Abstract
Short tandem repeats have been essential and fundamental genetic markers used in forensic individual discrimination and paternity testing since their discovery, especially those used in the Combined DNA Index System. Nevertheless, in cases of complex kinship identification, such as full-sibling, half-sibling, and uncle–niece relationships, the combined application of additional short tandem repeat loci is necessary to reach reliable identification conclusions. In this study, we evaluated the efficiency of an updated novel short tandem repeat genotyping system for kinship identification in the Eastern Chinese Han population. This 23-plex short tandem repeat system demonstrated strong discrimination power among individuals in the target population, with a combined power of discrimination and cumulative probability of exclusion of 1–2.107 1 × 10−27 and 0.999 999 999 800, respectively. When 74 short tandem repeats were used and the threshold log10(likelihood ratio) was set to 4, the system efficiency reached 0.999 9 and 0.707 3 for simulated full-sibling and half-sibling pairs, respectively. Furthermore, in two real secondary kinship identification cases, incorporation of the novel 23-plex short tandem repeat system increased the probabilities of the prior kinship hypotheses from 154.259 5 and 1 031.699 5 to 56 597.118 4 and 134 829.791 5, respectively, yielding reliable identification conclusions. Hence, it is evident that the novel 23-plex short tandem repeat system has notable potential as a tool for forensic kinship identification in the Eastern Chinese Han population and could serve as a complementary set of short tandem repeat loci for the identification of distant kinship.
Keywords: forensic sciences, forensic genetics, short tandem repeat, full-sibling identification, half-sibling identification, case report
Introduction
Short tandem repeat (STR) genetic markers have played an important role in forensic individual identification and paternity testing, owing to their high degree of polymorphism, and have provided key evidence during numerous case investigations. The Combined DNA Index System (CODIS) was the first STR system established to enable the off-site query and search of criminal DNA. Subsequently, to further improve the identification capability, the CODIS core loci working group constituted a new CODIS core STR system after adding six autosomal STRs (A-STRs) and eliminating the TPOX locus. Currently, most commercial STR typing kits used for individual identification are based on the new CODIS core STR system [1–3]. However, relying solely on these CODIS core STR loci often proves inadequate for definitively identifying mutant genotypes and complex kinships (e.g., full- and half-sibling relationships).
Increasing the number of STR loci is an effective method for identifying kinship when mutational events between the parent and offspring prevent multiple STR loci from conforming to the inheritance pattern. This approach is also useful in parentage testing when inbreeding interference is present [4]. The accuracy of complex kinship identification can be improved by including additional reference individuals, detecting more STR loci, and incorporating other genetic markers such as mitochondrial DNA (mtDNA), Y chromosomal STRs (Y-STRs), and X chromosomal STRs (X-STRs) [5–7]. Among these methods, detecting additional STRs is the most efficient and widely used approach in current forensic practice. Several commercial STR typing kits have been developed for this purpose, such as DNATyper 25 [8], the Microreader™ 23sp ID system [9], the AGCU 21 + 1 STR polymerase chain reaction (PCR) amplification kit [10], and the Microreader™ 23HS plex ID system [11].
Adequate investigation of STR polymorphisms is a fundamental prerequisite for the application of STR loci for individual discrimination and kinship identification. Previous studies have suggested that slight differences in the polymorphisms of the same STR loci in different populations occur due to differences in genetic structure [12–15]. Furthermore, in a population settled in disparate regions, differences in the observed alleles and allele frequencies at the same STR locus occur due to the influence of genetic mutations and genetic cross-fertilization resulting from intermarriages with other populations in geographic proximity [12, 15]. Therefore, it is imperative to conduct population genetics investigations of STR loci in the target population prior to using those STR loci in forensic practice in order to guarantee the accuracy of the results during the evidential power assessment.
