 468, or BIOCORE 587. Not open to graduate students.

GENETICS 565 – Human Genetics

Principles, problems, and methods of modern human genetics.  Focuses on how researchers discover the genetics of diseases and how those discoveries are used to improve clinical practice.  Surveys aspects of (i) the molecular function of the human genome, (ii) the basic principles of human genetics including statistical genetics, quantitative genetics, and genomic variation in human populations, (iii) the genetics of rare disorders and common diseases, and genomic analysis approaches, including genome-wide association studies and sequencing, and (iv) how genetics are used in medicine and discussions covering ethical considerations of human genomic data.

Offered every Fall, 3 credits. Instructors: Donna Werling and Steven Schrodi.

Pre-requisites: GENETICS 466, 468, BIOCORE 587, or graduate/professional standing.

STAT 620 – Statistics in Human Genetics

This course provides a comprehensive survey on the statistical and computational methods frequently used in human genetics and genomics research.

Offered every Spring, 3 credits. Instructor: Qiongshi Lu

Pre-requisites: STAT 333, 340, or graduate/professional standing

BIOCHEM/GENETICS 631 – Plant Genetics and Development

Covers the basic concepts of genetics and genomics as applied to plants and their development, including discussions on breeding systems (modes of reproduction, sex determination, self incompatibility and crossing barriers), linkage analysis, genome structure and function (structure, function and evolution of nuclear and organellar chromosomes; haploidy and polyploidy; expression regulation and epigenetics), along with a description of current methodologies used in the analysis of these processes within the context of plant development. The objective is to instigate a broader knowledge and understanding of the principles and methodologies used in plant genetics and their applications in investigations of the molecular mechanisms that modulate plant development.

Fall, 3 credits. Instructors: Patrick Masson, Jake Brunkard.

Pre-requisites: GENETICS 466, 468, BIOCORE 587, or graduate/professional standing.

GENETICS 636 – Public Health Genomics

Provides an introduction to public health genomics through a review of fundamental principles of genetics, the use of genetic information in clinical and research settings, and its implications for disease management and prevention, and health promotion. Explores policies that guide public health and discusses current ethical, legal, and social implications of these policies.

Spring, 1 credit. Instructors: Corinne Engelman and Silvia Barcellos

Pre-requisites: Junior standing and BIOLOGY/BOTANY/ZOOLOGY 151 or graduate/professional standing

GENETICS 650 – Functional Genomics of Brain Disorders

Functional genomics methods (RNA-seq, ATAC-seq, Hi-C, ChIP-seq, CUT&RUN/Tag, etc.) and their applications in the study of molecular and cellular mechanisms governing brain development, evolution, and neurodevelopmental and neuropsychiatric disorders. Overview of relevant aspects of Genetics and Neuroscience, including genomic approaches for gene discovery for human disorders and key properties of brain cells and circuit development. Bioinformatic approaches for analyzing genome-scale data sets. Critical consideration of experimental design and analysis strategies through reading and discussion of primary research literature and the development of an original research proposal. Emphasis will be placed upon how to effectively communicate science (written and oral).

Spring, 3 credits. Instructors: Donna Werling and Andre Moura Da Costa E Sousa

Pre-requisites: GENETICS 466, 468, BIOCORE 383, ZOOLOGY/PSYCH 523, or graduate/professional standing

MICROBIO 657 – Bioinformatics for Microbiologists

Provides a practical and fundamental introduction to sequence-based analysis focused on microbial systems. Emphasis on gaining a basic understanding of the principles of both classical and newer algorithms useful for bioinformatic analysis. Topics include: BLAST; RNA-seq analysis; transcriptional binding prediction; genome sequence assembly, analysis and annotation; and comparative genomics. Note that this course requires that each student have access to a laptop that runs a linux/unix Operating System such as a Mac or a ChromeBook. PC Laptops running a VM are also acceptable. No prior knowledge of computational biology is required.

