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Cross-species outlier detection reveals different evolutionary pressures between sister species.

Cullingham CI, Cooke JE, Coltman DW - New Phytol. (2014)

Bottom Line: To better understand this we aim to identify genetic regions that have adaptive potential.We found contrasting relationships between environmental variation and genetic diversity for the species.Using rigorous criteria we have been able to identify potential outlier SNPs.

View Article: PubMed Central - PubMed

Affiliation: Department of Biological Sciences, University of Alberta, Biological Sciences Building, Edmonton, AB, T6G 2E9, Canada.

No MeSH data available.


Venn diagrams illustrating the overlap in outlier detection across the three data sets for the different outlier detection methods, and among the data sets overall: (a) combined subset, (b) pure lodgepole pine (Pinus contorta var. latifolia), (c) pure jack pine (Pinus banksiana), and (d) across the data sets before filtering based on consensus (e) consensus set of outliers. We used the results for the hierarchical model for arelquin and the prior odds for the bayscan results.
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fig02: Venn diagrams illustrating the overlap in outlier detection across the three data sets for the different outlier detection methods, and among the data sets overall: (a) combined subset, (b) pure lodgepole pine (Pinus contorta var. latifolia), (c) pure jack pine (Pinus banksiana), and (d) across the data sets before filtering based on consensus (e) consensus set of outliers. We used the results for the hierarchical model for arelquin and the prior odds for the bayscan results.

Mentions: Using bayescan we consistently identified nine loci within lodgepole pine across all iterations. We identified four of these nine loci with the prior odds set to the total number of loci detected, and three of these loci for 1000 and 10 000 prior odds (Fig. 1). All of these exhibited a signature of positive selection. We chose to use the set of nine loci because all of these belonged to the set of common SNPs also detected using the other outlier detection methods (Fig. 2). We identified only one locus showing positive selection in jack pine using both the default parameters and the adjusted prior odds, and no loci using 1000 or 10 000 prior odds. For the combined subset we detected 116 loci using the default parameters, 50 loci using the number of loci prior odds, 34 loci at a prior odd of 1000, and only six loci with a prior odd of 10 000. The loci identified for each of these sets were also identified using the default parameters. We chose to use the 34 loci identified using the prior of 1000 as there was greater overlap for this set with the other outlier detection methods, as described below. Of these 34 loci, 11 had signatures of negative selection. Only one locus was identified in common between the lodgepole pine and the combined subsets.


Cross-species outlier detection reveals different evolutionary pressures between sister species.

Cullingham CI, Cooke JE, Coltman DW - New Phytol. (2014)

Venn diagrams illustrating the overlap in outlier detection across the three data sets for the different outlier detection methods, and among the data sets overall: (a) combined subset, (b) pure lodgepole pine (Pinus contorta var. latifolia), (c) pure jack pine (Pinus banksiana), and (d) across the data sets before filtering based on consensus (e) consensus set of outliers. We used the results for the hierarchical model for arelquin and the prior odds for the bayscan results.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4260136&req=5

fig02: Venn diagrams illustrating the overlap in outlier detection across the three data sets for the different outlier detection methods, and among the data sets overall: (a) combined subset, (b) pure lodgepole pine (Pinus contorta var. latifolia), (c) pure jack pine (Pinus banksiana), and (d) across the data sets before filtering based on consensus (e) consensus set of outliers. We used the results for the hierarchical model for arelquin and the prior odds for the bayscan results.
Mentions: Using bayescan we consistently identified nine loci within lodgepole pine across all iterations. We identified four of these nine loci with the prior odds set to the total number of loci detected, and three of these loci for 1000 and 10 000 prior odds (Fig. 1). All of these exhibited a signature of positive selection. We chose to use the set of nine loci because all of these belonged to the set of common SNPs also detected using the other outlier detection methods (Fig. 2). We identified only one locus showing positive selection in jack pine using both the default parameters and the adjusted prior odds, and no loci using 1000 or 10 000 prior odds. For the combined subset we detected 116 loci using the default parameters, 50 loci using the number of loci prior odds, 34 loci at a prior odd of 1000, and only six loci with a prior odd of 10 000. The loci identified for each of these sets were also identified using the default parameters. We chose to use the 34 loci identified using the prior of 1000 as there was greater overlap for this set with the other outlier detection methods, as described below. Of these 34 loci, 11 had signatures of negative selection. Only one locus was identified in common between the lodgepole pine and the combined subsets.

Bottom Line: To better understand this we aim to identify genetic regions that have adaptive potential.We found contrasting relationships between environmental variation and genetic diversity for the species.Using rigorous criteria we have been able to identify potential outlier SNPs.

View Article: PubMed Central - PubMed

Affiliation: Department of Biological Sciences, University of Alberta, Biological Sciences Building, Edmonton, AB, T6G 2E9, Canada.

No MeSH data available.