Cryptic and Repeated Allopolyploid Speciation Within Allium Przewalskianum Regel. (Alliaceae)

Cryptic and repeated ‘allopolyploid’ speciation within Allium przewalskianum Regel. (Alliaceae) from the Qinghai-Tibet Plateau

Organisms Diversity & Evolution

Qianlong Liang, Xiaoxiao Hu, Guili Wu, Jianquan Liu*

*Corresponding author, e-mail: , postal address:MOE Key Laboratory for Bio-resources and Eco-environment, College of Life Science,Sichuan University, 24，South Section 1, Yihuan Road, Chengdu 610065, China

Table S1 Details of the Allium przewalskianumdiploid–tetraploid complex sampling locations and sample sizes analyzed; P. denotes the population code.

Note: (1) Abbreviations: QH, Qinghai; GS, Gansu; SC, Sichuan; XZ, Xizang; YN, Yunnan; (2) populations 1-12 are diploid; populations 13-28 are tetraploid and the population codes are in bold.

Table S2 AFLP adapter and primer sequences used in this study

Table S3 Population codes (P.), plant sources, and locality of the sequenced material; ITS and CHS GenBank accession numbers for all sequences included in this study.

Table S4 Details of the 60 sites used for ecological niche modeling

Note: DP, the diploid population; NTP, tetraploid populations in the northern QTP; STP, tetraploid populations in the southern QTP; DPNTP indicates that the population has both cytotypes (from Cui et al., 2008).

Table S5 The 12 environmental variables used for ENM in this study

Table S6 Analysis of STRUCTURE output

Note: K, the number of clusters; RepTimes, repeat times of independent simulations run for each value of K; lnP (D),the log likelihood of the observed genotype distribution in K clusters that can be output by STRUCTURE simulation (Pritchard et al., 2000); ΔK,an ad hoc quantity related to the second order rate of change of the log probability of data with respect to K,this is a good predictor of the real value of K (Evanno et al., 2005).

Table S7 ITS genotypes (H) and CHS genotypes (C) among the 28 populations

Fig. S1 Principal Co-ordinate Analysis (PCoA) plot based on a matrix of Jaccard distances among 157 individuals using NTSYS-PC 2.0. All the individuals could be identified within seven groups, which correspond to the output of the Structure analysis when K=6: the tetraploid populations clustered into three groups, STP (populations in southern QTP), ETP (populations in eastern QTP) and NTP (populations in northern QTP); the diploid populations readily clustered into five groups and DP-2 was intermixed with NTP.

Fig. S2 ITS phylogenetic relationships of sampled Allium przewalskianum in the present study using Bayesian, ML and MP analyses. All analyses were performed according to the methods outlined in the main paper. We used Allium ovalifolium, Allium eduardii and Allium mongolicum as outgroups. All newly obtained ITS sequences were deposited in GenBank (accessions KC189069–KC189120). We recovered 34 genotypes from 28 populations (Table S7). The ML tree and the MP tree were congruent with the 50% major consensus tree obtained from Bayesian analysis (shown in this Fig., under the GTR+I+G model) and had a similar topology. The support values are given above the branches (Left: posterior probabilities of Bayesian analysis; Middle: bootstrap values of maximum-parsimony and Right: bootstrap values of maximum-likelihood). These analyses based on the nuclear ITS sequences suggest that all sampled diploid and tetraploid individuals of A. przewalskianum can be grouped into five lineages, A-E.

Fig. S3CHSphylogenetic relationships of sampled Allium przewalskianum in the present study using Bayesian, ML and MP analyses.All analyses were performed according to the methods outlined in the main paper. We used Allium cepa as the outgroup. All newly obtained CHS sequences were deposited in GenBank (accession numbers KC188957–KC189068). We recovered 75 genotypes from 28 populations (Table S7). The ML tree and the MP tree were congruent with the 50% major consensus tree obtained from Bayesian analysis (shown in this Fig., under the GTR+I+G model) and had a similar topology with respect to the main branches. The support values are given above the branches (Left: posterior probabilities of Bayesian analysis; Middle: bootstrap values of maximum-parsimony and Right: bootstrap values of maximum-likelihood). These analyses based on the nuclear CHS sequences also suggest that all sampled diploid and tetraploid individuals of A. przewalskianum can be grouped into five lineages, I-V.

References:

Cui, X. K., Ao, C. Q., Zhang, Q., Chen, L. T., Liu, J. Q. (2008). Diploid and tetraploid distribution of Allium przewalskianum Regel. (Liliaceae) in the Qinghai-Tibetan Plateau and adjacent regions.Caryologia, 61, 192–200.

Evanno, G., Regnaut, S., Goudet, J. (2005). Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Molecular Ecology, 14, 2611–2620.

Pritchard, J. K., Stephens, M., Donnelly, P. (2000). Inference of population structure using multilocus genotype data. Genetics,155, 945–959.