The influence of landscape configuration and environment on population genetic structure in a sedentary passerine: insights from loci located in different genomic regions. (17th November 2015)

• Record Type: Journal Article
• Authors: Ferrer, E. S.; García‐Navas, V.; Bueno‐Enciso, J.; Barrientos, R.; Serrano‐Davies, E.; Cáliz‐Campal, C.; Sanz, J. J.; Ortego, J.
• Is Part Of: Journal of evolutionary biology. Volume 29:Number 1(2016:Jan.)
• Page Start: 205
• Page End: 219
• Publication Date: 2015-11-17
• Subjects: Cyanistes caeruleus -- gene flow -- isolation‐by‐distance -- isolation‐by‐environment -- isolation‐by‐resistance -- multiple matrix regression; Evolution (Biology) -- Periodicals; Biology -- Periodicals; 576.8
• DOI: 10.1111/jeb.12776
• Languages: English
• ISSNs: 1010-061X

Abstract

Abstract: The study of the factors structuring genetic variation can help to infer the neutral and adaptive processes shaping the demographic and evolutionary trajectories of natural populations. Here, we analyse the role of isolation by distance (IBD), isolation by resistance (IBR, defined by landscape composition) and isolation by environment (IBE, estimated as habitat and elevation dissimilarity) in structuring genetic variation in 25 blue tit ( Cyanistes caeruleus ) populations. We typed 1385 individuals at 26 microsatellite loci classified into two groups by considering whether they are located into genomic regions that are actively (TL; 12 loci) or not (NTL; 14 loci) transcribed to RNA. Population genetic differentiation was mostly detected using the panel of NTL. Landscape genetic analyses showed a pattern of IBD for all loci and the panel of NTL, but genetic differentiation estimated at TL was only explained by IBR models considering high resistance for natural vegetation and low resistance for agricultural lands. Finally, the absence for IBE suggests a lack of divergent selection pressures associated with differences in habitat and elevation. Overall, our study shows that markers located in different genomic regions can yield contrasting inferences on landscape‐level patterns of realized gene flow in natural populations.