PGEN5001: Semester 2, 2025

Units PGEN5001 Semester 2 2025 [Normal day]

Unit outline_

PGEN5001: Pathogen Genomics

Semester 2, 2025 [Normal day] - Westmead, Sydney

Overview

Genomics has revolutionised medicine, providing information on a scale not previously available. Pathogen Genomics is part of this revolution and the applications of this technology have provided crucial information on pathogen discovery, new drug development, control of outbreaks, pandemics and antibiotic resistance. This unit of study will introduce students to analysis of bacterial and viral genomes and main applications of genomics for translational research, precision medicine and control of diseases with epidemic potential. Students will learn how DNA or RNA is sequenced in the laboratory and develop analytical skills in microbial genomics, using public databases and the University of Sydney's high performance computing cluster. A combination of lectures delivered by domain experts and interactive practicals will provide detailed understanding of the key concepts of genomics utilized in research and clinical practice. Through targeted assignment, oral presentations and group projects students are encouraged to apply their learnings to critically examine genomic evidence and answer practical questions relevant to outbreak investigations and disease emergence.

Unit details and rules

Academic unit	Department of Medical Sciences
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	Basic understanding of microbiology or medical microbiology and genetics
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Rebecca Rockett, rebecca.rockett@sydney.edu.au
Guest lecturer(s)	King Gee Tam, kinggee.tam@sydney.edu.au
Lecturer(s)	Carl Suster, carl.suster@sydney.edu.au
	Rebecca Rockett, rebecca.rockett@sydney.edu.au
	Shona Chandra, shona.chandra@sydney.edu.au
	Eby Sim, eby.sim@sydney.edu.au
	Connie Lam, connie.lam@sydney.edu.au
	Tanya Golubchik, tanya.golubchik@sydney.edu.au

Assessment

The census date for this unit availability is 1 September 2025

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Written exam ?	Final exam extended answer questions	50%	Formal exam period	1.5 hours	AI prohibited
Outcomes assessed:
Presentation	Journal club presentation 15 min group presentation	10%	Week 05 Due date: 07 Sep 2025 at 23:59	15 min	AI allowed
Outcomes assessed:
Presentation	Group assignment/report and presentation Bioinformatic group proj. with selected pathogens relevant - course content	20%	Week 11 Due date: 26 Oct 2025 at 23:59	Week 5 - Week 10 (15 min grp presentati)	AI allowed
Outcomes assessed:
Written work	Paper review/written assessment 1000 words written report on pre-selected topics	20%	Week 13 Due date: 07 Nov 2025 at 23:59	1000 words	AI allowed
Outcomes assessed:
= group assignment ?

Assessment summary

Assessment	Weighting	Due date
Final exam	50%	Exam period
Journal club presentation	10%	Wk 5
Group assignment/report and presentation	20%	Wk 10
Paper review/written assignment	20%	Wk13

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

For more information see guide to grades.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

Late penalties apply from the day after the published due date (two marks (out of 100) per day)

