| Literature DB >> 21674834 |
Kristin L Young1, Guangyun Sun, Ranjan Deka, Michael H Crawford.
Abstract
AIM: To examine population genetic structure and hypotheses of the origin of the modern Basque population in Spain using autosomal short tandem repeat (STR) data from individuals living in 27 mountain villages in the provinces of Alava, Vizcaya, Guipuzcoa, and Navarre, by comparing Basque autosomal STR variation with that of neighboring populations in Europe, as well as proposed ancestral populations in North Africa and the Caucasus.Entities:
Mesh:
Year: 2011 PMID: 21674834 PMCID: PMC3118713 DOI: 10.3325/cmj.2011.52.372
Source DB: PubMed Journal: Croat Med J ISSN: 0353-9504 Impact factor: 1.351
Previous autosomal short tandem repeat studies in the Basque population.
| Population | Location | N | Loci | Analyses | Reference |
|---|---|---|---|---|---|
| Rural autochthonous Basque females | Rural Basque region | 57 | 1 | allele frequencies, population genetic parameters, genetic distances, neighbor-joining (NJ) tree | ( |
| Autochthonous Basques | Basque Country | 326 | 6 | allele frequencies | ( |
| Basque autochthonous residents | Guipuzcoa | 50 | 13 | allele frequencies, population genetic parameters | ( |
| Unrelated autochthonous Basques | Basque Country | 206 | 5 | allele frequencies, population genetic parameters | ( |
| Basque Country autochthonous individuals | Basque Country | 202-208 | 7 | allele frequencies, population genetic parameters | ( |
| Unrelated “native Basques” | Alava | 101 | 13 | allele frequencies, population genetic parameters, forensic parameters | ( |
| Unrelated Basque country residents | Basque Country | 100 | 3 | allele frequencies, population genetic parameters, population comparison | ( |
| Unrelated autochthonous Basque students | Navarre | 107 | 3 | allele frequencies, population genetic parameters, population comparison | ( |
| Unrelated autochthonous Basques | Basque Country | 200 | 3 | allele frequencies, population genetic parameters, forensic parameters, population comparison | ( |
| Unrelated autochthonous Basques | Vizcaya | 73 | 13 | allele frequencies, population genetic parameters, forensic parameters, NJ tree | ( |
| Unrelated autochthonous Basques | Vizcaya | 68 | 9 | allele frequencies, population genetic parameters, NJ tree, multidimensional scaling plots | ( |
Figure 1Map of the Basque provinces in France and Spain. Sampling locations – black circles, provincial capitals – ball-and-stick.
Exact test of Hardy-Weinberg Equilibrium for 9 autosomal loci in 4 Basque Provinces. Significant P-values are in bold*
| Locus | Alava | Vizcaya | Guipuzcoa | Navarre |
|---|---|---|---|---|
| D3S1358 | n = 96 | n = 89 | n = 154 | n = 38 |
| 0.77320 | 0.76404 | 0.76623 | 0.68421 | |
| 0.80615 | 0.77433 | 0.77829 | 0.80000 | |
| 0.28137 | 0.34904 | 0.57454 | ||
| FGA | ||||
| 0.87500 | 0.85393 | 0.81818 | 0.81579 | |
| 0.86044 | 0.88574 | 0.87578 | 0.87930 | |
| 0.90451 | 0.12451 | 0.14558 | ||
| D5S818 | ||||
| 0.65625 | 0.79775 | 0.72727 | 0.60526 | |
| 0.70610 | 0.72780 | 0.74159 | 0.73439 | |
| 0.14642 | 0.82662 | 0.65212 | 0.42251 | |
| D7S820 | ||||
| 0.71875 | 0.77528 | 0.78571 | 0.73684 | |
| 0.80928 | 0.81553 | 0.80132 | 0.82596 | |
| 0.07874 | 0.32608 | 0.29700 | 0.70250 | |
| D8S1179 | ||||
| 0.77083 | 0.76404 | 0.75325 | 0.86842 | |
| 0.80988 | 0.80956 | 0.81006 | 0.83474 | |
| vWA | ||||
| 0.85417 | 0.82022 | 0.79870 | 0.92105 | |
| 0.81086 | 0.81946 | 0.79864 | 0.82561 | |
| 0.05728 | 0.88346 | 0.07616 | 0.43085 | |
| D13S317 | ||||
| 0.76042 | 0.76404 | 0.75325 | 0.71053 | |
| 0.76167 | 0.79794 | 0.78282 | 0.76596 | |
| 0.27417 | 0.11321 | 0.80221 | 0.56594 | |
| D18S51 | ||||
| 0.80208 | 0.79775 | 0.81818 | 0.81579 | |
| 0.86938 | 0.88282 | 0.87571 | 0.87053 | |
| 0.12041 | 0.09120 | 0.24056 | 0.86468 | |
| D21SS11 | ||||
| 0.89583 | 0.83146 | 0.80519 | 0.86842 | |
| 0.84004 | 0.84067 | 0.84073 | 0.82246 | |
| 0.97004 | 0.05701 | 0.50981 | 0.53438 |
*Abbreviations: HO – observed heterozygosity; HE– expected heterozygosity.