Spring, 3 credits. Instructor: Garret Suen

Pre-requisites: MICROBIO 303, BIOCHEM 501, GENETICS 466, or 467 or graduate/professional standing

ONC 675 – Mining Genomics Data

The availability of current publicly available genomics and bioinformatics tools expands opportunities for in silico approaches towards hypothesis testing and hypothesis-generating biological research. While reading background literature is still necessary for forming the right questions to ask, we are developing a course to introduce students to resources and analysis skill sets needed to mine publicly available datasets. With an appreciation of the individual programming and bioinformatics capabilities of each student, the instructors will assemble small groups of students to understand: 1) what are the questions that can be addressed based on the available data, 2) where/how to find the most appropriate publicly available data; and 3) what basic analyses are needed to mine the genomic data. This class targets graduate students who use or plan to use genomic data in their research. Participants will either come up with their own biological questions or be assigned them by the instructors. Students will need to work/meet weekly as a group to develop the analysis pipeline for their project under the supervision of the instructors. Finally, students will be evaluated by presenting their contribution to their group project and feedback on other presentations.

Offered every Fall, 3 credit. Instructor: Huy Dinh.

Pre-requisite: Graduate student standing; students with no or little coding experience will need to meet the instructors to plan on learning coding basis 2 weeks before the course, depending on their needs.

BMI/COMP SCI 775 – Computational Network Biology

This course aims to provide students an introduction to different computational problems that arise in the biological networks, key algorithms to solve these problems, and in-depth case studies showing practical applications of these concepts.

Offered in Fall, 3 credits. Instructors: Sushmita Roy and Anthony Gitter.

Pre-requisite: Some experience with programming, computer science algorithms, and probability. Students can email the instructors about questions and concerns about their background.

ABT 775 – Tools for Data Analysis

Using a variety of existing and emerging bioinformatics tools and computational methods, emphasizes hands-on experiences analyzing and interpreting large data sets (e.g. genomic, proteomic, microbiomics, interactome, target discovery). Evaluate and adapt existing computational approaches for specific use in solving a problem in biotechnology.

Spring, 3 credits. Instructor: Natalie Betz

Pre-requisites: ABT 700 and 715

BME 780 – Methods in Quantitative Biology 

Focuses on understanding the key methods and principles of quantitative biology through a close reading of the primary literature. Topics covered will include deterministic and stochastic methods for modeling cellular systems, techniques in systems and synthetic biology, image processing tools and image analysis for biology, data-driven network models, genomic approaches, single-molecule approaches, and key computational biology tools. This course is intended for graduate students from a variety of backgrounds who are interested in pursuing quantitative biology during their graduate studies. 

1 credit. Instructors: Megan McClean.

Pre-requisites: Graduate/professional standing.

GENETICS 849 – Genomic Epidemiology

An introduction to genomic epidemiology, including a general overview of genetics and Mendelian and complex inheritance, as well as various elements of study design, such as participant ascertainment; phenotype definition; biologic sample selection; genotyping, sequencing, and quality control; measurement of covariates; and choice of analytic methods. Briefly covers original study designs; focuses on current study designs.

Spring, 2 credits. Instructor: Corinne Engelman

Pre-requisites: Graduate/professional standing

BMI 826-012 – Animal Experiments and Alternatives

Non-human animal experiments are typically motivated by their ability to contribute substantially to our understanding of the biological mechanisms underlying human health and disease. Nevertheless, results from non-human animal experiments are often limited in their translational value due in part to fundamental differences in physiology, poor experimental design, and/or lack of attention to hierarchical outcomes.

This course will examine what can and cannot be gained from different classes of non-human animal experiments. Alternatives to animal testing will also be discussed in detail. The course will provide students with an understanding of the assumptions imposed by different model systems and experimental designs as well as their impact on scientific inference. Students will also become familiar with alternatives to animal experiments and methods for designing optimal experiments given a particular set of scientific objectives.

This class is designed for graduate students interested in experimental design, analysis, and/or inference in non-human animal experiments. Those with a general interest in the use of animals in science are also welcome and encouraged to attend.

1 credit. Instructor: Christina Kendziorski

STAT/BMI 877 – Statistical Methods for Molecular Biology

Statistical and computational methods in statistical genomics for human and experimental populations. Methods for quality control, experimental design, clustering, network analysis, and other downstream analysis of next-generation sequencing studies will be reviewed along with methods for genome wide association studies.

