Abstracts (first author)

Talk 

Population genomics of parallel evolution in the Trinidadian guppy (Poecilia reticulata)

Author(s): Fraser BA, Dreyer C, Weigel D

Summary:

Often the clearest evidence we have of natural selection is when populations or species independently adapt to a similar environment in a similar way. Despite its importance, however, we often do not know the genetic architecture of such evolution. The guppy (Poecilia reticulata) offers an exciting opportunity to study parallel evolution. In northern Trinidad guppies below waterfalls co-exists with many predators, while guppies above waterfalls experience low predation. Guppies in separate rivers often evolve similarly to predation pressure independently, e.g. more colouration, larger size at maturity, and less shoaling in low predation localities. Furthermore, the guppy, offers another advantage because their natural history facilitates experimental studies in nature. Researchers have established experimental populations, by transplanting fish from high predation populations, to areas without guppies or predators. The evolution at the phenotypic level has been well documented in these populations, where guppies adapt to their new environment in four years or less. I am using a population genomics approach to identify selected alleles in high and low predation population pairs and experimentally established populations. I genotyped approximately 20 individuals each from 14 populations using a RAD-Seq approach. The reads were sequenced on an Illumina HiSeq 2000, 100 bp single end. A total of 967 million reads were generated. The reads were then filtered for sequence quality, sorted for unique barcode, and mapped to a preliminary draft of the guppy genome. A signature of selection is detected when SNPs are more diverged at specific loci then what would be expected by neutrality. Parallel evolution is detected when outliers occur in the same region in multiple pairwise comparisons. This study will be the first to examine the genetics underpinning local adaptation in this evolutionary model system.



Contacts

Chairman: Octávio S. Paulo
Tel: 00 351 217500614 direct
Tel: 00 351 217500000 ext22359
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email: mail@eseb2013.com

Address

XIV Congress of the European Society for Evolutionary Biology

Organization Team
Department of Animal Biology (DBA)
Faculty of Sciences of the University of Lisbon
P-1749-016 Lisbon
Portugal

Website

Computational Biology & Population Genomics Group 
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