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http://hdl.handle.net/10609/98010
Title: Analysis of scRNA-Seq from drosophila developmental tissues
Author: Pérez Lluch, Sílvia
Director: Cánovas Izquierdo, Javier Luis  
Tutor: Blanco García, Enrique
Keywords: scRNA-Seq
drosophila melanogaster
Issue Date: 4-Jun-2019
Publisher: Universitat Oberta de Catalunya (UOC)
Abstract: Organisms are formed by a huge variety of cell types. Conventional genomics approaches do not allow for the understanding of the diversity of cell populations forming tissues and organs. Recently, and with the aim of scrutinizing the cellular complexity of organisms, single-cell technologies have arisen, challenging the limitations of former methods. In this project, we have analyzed single-cell transcriptomics data generated in different laboratories and using a manifold of technologies. We first explored scRNA-Seq data produced by two independent groups on Drosophila melanogaster brain cells. Data from these reference datasets were generated using four different technologies, allowing for the assessment and correction of putative batch effects caused by the multiple platforms used. By implementing a number of pipelines in bash and R environments, we have processed these datasets from the mapping of raw fastq files to the identification of subpopulations of cells. Cells from the 8 identified clusters expressed several known marker genes involved in neuron and glia differentiation, permitting the full characterization of these populations. The pipeline implemented along this first part of the project was, afterwards, used to analyze scRNA-Seq data generated in our own lab on Drosophila wing imaginal discs. Within our dataset, we distinguished four clusters, although the low expression of known marker genes did not allow for a precise characterization of these populations. Still, we were able to identify several markers showing high variability between clusters, indicating that, indeed, these subpopulations represent different cell types within the wing.
Language: English
URI: http://hdl.handle.net/10609/98010
Appears in Collections:Bachelor thesis, research projects, etc.

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