Here, I elaborate on the hypothesis that complex multicellularity (CM, sensu Knoll) is a major evolutionary transition (sensu Szathmary), which has convergently evolved a few times in Eukarya only: within red and brown algae, plants, animals, and fungi. Paradoxically, CM seems to correlate with the expansion of non-coding DNA (ncDNA) in the genome rather than with genome size or the total number of genes. Thus, I investigated the correlation between genome and organismal complexities across 461 eukaryotes under a phylogenetically controlled framework. To that end, I introduce the first formal definitions and criteria to distinguish ‘unicellularity’, ‘simple’ (SM) and ‘complex’ multicellularity. Rather than using the limited available estimations of unique cell types, the 461 species were classified according to our criteria by reviewing their life cycle and body plan development from literature. Then, I investigated the evolutionary association between genome size and 35 genome-wide features (introns and exons from protein-coding genes, repeats and intergenic regions) describing the coding and ncDNA complexities of the 461 genomes. To that end, I developed ‘GenomeContent’, a program that systematically retrieves massive multidimensional datasets from gene annotations and calculates over 100 genome-wide statistics. R-scripts coupled to parallel computing were created to calculate >260,000 phylogenetic controlled pairwise correlations. As previously reported, both repetitive and non-repetitive DNA are found to be scaling strongly and positively with genome size across most eukaryotic lineages. Contrasting previous studies, I demonstrate that changes in the length and repeat composition of introns are only weakly or moderately associated with changes in genome size at the global phylogenetic scale, while changes in intron abundance (within and across genes) are either not or only very weakly associated with changes in genome size. Our evolutionary correlations are robust to: different phylogenetic regression methods, uncertainties in the tree of eukaryotes, variations in genome size estimates, and randomly reduced datasets. Then, I investigated the correlation between the 35 genome-wide features and the cellular complexity of the 461 eukaryotes with phylogenetic Principal Component Analyses. Our results endorse a genetic distinction between SM and CM in Archaeplastida and Metazoa, but not so clearly in Fungi. Remarkably, complex multicellular organisms and their closest ancestral relatives are characterized by high intron-richness, regardless of genome size. Finally, I argue why and how a vast expansion of non-coding RNA (ncRNA) regulators rather than of novel protein regulators can promote the emergence of CM in Eukarya. As a proof of concept, I co-developed a novel ‘ceRNA-motif pipeline’ for the prediction of “competing endogenous” ncRNAs (ceRNAs) that regulate microRNAs in plants. We identified three candidate ceRNAs motifs: MIM166, MIM171 and MIM159/319, which were found to be conserved across land plants and be potentially involved in diverse developmental processes and stress responses. Collectively, the findings of this dissertation support our hypothesis that CM on Earth is a major evolutionary transition promoted by the expansion of two major ncDNA classes, introns and regulatory ncRNAs, which might have boosted the irreversible commitment of cell types in certain lineages by canalizing the timing and kinetics of the eukaryotic transcriptome.:Cover page
Abstract
Acknowledgements
Index
1. The structure of this thesis
1.1. Structure of this PhD dissertation
1.2. Publications of this PhD dissertation
1.3. Computational infrastructure and resources
1.4. Disclosure of financial support and information use
1.5. Acknowledgements
1.6. Author contributions and use of impersonal and personal pronouns
2. Biological background
2.1. The complexity of the eukaryotic genome
2.2. The problem of counting and defining “genes” in eukaryotes
2.3. The “function” concept for genes and “dark matter”
2.4. Increases of organismal complexity on Earth through multicellularity
2.5. Multicellularity is a “fitness transition” in individuality
2.6. The complexity of cell differentiation in multicellularity
3. Technical background
3.1. The Phylogenetic Comparative Method (PCM)
3.2. RNA secondary structure prediction
3.3. Some standards for genome and gene annotation
4. What is in a eukaryotic genome? GenomeContent provides a good answer
4.1. Background
4.2. Motivation: an interoperable tool for data retrieval of gene annotations
4.3. Methods
4.4. Results
4.5. Discussion
5. The evolutionary correlation between genome size and ncDNA
5.1. Background
5.2. Motivation: estimating the relationship between genome size and ncDNA
5.3. Methods
5.4. Results
5.5. Discussion
6. The relationship between non-coding DNA and Complex Multicellularity
6.1. Background
6.2. Motivation: How to define and measure complex multicellularity across eukaryotes?
6.3. Methods
6.4. Results
6.5. Discussion
7. The ceRNA motif pipeline: regulation of microRNAs by target mimics
7.1. Background
7.2. A revisited protocol for the computational analysis of Target Mimics
7.3. Motivation: a novel pipeline for ceRNA motif discovery
7.4. Methods
7.5. Results
7.6. Discussion
8. Conclusions and outlook
8.1. Contributions and lessons for the bioinformatics of large-scale comparative analyses
8.2. Intron features are evolutionarily decoupled among themselves and from genome size throughout Eukarya
8.3. “Complex multicellularity” is a major evolutionary transition
8.4. Role of RNA throughout the evolution of life and complex multicellularity on Earth
9. Supplementary Data
Bibliography
Curriculum Scientiae
Selbständigkeitserklärung (declaration of authorship
