Day 2 Agenda

Goals

Gain an overview of the challenges of transcript identification and the variety of computational methods.
Gain practical proficiency in the identification of known and novel transcript isoforms, as well as quality control of transcriptomes using tools like IsoTools and SQANTI3.
Understand how to create structural annotations using an evidence-driven approach that integrates long-read sequencing data.
Gain practical experience in deriving isoform-resolved functional annotations and drawing biological conclusions through visualization and exploration.

Time	Activity	Details
09:00 - 09:20	Transcript Identification	Yalan & Ana: Give an overview of basic concepts and the space of transcript identification and quantification tools (reference-reliant vs. de novo vs. quantification only)
09:20 - 09:40	IsoTools Theory	Yalan: Overview of theory and concepts of IsoTools algorithm and functionalities
09:40 - 10:30	IsoTools Practice	Yalan: Applying IsoTools to identify and quantify both known and novel transcripts, investigating results
10:30 - 11:00	Coffee Break
11:00 - 11:30	SQANTI3 Theory	Pablo: Motivate why we need transcriptome quality control and filter, and introduce SQANTI3 concepts like structural categories
11:30 - 12:20	SQANTI3 Practice	Pablo: Applying SQANTI3 to perform quality control, filtering, and rescue on a custom transcriptome
12:30 - 13:30	Lunch break
13:30 - 15:00	Structural Annotation Evaluation Theory	Pablo: How long-read sequencing integrates into structural genome annotation and its evaluation (ab initio predictions, identification of alternative splicing).
15:00 - 15:30	Coffee Break
15:30 - 16:00	Functional Annotation Theory	Pablo: How to map functions (from public databases or predictors) to isoform-resolved sequences
16:00 - 16:50	Functional Annotation Practice	Pablo: Utilizing IsoAnnotLite to obtain isoform-resolved annotations and visualization of results
16:50 - 17:00	Summary	Questions

Students should be able to understand common problems for transcript identification and quantification.
Students should be able to apply tools to identify and quantify transcript isoforms.
Students should be able to understand how long-read sequencing integrates in the structural genome annotation workflow.
Students should be able to use long-read sequences to validate gene models and assess performance
Students should be able to functionally annotate transcript models and evaluate annotation results.

Monzó, C., Liu, T. & Conesa, A. Transcriptomics in the era of long-read sequencing. Nature Reviews Genetics (2025). https://doi.org/10.1038/s41576-025-00828-z
Bi, Yalan, et al. “IsoTools 2.0: software for comprehensive analysis of long-read transcriptome sequencing data.” Journal of Molecular Biology (2025): 169049. https://doi.org/10.1016/j.jmb.2025.169049