Locus-by-locus analysis of molecular variance of 9 autosomal short tandem repeat loci. Negative values result from the manner in which the covariance components are estimated, from the mean squares and lower level variances rather than as sums of squares (91)*
| Among groups | Among populations | Within populations | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Locus | percent variance | FCT | percent variance | FSC | percent variance | FST | |||
| D3S1358 | -0.026 | -0.0003 | 0.353 | 1.257 | 0.0126 | 0.142 | 98.768 | 0.0123 | 0.153 |
| FGA | -0.161 | -0.0016 | 0.677 | -0.591 | -0.0059 | 0.814 | 100.752 | -0.0075 | 0.849 |
| D5S818 | 0.384 | 0.0038 | 0.182 | -0.292 | -0.0029 | 0.646 | 99.908 | 0.0009 | 0.544 |
| D7S820 | -1.036 | -0.0104 | 0.939 | 3.350 | 0.0332 | 0.023 | 97.686 | 0.0231 | 0.032 |
| D8S1179 | -0.564 | -0.0056 | 0.904 | 0.573 | 0.0057 | 0.203 | 99.990 | 0.0001 | 0.322 |
| vWA | 0.011 | 0.0001 | 0.371 | 1.851 | 0.0185 | 0.045 | 98.138 | 0.0186 | 0.045 |
| D13S317 | -0.318 | -0.0032 | 0.641 | 0.110 | 0.0011 | 0.497 | 100.208 | -0.0021 | 0.614 |
| D18S51 | -0.546 | -0.0055 | 0.504 | 3.204 | 0.0319 | 0.021 | 97.342 | 0.0266 | 0.010 |
| D21S11 | -0.308 | -0.0031 | 0.602 | 0.767 | 0.0076 | 0.316 | 99.541 | 0.0046 | 0.321 |
| Global estimates | -0.355 | -0.0036 | 0.878 | 1.309 | 0.0131 | 0.011 | 99.045 | 0.0096 | 0.019 |
| Covariance estimates | Va = -0.095 | Vb = 0.351 | Vc = 26.517 | ||||||
*Abbreviations: FCT – fixation index among groups; FSC – fixation index among populations within groups; FST – fixation index within populations.
Gene diversity between populations based on autosomal short tandem repeat data
| Population | D3S1358 | FGA | D5S818 | D7S820 | D8S1179 | vWA | D13S317 | D18S51 | D21S11 | Average |
|---|---|---|---|---|---|---|---|---|---|---|
| Alava* | 0.804 | 0.860 | 0.705 | 0.808 | 0.790 | 0.807 | 0.758 | 0.869 | 0.840 | 0.805 |
| Vizcaya* | 0.772 | 0.886 | 0.728 | 0.816 | 0.781 | 0.817 | 0.792 | 0.876 | 0.840 | 0.812 |
| Guipuzcoa* | 0.778 | 0.875 | 0.741 | 0.801 | 0.801 | 0.799 | 0.773 | 0.876 | 0.840 | 0.809 |
| Navarre* | 0.798 | 0.879 | 0.705 | 0.826 | 0.815 | 0.826 | 0.754 | 0.870 | 0.819 | 0.810 |
| Andalusia | 0.803 | 0.868 | 0.708 | 0.797 | 0.824 | 0.805 | 0.795 | 0.879 | 0.856 | 0.815 |
| Cantabria | 0.796 | 0.871 | 0.715 | 0.796 | 0.826 | 0.803 | 0.779 | 0.882 | 0.846 | 0.813 |
| Catalonia | 0.785 | 0.860 | 0.714 | 0.815 | 0.781 | 0.825 | 0.769 | 0.879 | 0.809 | 0.804 |
| Galicia | 0.786 | 0.855 | 0.712 | 0.796 | 0.817 | 0.822 | 0.795 | 0.880 | 0.830 | 0.810 |
| Murcia | 0.815 | 0.860 | 0.718 | 0.787 | 0.807 | 0.820 | 0.758 | 0.866 | 0.826 | 0.806 |
| Valencia | 0.800 | 0.872 | 0.702 | 0.803 | 0.826 | 0.807 | 0.781 | 0.875 | 0.839 | 0.812 |
| Austria | 0.806 | 0.864 | 0.709 | 0.808 | 0.814 | 0.806 | 0.801 | 0.872 | 0.854 | 0.815 |
