RNA Transcriptomics (Virtual) (cancelled)

Please note: Due to the ongoing Covid-19 pandemic, the 2021 RNA Transcriptomics course will be delivered in a virtual format.

Rapid advances in genome analysis technology have opened up new and exciting possibilities for the study the transcriptome and its function.

In particular, third generation, single molecule sequencing technologies and single cell technologies, combined with perturbation tools, allow the analysis of complete RNA species – both short and long – at high resolution. In parallel, these tools have opened new ways in understanding gene functions at the tissue, network and pathway level, as well as detailed characterization of their function.

This virtual course will provide training in advanced laboratory and computational methodologies for the analysis of transcriptomes, including long non-coding RNAs and microRNAs, along with their post-transcriptional and epi-transcriptomic modification.

The programme will focus on new technologies for:

• complete single molecule cDNA sequencing
• single cell RNA sequencing and the characterization and analysis of non-coding RNAs (such as lncRNAs and microRNAs)
• analysis of the epi-transcriptome, including RNA methylation and modification

The teaching sessions will be complemented by instructor seminars and informal discussions, along with a distinguished keynote speaker lecture, who will present the latest research in this fast-moving field.

For our virtual courses, we use video conferencing (Zoom) and instant messaging (Slack) applications along with other online and virtual machine (VM) teaching resources to deliver the different elements of the course as interactively as possible.

The course will run approximately 10:00-17:00 (BST) daily. Some teaching materials will be pre-recorded but participants must be available to attend live, interactive sessions online between these times.

The programme will include virtual lectures, discussions and hands-on, interactive sessions covering the following topics:

• Overview of single molecule long read sequencing technologies
• Full length cDNA sequencing
• Small RNA sequencing
• Single cell transcriptome data generation and analysis
• Identification of post-transcriptional modifications in RNA (epi-transcriptomics)
• Functional assays for lncRNA biology
• Integration of microRNA and mRNA data; functional analysis of microRNAs
• Expression network and pathway integration and analysis

*Please note: To fully benefit from the data analysis sessions participants will require a basic knowledge of Linux/Unix command line as well as the R programming environment. Numerous free online tutorials are available in these resources. e.g.:
http://www.ee.surrey.ac.uk/Teaching/Unix/
https://www.datacamp.com/courses/free-introduction-to-r

Learning Outcomes
After attending this course, participants will able to:

• Evaluate advanced RNA transcriptomic analysis methodologies and their applications
• Appreciate different approaches currently in use to address specific research questions in the field
• Assess the strengths, weaknesses and limitations of different methodologies and approaches
• Integrate and apply the knowledge and training from the course to their own research interests

Course instructors

Jiannis Ragoussis
McGill University, Canada

Francesca Buffa
University of Oxford, UK

Alena Shkumatava
Curie Institute, France

Anton Enright
University of Cambridge, UK

Keynote Speaker

David Bartel
MIT Department of Biology, USA

Prerequisites
Applicants should be PhD students, postdocs or clinical scientists/clinicians/healthcare professionals engaged in relevant research.

Please note that due to the virtual format for this course, participants will require minimum computer specifications and internet access to fully benefit. A guide to these requirements can be found here (PDF).

How to Apply
Please click the Apply button above to begin the online application process. Places are limited and will be awarded on merit. If you have any problems with the online application process, please contact us.

Please note: Applications must be supported by a recommendation from a scientific or clinical sponsor (e.g. supervisor, line manager or head of department). A request for a supporting statement will be sent to your nominated sponsor automatically during the application process. Applicants must ensure that their sponsor provides this supporting statement by the application deadline. Applications without a supporting statement cannot be considered.

*The course fee is subsidised by Wellcome Genome Campus Advanced Courses and Scientific Conferences and applies to non-commercial applicants. Please contact us for the commercial fee.

Bursaries
Limited bursaries are available (up to 50% reduction on the course fee) and are awarded on merit. If you would like to apply for a bursary, please complete the bursary section of the online application form.

Where there are many bursary applications, the selection committee may issue smaller amounts.

Bursaries can be applied for as part of the course application form. Applicants will be notified of a bursary award along with their place on the course, usually within one month of the application deadline. The decision of the selection committee is final.

Please note that both the applicant and sponsor are required to provide a justification for the bursary as part of the application.

Additional funding opportunities
Visit our support page for additional financial support currently available.

Accommodation services phishing scam – please be vigilant. More information.

Feedback from the 2019 course:

“All the instructors on the course were very knowledgeable. Having an aspect of wet lab with bioinformatics was perfect! This course helped me get an overview of all the techniques and tools available for data analysis which would be very helpful for my future work. The food and accommodation were great too!”

“The course was amazing! The quality of the teaching was extremely high and the lecturers were such experts!”

“Just a big thank you to all organisers, instructors, and everyone involved for amazing experience and great opportunity to discuss my research as well as the ideas inspired from this course”

“Thank you so much for organising this intensive, comprehensive and amazing course.”

“The course content was well organized, course trainers were very very passionate about making this course successful”

“Thank you so, so much to everyone involved. The huge amount of time and effort behind the scenes and every night working on the data was just incredible and I really appreciated it.”

“Excellent course! Definitely would recommend!”

“Thank you for allowing me the opportunity to attend this course. It was extremely beneficial.”