@article{eae9e52e61034616bf6b5ec84c8d003e,
title = "Stable genetic structure and connectivity in pollution-adapted and nearby pollution-sensitive populations of Fundulus heteroclitus",
abstract = "Populations of the non-migratory estuarine fish Fundulus heteroclitus inhabiting the heavily polluted New Bedford Harbour (NBH) estuary have shown inherited tolerance to local pollutants introduced to their habitats in the past 100 years. Here we examine two questions: (i) Is there pollution-driven selection on the mitochondrial genome across a fine geographical scale? and (ii) What is the pattern of migration among sites spanning a strong pollution gradient? Whole mitochondrial genomes were analysed for 133 F. heteroclitus from seven nearby collection sites: four sites along the NBH pollution cline (approx. 5 km distance), which had pollution-adapted fish, as well as one site adjacent to the pollution cline and two relatively unpolluted sites about 30 km away, which had pollution-sensitive fish. Additionally, we used microsatellite analyses to quantify genetic variation over three F. heteroclitus generations in both pollution-adapted and sensitive individuals collected from two sites at two different time points (1999/2000 and 2007/2008). Our results show no evidence for a selective sweep of mtDNA in the polluted sites. Moreover, mtDNA analyses revealed that both pollution-adapted and sensitive populations harbour similar levels of genetic diversity. We observed a high level of non-synonymous mutations in the most polluted site. This is probably associated with a reduction in Ne and concomitant weakening of purifying selection, a demographic expansion following a pollution-related bottleneck or increased mutation rates. Our demographic analyses suggest that isolation by distance influences the distribution of mtDNA genetic variation between the pollution cline and the clean populations at broad spatial scales. At finer scales, population structure is patchy, and neither spatial distance, pollution concentration or pollution tolerance is a good predictor of mtDNA variation. Lastly, microsatellite analyses revealed stable population structure over the last decade.",
keywords = "Genetic variation, Microsatellites, MtDNA, Pollution cline, Population genetics, SNP",
author = "Nunez, {Joaquin C.B.} and Biancani, {Leann M.} and Flight, {Patrick A.} and Nacci, {Diane E.} and Rand, {David M.} and Crawford, {Douglas L.} and Oleksiak, {Marjorie F.}",
note = "Funding Information: Funding was provided by National Science Foundation (NSF) grant nos. MCB-1158241 and IOS-1147042 to M.F.O., the Rosenstiel School of Marine and Atmospheric Science (RSMAS) grant nos. SURGE 2014 and SURGE 2015 to J.C.B.N. This work was supported, in part, by NIH grant no. 2R01GM067862 and the NSF IGERT DGE-0966060 to D.M.R. P.A.F. was supported by an Experimental Program to Stimulate Competitive Research (Rhode Island EPSCoR) fellowship. Data analysis was aided by reference to a draft F. heteroclitus genome, which was supported by funding from NSF (collaborative research grant nos. DEB-1120512, DEB-1265282, DEB-1120013, DEB-1120263, DEB-1120333, DEB-1120398). J.C.B.N. thanks Alejandro Damian-Serrano (at Yale University), Kimberley Neil and Stephen Rong, at Brown University, for their insightful discussion on genetic variation, statistical genetics and pipeline design. To Dylan R. Gaddes for his support and help editing the manuscript. Also to Xiao Du, Tara Z. Baris, Kevin McCracken (at RSMAS) for comments on the early stages of this research. And to the Undergraduate Program in Marine Science and Biology of the University of Miami for its support through the Small Undergraduate Research Grant Experience (SURGE) programme. L.M.B. thanks Dawn Abt for all the help and logistical support. This work was made possible by Brown University through the use of the facilities of its Centre for Computation and Visualization. We acknowledge four anonymous reviewers who helped us improve this manuscript. Funding Information: Funding. Funding was provided by National Science Foundation (NSF) grant nos. MCB-1158241 and IOS-1147042 to M.F.O., the Rosenstiel School of Marine and Atmospheric Science (RSMAS) grant nos. SURGE 2014 and SURGE 2015 to J.C.B.N. This work was supported, in part, by NIH grant no. 2R01GM067862 and the NSF IGERT DGE-0966060 to D.M.R. P.A.F. was supported by an Experimental Program to Stimulate Competitive Research (Rhode Island EPSCoR) fellowship. Data analysis was aided by reference to a draft F. heteroclitus genome, which was supported by funding from NSF (collaborative research grant nos. DEB-1120512, DEB-1265282, DEB-1120013, DEB-1120263, DEB-1120333, DEB-1120398). Acknowledgements. J.C.B.N. thanks Alejandro Damian-Serrano (at Yale University), Kimberley Neil and Stephen Rong, at Brown University, for their insightful discussion on genetic variation, statistical genetics and pipeline design. To Dylan R. Gaddes for his support and help editing the manuscript. Also to Xiao Du, Tara Z. Baris, Kevin McCracken (at RSMAS) for comments on the early stages of this research. And to the Undergraduate Program in Marine Science and Biology of the University of Miami for its support through the Small Undergraduate Research Grant Experience (SURGE) programme. L.M.B. thanks Dawn Abt for all the help and logistical support. This work was made possible by Brown University through the use of the facilities of its Centre for Computation and Visualization. We acknowledge four anonymous reviewers who helped us improve this manuscript. Publisher Copyright: {\textcopyright} 2018 The Authors.",
year = "2018",
month = may,
day = "9",
doi = "10.1098/rsos.171532",
language = "English (US)",
volume = "5",
journal = "Royal Society Open Science",
issn = "2054-5703",
publisher = "The Royal Society",
number = "5",
}