Global warming refers to the observed heating of the Earth’s land and ocean surfaces, which has led to an increase in average temperatures. It is anticipated that by 2046–2065, the average temperatures will rise 2.6 degrees Celsius higher than during the industrial period, intensifying the frequency and amplitude of heat waves and altering precipitation patterns, becoming one of the most important issues of our time. The increase in temperature poses severe challenges to biodiversity and the functions of ecosystems, particularly for the survival and adaptation of microorganisms adapted to cold. Species such as freshwater fungi, which possess mechanisms like cold-active enzymes and antifreeze proteins to survive in Arctic and subarctic streams and increase their activity in continental freshwater during the colder seasons, might be directly impacted by global warming. On the other hand, other lifestyle fungi, such as phytopathogens, may migrate to new geographic locations and intensify diseases, causing higher economic damage. Therefore, understanding the fungal genome machinery for adaptations to temperature has become fundamental to preventing the disappearance of species or predicting fungi that can become more active during global warming events. In our study, we explore the temperature adaptations of fungi by applying machine learning and genome annotation for genes associated with plant-fungi interaction in different lifestyle fungi. This approach has proven to be an essential tool for understanding the genome machinery for temperature and other adaptation in plant-associated fungi.
Vasconcelos Rissi D. and Baschien C. Phylogenomics of Freshwater Hyphomycetes. DSMZ Kolloquium, Braunschweig. 08.08.2024. (Invited lecture: long)
@misc{Vasconcelos Rissi2024,
Title = {Phylogenomics of Freshwater Hyphomycetes},
Author = {Vasconcelos Rissi, Daniel and Baschien, Christiane},
Editor = {},
Year = {2024},
Abstract = {Global warming refers to the observed heating of the Earth’s land and ocean surfaces, which has led to an increase in average temperatures. It is anticipated that by 2046–2065, the average temperatures will rise 2.6 degrees Celsius higher than during the industrial period, intensifying the frequency and amplitude of heat waves and altering precipitation patterns, becoming one of the most important issues of our time. The increase in temperature poses severe challenges to biodiversity and the functions of ecosystems, particularly for the survival and adaptation of microorganisms adapted to cold. Species such as freshwater fungi, which possess mechanisms like cold-active enzymes and antifreeze proteins to survive in Arctic and subarctic streams and increase their activity in continental freshwater during the colder seasons, might be directly impacted by global warming. On the other hand, other lifestyle fungi, such as phytopathogens, may migrate to new geographic locations and intensify diseases, causing higher economic damage. Therefore, understanding the fungal genome machinery for adaptations to temperature has become fundamental to preventing the disappearance of species or predicting fungi that can become more active during global warming events. In our study, we explore the temperature adaptations of fungi by applying machine learning and genome annotation for genes associated with plant-fungi interaction in different lifestyle fungi. This approach has proven to be an essential tool for understanding the genome machinery for temperature and other adaptation in plant-associated fungi.},
}
TY - SLIDE
AU - Vasconcelos Rissi, Daniel
AU - Baschien, Christiane
TI - Phylogenomics of Freshwater Hyphomycetes
PY - 2024
AB - Global warming refers to the observed heating of the Earth’s land and ocean surfaces, which has led to an increase in average temperatures. It is anticipated that by 2046–2065, the average temperatures will rise 2.6 degrees Celsius higher than during the industrial period, intensifying the frequency and amplitude of heat waves and altering precipitation patterns, becoming one of the most important issues of our time. The increase in temperature poses severe challenges to biodiversity and the functions of ecosystems, particularly for the survival and adaptation of microorganisms adapted to cold. Species such as freshwater fungi, which possess mechanisms like cold-active enzymes and antifreeze proteins to survive in Arctic and subarctic streams and increase their activity in continental freshwater during the colder seasons, might be directly impacted by global warming. On the other hand, other lifestyle fungi, such as phytopathogens, may migrate to new geographic locations and intensify diseases, causing higher economic damage. Therefore, understanding the fungal genome machinery for adaptations to temperature has become fundamental to preventing the disappearance of species or predicting fungi that can become more active during global warming events. In our study, we explore the temperature adaptations of fungi by applying machine learning and genome annotation for genes associated with plant-fungi interaction in different lifestyle fungi. This approach has proven to be an essential tool for understanding the genome machinery for temperature and other adaptation in plant-associated fungi.
CY - Braunschweig
ER -