Offered every other Spring, 3 credits. Instructors: Christina Kendziorski; Sunduz Keles; Qiongshi Lu; Colin Dewey; Sushmita Roy; Michael Newton; Tony Gitter; Daifeng Wang; Karl Broman; Zhengzheng Tang; Huy Dinh

Pre-requisites: Professional/graduate standing

GENETICS 885 – Advanced Genomic and Proteomic Analysis

With the availability of genome sequences and high-throughput techniques, organismal physiology can now be examined on a global scale by monitoring the behavior of all genes, proteins, metabolites, and molecules as well as how those components interact to form a functioning cell. This course will present modern techniques in genomics, proteomics, and systems biology with particular focus on analyzing the data generated by these techniques.  Course material will cover genomic sequencing, comparative sequence analysis, phylogenomics, single-cell and bulk RNA sequencing, sequence motif discovery, high- throughput screens, techniques in mass spectrometry, and network analysis. The course is designed for biologists who are motivated to understand underlying computational and statistical methods, with the goal of analyzing their own or published datasets.  In addition to lecture time, the course includes a weekly computer lab where students get hands-on experience analyzing genomic and proteomic datasets. An introduction to R and Python is included in the labs. Students also conduct a semester-long computational project of their choice that uses multiple computational methods discussed in class.

Offered every other Fall, 3 credits. Class enrollment is limited to 20 students due to computer-lab space and is restricted to graduate students. Prerequisites include: Genetics 466 or equivalent, basic statistics knowledge, & experience with Excel or R or other programming language.

Enrollment requires consent of instructor – please email Nicole Perna (ntperna@wisc.edu) or Audrey Gasch (agasch@wisc.edu) to enroll.

MD GENET 911 – Modern Clinical Genetics: How to Approach a Rapidly Changing Field 

Genetics and genomics are rapidly evolving fields. In modern clinical care settings, clinicians will be exposed to genetic and genomic data, including that brought by patients, and knowing how to read genetic and genomic data is increasingly necessary in clinical practice. Genetics and genomics in a clinical setting spans a wide range of topics including diagnosis and treatment of genetic diseases. Familiarity with clinical genetic analysis, and the genetic approaches used in basic science, helps medical students better understand genetic disease background. Learn how to bridge basic concepts of human genetics and clinical genetics (actual diseases). Emphases will include research into human genetic diseases, including designing genetic testing, using model organisms and/or cell culture systems, and the development of genetic testing technologies. 

Spring, 2 credits. Instructor: Akihiro Ikeda.

Pre-requisites: MED SC-M 810, 811, 812, and 813.

CHEM 923 – Genomic Sciences Program Seminar

Cross-disciplinary exposure to cutting edge research in genomic sciences. Seminars presented by trainees and other scientists who study genomics using approaches based in chemistry, computer science, biostatistics, engineering and biological and biomedical sciences. Research objectives, findings and future directions are discussed.

Offered every Spring and Fall, 1 credit. Instructor: Qiongshi Lu

Pre-requisites: Graduate/professional standing

ZOOLOGY 957 – Genome Architecture Evolution

Sections in various fields of zoological research.

Fall, 1 credit. Instructor: Carol Lee

Pre-requisites: Graduate/professional standing

PATH 970 – Genomics, Proteomics, and Metabolomics: A Deep Dive into Omics Data Analysis 

Advances in medicine are increasingly being driven by “big data” analyses, including proteomics, genomics, and metabolomics. Basic knowledge of how to analyze these datasets can allow one to generate and test hypotheses that have the potential to transform a field. In this course, students will conduct individual data mining expeditions using a collection of large proteomics and metabolomics data sets. Formulate hypotheses about the interrelationships of molecules and their potential relationship to health, disease, and biological phenotypes. Basic background instruction on “omics” methodologies, heritability studies, and analytical methods will be provided. Provides the basic knowledge to carry out future ‘omics analyses; using scientific inquiry to potentially transform the practice of medicine. 

Spring, 2 credits. Instructor: Irene Ong.

Pre-requisite: MED SC-M 810, 811, 812 and 813; or Declared in Cellular and Molecular Pathology Graduate Program.