2018
DOI: 10.3389/fgene.2018.00215
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Editorial: The Least Cost Path From Landscape Genetics to Landscape Genomics: Challenges and Opportunities to Explore NGS Data in a Spatially Explicit Context

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Cited by 12 publications
(13 citation statements)
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“…The obtained genome information for F. suspensa will therefore be an essential resource for biological research and breeding. Here, we used genomic information in combination with a landscape genomics approach 2 to explore the genetic basis of the local adaptation of F. suspensa .…”
Section: Discussionmentioning
confidence: 99%
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“…The obtained genome information for F. suspensa will therefore be an essential resource for biological research and breeding. Here, we used genomic information in combination with a landscape genomics approach 2 to explore the genetic basis of the local adaptation of F. suspensa .…”
Section: Discussionmentioning
confidence: 99%
“…Spatial heterogeneity of the environment exerts differential selection pressures on natural populations, potentially leading to the local adaptation of a species across its range 1,2 . For naturally distributed plant species, selection pressure is mainly generated by abiotic factors such as soil chemistry, temperature, precipitation, and solar radiation 3 .…”
Section: Introductionmentioning
confidence: 99%
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“…The continental margin of the Caribbean has been exposed to a wide variety of orogenic processes (Reyes et al, 2004) that have invoked changes in water bodies, consequently influencing the associated fauna. Based on a range of information on organism dynamics, the use of whole-genome sequence (WGS) data offers a high molecular resolution but is costly (Cushman et al, 2018). In order to generate an approximation of evolutionary histories and genetic inferences, we selected to use mitochondrial and nuclear genetic markers that offered a base line and good resolution of haplotype histories in A. latifrons.…”
Section: Discussionmentioning
confidence: 99%
“…Microsatellite loci assumed or identified as being neutral are the most frequent type of markers used in landscape genetics (Storfer et al., 2010). Besides, SNP markers are now becoming widespread and can also be used to perform these analyses provided that loci under selective pressures (identified as outliers) have been discarded (Cushman et al., 2018; Foll & Gaggiotti, 2008). Accordingly, graph4lg functions use genetic data with two‐ or three‐digit allele coding to fit the common microsatellite coding.…”
Section: Workflowmentioning
confidence: 99%