| Belgium | 0.801 | 0.854 | 0.707 | 0.811 | 0.806 | 0.808 | 0.793 | 0.880 | 0.831 | 0.810 |
| Bosnia | 0.794 | 0.850 | 0.713 | 0.803 | 0.815 | 0.807 | 0.745 | 0.879 | 0.867 | 0.808 |
| Germany | 0.781 | 0.870 | 0.709 | 0.814 | 0.790 | 0.818 | 0.774 | 0.885 | 0.841 | 0.809 |
| Greece | 0.788 | 0.855 | 0.733 | 0.794 | 0.814 | 0.822 | 0.775 | 0.881 | 0.846 | 0.812 |
| Hungary | 0.794 | 0.864 | 0.728 | 0.798 | 0.809 | 0.805 | 0.787 | 0.886 | 0.855 | 0.814 |
| Tuscany | 0.788 | 0.865 | 0.722 | 0.796 | 0.832 | 0.793 | 0.745 | 0.868 | 0.852 | 0.807 |
| Poland | 0.802 | 0.863 | 0.717 | 0.812 | 0.797 | 0.804 | 0.759 | 0.873 | 0.866 | 0.810 |
| Portugal | 0.786 | 0.862 | 0.710 | 0.811 | 0.816 | 0.810 | 0.785 | 0.876 | 0.848 | 0.811 |
| Russia | 0.783 | 0.860 | 0.734 | 0.811 | 0.799 | 0.803 | 0.781 | 0.878 | 0.845 | 0.810 |
| Scotland | 0.799 | 0.856 | 0.727 | 0.804 | 0.834 | 0.811 | 0.828 | 0.864 | 0.855 | 0.820 |
| Slovenia | 0.797 | 0.876 | 0.718 | 0.810 | 0.780 | 0.809 | 0.785 | 0.879 | 0.855 | 0.812 |
| Switzerland | 0.791 | 0.869 | 0.725 | 0.821 | 0.830 | 0.809 | 0.773 | 0.877 | 0.842 | 0.815 |
| Egypt | 0.772 | 0.873 | 0.763 | 0.784 | 0.819 | 0.806 | 0.792 | 0.858 | 0.825 | 0.810 |
| Morocco | 0.779 | 0.851 | 0.727 | 0.772 | 0.824 | 0.822 | 0.748 | 0.878 | 0.831 | 0.803 |
| Turkey | 0.780 | 0.864 | 0.751 | 0.813 | 0.822 | 0.802 | 0.779 | 0.872 | 0.842 | 0.814 |
| Georgia | 0.775 | 0.871 | 0.749 | 0.810 | 0.806 | 0.765 | 0.746 | 0.874 | 0.855 | 0.806 |
| HS† | 0.788 | 0.862 | 0.720 | 0.801 | 0.808 | 0.807 | 0.773 | 0.872 | 0.839 | 0.807 |
| HT‡ | 0.792 | 0.866 | 0.724 | 0.806 | 0.814 | 0.812 | 0.780 | 0.878 | 0.847 | 0.813 |
| GST§ | 0.006 | 0.006 | 0.007 | 0.006 | 0.008 | 0.006 | 0.009 | 0.006 | 0.009 | 0.007 |
*Present study.
†Gene diversity within subpopulations.
‡Gene diversity between subpopulations.
§Coefficient of gene differentiation (92).
Figure 2Multidimensional Scaling plot of genetic distance between 27 populations (Basques – closed circles, Iberia – open circles, Europe – closed squares, Middle East – cross, Caucasus – closed triangles, North Africa – open triangles). The first two axes account for 26.02% of the total genetic variation present in the sample. The stress value of 0.169, well below the threshold of 0.317 for 27 populations in 2 dimensions (90), demonstrates that the plot is an accurate representation of the genetic distance matrix. A Mantel test of matrix correlation between the original distance matrix and the MDS matrix also demonstrated that the MDS plot was an accurate represent of the genetic distances between populations (correlation coefficient: r = 0.93498, t test: t = 5.7717, P = 1.0). The Basque groups cluster together on the right side of the plot, near their neighbors in Cantabria. The North African and Georgian populations are found near the bottom center of plot, differentiated from the other European groups.