The Microreader™ 23spB ID system applied in this study is an updated version of the Microreader™ 23sp ID system, including three CODIS STR loci and 19 non-CODIS STR loci. In previous studies, the 19 non-CODIS STR loci exhibited a high degree of polymorphism in the Guanzhong Han [16], Mongolian [17], Southern Han [18], and Northwestern Hui [19] populations. This study is the first to assess the updated STR detection system. The genetic polymorphisms of the 22 STR loci included in the system were thoroughly evaluated in the Eastern Chinese Han population, based on 500 unrelated individuals. In addition, based on the requirements for the number of STR loci in full-sibling and half-sibling testing practices, the identification work was based on four different combinations: 21 STRs (SiFaSTR™ 23plex kit), 40 STRs (SiFaSTR™ 23plex kit and AGCU 21 + 1 STR PCR amplification kit), 56 STRs (SiFaSTR™ 23plex kit, AGCU 21 + 1 STR PCR amplification kit, and Microreader™ 23HS plex ID system) and 74 STRs (SiFaSTR™ 23plex kit, AGCU 21 + 1 STR PCR amplification kit, Microreader™ 23HS plex ID system and Microreader™ 23spB ID system). Finally, the effectiveness of the supplementary STR loci in this novel system for identifying target kinship was evaluated through two real secondary kinship identification cases.
Materials and methods
Sample collection
Fingertip blood samples were collected from 500 unrelated individuals of Eastern Chinese Han descent and stored on FTA cards. All volunteers were informed in advance about the sample use and research purpose and were asked to sign informed consent forms at the time of sample collection. Additionally, four fingertip blood samples were collected from individuals involved in two real forensic identification cases. One pair was an alleged half-sibling pair (Case 1), and the other was an alleged uncle–niece relationship (Case 2). This study was approved by the Ethics Committee of the Academy of Forensic Science, Ministry of Justice, People’s Republic of China (approval number: 2023-1).
STR amplification and genotyping
All of the unrelated individual samples were analyzed using the Microreader™ 23spB ID system (Suzhou Microread Genetics, Suzhou, China) [9]. The system contains three CODIS STRs (D12S391, D1S1656, and D2S441), 19 non-CODIS STRs (D10S1435, D11S2368, D13S325, D14S608, D15S659, D17S1290, D18S535, D19S253, D20S470, D20S478, D21S1270, D22-GATA198B05, D3S3045, D4S2366, D5S2500, D6S477, D7S3048, D8S1132, and D9S925), and one sex determination locus (amelogenin). PCR amplification was performed using the ProFlex™ PCR system (Thermo Fisher Scientific, Waltham, MA, USA). Four case samples were amplified by using the SiFaSTR™ 23plex kit, AGCU 21 + 1 STR PCR amplification kit, Microreader™ 23HS plex ID system, and Microreader™ 23spB ID system simultaneously. The PCR amplicons were separated on the 3500xL Genetic Analyzer (Thermo Fisher Scientific). Fragment sizes and genotypes were analyzed using GeneMapper ID-X software v1.5 (Thermo Fisher Scientific).
Hardy–Weinberg equilibrium and linkage disequilibrium tests
Allele frequencies and forensic parameters, including genetic diversity (GD), polymorphism information content (PIC), probability of match (PM), power of discrimination (PD), observed heterozygosity (Hobs), power of exclusion (PE), and typical paternity index (TPI), of the 22 STR loci were calculated using the STR Analysis for Forensics (STRAF) 2.1.5 online tool [20]. In addition, STR loci and corresponding frequencies from the SiFaSTR™ 23plex kit [21], AGCU 21 + 1 STR PCR amplification kit [10], and Microreader™ 23HS plex ID system [11] were used; relevant frequency data were collected from previous studies [22, 23]. The Hardy–Weinberg equilibrium (HWE) and linkage disequilibrium (LD) in the Eastern Chinese Han population were estimated using Arlequin v3.5 [24], based on the allele genotypes from previous studies.
Simulation test
In order to thoroughly evaluate the identification efficiency of the 22-STR system when applied to full- and half-sibling kinships, 10 000 full-sibling pairs, 10 000 half-sibling pairs, and 10 000 unrelated individual pairs were simulated, using the R language (https://www.r-project.org). The simulated data for full-sibling and half-sibling relationships were obtained based on family reconstructions. Allele frequency data for the STR loci used in the simulations were obtained from previous studies [10, 22, 23], except for the 22 STR loci used in this study.