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Week 01	Lecture: Pathogen genomics, introduction to the course	Lecture (1 hr)
	Lecture: Microbial genomes, units of analysis, core and accessory genomes	Lecture (1 hr)
	Seminar: Genome mapping, alignment and assembly	Seminar (2.5 hr)
Week 02	Lecture: High-throughput sequencing methods	Lecture (1 hr)
	Lecture: Genome polymorphisms and recombinations	Lecture (1 hr)
	Practical 1: Genomic nucleic acid extraction, sequencing library preparation and short read sequencing	Practical (3 hr)
Week 03	Lecture: Genomic markers of virulence in viruses and bacteria	Lecture (1 hr)
Week 03	Practical 2: Identification of the taxonomic position of viruses and bacteria from genomic data	Practical (2 hr)
Week 04	Lecture: Genomic mechanisms of emergence of pathogens	Lecture (1 hr)
	Lecture: Genome-wide association studies for discovery of mechanisms of virulence and resistance	Lecture (1 hr)
	Practical 3: Detection of genes for virulence assessment	Practical (3 hr)
	Core genome analysis for bacterial genomics – case studies	Seminar (1 hr)
Week 05	Lecture: Phylogenomics of pathogens	Lecture (1 hr)
	Practical 4: Estimation of phylogenetic relationships between genomes	Practical (1.5 hr)
	Self-directed learning: Journal Club Presentations	Presentation (3.5 hr)
Week 06	Lecture: In silico testing for drug resistance	Lecture (1 hr)
	Lecture: Plasmid-mediated antibiotic resistance	Lecture (1 hr)
	Seminar: Critical review of AMR databases	Seminar (1 hr)
	Practical 5: Detection of mutations and inference of antibiotic resistance	Practical (1.5 hr)
Week 07	Lecture: Pathogen discovery	Lecture (1 hr)
	Lecture: Culture-independent sequencing for pathogen detection and microbiome assessment	Lecture (1 hr)
	Seminar: RNAseq workflow for meta-transcriptomics	Seminar (1 hr)
Week 08	Lecture: Genomics-guided public health surveillance	Lecture (1 hr)
	Lecture: Genomics for outbreak investigations	Lecture (1 hr)
	Seminar: Visualisation of multi-dimensional genomic and clinical data	Seminar (1 hr)
	Practical 6: Deciphering an outbreak of tuberculosis and approximation of transmission pathways from genomic data	Practical (2 hr)
Week 10	Lecture: Genomic surveillance during COVID-19 pandemic	Lecture (1 hr)
	Lecture: Integration of genomic, epidemiological and clinical data	Lecture (1 hr)
	Site visit: Visit of the NSW Public Health Pathogen Genomics Laboratory, NSW Health Pathology, Westmead Hospital	Field trip (2 hr)
Week 11	Lecture: Evolution of genomes and proteomes under vaccine pressure	Lecture (1 hr)
	Lecture: Integration of genomic, epidemiological and clinical data	Lecture (1 hr)
	Self-directed learning: Group project presentations & reports	Presentation (4 hr)
Week 12	Lecture: Genomics of host-pathogen interactions	Lecture (1 hr)
	Lecture: Genome graphs: from reference genomes to decision support systems	Lecture (1 hr)
	Seminar: Genomic analysis of microbial within-host subpopulations	Seminar (1 hr)
Week 13	Lecture: Transcriptomics for study of different approaches to virulence and microbial growth	Lecture (1 hr)
	Lecture: Transcriptome reconstruction and profiling for next generation risk assessment	Lecture (1 hr)
	Tutorial: Subtractive genomics for assessment of targets from drugs and diagnostic assays and vaccine redesign	Tutorial (1 hr)
	Expert Panel: Genomic data governance and responsible data sharing and mobilisation	Tutorial (1.5 hr)

Attendance and class requirements

In-person attendance is expected for all lectures, seminars, and practicals, as active participation is essential for developing key skills and engaging with your peers. Students are permitted up to three absences with prior notification. While no marks will be deducted for further absences, students with ongoing non-attendance may be contacted to discuss participation and support needs.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

available on Canvas

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. Understand sequencing data and relevant quality metrics
LO2. Taxonomically classify microorganisms using short read sequencing data
LO3. Identify variation in viral, bacterial and metagenomics data
LO4. Generate and examine phylogenetic trees based on nucleotide polymorphisms and core genomes
LO5. Perform genome mapping, assembly and annotation using different resources
LO6. Interpret genomic data from an outbreak investigation
LO7. Determine relevant drug resistance genes and mutations
LO8. Understand main approaches for genome data visualisation
LO9. Recognise challenges and identify solutions for pathogen genomic data gathering, analysis, governance and reporting

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

Decreased focus on COVID and integration of laboratory based practical

Additional information

OLEO5502-Introduction to Pathogen Genomics

Site visit guidelines

NSW Health Pathology site visit in Week 10 will require student to wear closed toed shoes as they will be entering laboratory areas

Work, health and safety

Closed toe shoes to practical laboratory session in week two

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Site visit guidelines

Work, health and safety

Disclaimer

On this page

Useful links