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Dissertation zugänglich unter
URN: urn:nbn:de:gbv:18-94738
URL: http://ediss.sub.uni-hamburg.de/volltexte/2018/9473/

Comparative and population transcriptomics of Daphnia galeata

Ravindran, Suda Parimala

 Dokument 1.pdf (2.752 KB) 
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 Appendix.zip (6,834 KB) 

Basisklassifikation: 42.20 , 42.90 , 42.21
Institut: Biologie
DDC-Sachgruppe: Biowissenschaften, Biologie
Dokumentart: Dissertation
Hauptberichter: Cordellier, Mathilde (Prof. Dr.)
Sprache: Englisch
Tag der mündlichen Prüfung: 27.09.2018
Erstellungsjahr: 2018
Publikationsdatum: 14.12.2018
Kurzfassung auf Englisch: Natural environments are increasingly fragmented through habitat destruction and organisms shift their geographical distribution by altering their growth and reproduction patterns to persist in the habitat. Organisms are subjected to severe selection pressures and they undergo rapid evolutionary changes to avoid extinction. This is particularly evident in aquatic environments especially for species like Daphnia. Therefore, understanding the genetic basis of local adaptation and phenotypic variation and their interplay with the environment are important factors to predict the consequences of ongoing climate change. Daphnia are cyclical parthenogens and they produce resting eggs which make them a well-suited model organism for this purpose.
The aim of the thesis was to assess the impact of transcriptomic basis of local adaptation and phenotypic variation in four European D. galeata populations and identify their ecological roles. To this aim, I used the D. galeata transcriptome data to identify transcripts potentially under local adaptation at the regulatory and sequence level. I revealed candidate transcripts under local adaptation which is influenced by the interplay of forces such as drift, selection and gene flow. Furthermore, I performed a functional annotation of D. galeata transcripts. However, several transcripts identified in D. galeata were “hypothetical” in function. To be able to assess the ecological role and improve the existing annotations of these transcripts, I employed a data mining approach and developed a database based on the expression profiles in Daphnia species from several previous studies. This meta-analysis helped to improve the existing functional annotation of Daphnia by linking them to their ecological roles. Finally, to reveal the transcriptomic basis of phenotypic variation, I performed an association analysis with sequence polymorphisms and ten life-history traits data in the absence and presence of predator-kairomones obtained from another experiment. This study revealed a transcriptomic basis for two life-history traits and the role of plasticity in determining adaptations was inferred.
In conclusion, I detected signs of local adaptation at the transcriptomic level and the association analysis allowed assessing the interplay between the genotype, phenotype and environment. I also improved the existing functional annotation of Daphnia genes/transcripts by developing the Daphnia stressor database. However, further information and work are required to predict the consequences of Daphnia species accurately in the light of environmental fluctuations.


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