Evaluation of the effectiveness of kinship testing
The likelihood ratio method was applied for full-sibling, half-sibling, and uncle–niece relationship determination. The likelihood ratio values for the three types of relationships are described in terms of the full-sibling index (FSI), half-sibling index (HSI), and avuncular index (AI), respectively. Taking full-sibling identification as an example, the FSI equals the probability that two individuals are full siblings divided by the probability that the two individuals are unrelated. The cumulative FSI (CFSI), cumulative HSI (CHSI), and cumulative AI (CAI) were obtained by multiplying the values from different loci. The accuracy, sensitivity, specificity, effectiveness, positive predictive value (PPV), and negative predictive value (NPV) of four different STR combinations for identifying full-sibling and half-sibling relationships were calculated in the simulated lineage analyses, with thresholds [log10(likelihood ratio)] set at 1, 2, 3, and 4, respectively. The formulas used for these calculations are as follows:
Accuracy = (true positive pairs + true negative pairs)/(true positive pairs + false negative pairs + false positive pairs + true negative pairs).
Sensitivity = true positive pairs/(true positive pairs + false negative pairs).
Specificity = true negative pairs/(true negative pairs + false positive pairs).
Effectiveness = (true positive pairs + true negative pairs)/all pairs.
PPV = true positive pairs/(true positive pairs + false positive pairs).
NPV = true negative pairs/(true negative pairs + false negative pairs).
Results and discussions
We calculated the allele frequencies of the 22 STRs in the Eastern Chinese Han population and meticulously evaluated the efficacy of different numbers of STRs for the identification of full- and half-sibling pairs.
Allele frequency
The 22 STRs had a total of 252 alleles in the Eastern Chinese Han population. The number of alleles at different loci ranged from 7 (D4S2366) to 15 (D1S1656 and D21S1270). The average allele frequency was 0.087 3, with a minimum value of 0.001 and a maximum value of 0.403 0. The frequency of different alleles per locus is presented in Figure 1 and Supplementary Table S1. Using the same system, 247, 264, 237, and 246 alleles were observed in the Guanzhong Han, Mongolian, Southern Han, and Northwestern Hui populations, respectively [16–19]. The differences in the observed allele numbers and allele frequencies among the different populations supported the hypothesis that differences in genetic polymorphisms exist among different groups. This underscores the importance of selecting the allele frequency data of the target individual’s population when conducting forensic individual identification and kinship identification to ensure an accurate quantitative assessment of evidence strength.
Figure 1.
Allele distributions and frequencies of the 22 STRs in the Eastern Chinese Han population (A). Chromosomal locations of 74 autosomal STR loci (B). The “Low” and “High” labels on chromosomes indicate relative gene density levels.
Hardy–Weinberg equilibrium and linkage disequilibrium tests
The P-values of the HWE tests for the 22 STR loci in the Eastern Chinese Han population were calculated and are shown in Supplementary Table S2 (column B). After a Bonferroni correction (P < 0.002 3), all of the STR loci were found to be in accordance with HWE in the Eastern Chinese Han population. No LD was found for any pairs of loci after the Bonferroni correction (P < 0.000 1), except for the combination of the D14S608 and D15S659 loci, which are located on two different chromosomes. This confirms that when more STRs are needed for distant kinship identification, the STR loci in these combinations can be used directly in the calculation of kinship indices, using the law of products. The P-values of the LD tests of the 22 STRs are shown in Supplementary Table S3.
Forensic parameters
The forensic efficacy of the 22 STR loci in the Eastern Chinese Han population was evaluated using seven forensic parameters, namely, GD, PIC, PM, PD, Hobs, PE, and TPI. The results are summarized in Supplementary Table S2. The average GD value of the 22 STRs was 0.810 7, with a maximum value of 0.875 9 at D20S470 and a minimum value of 0.729 8 at D4S2366. The mean Hobs value was 0.813 9, with a maximum value of 0.904 0 at D7S3048 and a minimum value of 0.704 0 at D4S2366. The average PD value was 0.935 6, with a maximum value of 0.969 3 at D20S470 and a minimum value of 0.892 6 at D4S2366. These values are in full compliance with the most recent national standards for PD values of the STR locus for full-sibling identification. The PIC values of the 22 loci ranged from 0.689 3 (D4S2366) to 0.862 0 (D20S470), with an average of 0.784 5. The PM, PE, and TPI values ranged from 0.030 7 to 0.107 4, 0.434 5 to 0.803 6, and 1.689 2 to 5.208 3, respectively. The combined PD (CPD) and cumulative PE (CPE) values were 1–2.107 1 × 10−27 and 0.999 999 999 800, respectively.
