Long-read transcriptomic profiling across human tissues and scales: from bulk to single-cell resolution

Kudasheva, Sofia (2025) Long-read transcriptomic profiling across human tissues and scales: from bulk to single-cell resolution. Doctoral thesis, University of East Anglia.

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Abstract

The advent of long-read sequencing technologies offers an unprecedented opportunity to systematically characterise transcript diversity, yet analytical frameworks for accurate isoform discovery and quantification remain underdeveloped.

This thesis leverages Oxford Nanopore long-read RNA sequencing to develop and benchmark computational approaches for isoform-level analysis, applying them to diverse biological contexts ranging from post-mortem human brain tissue to induced pluripotent stem cell (iPSC)-derived neuronal and cardiac models.

In Chapter 2, I employed targeted long-read CaptureSeq across multiple human brain regions and conditions to generate a comprehensive isoform catalogue. By benchmarking competing annotation pipelines and integrating orthogonal evidence, I identified novel isoforms of risk genes, some of which were differentially enriched between brain regions and in the brains of donors with psychiatric disease. The pipeline developed in this chapter was then tailored and applied to the datasets in chapters 3 and 4.

In Chapter 3, I adapted these workflows for single-cell long-read sequencing, enabling the construction of transcriptome references for iPSC-derived neurons, astrocytes, and microglia from a shared genotype. This work revealed cell–type–specific isoform regulation and splicing heterogeneity, and highlighted both the opportunities and limitations of single-cell long-read methods for resolving transcript diversity.

In Chapter 4, I investigated the role of the small nucleolar RNA SNORD116 in cardiomyocyte differentiation using long-read RNA-seq of knockout and control iPSC-derived cardiomyocytes. This analysis uncovered differentiation stage-specific changes in splicing and alternative polyadenylation, pointing to putative targets of SNORD116 regulation during cardiac development.

Together, these studies show that long-read sequencing is a powerful approach for uncovering
isoform diversity and its functional relevance in the human brain and in stem cell–derived models of neuronal and cardiac differentiation. This work improves both the interpretability of ONT data and the robustness of downstream analyses. It also begins to establish methodological foundations for integrating long-read transcriptomics with orthogonal functional assays, moving towards a systematic characterisation of the molecular and phenotypic impact of specific RNA isoforms in health and disease.

Item Type:	Thesis (Doctoral)
Faculty \ School:	Faculty of Science > School of Biological Sciences
Depositing User:	Chris White
Date Deposited:	12 Feb 2026 11:56
Last Modified:	12 Feb 2026 11:56
URI:	https://ueaeprints.uea.ac.uk/id/eprint/101927
DOI:

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