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Ebrahimi, Ghazal

University of British Columbia

The most severe type of male infertility, known as non-obstructive azoospermia (NOA), is characterized by the absence of sperm in the ejaculate due to spermatogenesis failure. Of all NOA patients, only ~30% are ultimately given a precise diagnosis, leaving the vast majority with no clear explanation for their infertility. Genome/exome-wide studies identified a range of candidate genes responsible for proper sperm formation and testis development. However, bulk sequencing studies have limitations in studying tissue with numerous cell types. Specifically, this is problematic when investigating cellular dysfunction in the testis tissue, whether it be normal control tissue or idiopathic infertility. Alternatively, single-cell RNA sequencing (scRNA-seq) provides gene expression profiles at the level of individual cells and can overcome the limitations of bulk RNA sequencing in this regard. Gene expression data within cells are useful in providing insight into cellular programs and intrinsic biological processes. However, single genes can be comprised of various isoforms that differ in the order and composition of their respective exons, which have significant biological implications in subsequent protein translation and function. Regardless of bulk or single cell, short-read RNA-sequencing technology has limitations in revealing the gene structure, i.e., isoforms. On the other hand, long-read RNA-seq makes it possible to determine the sequence of exons in the transcript isoforms. Recently, new library preparation techniques in single-cell workflows have been developed to take advantage of both long-read RNA sequencing and short-read scRNA-seq libraries. However, computational identification of originating cells of the resultant long-reads using the short-read generated single cell barcodes is not a trivial task because of the relatively high error rate in long-reads. The human testis has been shown to have the highest RNA splicing compared to other tissues. A previous study investigating bulk proteomics of NOA tissue identified RNA splicing machinery as being among the most dysregulated compared to healthy controls. Therefore, we hypothesize that characterizing RNA isoforms on a single cell level will provide critical biologic insights to normal human spermatogenesis as well as pathologic underpinnings of dysregulated spermatogenesis present in NOA.

Text

2023-09-30

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/82642

Bioinformatics

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/