The efficiency of the 22-STR system varied slightly when the system was used for individual identification in other populations in China. The CPD and CPE values of the Guanzhong Han, Mongolian, Southern Han, and Northwest Hui populations were 1–6.536 4 × 10−28 and 0.999 999 999 709 740 [16], 1–7.826 8 × 10−28 and 0.999 999 999 776 042 [17], 1–2.497 9 × 10−28 and 0.999 999 999 890 [18], and 1–5.732 3 × 10−28 and 0.999 999 999 860 491 [19], respectively. The series of studies confirmed that the 22-STR system showed superior individual identification efficacy in several Chinese populations, with no significant differences in the CPD and CPE values. The results suggested that, in forensic practice, if there are no published reference allele frequency data for the target individual, the frequency data of other geographically closed populations could be used to assess evidential power without affecting the scientific rationality of the conclusion.
Efficiency of full-sibling testing
Based on the inheritance laws of segregation and independent assortment, STR typing data of 10 000 full-sibling pairs and 10 000 unrelated pairs were simulated by applying the frequencies from previous studies. The locational distribution of the 74 unduplicated STR loci contained in the four STR panels applied in this study on the 22 chromosomes is shown in Figure 1B. The density plot and box plot of the distributions of log10(CFSI) values for different STR combinations are shown in Figure 2. The median log10(CFSI) values for the 21, 40, 56, and 74 STR combinations under the a priori assumption of full siblings were 6.080 9 (SD = 2.587 8), 9.986 6 (SD = 3.308 2), 14.669 8 (SD = 3.976 8), and 20.160 9 (SD = 4.627 6) among simulated full-sibling pairs; the corresponding values for unrelated pairs were −4.850 8 (SD = 1.776 8), −8.204 7 (SD = 2.336 7), −11.917 7 (SD = 2.826 2), and −16.156 4 (SD = 3.284 1), respectively.
Figure 2.
Density plots and box plots of log10(CFSI) values of 10 000 simulated full-sibling pairs and 10 000 unrelated individual pairs under different short tandem repeat (STR) combinations. CFSI: cumulative full-sibling index; UR: unrelated individual; FS: full-sibling.
We evaluated the efficiencies of different STR combinations for full-sibling identification under four different CFSI thresholds (10, 100, 1 000, and 10 000). The accuracy, sensitivity, specificity, effectiveness, PPV, and NPV values of different STR combinations at log10(CFSI) thresholds of 1, 2, 3, and 4 are shown in Supplementary Table S4. The system’s efficiency for full-sibling identification using 21, 40, 56, and 74 STRs was 0.740 2, 0.965 1, 0.996 8, and 0.999 9, respectively, at a log10(CFSI) threshold of 4. As the number of STRs increased, there was a notable increase in the system efficiency for full-sibling identification. For the same STR combination, as the log10(CFSI) threshold increased, the efficacy of the system for full-sibling identification decreased, but the accuracy and sensitivity increased. These observations align with findings from prior studies [5–7, 25, 26].
Efficiency of half-sibling testing
Density plots and box plots of the log10(CHSI) values of 10 000 simulated half-sibling pairs and 10 000 unrelated pairs analyzed using different STR combinations with the a priori assumption of half-sibling relationship pairs and unrelated pairs are shown in Figure 3. For the 21-, 40-, 56-, and 74-STR systems, overlaps of 10.03%, 4.76%, 2.01%, and 0.77% between the density curves of half-sibling pairs and unrelated pairs were observed, respectively. The median log10(CHSI) values of the four STR combinations among the 10 000 simulated half-sibling pairs were 1.639 1 (SD = 1.317 5), 2.668 2 (SD = 1.678 6), 3.956 3 (SD = 2.026 1), and 5.428 7 (SD = 2.368 8), and the corresponding median log10(CHSI) values among unrelated pairs were − 1.537 7 (SD = 1.070 0), −2.480 4 (SD = 1.381 9), −3.638 3 (SD = 1.665 5), and − 4.904 0 (SD = 1.934 8), respectively. The accuracy, sensitivity, specificity, effectiveness, PPV, and NPV of the different STR combinations for half-sibling identification at the log10(CFSI) thresholds of 1, 2, 3, and 4 are shown in Supplementary Table S5. The efficiency for half-sibling identification at a log10(CHSI) threshold of 4 was 0.025 7, 0.175 5, 0.453 3, and 0.707 3 for the combinations of 21, 40, 56, and 74 STRs, respectively, with accuracy, sensitivity, specificity, PPV, and NPV values almost at 100% [except the accuracy (0.999 9), specificity (0.999 8) and PPV (0.999 8) for the combination of 56 STRs]. The results suggested that the 22 STR loci introduced in this study could serve as optimal genetic markers for complementing and enhancing the efficacy of half-sibling testing.
