Summary
Our understanding of how genomic changes translate into organismal novelties is often confounded by the complexity of the underlying genome architecture. My previous studies revealed a complex interplay between several levels of genomic organization during major metazoan evolutionary transitions, ranging from modifications of regulatory elements to the gene order on the chromosomal scale. A major gap in our understanding is the extent to which those different genomic scales are evolutionarily linked and reflect an inherent functional property or mode of genome evolution. In this proposal, I focus on the emerging model system within the highly advanced clade of cephalopod molluscs, the Hawaiian bobtail squid Euprymna scolopes, to study how changes in the mode of metazoan genome evolution have yielded unique cephalopod innovations (e.g., the largest invertebrate brain). To address this question, I will (1) take a novel global pan-metazoan comparative genomics approach to test and reveal the extent of genomic character co-evolution, identifying, for the first time, modes of genome evolution. I will then (2) test whether co-evolving characters form inherent regulatory units in metazoan genomes by an in-depth characterization using emerging and available regulatory genomic data. Finally, using latest molecular approaches, I will (3) study the regulatory composition of co-evolving character units associated with cephalopod brain development and functionally test their organismal impact. This proposal will develop a novel and holistic approach to study genome evolution, constituting a departure from the previous analyses based on individual genomic characters. It will link genomic evolutionary units to their function, revealing the genomic changes behind major innovations (cephalopod brain). Finally, this project will develop predictive models that use evolutionary data to identify novel regulatory units aiding both biological and biomedical applications.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/945026 |
| Start date: | 01-07-2021 |
| End date: | 30-06-2026 |
| Total budget - Public funding: | 1 483 477,00 Euro - 1 483 477,00 Euro |
Cordis data
Original description
Our understanding of how genomic changes translate into organismal novelties is often confounded by the complexity of the underlying genome architecture. My previous studies revealed a complex interplay between several levels of genomic organization during major metazoan evolutionary transitions, ranging from modifications of regulatory elements to the gene order on the chromosomal scale. A major gap in our understanding is the extent to which those different genomic scales are evolutionarily linked and reflect an inherent functional property or mode of genome evolution. In this proposal, I focus on the emerging model system within the highly advanced clade of cephalopod molluscs, the Hawaiian bobtail squid Euprymna scolopes, to study how changes in the mode of metazoan genome evolution have yielded unique cephalopod innovations (e.g., the largest invertebrate brain). To address this question, I will (1) take a novel global pan-metazoan comparative genomics approach to test and reveal the extent of genomic character co-evolution, identifying, for the first time, modes of genome evolution. I will then (2) test whether co-evolving characters form inherent regulatory units in metazoan genomes by an in-depth characterization using emerging and available regulatory genomic data. Finally, using latest molecular approaches, I will (3) study the regulatory composition of co-evolving character units associated with cephalopod brain development and functionally test their organismal impact. This proposal will develop a novel and holistic approach to study genome evolution, constituting a departure from the previous analyses based on individual genomic characters. It will link genomic evolutionary units to their function, revealing the genomic changes behind major innovations (cephalopod brain). Finally, this project will develop predictive models that use evolutionary data to identify novel regulatory units aiding both biological and biomedical applications.Status
SIGNEDCall topic
ERC-2020-STGUpdate Date
27-04-2024
Geographical location(s)
