| Literature DB >> 27978815 |
Björn Stelbrink1, Alena A Shirokaya2, Kirstin Föller3, Thomas Wilke3, Christian Albrecht3.
Abstract
BACKGROUND: Ancient Lake Ohrid, located on the Albania-Macedonia border, is the most biodiverse freshwater lake in Europe. However, the processes that gave rise to its extraordinary endemic biodiversity, particularly in the species-rich gastropods, are still poorly understood. A suitable model taxon to study speciation processes in Lake Ohrid is the pulmonate snail genus Acroloxus, which comprises two morphologically distinct and ecologically (vertically) separated endemic species. Using a multilocus phylogenetic framework of Acroloxus limpets from the Euro-Mediterranean subregion, together with molecular-clock and phylogeographic analyses of Ohrid taxa, we aimed to infer their geographic origin and the timing of colonization as well as the role of geography and ecology in intra-lacustrine diversification.Entities:
Keywords: Ancient lakes; Balkans; Biogeography; Freshwater limpets; Incipient speciation; Molecular clock; Molecular phylogeny; Phylogeography
Mesh:
Substances:
Year: 2016 PMID: 27978815 PMCID: PMC5159953 DOI: 10.1186/s12862-016-0826-6
Source DB: PubMed Journal: BMC Evol Biol ISSN: 1471-2148 Impact factor: 3.260
Fig. 1Substrate types and sampling sites inside and outside Lake Ohrid. a Bathymetric map of Lake Ohrid with 10 m contour lines. Coloured rectangles represent substrate types for a particular locality classified based on information recorded during field trips (see Methods for details on substrate classification). Sampling sites of Acroloxus are colour-coded according to substrate type, b Map of the Euro-Mediterranean subregion with sampling sites (grey: Balkans; pink: Lake Ohrid; © d-maps.com), c Shell of the littoral A. macedonicus, d Shell of the sublittoral A. improvisus
Primers used for sequencing
| Primer | 5′–3′ sequence | Source |
|---|---|---|
| 16Sar | CGC CTG TTT ATC AAA AAC AT | [ |
| 16Sbr | CCG GTC TGA ACT CAG ATC ACG T | [ |
| 28SD23F | GAG AGT TCA AGA GTA CGT G | [ |
| 28SD6R | CCA GCT ATC CTG AGG GAA ACT TCG | [ |
| LCO1490 | GGT CAA CAA ATC ATA AAG ATA TTG G | [ |
| COR722b | TAA ACT TCA GGG TGA CCA AAA AAT YA | [ |
| H3F | ATG GCT CGT ACC AAG CAG ACV GC | [ |
| H3R | ATA TCC TTR GGC ATR ATR GTG AC | [ |
| LT1 (ITS2) | TCG TCT GTG TGA GGG TCG | [ |
| ITS2-RIXO | TTC TAT GCT TAA ATT CAG GGG | [ |
Best-fit substitution models for the different partitions estimated with jModelTest
| Partition | Length (bp) | AIC | AICc |
|---|---|---|---|
| 16S rRNA | 468 | GTR + Γ | GTR + Γ |
| 28S rRNA | 757 | GTR + Γ | GTR + Γ |
| COI | 655 | HKY + Γ | HKY + Γ |
| H3 | 328 | GTR + I | GTR + I |
Fig. 2Phylogenetic relationships and estimation of divergence times of Euro-Mediterranean Acroloxus species and populations. a BEAST MCC tree (UCLN-Y) based on 16S rRNA, 28S rRNA, COI and H3 with selected node ages (see Table 4), posterior probabilities and 95% HPD (outgroup removed). Country codes used: ALB = Albania, DEU = Germany, GRC = Greece, IRL = Ireland (GenBank sequence, GB), ITA = Italy, MKD = Macedonia, SVN = Slovenia, SRB = Serbia, and TUR = Turkey, b MrBayes phylogram with posterior probabilities and RAxML bootstrap values (outgroup removed). Acroloxus macedonicus* individuals refer to non-ribbed specimens of A. macedonicus