Figure 3.
Density plots and box plots of log10(CHSI) values of 10 000 simulated half-sibling pairs and 10 000 unrelated individual pairs under different short tandem repeat (STR) combinations. CHSI: cumulative half-sibling index; UR: unrelated individual; HS: half-sibling.
Case reports of two secondary-kinship identifications
To verify the efficacy of the system in kinship identification practice, the novel updated system, combined with three other commercial STR panels, was used in two real secondary kinship identification cases: an alleged half-sibling relationship and an alleged uncle–niece relationship. The genotypes, HSI values, and AI values of 74 STRs for each relationship are shown in Tables 1 and 2. Additionally, the CHSI and CAI values of 21, 40, 56, and 74 STRs for the two relationships are shown in Figure 4. The genotypes of the overlapped loci (D12S391, D1S1656, D2S441, and D10S1435) between different panels in the same sample were consistent. In Case 1, the CHSI values were 4.04, 63.56, and 154.259 5 when 21, 40, and 56 STRs were used, respectively, as three commonly used commercial STR kits were gradually added. These values fall between the CHSI threshold of 10 000, indicative of a half-sibling relationship, and the CHSI threshold of 0.000 1, indicative of an unrelated relationship [26], making it impossible to draw an identification conclusion. After introducing the novel updated STR panel, a marked enhancement was observed, as the CHSI value reached 56 597.118 4. Based on this result, it could be reasonably concluded that these two individuals are half-siblings. In Case 2, the CAI values increased from 12.93, 183.80, and 1 031.699 5 to 134 829.791 5 after adding nonoverlapped STRs of the studied system to the 21, 40, 56, and 74 STRs. In these two real secondary kinship identification cases, the novel system’s advantages and robust capabilities were validated. The system considerably enhanced the strength of evidence and allowed a definite identification conclusion to be reached.
Table 1.
Genotypes and half-sibling indexes (HSIs) for 74 STRs in Case 1.
| Loci | Half-sibling sister | Half-sibling brother | HSI | Loci | Half-sibling sister 1 | Half-sibling sister 2 | HSI |
|---|---|---|---|---|---|---|---|
| D19S433 | 14.2, 15.2 | 15.2, 16.2 | 1.254 8 | D1GATA113 | 7, 11 | 12, 12 | 0.500 0 |
| D5S818 | 11, 12 | 11, 12 | 1.407 5 | D5S2800 | 14, 14 | 17, 18 | 0.500 0 |
| D21S11 | 30, 31 | 31, 32.2 | 1.756 3 | D10S2325 | 11, 12 | 11, 13 | 1.432 8 |
| D18S51 | 15, 17 | 14, 15 | 1.230 1 | D13S305 | 18, 19 | 18, 19 | 1.592 6 |
| D6S1043 | 11, 19 | 10, 19 | 1.327 8 | D16S3391 | 10, 14 | 10, 15 | 1.194 4 |
