Computational protocol: What drivers phenotypic divergence in Leymus chinensis (Poaceae) on large-scale gradient, climate or genetic differentiation?

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Protocol publication

[…] One-way analysis of variance (ANOVA) was performed to analyze the differences in morphological and physiological phenotypes among the 18 populations. Linear regression analyses were performed to evaluate the relationship of quantitative traits with environmental factors (MAP, MAT, SWC, soil N, soil pH and elevation). All statistics for phenotypes were analyzed using SPSS 20.0 for windows.Population genetic analyses were performed on microsatellite dataset scored by the program GeneMarker v2.2.0. Descriptive statistics including HE, I, and E and population pairwise genetic distances were calculated with Atetra program. To assess the population genetic structure, following analyses were conducted: 1) Nei’s genetic distance was used to generate the Neighbor-joining tree with Neighbor of Phylip v3.63. 2) The Mantel test was assessed on genetic distance and geographic distance (km) matrices by TFPGA 1.3. 3) Population genetic structure was inferred by a Bayesian method using STRUCTURE 2.3.4. 4) AMOVA was performed to quantify the genetic variance among populations with Arlequin 3.5. 5) Pairwise FST values were evaluated by Polysat package running on the R platform. Gene flow (the mean number of immigrants) was calculated by following: Quantitative differentiation was estimated by the formula described below. where and are between- and within- population components of variance. The partitioning of phenotypic variance within and between populations was appraised using ANOVA by SPSS 17.0. PST is a QST analogous that estimated from the wild sampling data. […]

Pipeline specifications

Software tools GeneMarker, PHYLIP, TFPGA, Arlequin
Application Population genetic analysis
Organisms Uroteuthis chinensis