Estimated divergence times in My obtained for the four molecular-clock analyses
| STR-BD | STR-Y | UCLN-BD | UCLN-Y | *UCLN-BD | |
|---|---|---|---|---|---|
| RootHeight | 42.45 (31.37, 55.11) | 35.91 (26.42, 45.97) | 31.71 (18.32, 45.95) | 20.63 (13.24, 28.79) | 34.23 (21.08, 52.34) |
| Node 1 | 3.86 (2.98, 4.78) | 3.82 (2.99, 4.78) | 4.49 (3.23, 5.87) | 4.44 (3.23, 5.76) | 4.58 (3.24, 6.31) |
| Node 2 | 3.15 (2.31, 4.05) | 3.14 (2.31, 4.02) | 3.57 (2.33, 4.81) | 3.58 (2.39, 4.85) | 3.40 (1.93, 5.00) |
| Node 3 | 1.13 (0.78, 1.51) | 1.16 (0.79, 1.53) | 1.29 (0.81, 1.82) | 1.37 (0.86, 1.94) | - |
| Node 4 | 1.38 (0.91, 1.86) | 1.41 (0.96, 1.92) | 1.55 (0.88, 2.34) | 1.62 (0.92, 2.41) | - |
| Node 5 | 3.25 (2.46, 4.09) | 3.24 (2.44, 4.05) | 3.57 (2.36, 4.83) | 3.55 (2.40, 4.73) | 2.71 (1.39, 4.37) |
| Node 6 | 2.31 (1.74, 2.96) | 2.32 (1.73, 2.94) | 2.15 (1.41, 2.91) | 2.20 (1.47, 2.95) | 1.89 (1.01, 2.80) |
| Node 7 | 1.91 (1.41, 2.44) | 1.93 (1.44, 2.46) | 1.73 (1.20, 2.35) | 1.80 (1.24, 2.42) | 1.24 (0.67, 2.02) |
| Node 8 | 1.69 (1.23, 2.19) | 1.71 (1.25, 2.20) | 1.19 (0.79, 1.61) | 1.27 (0.86, 1.72) | - |
See Fig. 2 for respective node numbers; node 3 provides estimated ages of the focal Lake Ohrid group (UCLN-Y and *UCLN-BD (*BEAST species tree analysis) represent the favoured models, respectively; divergence times refer to mean, lower and upper 95% HPD values). Note that not all nodes are available in the *BEAST analyses
Results of the BF analysis (log10 Bayes factors)
| Ln P (model | data) | S.E. | STR-BD/*STR-BD | STR-Y/*STR-Y | UCLN-BD/*UCLN-BD | UCLN-Y/*UCLN-Y | |
|---|---|---|---|---|---|---|
| STR-BD | −8,802.908 | +/− 0.126 | - | 2.032 | −46.650 | −46.962 |
| STR-Y | −8,807.588 | +/− 0.163 | −2.032 | - | −48.683 | −48.995 |
| UCLN-BD | −8,695.492 | +/− 0.269 | 46.650 | 48.683 | - | −0.312 |
| UCLN-Y | −8,694.774 | +/− 0.267 | 46.962 | 48.995 | 0.312 | - |
| *STR-BD | −8704.524 | +/− 0.238 | - | −0.002 | −26.918 | −26.844 |
| *STR-Y | −8704.518 | +/− 0.245 | 0.002 | - | −26.915 | −26.842 |
| *UCLN-BD | −8642.544 | +/− 0.256 | 26.918 | 26.915 | - | 0.073 |
| *UCLN-Y | −8642.712 | +/− 0.286 | 26.844 | 26.842 | −0.073 | - |
The favoured analyses are UCLN-Y and *UCLN-BD (models marked with an asterisk refer to the *BEAST species tree analyses). See Methods for details
Fig. 3Parsimony networks for COI (central), 16S rRNA and ITS2 (top). The central COI haplotype network consists of one major and four minor networks. Position of haplotypes and haplotype groups for the COI dataset approximately refer to sampling sites across the lake. Numbers in circles refer to haplotype numbers shown in Additional file 1: Table S1. Sampling sites (pink) with locality numbers (grey) and haplotype numbers (black, bold), corresponding to the haplotype numbers shown in the networks