One-Year Training Curriculum

As a GG Scholar, students will take a series of courses their first year as a cohort. The courses descriptions are listed below. In addition, the first semester students, even those who have already identified a PI, will participate in at least two rotations (and this can include the chosen PI). We help facilitate and arrange these rotations based on the students interests and interest of the faculty. We have included example syllabi here as well, but please note these courses evolve year-to-year, including instructors and topics.


Genetics & Genomics Survey Course

  • 6 credit hours


The goal of this course is to provide students with the broad understanding of pivotal topics in the field of genetics and genomics. A background in concepts and methods will be provided and followed by critical analyses of the reading and primary literature utilizing interactive discussions. This course gives the graduate students in the Genetics & Genomics Initiative program direct and engaged contact with all the major areas of research at the forefront of this field while providing an appreciation for where the field has been and what the big ideas are for the future.

Learning outcomes
  • Summarize & critically review pivotal papers and research in the field of genetics and genomics
  • Demonstrate understanding of the material through participation and leading of active discussions
  • Synthesize the breadth of topics covered and propose the next big research questions in the field

This course will meet 4-days per week (M, T, W, TH) for 75 minutes. This course is Team Taught by the GGI faculty and coordinated closely by Dr. Martha Burford Reiskind. The course is broken up into 2 to 3 week sections or modules, an example is below.

Topics covered

All modules will include interactive discussions and synthesis

  • Module 1: GG Scholars course orientation & critical thinking skill development: This module builds the student’s understanding of the knowledge base underpinning the field of genetics and genomics by exploring seminal papers, important technological advances and the variety of approaches to hypothesis testing. While expanding understanding of the field, students learn the critical skills for reading and reviewing the literature.
  • Module 2: Molecular population genetics: This module focuses on fundamental aspects of research in molecular evolution, from a population genetics perspective. This module uses the primary literature and assignments that help related patterns in population genetic data to inferences about how populations evolve.
  • Module 3: Epigenomics: This module explores the epigenome and the current state of research in epigenomics at the molecular, cellular and population scales. This module uses the primary literature, both review articles and experimental investigations and discussion of the important open question in the field.
  • Module 4: Genetic advances in evolution & development: This module introduces students to the history, goals, and questions in the field of Evolution & Development (EvoDevo). Students apply this knowledge to critically read and review the EvoDevo literature and case studies through interactive discussions.
  • Module 5: Concept and application of gene drive: In this module students synthesize across the topics introduced in previous modules and introduce the students to the exciting biology and evolution of natural, selfish genetic elements that inspired development of synthetic gene drive systems. Students assess the strengths and weaknesses of various gene drives for addressing specific problems.
  • Module 6: Synthesis and Group Projects: This module explores and integrate the concepts and methodologies learned in earlier modules, and apply them to topical research. This module challenges students to propose the next big ideas, technologies, and experiments in the field. Students conduct group projects, based on ideas and questions that emerged from earlier discussion during the course.

Genetics & Genomics Professional Development and Ethics

  • 3 credit hours


The main objective for this course is to help graduate students develop the tools and skills that they need to excel in graduate school and throughout their careers. The topics range from the practical to the philosophical. In addition, we will explore the ethical concerns facing professionals in the genetics and genomic fields in the 21st century, allowing the past to help inform the present and future. We focus on scientific writing in a variety of forms culminating in writing a grant proposal and  work on effective science communication. This course s value peer collaboration and feedback, developing professional relationships that will be important in graduate school and in their future careers.

Learning outcomes
  • Identify a philosophical & ethical perspective on science generally and the broad field of genetics and genomics specifically
  • Identify & evaluate critical features of excellent science writing and communication in the field of Genetics and Genomics
  • Develop a competitive grant proposal
  • Design & develop an effective poster and poster pitch
  • Identify & design their own path through their individual graduate program

This course will meet two days a week for 75 minutes. This course will be taught by the program coordinator Dr. Martha Burford Reiskind.


Genetics & Genomics Data Project Course

  • 3 credit hours


The main objective for this course is to help graduate students develop the tools and skills that they need conduct their own research in the data heavy field of genetics & genomics. In this course students learn how to apply principles of data science to the analysis of large multi-faceted data sets central to modern-day genetics and genomics. They develop basic skills for reproducible research, including project organization, version control and test-evaluate-diagnose development. Students explore the universe of genetic and genomics analysis packages, with a focus on the R data-science platform, and develop skills in genetics and genomics analyses, including RNA-seq differential expression and population genetics statistics.

Learning outcomes
  • Identify, evaluate & apply specific data analysis tools, software, and approaches to a variety of research question in the field of genetics & genomics
  • Demonstrate basic proficiency with data science skills including use of the command line (bash), version control (git/Github), and R (Rstudio)
  • Identify appropriate software packages for a genetic & genomic analysis, and execute the install, use and articulate problems with selected software.
  • Design and develop a computational analysis of genetics or genomic data set
  • Manage and negotiate collaborative computational analyses

This course will meet two days a week for 75 minutes. This course will be team taught by identified faculty in the GGI.

Scholars Program

Graduate Student Resources
Professional Development