One-Year Training Curriculum

 

One-Year Training Curriculum

 

Fall Semester

Genetics & Genomics Survey Course

6 credit hours

Overview

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 will provide 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

Logistics

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

Topics covered

Introduction to the course and History of the field of Genetics & Genomics

  • Module 1: GG Scholars course orientation & critical thinking skill development: This module will build 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.
  • Module 2: Molecular population genetics: This module will focus on fundamental aspects of research in molecular evolution, from a population genetics perspective. This module will use the primary literature and assignments that help related patterns in population genetic data to inferences about how populations evolve. The module will include interactive discussions and synthesis.
  • Module 3: Epigenomics: This module will explore the epigenome. Students will explore the current state of research in epigenomics at the molecular, cellular and population scales. This module will use the primary literature, both review articles and experimental investigations and discussion the important open question in the field. The module include interactive discussions and synthesis.
  • 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 will explore will apply this knowledge to critically read and review the EvoDevo literature. Students will review several case studies through interactive discussions.
  • Module 5: Concept and application of gene drive: In this module students will 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 will assess the strengths and weaknesses of various gene drive for addressing specific problems. The module include interactive discussions and synthesis.
  • Module 6: Synthesis and Group Projects: This module will explore and integrate the concepts and methodologies learned in earlier modules, and apply them to topical research.This module will also challenge students to propose the next big ideas, technologies, and experiments in the field. Students will conduct group projects, based on ideas and questions that emerged from earlier discussion during the course. The focus will be on synthesizing material from the breadth of topics covered during the course to address these questions and ideas.

 

Spring Semester

Genetics & Genomics Professional Development and Ethics

3 credit hours

Overview

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 will focus on scientific writing in a variety of forms culminating in writing a grant proposal and will work on effective science communication. This course will 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

Logistics

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

Overview

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.Large multi-faceted datasets are central to modern-day genetics and genomics. In this course students will learn how to apply principles of data science to the analysis of genetics and genomic data. They will develop basic skills for reproducible research, including project organization, version control and test-evaluate-diagnose development. Students will explore the universe of genetic and genomics analysis packages, with a focus on the R data-science platform. They will develop their skills in common 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

Logistics

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