Candidate Gene Database for Stress Traits

The last decade has produced a number of studies using an array of methods to detect candidate genes for stress traits in Drosophila melanogaster.  This database has been developed as a tool to rapidly identify all the genes that have been implicated as candidate for specific stress traits.  There are a number of different methods that have been used to identify specific candidate genes, these methods include: geographic association, phenotypic / genotypic association studies, microarray, quantitative trait loci (QTL) or mutation studies (P-element). This database restricted to Drosophila melanogaster includes a detailed list of candidate genes for stress traits, desiccation, starvation, cold and heat resistance.  For each given candidate gene you will find information concerning the implicated trait, a brief description of the study and its reference, the genes chromosomal position, molecular and biological function and a fly base link.

 

Search by trait: Cold, Heat, Desiccation, Starvation

Please note included within this list are cases where potential candidate genes have been explored yet no evidence was found, therefore, the presence of a gene within the database does not suggest the candidate gene is involved in that trait and the merits must be evaluated by the user. 

Sources of information

This information has been complied through the results of published empirical papers with more than 80 scientific publications, with full references including abstract provided.

Feedback or comments:

We welcome any feedback or comments concerning the use and accuracy of this database.  please contact us through the contact form.

Disclaimer

The data presented in the website regarding candidate genes for climatic stress resistance is based on an extensive review of the scientific literature.  We have taken all reasonable care in compiling this information, but do not warrant the accuracy or completeness of the information contained herein.

 Acknowledgements

This website and associated database was created by Dr Vanessa Kellermann, Dr Belinda van Heerwaarden, Dr Carla Sgró, Ms Emily Thomson and Prof Ary Hoffmann.  We would also like to thank the Australian Research Council for their support via their Special Research Centre scheme and also CERF.

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