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Genome-wide analysis of signatures of selection in populations of African honey bees (Apis mellifera) using new web-based tools
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 s...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4496815/ https://www.ncbi.nlm.nih.gov/pubmed/26159619 http://dx.doi.org/10.1186/s12864-015-1712-0 |
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author | Fuller, Zachary L. Niño, Elina L. Patch, Harland M. Bedoya-Reina, Oscar C. Baumgarten, Tracey Muli, Elliud Mumoki, Fiona Ratan, Aakrosh McGraw, John Frazier, Maryann Masiga, Daniel Schuster, Stephen Grozinger, Christina M. Miller, Webb |
author_facet | Fuller, Zachary L. Niño, Elina L. Patch, Harland M. Bedoya-Reina, Oscar C. Baumgarten, Tracey Muli, Elliud Mumoki, Fiona Ratan, Aakrosh McGraw, John Frazier, Maryann Masiga, Daniel Schuster, Stephen Grozinger, Christina M. Miller, Webb |
author_sort | Fuller, Zachary L. |
collection | PubMed |
description | 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-1712-0) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4496815 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-44968152015-07-10 Genome-wide analysis of signatures of selection in populations of African honey bees (Apis mellifera) using new web-based tools Fuller, Zachary L. Niño, Elina L. Patch, Harland M. Bedoya-Reina, Oscar C. Baumgarten, Tracey Muli, Elliud Mumoki, Fiona Ratan, Aakrosh McGraw, John Frazier, Maryann Masiga, Daniel Schuster, Stephen Grozinger, Christina M. Miller, Webb BMC Genomics Research Article 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-1712-0) contains supplementary material, which is available to authorized users. BioMed Central 2015-07-10 /pmc/articles/PMC4496815/ /pubmed/26159619 http://dx.doi.org/10.1186/s12864-015-1712-0 Text en © Fuller et al. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Fuller, Zachary L. Niño, Elina L. Patch, Harland M. Bedoya-Reina, Oscar C. Baumgarten, Tracey Muli, Elliud Mumoki, Fiona Ratan, Aakrosh McGraw, John Frazier, Maryann Masiga, Daniel Schuster, Stephen Grozinger, Christina M. Miller, Webb Genome-wide analysis of signatures of selection in populations of African honey bees (Apis mellifera) using new web-based tools |
title | Genome-wide analysis of signatures of selection in populations of African honey bees (Apis mellifera) using new web-based tools |
title_full | Genome-wide analysis of signatures of selection in populations of African honey bees (Apis mellifera) using new web-based tools |
title_fullStr | Genome-wide analysis of signatures of selection in populations of African honey bees (Apis mellifera) using new web-based tools |
title_full_unstemmed | Genome-wide analysis of signatures of selection in populations of African honey bees (Apis mellifera) using new web-based tools |
title_short | Genome-wide analysis of signatures of selection in populations of African honey bees (Apis mellifera) using new web-based tools |
title_sort | genome-wide analysis of signatures of selection in populations of african honey bees (apis mellifera) using new web-based tools |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4496815/ https://www.ncbi.nlm.nih.gov/pubmed/26159619 http://dx.doi.org/10.1186/s12864-015-1712-0 |
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