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CD Genomics Perspective: RNA Sequencing, A Powerful Method for Studying Various Diseases

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Kiko Garcia

Although post-mortem brains have been frequently reported as the "gold standard" in transcriptomic research for ND and neuropsychiatric abnormalities, the main sources has been mRNA separated from transgenic animal models and, more lately, patient-derived cell lines. However, despite their promise, transcriptome studies are difficult due to the obvious difficulties in obtaining brain tissue and the fragile nature of isolated RNA.

 

 Microarray analysis, which is widely used for ND and neuropsychiatric disorders, has provided a wealth of information about transcriptional profiles in pathological states, despite mixed results. The loss of convergence could be credited to microarray limitations, as well as the variable quality/integrity of RNAs, which is heavily impacted by pH and can dramatically alter nucleotide probe binding, influencing gene expression levels. Because ND patients have a prolonged agonal state in brain tissue (which is strongly linked to pH changes), differences in RNA integrity may account for aberrant gene expression profiles to some extent. This could be mitigated in part by using a sequencing-based technology that is less delicate to fragmentation, if at all.

 

RNA Sequencing in Cardiovascular Disease Research

The use of scRNA-seq technology in cardiovascular research has a wide range of applications. scRNA-seq not only identifies rare cell subpopulations, but it also allows for cellular trajectory analysis based on each cell's transcriptome, which has been particularly beneficial in clarifying cell state transitions during development and progenitor or stem cell differentiation. Furthermore, scRNA-seq has allowed the creation of transcriptomic and epigenetic atlases of crucial tissues in adult mice and human fetuses, such as the heart and coronary arteries.

 

Organ-specific or tissue-specific transcriptomic features of common cardiovascular cell types like endothelial cells, vascular smooth muscle cells (VSMCs), and fibroblasts can be evaluated using these datasets, shedding light on the functional heterogeneity of ubiquitously present cell types that underpin their organ-specific roles.

 

Intercellular communication via ligand-to-receptor binding can also be anticipated on the premise of gene expression, thanks to the ability of scRNA-seq to cross-analyse the single-cell transcriptome of multiple cell types present in a given sample. Progress in spatial transcriptomics14–18, particularly the use of RNA-seq with spatially barcoded primers on a fixed and permeabilized segment of tissue to trace the transcriptomic information from the known coordinates of the tissue, are anticipated to supplement these kinds of analysis. Notably, assessing cell population heterogeneity and its contributions to patient-specific drug responses and adverse effects will require a combination of single-cell genomics, transcriptomics, epigenomics, and proteomics.

 

RNA Sequencing in Ophthalmology Disease Research

The emphasis on temporal gene expression through examination of the active transcriptome of tissues, cells, and model systems using RNA-seq has risen since the advent of high-throughput sequencing technologies. The use of RNA-seq in ophthalmology and vision research is widespread. Investigation of gene expression shifts in keratoconus patients' corneal epithelial tissue, for example, has revealed the cause of this progressive corneal degeneration. In keratoconus epithelium, signaling pathways such as Wnt, Hedgehog, and Notch1 were found to be significantly reduced.

 


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Kiko Garcia
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