Genome-wide analysis of signatures of selection in populations of African honey bees (Apis mellifera) using new web-based tools

BMC Genomics

Webb Miller⁴  Christina M. Grozinger¹  Stephen Schuster⁴  Daniel Masiga⁵  Maryann Frazier¹  John McGraw²  Aakrosh Ratan⁴  Fiona Mumoki⁵  Elliud Muli⁶  Tracey Baumgarten¹  Oscar C. Bedoya-Reina⁴  Harland M. Patch¹  Elina L. Niño¹  Zachary L. Fuller³ 

[1] Department of Entomology, Center for Pollinator Research, Pennsylvania State University, University Park, PA, USA;Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA, USA;Department of Biology, Pennsylvania State University, University Park, PA, USA;Center for Comparative Genomics and Bioinformatics, Pennsylvania State University, University Park, PA, USA;The International Center of Insect Physiology and Ecology (icipe), Nairobi, Kenya;Department of Biological Sciences, South Eastern Kenya University (SEKU), Kitui, Kenya

关键词: Adaptive evolution;    Genome sequencing;    Galaxy;    Apis mellifera;   

Others  :  1218466
DOI  :  10.1186/s12864-015-1712-0

 received in 2014-12-26, accepted in 2015-06-22,  发布年份 2015

【 摘 要 】

Background

With the development of inexpensive, high-throughput sequencing technologies, it has become feasible to examine questions related to population genetics and molecular evolution of non-model species in their ecological contexts on a genome-wide scale. Here, we employed a newly developed suite of integrated, web-based programs to examine population dynamics and signatures of selection across the genome using several well-established tests, including F_ST , pN/pS, and McDonald-Kreitman. We applied these techniques to study populations of honey bees (Apis mellifera) in East Africa. In Kenya, there are several described A. mellifera subspecies, which are thought to be localized to distinct ecological regions.

Results

We performed whole genome sequencing of 11 worker honey bees from apiaries distributed throughout Kenya and identified 3.6 million putative single-nucleotide polymorphisms. The dense coverage allowed us to apply several computational procedures to study population structure and the evolutionary relationships among the populations, and to detect signs of adaptive evolution across the genome. While there is considerable gene flow among the sampled populations, there are clear distinctions between populations from the northern desert region and those from the temperate, savannah region. We identified several genes showing population genetic patterns consistent with positive selection within African bee populations, and between these populations and European A. mellifera or Asian Apis florea.

Conclusions

These results lay the groundwork for future studies of adaptive ecological evolution in honey bees, and demonstrate the use of new, freely available web-based tools and workflows (http://usegalaxy.org/r/kenyanbee) that can be applied to any model system with genomic information.

【 授权许可】

   
2015 Fuller et al.

【 图 表 】

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