Page 20 - Molecular features of low-grade developmental brain tumours

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side effects, including stomatitis, diarrhea, nasopharyngitis, pyrexia, and upper respiratory tract infections181,192,193. Therefore, identifying other targets for therapy are of the utmost importance and can be established with new techniques such as next-generation sequencing.
Unraveling the transcriptome using RNA-sequencing
Over the past two decades, the development of various next-generation sequencing have transformed the landscape of research in molecular biology 194. The use of microarrays, which uses a predesigned set of probes, have been replaced by next generation RNA- sequencing (RNA-seq), which allows for the entire gene expression profile of a sample to be assessed in a high-throughput manner 194,195. Giving a snapshot of the gene-expression profile of a tissue or cell at a specific moment in time. Additionally, alternative splicing events, novel transcripts, gene fusion events, map transcription start sites, sequence variation in transcripts and circular RNAs (circRNAs) can be detected with RNA-seq 194-197. Furthermore, modifications of the standard RNA-seq workflow has given rise to several different RNA-seq based technologies, including small RNA-seq, single-cell RNA-seq (scRNA-seq), single-nuclei RNA-seq (snRNA-seq) and spatial transcriptomics.
A next-generation RNA-seq experiment can be divided into three distinct phases; sample or library preparation, sequencing, and data analysis. During library preparation, RNA is isolated from a sample and reversed transcribed into cDNA, which is followed by ligation of adapters to the end of the ensuing molecules resulting in the generation of cDNA library 196. The ligation of adapters introduces a unique barcode to each sample allowing for multiplexing of samples during sequencing. Throughout the library preparation steps there are a number of options which can be chosen that will impact on the data produced 195,198. RNA for RNA-seq can be poly-A selected or selected via ribosomal(ribo)-depletion; poly-A selection enriches for mRNAs and the polyadenylated fraction of non-coding RNAs (ncRNAs), while ribo-depletion enriches for mRNA, pre-mRNA and ncRNA and also allows for the identification of circRNAs 199. The generated cDNA library is then subject to sequencing, utilising the sequencing-by-synthesis strategy. While sequencing itself is a rather trivial process there are a number of parameters or sequencing conformations that must be considered, including read-length, single-end (SE) or paired-end (PE), and read depth 200. Regardless of the type of RNA-seq carried out the data-analysis workflow is made up of the following steps; quality control (QC), mapping of reads, quantification of expression of genes or transcripts to generate a count (or expression) matrix. Once a gene or transcript count matrix has been constructed differentially expressed genes can be identified, followed by a pathway or gene ontology enrichment analysis. More advanced analysis techniques can also be used, including weighted gene co-expression network analysis (WGCNA) or various machine learning techniques.
For pLGGs RNA-seq has provided evidence that supports the role of the ERK/MAPK pathway in these tumours and has helped in identifying genetic alteration in these tumours 21,22,38. Recently, the transcriptional profile of LEATs identified four clusters each with distinct signature genes that do not fully resemble the histopathological classification of LEATs 201.