| Literature DB >> 27649313 |
Zbigniew Borowski1, Magdalena Świsłocka2, Maciej Matosiuk2, Paweł Mirski2, Kamil Krysiuk1, Magdalena Czajkowska2, Anetta Borkowska2, Mirosław Ratkiewicz2.
Abstract
The trajectories of postglacial range expansions, the occurrence of lineage patches and the formation and maintenance of secondary contact between lineages may mostly reflect neutral demographic processes, including density blocking, that may leave long-lasting genetic signatures. However, a few studies have recently shown that climate may also play a role. We used red deer, a large, mobile herbivore that is assumed to be sensitive to climate change, to test hypotheses of possible selection on the mitochondrial DNA cytochrome b gene (mtDNA cytb) and competitive and/or density-blocking (using mtDNA control region). We searched for a possible link between the phylogeographic structure and abiotic climatic variables. Finally, we tested for isolation by distance and isolation by environment and assessed the impact of human-mediated translocations on the genetic structure of red deer. Our analysis of 30 red deer populations in Poland using the mtDNA control region (N = 357) and cytochrome b (N = 50) markers not only confirmed the presence of the Western and South-Eastern lineages of the species but also indicated the presence of a previously unnoticed, rare relic haplotype that grouped together C. e. italicus from Italy (the Mesola deer). No significant signs of positive selection were detected for the mtDNA cytb gene in the studied red deer. However, a significant signal for purifying selection was found in our study that may explain the narrowness of the contact zone because gene flow between the Western and South-Eastern lineages should drive relatively strong mito-nuclear incompatibilities. MtDNA control region differentiation among red deer populations in Poland correlated with different abiotic climatic variables. Strikingly, the southernmost ice sheet limits during the Elsterian was the most important factor, and it explained the largest amount of variation. However, neither isolation by distance (IBD) nor isolation by environment (IBE) were recorded, and a very limited impact of human translocations was evident. The above-mentioned results suggest that in contemporary red deer populations in Poland, the phylogeographic pattern is well preserved, and long-term processes (density and/or competitive blocking) still play a major role.Entities:
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Year: 2016 PMID: 27649313 PMCID: PMC5029925 DOI: 10.1371/journal.pone.0163191
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Fig 1(A) Pie diagrams indicate the frequency of cr mtDNA haplotypes belonging to the Western lineage (green), the Eastern lineage (red) and the Mesola lineage (yellow) of red deer. PC1 values from principal component analysis (PCA) performed on a population pairwise matrix of ΦST values (black solid line) for cr mtDNA provided a synthetic genetic map that was superimposed onto a geographic map of Poland. The dotted blue line indicates the southernmost ice sheet limit (the Elsterian; Ehlers, et al. 2004) during the maximum extension in the Pleistocene. * Frequencies of cr mtDNA from Krojerová-Prokešová, et al. (2015). ** Occurrence of cr mtDNA control region haplotypes from Niedziałkowska et al. (2011). (B) Correlation latitude with nucleotide diversity (π) showing the width of the contact zone between two distinct cr mtDNA lineages (Western and South-Eastern) of red deer in Poland.
Mitochondrial DNA control region diversity indices for 30 red deer populations studied in Poland.
| No | Population | PD | |||||
|---|---|---|---|---|---|---|---|
| 1. | Bierzwnik | 16 | 3 | 0.43 (0.14) | 0.62 (±0.36) | 12 | 4.63 (±2.40) |
| 2. | Strzałowo | 22 | 3 | 0.57 (0.05) | 0.43 (±0.26) | 7 | 3.23 (±1.73) |
| 3. | Trzebielino | 12 | 3 | 0.62 (0.09) | 0.75 (±0.44) | 11 | 2.62 (±2.90) |
| 4. | Podanin | 9 | 2 | 0.22 (0.17) | 0.03 (±0.04) | 1 | 0.22 (±0.29) |
| 5. | Gołdap | 8 | 5 | 0.86 (0.11) | 0.56 (±0.35) | 11 | 4.18 (±2.32) |
| 6. | Lutowiska | 8 | 3 | 0.68 (±0.12) | 1.03 (±0.61) | 25 | 7.71 (±4.02) |