| D13S317 | 8, 12 | 11, 12 | 1.285 2 | D18S1364 | 14, 19 | 13, 18 | 0.500 0 |
| D3S1358 | 16, 18 | 17, 17 | 0.500 0 | D19S400 | 11, 13 | 11, 13 | 2.761 8 |
| D16S539 | 9, 10 | 9, 9 | 1.380 3 | D1S2142 | 16, 17 | 12, 15 | 0.500 0 |
| CSF1PO | 10, 12 | 11, 13 | 0.500 0 | D1S549 | 13, 16 | 12, 14 | 0.500 0 |
| vWA | 16, 19 | 17, 17 | 0.500 0 | D20S161 | 16, 16 | 16, 18 | 1.504 0 |
| D8S1179 | 10, 13 | 12, 13 | 1.062 8 | D20S85 | 7, 12 | 7, 7 | 1.190 6 |
| Penta E | 11, 14 | 11, 16 | 1.141 7 | D21S2055 | 19, 19 | 10.1, 24 | 0.500 0 |
| TH01 | 9, 9 | 6, 9 | 0.979 4 | D2S1360 | 22, 23 | 22, 22 | 0.937 8 |
| D12S391 | 18, 20 | 18, 18 | 1.815 1 | D3S1545 | 11, 12 | 12, 13 | 0.851 1 |
| FGA | 24, 25 | 23, 23 | 0.500 0 | D3S1744 | 14, 17 | 17, 18 | 0.899 4 |
| D10S1248 | 14, 16 | 13, 14 | 1.046 1 | D3S2459 | 12, 12 | 12, 12 | 2.285 7 |
| D1S1656 | 11, 15 | 13, 15 | 0.898 1 | D7S1517 | 19, 23 | 21, 23 | 1.333 3 |
| D7S820 | 9, 9 | 9, 10 | 4.474 6 | D9S2157 | 13, 16 | 13, 13 | 1.317 0 |
| Penta D | 9, 9 | 9, 12 | 1.185 5 | CHSI (56 STRs) | 154.259 5 | ||
| TPOX | 8, 11 | 11, 11 | 1.337 0 | D11S2368 | 17, 22 | 17, 22 | 2.683 8 |
| D2S1338 | 18, 19 | 23, 25 | 0.500 0 | D13S325 | 20, 22 | 18, 22 | 1.461 5 |
| D6S474 | 14, 15 | 14, 15 | 1.212 2 | D14S608 | 7, 11 | 11, 12 | 1.125 0 |
| D3S4529 | 13, 16 | 15, 16 | 1.315 9 | D15S659 | 13, 16 | 13, 14 | 1.063 1 |
| D18S853 | 11, 11 | 11, 11 | 1.716 2 | D17S1290 | 17, 19 | 17, 19 | 3.631 3 |
| D12ATA63 | 16, 17 | 17, 17 | 1.321 3 | D18S535 | 9, 14 | 9, 16 | 1.202 2 |
| D2S441 | 10, 10 | 10, 11 | 1.793 3 | D19S253 | 10, 11 | 11, 13 | 1.461 5 |
| D20S482 | 13, 14 | 14, 14 | 1.108 3 | D20S470 | 15, 17 | 13, 17 | 1.762 6 |
| D22S1045 | 15, 15 | 15, 16 | 1.561 1 | D20S478 | 13, 15 | 15, 16 | 0.990 2 |
| D6S1017 | 13, 13 | 12, 13 | 3.541 4 | D21S1270 | 10, 14 | 11, 14 | 0.944 8 |
| D14S1434 | 13, 14 | 11, 14 | 0.780 0 | D22GATA198B05 | 16, 20 | 16, 22 | 2.144 7 |
| D4S2408 | 10, 10 | 9, 10 | 1.245 2 | D3S3045 | 9, 14 | 9, 13 | 0.876 5 |
| D9S1122 | 11, 12 | 10, 11 | 1.203 0 | D4S2366 | 9, 14 | 11, 14 | 2.453 1 |
| D1S1677 | 15, 15 | 14, 14 | 0.500 0 | D5S2500 | 15, 15 | 11, 13 | 0.500 0 |
| D2S1776 | 9, 11 | 9, 11 | 1.816 0 | D6S477 | 13, 14 | 14, 14 | 1.795 3 |
| D11S4463 | 14, 15 | 14, 15 | 1.318 1 | D7S3048 | 22, 23 | 20, 22 | 2.166 7 |
| D17S1301 | 11, 13 | 11, 12 | 1.281 3 | D8S1132 | 19, 21 | 20, 23 | 0.500 0 |
| D10S1435 | 11, 13 | 10, 12 | 0.500 0 | D9S925 | 15, 17 | 15, 17 | 1.657 4 |
| D1S1627 | 12, 13 | 12, 13 | 1.768 7 | CHSI (74 STRs) | 56 597.118 4 |
CHSI: cumulative half-sibling index. Bold formatting in the table indicates the 18 non-overlapping STR loci additionally included in the novel STR panel of this study.
Table 2.
