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Genetic population data of 15 autosomal loci from the Central Region of Venezuela
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Forensic Science International: Genetics Supplement Series 1 (2008) 303–305 www.elsevier.com/locate/FSIGSS
Research article
Genetic population data of 15 autosomal loci from the Central Region of Venezuela Maritza Alvarez a,*, Anna Chiarello a, Airene Dictamen a, Yelitza Zambrano a, Francys Escobar a, Anabel Arends b, Miguel Marrero a, Raul Ferreira c a Laboratorio Genomik, Maracay,Venezuela Servicio Hematologia, Hospital Universitario Caracas, Venezuela c Departamento de Genetica,Hospital Hermanos Ameijeiras, Cuba
b
Received 29 August 2007; accepted 10 October 2007
Abstract Fifteen autosomal markers (CSF1PO, TH01, TPOX, F13A01, FESFPS, VWA, D16S539, D7S820, D13S317, D5S818, D3S1358, D8S1179, LPL, F13B and D1S80) were evaluated in the Central Region of Venezuela (States of Aragua, Carabobo and Cojedes) in order to test their usefulness in filial relationship studies. Allele frequencies for each marker, statistical parameters of forensic interest, Hardy–Weinberg equilibrium, loci independence, substructuration of our population and presence of null alleles and dropout were tested for each marker. Our population was compared with other Venezuelan populations (Caracas and Maracaibo) taking into account allele frequencies corresponding to 10 markers which have been typed in all these three populations. # 2008 Published by Elsevier Ireland Ltd. Keywords: STRs; Venezuelan population database; Forensic genetics
1. Introduction Amplified variable number of tandem repeats markers are the most frequently used for human identification and paternity testing. It is important to validate its usefulnes and to establish a populational data base for reliable statistical analysis in each population. Our aim is to obtain this information from Central Region of Venezuela and to compare it with those corresponding to Caracas and Maracaibo populations previously tested. 2. Materials and methods Blood samples were collected from 1031 non-related individuals living in the Central Region of Venezuela (States of Aragua, Carabobo and Cojedes) after informed consent, and DNA was extracted using the DNA IQ System from PROMEGA. Fourteen STR loci (CSF1PO, TH01, TPOX, F13A01, FESFPS, VWA, D16S539, D7S820, D13S317, D5S818, D3S1358, D8S1179, LPL and F13B) and one * Corresponding author. Tel.: +58 243 2450534; fax: +58 243 2464705. E-mail address: [email protected] (M. Alvarez). 1875-1768/$ – see front matter # 2008 Published by Elsevier Ireland Ltd. doi:10.1016/j.fsigss.2007.10.072
AmpFLP loci (D1S80) were amplified using commercial kits from PROMEGA and Applied Biosystems, respectively. Allele typing was carried out by denaturant polyacrilamide gel electrophoresis and silver staining detection according to manufacturer’s instructions. Parameters of forensic interest were calculated by means of software PowerStats [1]. Allele frequency, Hardy–Weinberg equilibrium and loci independence were tested using GENEPOP version 3.4 [2] and GDA version 1.1 [3] softwares. Population substructure in our population was evaluated by means of software STRUCTURE [4] and presence of either null alleles or dropout by means of MICROCHECKER program [5]. Minimum allele frequencies were calculated as recommended [6]. Allele frequencies for 10 markers (CSF1PO, TH01, TPOX, VWA, D16S539, D13S317, D7S820, D5S818, D3S1358 and D8S1179) were compared by chi-square test with contingency tables among populations of Central Region of Venezuela (our results), Caracas [7] and Maracaibo [8]. 3. Results and discussion Allele frequencies and main statistical parameters for each locus are shown in Table 1. No deviations from Hardy–