| 7. | Rudy | 17 | 5 | 0.51 (±0.14) | 0.11 (±0.09) | 5 | 0.79 (±0.60) |
| 8. | Białowieża | 25 | 2 | 0.15 (±0.09) | 0.02 (±0.03) | 1 | 0.15 (±0.22) |
| 9. | Głęboki Bród | 10 | 4 | 0.64 (±0.15) | 0.42 (±0.27) | 7 | 3.16 (±1.78) |
| 10. | Ruszów | 9 | 2 | 0.22 (±0.17) | 0.03 (±0.04) | 1 | 0.22 (±0.29) |
| 11. | Rudnik nad Sanem | 15 | 4 | 0.69 (±0.08) | 0.43 (±0.26) | 8 | 3.18 (±1.74) |
| 12. | Spała | 10 | 5 | 0.67 (±0.16) | 0.53 (±0.33) | 11 | 3.93 (±2.15) |
| 13. | Kobiór | 9 | 2 | 0.50 (±0.13) | 0.27 (±0.19) | 4 | 2.00 (±1.24) |
| 14. | Lądek Zdrój | 10 | 3 | 0.62 (±0.14) | 1.26 (±0.72) | 25 | 9.42 (±4.73) |
| 15. | Lubichowo | 15 | 7 | 0.87 (±0.06) | 0.78 (±0.44) | 18 | 5.83 (±2.95) |
| 16. | Piwniczna | 9 | 2 | 0.50 (±0.13) | 0.74 (±0.44) | 11 | 5.50 (±2.92) |
| 17. | Sarbia | 9 | 5 | 0.81 (±0.12) | 0.54 (±0.34) | 8 | 4.06 (±2.23) |
| 18. | Koszęcin | 19 | 7 | 0.73 (±0.09) | 0.73 (±0.41) | 18 | 5.47 (±2.76) |
| 19. | Niepołomice | 9 | 4 | 0.69 (±0.15) | 0.73 (±0.44) | 15 | 5.44 (±2.89) |
| 20. | Miłomłyn | 16 | 3 | 0.34 (±0.14) | 0.20 (±0.14) | 7 | 1.52 (±0.96) |
| 21. | Szklarska Poręba | 9 | 3 | 0.64 (±0.13) | 0.13 (±0.11) | 3 | 1.00 (±0.74) |
| 22. | Baligród | 16 | 5 | 0.67 (±0.11) | 1.19 (±0.65) | 27 | 8.87 (±4.32) |
| 23. | Bircza | 9 | 4 | 0.75 (±0.11) | 1.77 (±1.00) | 25 | 13.22 (±6.58) |
| 24. | Łomża | 7 | 3 | 0.52 (±0.21) | 0.57 (±0.37) | 11 | 4.29 (±2.41) |
| 25. | Ostrów Mazowiecka | 7 | 2 | 0.29 (±0.20) | 0.27 (±0.20) | 7 | 2.00 (±1.28) |
| 26. | Kiliniska | 10 | 1 | 0.00 (±0.00) | 0.00 (±0.00) | 0 | 0.00 (±0.00) |
| 27. | Łosie | 9 | 2 | 0.22 (±0.17) | 0.68 (±0.41) | 23 | 5.11 (±2.73) |
| 28. | Supraśl | 10 | 2 | 0.47 (±0.13) | 0.44 (±0.28) | 7 | 3.27 (±1.83) |
| 29. | Brodnica | 10 | 3 | 0.38 (±0.18) | 0.91 (±0.53) | 30 | 6.78 (±3.49) |
| 30. | Karczma Borowa | 13 | 3 | 0.60 (±0.09) | 0.38 (±0.24) | 6 | 2.85 (±1.60) |
| Total | 357 | 35 | 0.90 (±0.01) | 1.41 (±0.71) | 55 | 10.57 (±4.83) |
N–sample size; Nh–number of haplotypes; h–haplotype diversity; π –nucleotide diversity (%); S–number of segregating sites; PD–mean number of pairwise differences; SE–standard error.
Fig 2Bayesian tree computed with the GTR+I+G model of sequence evolution, representing the phylogenetic relationships among the concatenated control region and cytochrome b mtDNA sequences found in red deer samples from Poland.
Maximum-likelihood topology computed with the GTR+I+G model of substitution, which was identical to the Bayesian tree.
Fig 3Median-joining network of mtDNA haplotypes from Poland belonging to the Western lineage, the South-Eastern lineage and the Mesola lineage.
The network is based on an analysis of the concatenated control region and the cytochrome b sequences. Thirty-five haplotypes found in this study have a three letter code with a number, while the haplotype of C. e. italicus downloaded from GenBank is indicated by “C.e.i”. Missing haplotypes are indicated by a grey dot.
Effects of abiotic climatic factors on genetic differentiation (as measured by ΦST values) among 30 red deer populations in Poland based on cr mtDNA.
| Factor | Marginal tests | Conditional tests | Sequential tests | |||
|---|---|---|---|---|---|---|
| % var | % var | % var | ||||
| Latitude | 20.5 | <0.001 | - | - | 2.5 | ns |
| Longitude | 7.1 | ns | - | - | 6.6 | <0.05 |
| Snow cover depth | 19.6 | <0.001 | 13.9 | <0.001 | 1.5 | ns |
| Days with snow cover | 20.3 | <0.001 | 15.1 | <0.001 | 3.6 | ns |
| Frost days | 13.7 | <0.01 | 16.8 | <0.001 | 3.4 | ns |
| Temperature in January | 12.9 | <0.01 | 11.1 | <0.001 | nd | - |
| Annual rainfall | 29.3 | <0.001 | 12.5 | <0.001 | 1.7 | ns |
| Summer timing | 36.8 | <0.001 | 21.1 | <0.001 | 1.5 | ns |
| The Elsterian | 41.5 | <0.001 | 24.3 | <0.001 | 41.5 | <0.001 |
% var–percentage of genetic variation explained by the particular variable; P–probability values; ns–non significant; nd–the test not done because one of the variables (temperature in January) did not increase the regression SS in the conditional test; the Elsterian means the southernmost ice sheet limit during the maximum extension in the Pleistocene.