Genotypes and avuncular indexes (AIs) for 74 STRs in Case 2.
| Loci | Niece | Uncle | AI | Loci | Niece | Uncle | AI |
|---|---|---|---|---|---|---|---|
| D19S433 | 13, 13 | 14, 14.2 | 0.500 0 | D1GATA113 | 7, 11 | 7, 7 | 1.013 7 |
| D5S818 | 10, 11 | 10, 11 | 1.540 7 | D5S2800 | 14, 18 | 14, 18 | 1.337 9 |
| D21S11 | 32.2, 32.2 | 30, 32.2 | 2.506 4 | D10S2325 | 12, 13 | 12, 13 | 2.392 6 |
| D18S51 | 14, 18 | 17, 20 | 0.500 0 | D13S305 | 19, 20 | 18, 20 | 1.469 0 |
| D6S1043 | 12, 18 | 13, 14 | 0.500 0 | D16S3391 | 10, 13 | 10, 12 | 1.194 4 |
| D13S317 | 8, 12 | 8, 12 | 1.720 1 | D18S1364 | 15, 16 | 16, 17 | 1.151 0 |
| D3S1358 | 15, 16 | 16, 17 | 0.881 4 | D19S400 | 11, 12 | 8, 13 | 0.500 0 |
| D16S539 | 9, 12 | 9, 9 | 1.380 3 | D1S2142 | 14, 15 | 12, 15 | 1.161 4 |
| CSF1PO | 12, 12 | 8, 11 | 0.500 0 | D1S549 | 14, 15 | 12, 15 | 0.848 2 |
| vWA | 14, 19 | 17, 19 | 1.818 6 | D20S161 | 17, 18 | 18, 21 | 1.362 1 |
| D8S1179 | 12, 16 | 10, 12 | 1.471 3 | D20S85 | 7, 7 | 7, 11 | 1.190 6 |
| Penta E | 5, 10 | 15, 18 | 0.500 0 | D21S2055 | 9.1, 20 | 9.1, 26 | 1.596 5 |
| TH01 | 7, 9 | 7, 7 | 1.438 4 | D2S1360 | 22, 25 | 21, 23 | 0.500 0 |
| D12S391 | 18, 19 | 18, 21 | 1.157 5 | D3S1545 | 11, 11 | 11, 12 | 1.641 6 |
| FGA | 21, 22 | 22, 22 | 1.839 8 | D3S1744 | 13, 19 | 13, 19 | 8.877 5 |
| D10S1248 | 13, 14 | 13, 13 | 1.181 8 | D3S2459 | 8, 15 | 14, 14.1 | 0.500 0 |
| D1S1656 | 15, 15 | 15, 15 | 2.092 4 | D7S1517 | 19, 24 | 22, 23 | 0.500 0 |
| D7S820 | 8, 10 | 8, 11 | 1.404 5 | D9S2157 | 14, 15 | 12, 13 | 0.500 0 |
| Penta D | 9, 9 | 9, 12 | 1.185 5 | CAI (56 STRs) | 1 031.6995 | ||
| TPOX | 11, 11 | 8, 11 | 1.337 0 | D11S2368 | 18, 18 | 17, 19 | 0.500 0 |
| D2S1338 | 19, 25 | 19, 21 | 1.134 8 | D13S325 | 20, 21 | 20, 20 | 1.439 8 |
| D6S474 | 14, 16 | 14, 18 | 0.860 6 | D14S608 | 7, 10 | 7, 7 | 1.696 2 |
| D3S4529 | 14, 15 | 15, 16 | 0.838 9 | D15S659 | 13, 14 | 18, 18 | 0.500 0 |
| D18S853 | 13, 13 | 11, 13 | 1.561 1 | D17S1290 | 16, 17 | 11, 15 | 0.500 0 |
| D12ATA63 | 16, 17 | 12, 17 | 0.910 6 | D18S535 | 12, 15 | 12, 13 | 1.788 7 |
| D2S441 | 10, 11 | 10, 12 | 1.146 7 | D19S253 | 9, 14 | 9, 11 | 21.333 3 |
| D20S482 | 14, 14 | 13, 13 | 0.500 0 | D20S470 | 16, 19 | 12, 19 | 8.312 5 |
| D22S1045 | 11, 16 | 15, 16 | 0.946 4 | D20S478 | 14, 15 | 14, 15 | 1.418 3 |
| D6S1017 | 10, 12 | 10, 13 | 0.797 6 | D21S1270 | 14, 15 | 10, 10 | 0.500 0 |
| D14S1434 | 14, 14 | 14, 14 | 1.619 8 | D22GATA198B05 | 21, 21 | 18, 21 | 1.311 7 |
| D4S2408 | 10, 11 | 9, 10 | 0.872 6 | D3S3045 | 9, 15 | 9, 12 | 0.876 5 |
| D9S1122 | 11, 11 | 11, 12 | 1.906 1 | D4S2366 | 9, 11 | 11, 12 | 0.810 2 |
| D1S1677 | 15, 16 | 14, 16 | 2.314 2 | D5S2500 | 11, 16 | 12, 15 | 0.500 0 |
| D2S1776 | 12, 13 | 12, 13 | 1.840 7 | D6S477 | 13, 15 | 13, 14 | 1.118 8 |
| D11S4463 | 15, 16 | 14, 17 | 0.500 0 | D7S3048 | 24, 24 | 20, 24 | 2.082 3 |
| D17S1301 | 11, 11 | 11, 12 | 2.062 5 | D8S1132 | 19, 22 | 19, 19 | 1.626 1 |
| D10S1435 | 11, 12 | 12, 12 | 1.235 3 | D9S925 | 15, 17 | 15, 16 | 1.078 7 |
| D1S1627 | 13, 14 | 14, 14 | 1.614 1 | CAI (74 STRs) | 134 829.791 5 |
CAI: cumulative avuncular index. Bold formatting in the table indicates the 18 non-overlapping STR loci additionally included in the novel STR panel of this study.
Figure 4.