304
Table 1 Allele frequencies and statistical parameters in the Central Region of Venezuela CSF1P0
TH01
TPOX
FESFPS
F13A01
VWA
D16S539
D7S820
D13S317
D1S80
F13B
LPL
D5S818
D3S1358
D8S1179
N 3.2 4 5 6 7 8 9 9.3 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 Fmin. PIC MP PD PE TPI
2034
2048
2048
1990
2034 0.1986 0.0575 0.2109 0.2139 0.2699 0.0177 0.0029
2040
2054
2062
2048
1488
1110
786
1058
642
562
0.0123 0.0152 0.0270 0.2522 0.3097 0.3132 0.0610 0.0079 0.0015
0.0029 0.70 0.115 0.885 0.491 1.92
0.0005 0.0010 0.2539 0.2524 0.1118 0.1553 0.2056 0.0171 0.0024
0.0030 0.76 0.076 0.924 0.573 2.34
0.0112 0.0088 0.4487 0.1001 0.0635 0.2832 0.0820 0.0024
0.0028 0.65 0.136 0.864 0.406 1.59
0.0025 0.0186 0.0090 0.2427 0.4422 0.2136 0.0668 0.0040 0.0005
0.0029 0.66 0.131 0.869 0.424 1.65
0.0010 0.0010 0.0044 0.0054 0.0044 0.0064 0.0054 0.0005
0.0030 0.76 0.075 0.925 0.592 2.45
0.0015 0.0005 0.0034 0.0897 0.1191 0.2814 0.2618 0.1632 0.0618 0.0162 0.0015
0.0031 0.78 0.073 0.927 0.626 2.69
0.0263 0.1660
0.0005 0.0165 0.1411 0.1038
0.0024 0.0908 0.1230
0.1193 0.2824 0.2551 0.1315 0.0175 0.0019
0.2750 0.2536 0.1693 0.0335 0.0058 0.0010
0.0576 0.2573 0.2949 0.1230 0.0479 0.0029
0.0030 0.77 0.069 0.931 0.567 2,30
0.0031 0.77 0.070 0.930 0.648 2.88
0.0031 0.78 0.067 0.933 0.661 2.99
0.1108 0.0306 0.1829 0.2477 0.4198 0.0072 0.0009 0.0020 0.0034 0.0047 0.2379 0.0040 0.0175 0.0336 0.0343 0.0128 0.3085 0.0800 0.0094 0.0040 0.0672 0.0491 0.0349 0.0625 0.0020 0.0060 0.0128 0.0034 0.0040 0.0007 0.0007 0.0013 0.0013 0.0020 0.0042 0.81 0.052 0.948 0.636 2.77
0.0051 0.67 0.126 0.874 0.431 1.68
0.0038 0.0025 0.0509
0.0397 0.0095 0.0491
0.4491 0.2087 0.2316 0.0496 0.0038
0.0624 0.3469 0.3138 0.1682 0.0095 0.0009
0.0070 0.65 0.143 0.857 0.371 1.48
0.0054 0.70 0.109 0.891 0.445 1.73
0.0071 0.0231
0.0078 0.1168 0.3412 0.2555 0.1682 0.1012 0.0093
0.0093 0.73 0.100 0.900 0.600 2.51
0.0836 0.0480 0.1459 0.2918 0.2438 0.1281 0.0231 0.0036 0.0018
0.0109 0.78 0.064 0.936 0.668 3.05
N: total number of alleles; Fmin: minimum frequency; PIC: polymorphism information content; MP: matching probability; PD: power of discrimination; PE: power of exclusion; TPI: typical paternity index.
M. Alvarez et al. / Forensic Science International: Genetics Supplement Series 1 (2008) 303–305
Allele
M. Alvarez et al. / Forensic Science International: Genetics Supplement Series 1 (2008) 303–305
Weinberg equilibrium (HWE) were observed for markers CSF1PO, TPOX, F13A01, VWA, D16S539, D7S820, D13S317, D5S818, D3S1358, D8S1179, F13B and D1S80 ( p > 0.05). Markers TH01, LPL and FESFPS are in disequilibrium due to heterozygote excess, but sequential Bonferroni corrections of these results allow considering HWE for LPL marker ( p > 0.05), and FESFPS ( p > 0.01). Population substructure in our population was discarded as well as presence of either null alleles or dropout in these three markers. No statistically significant differences between our population and Caracas population were found. However, statistically significant differences were found between our population and Maracaibo population regarding allele frequencies distribution of markers TPOX and D16S539. The combined power of exclusion is 0.9999946 and the typical combined paternity index is 1,39,391. 4. Conclusion Further studies will be developed in order to know the reason of Hardy–Weinberg disequilibrium for marker TH01 in our population. Our results show that this battery of 15 markers is a powerful tool for paternity studies in the Central Region of Venezuela. We propose a joint evaluation of those Venezuelan populations which have been studied in order to develop a national data base of common markers.
