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Building A Better Transcriptome


From a single embryo to billions of cells, a whole organism is constructed in a carefully regulated symphony. Every cell in our body shares the same sheet of music in the form of DNA but it is through RNA transcription that rhyme and meter are kept; comprised of a complex regulatory system determining when genes get turned on or off. It is through this regulation that alterations occur, allowing two identical cells to ultimately give rise to completely separate organs and tissue systems. Our current understanding of these processes relies heavily on using short-read sequencing technology to analyze whole transcriptomes. However, this method requires fragmentation of full-length molecules, making it difficult to recapitulate the transcriptome landscape in its entirety. Requiring heavy computational tools to assemble the transcriptome, which only provides an estimation. This loss of contiguity makes it clear we cannot depend on short-read RNA sequencing alone to truly understand the complexities within our transcriptome. Thus, I have established a toolset for creating better, more precise transcriptomes from single cells to bulk RNA studies. This body of work entails how we can elucidate transcript features that tend to be lost in short-read sequencing data. These improvements include developing a 5’ capturing method for single cell data, employing a long-read single cell full-length cDNA sequencing method, increasing throughput and limiting length bias for bulk transcriptomic studies. Together, these improvements create a better snapshot of the transcriptome and will help change how we analyze transcriptomes.

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