Discovering the transcription factor code that specify neural stem cell identity in the Drosophila brain

Prakash, Lakshmi (2022) Discovering the transcription factor code that specify neural stem cell identity in the Drosophila brain. Masters thesis, Indian Institute for Science Education and Research Kolkata.

Text (MS dissertation of Lakshmi Prakash (17MS023)) 17MS023_Thesis_file.pdf - Submitted Version Restricted to Repository staff only Download (41MB)

Abstract

Drosophila neurogenesis is considered an excellent model for learning stem cell generation, renewal, and differentiation. The entire neuronal repertoire of Drosophila central brain originates from only approximately 100 pairs of neural stem cells, or neuroblasts (NB), which are derived from the embryonic neuroectoderm. During the early embryonic stage, the developing neuroectoderm is subjected to the same embryonic patterning that establishes the antero-osterior(A-P) and dorso-ventral(D-V) body axes. Thus, A-P patterning genes like gsb, en and the D-V patterning genes like ind, msh, vnd create a cartesian coordinate system developing a molecular heterogeneity in the neural stem cells. Since these genes are expressed in discrete spatial domains and mostly encodes transcription factors, we call these genes as spatial transcription factors in the context of the nervous system. Depending on the combination of these sTFs acting on a NB, each NB is made molecularly distinct, allowing it to make a unique, but stereotyped lineage of neurons and glia. Lineage development happens about 5-6 days after neuroectoderm patterning by which the neuroblast leaves the spatially patterned neuroectoderm by the process of delamination. The process by which these molecular identities are preserved long after delamination from the neuroectoderm is an interesting question tounravel. There are two possible mechanisms in which this could occur: 1) The spatial transcription factors can either alter the chromatin of the neural stem cells, or 2) They might show persistent expression in neural stem cells in each division resulting in maintaining the neuroblast identity. Here we are testing the possibility of persisting expression of spatial patterning genes in the neuroblast using publicly available scRNA sequencing data of the Drosophila brain. Initially, we extracted pure neural stem cells from whole-brain sequencing data using previously described molecular markers. To capture the expression patterns of low abundant genes like transcription factors, which might drop out of the data, we developed and validated a KNN-pooling algorithm that pools the count values of k nearest neighbor. Finally, following the optimized pipeline, we analyzed the transcriptional factor activity in type II neuroblasts, a class of neural stem cells found in the central brain to identify unique spatial transcription factor activity corresponding to each molecularly distinct subtype. A comprehensive classifier was built to categorize transcription factors based on their functionality.

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