305
Conflict of interest None. References [1] A. Tereba, Tools for the analysis of population statistics, Promega: Profiles DNA 2 (1999) 14. [2] M. Raymond, F. Rousset, GENEPOP (version 1.2): population genetics software for exact tests and ecumenicism, J. Hered. 86 (1995) 248. [3] P.O. Lewis , D. Zaykin, (2001). Genetic Data Analysis: Computer program for the analysis of allelic data. Version 1.0 (d16c) http://lewis.eeb.uconn.edu/lewishome/software.html. [4] J.K. Pritchard, M. Stepehns, P. Donnelly, Inference of population structure using multilocus genotype data, Genetics 155 (2000) 945 http://pritch.bsd.uchicago.edu/structure.html. [5] C. Oosterhout, B. Hutchinson, D. Wills, P. Shipley, MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data, Mol. Ecol. Notes 4 (2004) 535 www.microchecker.hull.ac.uk. [6] B. Budowle , K.L. Monson.,R. Chakraborty,Estimating minimum allele frequencies for DNA profile frequency estimates for PCR-based loci, Int. J. Legal Med. 108 (1996) 173–176 [7] M.A. Chiurillo, A. Morales, A.M. Mendes, et al., Genetic profiling of a central Venezuelan population using 15 STR markers that may be of forensic importance, Forensic Sci. Int. 136 (2003) 99. [8] L. Pineda Bernal, L. Borjas, W. Zabala, et al., Genetic variation of 15 STR autosomal loci using in the Maracaibo population from Venezuela, Forensic Sci. Int. 161 (2006) 60–63.
Forensic Science International: Genetics Supplement Series 1 (2008) 303–305 www.elsevier.com/locate/FSIGSS
Research article
Genetic population data of 15 autosomal loci from the Central Region of Venezuela Maritza Alvarez a,*, Anna Chiarello a, Airene Dictamen a, Yelitza Zambrano a, Francys Escobar a, Anabel Arends b, Miguel Marrero a, Raul Ferreira c a Laboratorio Genomik, Maracay,Venezuela Servicio Hematologia, Hospital Universitario Caracas, Venezuela c Departamento de Genetica,Hospital Hermanos Ameijeiras, Cuba
b
Received 29 August 2007; accepted 10 October 2007
Abstract Fifteen autosomal markers (CSF1PO, TH01, TPOX, F13A01, FESFPS, VWA, D16S539, D7S820, D13S317, D5S818, D3S1358, D8S1179, LPL, F13B and D1S80) were evaluated in the Central Region of Venezuela (States of Aragua, Carabobo and Cojedes) in order to test their usefulness in filial relationship studies. Allele frequencies for each marker, statistical parameters of forensic interest, Hardy–Weinberg equilibrium, loci independence, substructuration of our population and presence of null alleles and dropout were tested for each marker. Our population was compared with other Venezuelan populations (Caracas and Maracaibo) taking into account allele frequencies corresponding to 10 markers which have been typed in all these three populations. # 2008 Published by Elsevier Ireland Ltd. Keywords: STRs; Venezuelan population database; Forensic genetics
1. Introduction Amplified variable number of tandem repeats markers are the most frequently used for human identification and paternity testing. It is important to validate its usefulnes and to establish a populational data base for reliable statistical analysis in each population. Our aim is to obtain this information from Central Region of Venezuela and to compare it with those corresponding to Caracas and Maracaibo populations previously tested. 2. Materials and methods Blood samples were collected from 1031 non-related individuals living in the Central Region of Venezuela (States of Aragua, Carabobo and Cojedes) after informed consent, and DNA was extracted using the DNA IQ System from PROMEGA. Fourteen STR loci (CSF1PO, TH01, TPOX, F13A01, FESFPS, VWA, D16S539, D7S820, D13S317, D5S818, D3S1358, D8S1179, LPL and F13B) and one * Corresponding author. Tel.: +58 243 2450534; fax: +58 243 2464705. E-mail address: [email protected] (M. Alvarez). 1875-1768/$ – see front matter # 2008 Published by Elsevier Ireland Ltd. doi:10.1016/j.fsigss.2007.10.072