Cumulative half-sibling index (CHSI) and cumulative avuncular index (CAI) values under different STR combinations in two real cases.
Conclusion
In this study, we investigated the genetic polymorphisms of 22 A-STR loci in a newly updated STR system in an Eastern Chinese Han population of 500 unrelated individuals. The results demonstrated that the 22 STR loci were highly polymorphic, with a total of 252 alleles observed and an average PD value of 0.935 6. This system demonstrated significant efficiency in individual identification, with a CPD and CPE of 1–2.107 1 × 10−27 and 0.999 999 999 800, respectively, in the Eastern Chinese Han population. Analysis using simulated pedigree samples verified that the additional 19 highly polymorphic non-CODIS STR loci included in the system were an important source of supplementary genetic markers for full-sibling and half-sibling identification within the Eastern Chinese Han population. Furthermore, in the two real secondary kinship identification cases, the incorporation of the 18 supplementary non-CODIS STRs included in the novel STR panel significantly strengthened the evidence supporting the alleged kinship, as the cumulative kinship indexes were increased by hundreds of times.
Supplementary Material
Contributor Information
Man Chen, Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, Shanghai, China.
Fan Yang, Key Laboratory of Forensic Evidence and Science Technology, Ministry of Public Security, Institute of Forensic Science, Shanghai, China.
Zhixiao Gao, Suzhou Microread Genetics, Suzhou, China.
Weifen Sun, Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, Shanghai, China.
Xufeng Chu, Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, Shanghai, China.
Hui Li, Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, Shanghai, China.
Lei Jiang, Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, Shanghai, China.
Xiling Liu, Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, Shanghai, China.
Authors’ contributions
Man Chen conducted the experiments, analyzed the data, and drafted the initial manuscript. Fan Yang analyzed the data and revised the manuscript. Zhixiao Gao conducted the experiments and revised the manuscript. Weifen Sun analyzed the data and drew the figures. Xufeng Chu drew the figures. Hui Li verified the data. Lei Jiang verified the data. Xiling Liu accessed the funding, conceived the study, designed the research framework, and revised the manuscript. All authors contributed to the final text and approved it.
Compliance with ethical standards
This study was approved by the Ethics Committee of the Academy of Forensic Science, Ministry of Justice, People’s Republic of China (approval number: 2023-1). All volunteers were informed in advance about the sample use, research purpose and the intention to publish the results in a scientific journal. Written informed consent was obtained from all individuals prior to their participation.
Disclosure statement
None declared.
Funding
This project was supported by grants from the National Key Research and Development Program of China [grant number 2022YFC3302004] and the Science and Technology Commission of Shanghai Municipality [grant number 23DZ2202300].
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