Computational protocol: Genetic diversity and population structure of Prunus mira (Koehne) from the Tibet plateau in China and recommended conservation strategies

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Protocol publication

[…] GenAlEx version 6.501 [] was used to convert size data into various formats for genetic analysis. Based on the Bayesian method, we used STRUCTURE version 2.3.4 [] to determine the population structure of the 21 P. mira populations. Twenty independent runs were performed for each set, with a K value between 1 and 21, length of burn-in period of 1 × 105 iterations, and 1 × 105 MCMC iterations. No prior information about populations was used. The method described by Evanno et al. [] was used to calculate the distribution of delta K (ΔK) using the online website STRUCTURE HARVESTER [] (http://taylor0.biology.ucla.edu/struct_harvest/). Permutations of the most likely results among all runs for each K were performed in CLUMPP [], and the final figure was visualized using Distruct software [].GENELAND [,] is a powerful way to detect genetic boundaries in R (2011). This method was used to estimate the number of clusters and their spatial patterns. The analysis was based on an uncorrelated frequency model, and was conducted over 10 replicates for each K value (1–10). The null allele models were selected to infer the number of clusters using 1,000,000 MCMC iterations, of which every 1000th was retained. The replicates with the highest mean logarithm of posterior probability were used to compute the posterior probabilities of population membership for each pixel of the spatial domain with a burn-in of 500.P. mira genetic variation was estimated by conducting an analysis of molecular variance (AMOVA) in Arlequin version 3.5 []. This analysis subdivided all individuals into 21 populations and K genetic clusters. Three hierarchical divisions were identified based on the genetic variance: within populations, among populations within genetic clusters, and among genetic clusters using a nonparametric permutation procedure that incorporated 10,000 iterations. An unrooted unweighted pair-group method with arithmetic means (UPGMA) tree was constructed using Nei’s genetic distance [] in NTSYS PC version 2.10 []. Mantel tests were conducted between the genetic distance (FST/(1—FST)) and geographic distance (km) in GenAlEx version 6.501.GenAlEx version 6.501 was used to calculate the following genetic indices for loci, populations, and genetic clusters identified in the STRUCTURE analysis: allele number (A), effective allele number (Ae), private allele number (Np), Shannon’s information index (I), expected heterozygosity (He), observed heterozygosity (Ho), gene flow (Nm), and F-statistics indices (FIS, FIT, and FST). The Hardy-Weinberg equilibrium (HWE) was tested for each locus and population using Arlequin version 3.1 with 100,000,000 steps in the Markov chain and 100,000 dememorization steps. Polymorphism information content (PIC) was calculated using the following formula []: PIC=1−∑i=1nPi2−∑i=1n−1∑j=i+1n2Pi2Pj2 where Pi and Pj are the frequency of the amplified alleles, and n is the number of alleles at each SSR locus. [...] In all, 20 fruits and 20 nutlets were randomly selected per individual to measure and calculate the following 11 morphological characteristics: fruit weight, fruit length, fruit width, fruit diameter, fruit shape index (fruit length/fruit width), nutlet weight, nutlet length, nutlet width, nutlet diameter, nutlet shape index (nutlet length/nutlet width), and nutlet surface. The weights of fruits and nutlets were tested using an electronic balance (accuracy of 0.001 g). The lengths, widths, and diameters of fruits and nutlets were measured using a digital Vernier caliper (accuracy of 0.001 mm). The mean values of all morphological characteristics were used to construct an unrooted UPGMA tree in NTSYS PC version 2.10 based on Nei’s genetic distance (1978). IBM SPSS Statistics 19 software was used to conduct Duncan’s multiple comparison analysis, calculate coefficients of variation (CV, %), and draw the boxplots of the 11 morphological characteristics. For clustering and statistical analyses, the three types of nutlet surfaces were classified as follows: 1 (smooth), 2 (shallow groove), and 3 (deep groove). […]

Pipeline specifications

Software tools GenAlEx, Structure Harvester, CLUMPP, DISTRUCT, Arlequin, SPSS
Applications Miscellaneous, Population genetic analysis
Organisms Prunus persica