AmpFLP loci (D1S80) were amplified using commercial kits from PROMEGA and Applied Biosystems, respectively. Allele typing was carried out by denaturant polyacrilamide gel electrophoresis and silver staining detection according to manufacturer’s instructions. Parameters of forensic interest were calculated by means of software PowerStats [1]. Allele frequency, Hardy–Weinberg equilibrium and loci independence were tested using GENEPOP version 3.4 [2] and GDA version 1.1 [3] softwares. Population substructure in our population was evaluated by means of software STRUCTURE [4] and presence of either null alleles or dropout by means of MICROCHECKER program [5]. Minimum allele frequencies were calculated as recommended [6]. Allele frequencies for 10 markers (CSF1PO, TH01, TPOX, VWA, D16S539, D13S317, D7S820, D5S818, D3S1358 and D8S1179) were compared by chi-square test with contingency tables among populations of Central Region of Venezuela (our results), Caracas [7] and Maracaibo [8]. 3. Results and discussion Allele frequencies and main statistical parameters for each locus are shown in Table 1. No deviations from Hardy–
304
Table 1 Allele frequencies and statistical parameters in the Central Region of Venezuela CSF1P0
TH01
TPOX
FESFPS
F13A01
VWA
D16S539
D7S820
D13S317
D1S80
F13B
LPL
D5S818
D3S1358
D8S1179
N 3.2 4 5 6 7 8 9 9.3 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 Fmin. PIC MP PD PE TPI
2034
2048
2048
1990
2034 0.1986 0.0575 0.2109 0.2139 0.2699 0.0177 0.0029
2040
2054
2062
2048
1488
1110
786
1058
642
562
0.0123 0.0152 0.0270 0.2522 0.3097 0.3132 0.0610 0.0079 0.0015
0.0029 0.70 0.115 0.885 0.491 1.92
0.0005 0.0010 0.2539 0.2524 0.1118 0.1553 0.2056 0.0171 0.0024
0.0030 0.76 0.076 0.924 0.573 2.34
0.0112 0.0088 0.4487 0.1001 0.0635 0.2832 0.0820 0.0024
0.0028 0.65 0.136 0.864 0.406 1.59
0.0025 0.0186 0.0090 0.2427 0.4422 0.2136 0.0668 0.0040 0.0005
0.0029 0.66 0.131 0.869 0.424 1.65
0.0010 0.0010 0.0044 0.0054 0.0044 0.0064 0.0054 0.0005
0.0030 0.76 0.075 0.925 0.592 2.45
0.0015 0.0005 0.0034 0.0897 0.1191 0.2814 0.2618 0.1632 0.0618 0.0162 0.0015
0.0031 0.78 0.073 0.927 0.626 2.69
0.0263 0.1660
0.0005 0.0165 0.1411 0.1038
0.0024 0.0908 0.1230
0.1193 0.2824 0.2551 0.1315 0.0175 0.0019
0.2750 0.2536 0.1693 0.0335 0.0058 0.0010
0.0576 0.2573 0.2949 0.1230 0.0479 0.0029
0.0030 0.77 0.069 0.931 0.567 2,30
0.0031 0.77 0.070 0.930 0.648 2.88
0.0031 0.78 0.067 0.933 0.661 2.99
0.1108 0.0306 0.1829 0.2477 0.4198 0.0072 0.0009 0.0020 0.0034 0.0047 0.2379 0.0040 0.0175 0.0336 0.0343 0.0128 0.3085 0.0800 0.0094 0.0040 0.0672 0.0491 0.0349 0.0625 0.0020 0.0060 0.0128 0.0034 0.0040 0.0007 0.0007 0.0013 0.0013 0.0020 0.0042 0.81 0.052 0.948 0.636 2.77
0.0051 0.67 0.126 0.874 0.431 1.68
0.0038 0.0025 0.0509
0.0397 0.0095 0.0491
0.4491 0.2087 0.2316 0.0496 0.0038
0.0624 0.3469 0.3138 0.1682 0.0095 0.0009
0.0070 0.65 0.143 0.857 0.371 1.48
0.0054 0.70 0.109 0.891 0.445 1.73
0.0071 0.0231
0.0078 0.1168 0.3412 0.2555 0.1682 0.1012 0.0093
0.0093 0.73 0.100 0.900 0.600 2.51
0.0836 0.0480 0.1459 0.2918 0.2438 0.1281 0.0231 0.0036 0.0018
0.0109 0.78 0.064 0.936 0.668 3.05
N: total number of alleles; Fmin: minimum frequency; PIC: polymorphism information content; MP: matching probability; PD: power of discrimination; PE: power of exclusion; TPI: typical paternity index.
