Fish/Biol 340: Introduction to Genetics and Molecular Ecology

An overview of the fundamentals of molecular genetics and the application of genetic techniques to problems in ecology, evolution and natural resource management

Autumn Quarter 2025, 5 Credits

Course Description

Rationale

In the past few decades, molecular genetics has become one of the fastest growing fields in the life sciences. The application of molecular methods has spread to virtually all fields of modern biology, including ecology, conservation, breeding and natural resource management, leading to the establishment of a new discipline, Molecular Ecology. With the expansion of the application of molecular tools, it has become crucial that all biologists have a basic understanding of genetics and molecular biology, and the application of molecular tools to the detection of kin, the identification of populations, the reconstruction of phylogenetic relationships, and more recently, to the understanding of local adaptation and evolution. Rather than providing an overview of classical genetics, the aim of the course is to provide an understanding of the genetic principles underpinning these applications, thus allowing an assessment of the potential and limitations of molecular approaches to specific questions in ecology, evolution and resource management.

The course will be important to students for the following main reasons:

• Basic understanding: The current ubiquity of molecular genetic studies in virtually all fields of biology requires some basic understanding of the genetic principles underpinning molecular methods. Continuing developments in molecular technology, statistical analyses and computer power will further widen potential applications. Thus, even if students do not envisage using genetics in their own research, some genetic knowledge will be necessary in almost any career track.
• Practical application: If molecular genetic methods are to be applied effectively in ecology, evolution and general biology, they have to be carefully chosen according to the ecological and biological circumstances, assumptions of the methods and the specific aims of the study. Furthermore, an understanding of the evolutionary dynamics of molecular markers in the context of the biological question of the research is a crucial prerequisite for the interpretation of genetic data. It is thus necessary that students have a good overview of available methods, their appropriate application and potential shortcomings.
• Communication: Many of the current problems in the application of genetic data are founded in conceptual misunderstandings between scientists applying genetic methods and the end users of their research (fisheries managers, breeders, forest managers, conservationists). It is therefore important that students are aware of these misunderstandings and are able to understand and explain genetic research.

Aim and Objectives

To provide students with a fundamental understanding of genetic principles underlying the application of molecular genetic techniques.

Students will be able:

• To understand basic principles of molecular genetics
• To apply such principles to ecological, environmental and conservation research
• To interpret genetic data in an applied context
• To communicate and disseminate the results of their research

Basic Approach

We will achieve the above aim and objectives by the following means

• Lecture Videos: Most basic material will be delivered as short videos by subject. Watch those videos, and take notes! Most videos also contain one or two quiz questions, which will contribute to your grade. Make sure you watch these videos before class sessions, because  I will not repeat them in class.
• Class sessions: Class sessions on Tuesday and Thursday will be in person in FSH107 and will be used to go over examples and past exam questions. Class sessions will use graded PollEverywhere questions, so make sure you are registered.
• Textbook: there is no required textbook for this class, but there are lecture notes and book chapters that are required reading - you can find those on the Readings page.
• Primary literature: We will deal with primary literature in two aspects of the course:
  • the Research Project will require you to find, evaluate and incorporate primary literature in your project report. Some literature will be posted on the Lab Project page, but other you will have to find yourself on Google Scholar or the Web of Science. 
  • One of the labs will be about interpreting figures from publications. You won't have access to the original papers for this exercise, but we will distribute references afterwards,

You should read these papers - although they won't be on the exam per se, they may be used as examples in exam questions aiming at lecture material. Furthermore, they will help you deciding on style and detail needed for your project report.

• Laboratories:
  • Molecular Labs (Wet Labs, FTR 113): The first three weeks labs will be used to introduce you to molecular methods such as DNA extraction, PCR and electrophoresis. These methods usually involve a lot of waiting, so we will use these labs also to deepen your theoretical understanding of molecular methods. As part of these labs, you will write up a short report comparing two different DNA extraction techniques. 
  • Computer Labs (FSH 136) will be used to improve and deepen your understanding of concepts from lecture and textbook (see also the lab sections on the Modules page). We will use simulation programs to learn about genetic processes and analysis programs to analyze sample data sets. Although Windows PCs are available in the lab, please download all required software (which is free, links available on the Links page) on your own laptop. If you don't have a laptop, you can loan one from the Student Technology Loan Program. However, especially on Macs, we can't really help you if you run into specific problems. As part of these labs, you will conduct a study investigating hybridization of rockfish species in Puget Sound - details to come.  

See the 'Pages' (Front Page) link for more information about the course, lecture notes and lab handouts.

Technology

We will use a lot of technology, and here are a few pointers:

• If you are off-campus and you want to access on-campus resources, the best way is to install Husky-OnNet. This software will allow you to access library and other resources, though you will still have to sign on to Canvas.
• Communication: Please use EdDiscussion for any questions - our response time is likely much shorter there than by e-mail. Make sure to search EdDiscussion before asking questions. Also, feel free to reply to questions - instructors will monitor traffic and approve correct answers. Students who consistently answer questions correctly will  receive extra points.
• Clickers: As a classroom response system, we will use PollEverywhere, which is free for students. You are already registered, so make sure you login with your UWNetID to receive credit. Have your device handy, and respond under www.pollev.com/lorenz.
  

Artificial Intelligence (AI)

Artificial Intelligence is becoming more and more pervasive, and the reality is that it hard to avoid to use it. Even if you do a Google search, AI will provide a summary. The key is to use AI in a responsible and ethical manner, and we will discuss these issues in this class.

In this course, students are permitted to use AI-based tools for some assignments. In general, you should use AI to obtain feedback on something you produced already, rather than to create new content. The instructions for each assignment will include information about whether and how you may use AI-based tools to complete the assignment. All sources, including AI tools, must be properly cited. Use of AI in ways that are inconsistent with the parameters above will be considered academic misconduct and subject to investigation.

Please note that AI results can be biased and inaccurate. It is your responsibility to ensure that the information you use from AI is accurate. Additionally, pay attention to the privacy of your data. Many AI tools will incorporate and use any content you share, so be careful not to unintentionally share copyrighted materials, original work, or personal information. For this reason, Microsoft Copilot is the only UW-supported generative AI tool. The UW agreement with Microsoft provides added protections, including enhanced protection of user data and privacy, for all UW users. 

Learning how to thoughtfully and strategically use AI-based tools may help you develop your skills, refine your work, and prepare you for your future career. If you have any questions about citation or about what constitutes academic integrity in this course or at the University of Washington, please feel free to contact me to discuss your concerns.

Strategies for success

The most important thing in this class is to be an active participant, and be prepared for lectures and laboratories. Make sure you stay up to date with the lecture material, and ask if anything is unclear. Make sure to watch videos and complete quizzes before synchronous class sessions. DO NOT leave revisions until the day before the exam. Also, make sure to read lab handouts before lab, and submit your lab reports in time. Be aware that the project report (together with the drafts) counts for 35% of the class grade - you won't pass this class without submitting a final project report. Make sure to submit your drafts and reviews on time (Wednesdays, 23:59), and most importantly, keep on revising your drafts throughout the quarter.

Time table

This is a very rough timetable  by week. More specific details will be provided under Modules