To form complex organisms characterized by different tissues with specialized functions, cells must acquire distinct identities during development. Yet, all the cells of an organism are equipped with the same genomic information. Elucidating the mechanisms that regulate the determination of a cell identity, i.e. the cell-fate commitment, is a main purpose in developmental biology. Numerous studies focused on genes that are activated or repressed at each stage of differentiation, identifying several key regulators of development. However, this approach ignores the transcript variability derived from alternative splicing, the transcriptional process by which different gene coding segments, i.e. exons, are combined giving rise to multiple transcripts and proteins from the same gene. With the advent of novel sequencing technologies, it is becoming clear that alternative splicing is widespread in higher organisms, regulates several processes and presents tissue- and cell-specificity. In mammals, the brain shows the highest degree of alternative splicing, with neurons expressing a high variety of splice variants. In this project I investigated whether and how alternative splicing could regulate cell-fate determination in the context of the embryonic development of the mouse neocortex, a highly complex structure presenting several different neuronal subtypes generated at specific time points. For this purpose, I analyzed transcriptome data of cells of the neurogenic lineage isolated from the developing mouse neocortex at subsequent stages of differentiation. I showed that the expression pattern of the proteins regulating splicing, i.e. the splicing factors, changes during neocortical development. By employing several bioinformatic tools, I described the splicing profile that characterizes each differentiation stage and, for the first time, I identified the splicing events that mark cell-fate commitment to a neurogenic identity. Alternative splicing mostly involved genes with a role in nervous system development, cell growth and signaling, mainly leading to the production of alternative protein isoforms. Splicing choices taken during the neurogenic commitment were kept throughout neurogenesis. Thus, exons that start to be included during cell-fate determination are always included in post-mitotic neurons. Exons gained during neurogenic commitment were characterized by strong features in their upstream intron, presented a general short length with an overrepresentation of microexons in the 3-27 nucleotides length range and showed an enrichment for binding motifs of the neural splicing factor nSR100. In vivo manipulation in the embryonic mouse neocortex highlighted isoform-specific effects on neocortical development, strongly suggesting a causal relationship between alternative splicing choices and cell-fate commitment. Moreover, the higher cell-specificity offered by the present dataset, compared to similar studies, allowed a better understanding of previously identified splicing events that characterize the nervous system and the relationships between neural-specific splicing factors.:Table of Contents
Abstract I
Zusammenfassung III
Table of Contents V
List of Figures VII
List of Tables IX
Abbreviations X
Gene abbreviations XII
1 Introduction 1
1.1 Neurogenesis during embryonic development 2
1.1.1 Formation and patterning of the neural tube 2
1.1.2 Neural progenitors in the dorsal telencephalon 6
1.1.3 Neurogenesis 8
1.1.4 Regulation of neurogenesis 10
1.1.5 A novel tool to investigate cell-fate determination in the central nervous system: the Btg2RFP/Tubb3GFP mouse line 13
1.2 Alternative splicing: an additional level of genomic regulation 15
1.2.1 The splicing reaction 16
1.2.2 What makes splicing alternative? 18
1.2.3 Regulation of alternative splicing 19
1.2.4 The challenge to detect splicing 23
1.2.5 New sequencing technologies reveal a high transcriptome complexity 29
1.2.6 Splicing in nervous system development 31
1.2.7 Aims of the project 36
2 Materials and methods 38
2.1 Materials 38
2.1.1 Bacteria, cells, mouse strains 38
2.1.2 Vector 38
2.1.3 Primers 38
2.1.4 Chemicals and buffers 41
2.1.5 Antibodies 42
2.1.6 Kits and enzymes 42
2.2 Methods 43
2.2.1 Animal experiments 43
2.2.2 Molecular biology 44
2.2.3 Immunohistochemistry 46
2.2.4 Bioinformatics 47
3 Results 53
3.1 Splicing factors are differentially expressed during neurogenic commitment and neurogenesis 53
3.2 Detection of alternative splicing 55
3.2.1 Isoform-switching 55
3.2.2 Exon usage and splicing events 57
3.3 Validation 62
3.3.1 The isoform switching method has a poor validation rate 62
3.3.2 Analysis at the exon level has a high rate of validation 65
3.4 Pattern and representation of splicing events 67
3.4.1 Splicing choices during neurogenic commitment define the splicing profiles of neurons 67
3.4.2 Splicing events: microexon inclusion characterizes neurogenic
commitment 69
3.5 Alternative splicing changes the protein output of genes involved in neurogenesis 75
3.5.1 Spliced genes are involved in neurogenesis and signaling 75
3.5.2 Impact of alternative splicing on the proteome 77
3.6 Splicing regulation: neural exon features and splicing factor binding 79
3.6.1 Included neural exons are short and preceded by strong exon-definition
features 79
3.6.2 Early included exons are enriched for nSR100 binding sites 85
3.7 The Btg2RFP/Tubb3GFP mouse line outperforms previous models for the study of cell-type-specific splicing in the brain 88
3.8 In vivo manipulation of splice variants 90
4 Discussion 94
4.1 The combination of different bioinformatic approaches allows an accurate identification of splicing events at the exon-level 95
4.2 Splicing choices during neurogenic commitment establish a neural signature characterized by microexon inclusion 97
4.3 Splicing during neocortical development leads to the generation of alternative protein isoforms in genes involved in neurogenesis and signaling 98
4.4 Neural exons are short and present strong features facilitating inclusion 101
4.5 Neural exons are prevalently regulated by nSR100 during neurogenic commitment 102
4.6 In vivo overexpression of splice variants highlights isoform-specific functions in
neurogenic commitment 105
4.7 Concluding remarks and future perspectives 108
5 Supplementary figures 110
6 References 118
Acknowledgments 137
Anlange I 138
Anlange II 139
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:79748 |
| Date | 27 June 2022 |
| Creators | Haj Abdullah Alieh, Leila |
| Contributors | Kempermann, Gerd, Ader, Marius, Technische Universität Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
Page generated in 0.0031 seconds