M. Alvarez et al. / Forensic Science International: Genetics Supplement Series 1 (2008) 303–305
Allele
M. Alvarez et al. / Forensic Science International: Genetics Supplement Series 1 (2008) 303–305
Weinberg equilibrium (HWE) were observed for markers CSF1PO, TPOX, F13A01, VWA, D16S539, D7S820, D13S317, D5S818, D3S1358, D8S1179, F13B and D1S80 ( p > 0.05). Markers TH01, LPL and FESFPS are in disequilibrium due to heterozygote excess, but sequential Bonferroni corrections of these results allow considering HWE for LPL marker ( p > 0.05), and FESFPS ( p > 0.01). Population substructure in our population was discarded as well as presence of either null alleles or dropout in these three markers. No statistically significant differences between our population and Caracas population were found. However, statistically significant differences were found between our population and Maracaibo population regarding allele frequencies distribution of markers TPOX and D16S539. The combined power of exclusion is 0.9999946 and the typical combined paternity index is 1,39,391. 4. Conclusion Further studies will be developed in order to know the reason of Hardy–Weinberg disequilibrium for marker TH01 in our population. Our results show that this battery of 15 markers is a powerful tool for paternity studies in the Central Region of Venezuela. We propose a joint evaluation of those Venezuelan populations which have been studied in order to develop a national data base of common markers.
305
Conflict of interest None. References [1] A. Tereba, Tools for the analysis of population statistics, Promega: Profiles DNA 2 (1999) 14. [2] M. Raymond, F. Rousset, GENEPOP (version 1.2): population genetics software for exact tests and ecumenicism, J. Hered. 86 (1995) 248. [3] P.O. Lewis , D. Zaykin, (2001). Genetic Data Analysis: Computer program for the analysis of allelic data. Version 1.0 (d16c) http://lewis.eeb.uconn.edu/lewishome/software.html. [4] J.K. Pritchard, M. Stepehns, P. Donnelly, Inference of population structure using multilocus genotype data, Genetics 155 (2000) 945 http://pritch.bsd.uchicago.edu/structure.html. [5] C. Oosterhout, B. Hutchinson, D. Wills, P. Shipley, MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data, Mol. Ecol. Notes 4 (2004) 535 www.microchecker.hull.ac.uk. [6] B. Budowle , K.L. Monson.,R. Chakraborty,Estimating minimum allele frequencies for DNA profile frequency estimates for PCR-based loci, Int. J. Legal Med. 108 (1996) 173–176 [7] M.A. Chiurillo, A. Morales, A.M. Mendes, et al., Genetic profiling of a central Venezuelan population using 15 STR markers that may be of forensic importance, Forensic Sci. Int. 136 (2003) 99. [8] L. Pineda Bernal, L. Borjas, W. Zabala, et al., Genetic variation of 15 STR autosomal loci using in the Maracaibo population from Venezuela, Forensic Sci. Int. 161 (2006) 60–63.