The aim of this study was to evaluate the applicability of Cameriere's European formula for age estimation in children in South China and to adapt the formula to establish a more suitable formula for these children. Moreover, the performance of dental age estimation based on Cameriere's method combining the developmental information of permanent teeth (PT) and third molar (TM) was also analyzed. Orthopantomographs of 720 healthy children in Group A, and orthopantomographs of 320 children and 280 subadults in Group B were assessed. The samples of Group A were divided into training dataset 1 and test dataset 1, and the samples of Group B were also divided into training dataset 2 and test dataset 2. A South China-specific formula was established based on the training dataset 1, and the comparison of accuracy between the Cameriere's European formula and the South China-specific formula was conducted with the test dataset 1. Additionally, a PT regression model, a TM regression model, and a combined regression model (PT + TM) were established based on the training dataset 2, and the performance of these three models were validated on the test dataset 2. The Cameriere's European formula underestimated chronological age with a mean difference (ME) of -0.47 +/- 1.11 years in males and -0.69 +/- 1.19 years in females. However, the South China-specific formula underestimated chronological age, with a mean difference (ME) of -0.02 +/- 0.71 years in males and -0.14 +/- 0.73 years in females. Compared with PT model and TM model, the PT and TM combined model obtained the smallest root mean square error (RMSE) of 1.29 years in males and 0.93 years in females. In conclusion, the South China-specific formula was more suitable for assessing the dental age of children in South China, and the PT and TM combined model can improve the accuracy of dental age estimation in children.

The flanking region variants of nonbinary SNPs and phenotype-informative SNPs (piSNPs) have been observed, which may greatly improve the discriminative ability after constituting microhaplotype. In this study, 30 microhaplotype loci based on the nonbinary SNPs and piSNPs (shown to be related to phenotypes such as hair and eye color) were selected. Genotyping were conducted on 100 unrelated northern Han Chinese, and the 26 populations from the 1000 Genome Project were also included for comparison of populations differentiation. The simulated study was conducted for evaluating the efficiency of kinship testing. These 30 microhaplotype loci we selected had good polymorphism, with a mean effective number of alleles (Ae) of 3.46. The average Ae increase was 1.27 compared with the target SNPs. The populations from the five regions worldwide could also be distinguished using these loci. The results of kinship testing showed that these microhaplotype loci had the similar ability as 15 STR loci of AmpFlSTRR IdentifilerR PCR Amplification Kit to identify the biological parent and a stronger ability to exclude the nonbiological parents. So, these 30 microhaplotype loci may be multifunctional for forensic application, including the ability of personal identification and kinship testing equivalent to 15 STR loci, and the power of ancestry inference for distinguishing the main intercontinental population. Moreover, our selected phenotypic microhaplotype loci may theoretically have phenotype prediction capabilities. But the phenotype prediction efficiency of these phenotypic microhaplotype loci may be worse than that of piSNPs and the detailed prediction accuracy of different populations needs to be further studied.

Paternity testing involving close relatives is facing challenges in the field of forensic genetics. Microhaplotype has been proposed as a promising genetic marker for their low mutation rates and high discrimination power recently. In this study, we selected 30 microhaplotypes from 1000 genome projects, including one non-binary SNP, and other six microhaplotypes from published studies containing only binary SNPs to established a panel of microhaplotypes for paternity testing. Most microhaplotypes generated a high effective number of alleles (A(e)) with the harmonic mean value of A(e) of 3.91 and the arithmetic mean value of heterozygosity of 0.74, respectively. We collected 54 unrelated individuals and 53 samples from six extended families. It was noting that 13 samples from six extended families were unrelated so they were also included in unrelated individuals. The pedigrees of 38 parent-child duos, 55 uncle/aunt/grandparent-child duos (non-biological parent-child duos) and 29 full sibling pairs were constructed based on 53 samples from six extended families. The genotype and haplotype results demonstrated that the combined power of discrimination (CPD) reached 0.99999999999999999999999999999999799 and the cumulative probability of exclusion (CPE) reached 0.999999999999548. The combined probability of excluding relatives (uncle/aunt/grandparent) (CPER) was 0.999999993 ( > 0.9999), indicating that our panel had good effectiveness in preventing the misinterpretation of close relatives being biological parents. For 38 parent-child duos, the CPI by using the microhaplotypes panel was higher than the one by using Goldeneye 20A kit due to higher polymorphism and more loci in our panel. For 55 non-biological parent-child duos, the CPIs by using STR loci could not help determine 9 non-biological parent-child duos as "exclusions" of paternity while the CPIs by using microhaplotype loci could not help exclude the parenthood of 4 non-biological parent-child duos (CPI > 0.0001). Using the CPI derived from both datasets of STRs and microhaplotypes, all the non-biological parent-child duos could be considered as exclusions. The efficiency of excluding close relatives for this panel was evaluated by analyzing the parameters of 2000 simulated pairs, and the effectiveness was 0.988 at the threshold of t(1) = 4 and t(2) = - 4. Moreover, the average Log(10), combined full sibling index (CFSI) for all 29 full sibling pairs was about 7.55 after physical linkage taken account. These data demonstrated that this nonbinary SNPs-based microhaplotype panel has advantages in paternity testing, especially in STR mutated or close relatives involved cases.

Microhaplotype markers have become an important research focus in forensic genetics. However, many reported microhaplotype markers have limited polymorphisms. In this study, we developed a set of highly polymorphic microhaplotype markers based on tri-allelic single-nucleotide polymorphisms. Eleven newly discovered microhaplotypes along with nine previously identified in our laboratory were studied. The microhaplotype genotypes of unrelated individuals and familial samples were generated on the MiSeq PE300 platform. These 20 loci have an average greater than 3.5 effective number of alleles. Over the whole set, the cumulative power of discrimination was 1–3.3 × 10−18, the cumulative power of exclusion was 1–1.928 × 10−7 and the theoretical probability of detecting a mixture was 1–1.427 × 10−6. Differentiation comparisons of 26 populations from the 1000 Genomes Project distinguished among East Asian, South Asian, African and European populations. Overall, these markers enrich the current microhaplotype marker databases and can be applied for individual identification, paternity testing and biogeographic ancestry distinction.

•We investigated the genetic polymorphism of 16 X-STR loci in a Han population in Central South China.•508 male blood samples were amplified using the Multiplex PCR System Goldeneye 17X Kit.•Forensic parameters were calculated to assess the forensic application values of the 16 X-STR loci.•Allelic frequencies of the 16 X-STR loci in this study with previously published populations in China were compared.

The Microreader™ 23SP ID System is a novel STR kit, but there are no Mongolian data related to this kit. In this study, allelic frequencies and forensic parameters were obtained from 505 unrelated healthy Mongolians. These samples were amplified using the kit. The dataset successfully passed quality control after being submitted to STRidER (STRidER dataset reference STR000198). A total of 264 alleles were observed, with corresponding allelic frequencies ranged from 0.001 to 0.378. The combined power of discrimination (CPD) and combined probability of exclusion (CPE) of the 22 autosomal STR loci were 0.999999999999999999999999999217318 and 0.999999999776042, respectively. Furthermore, population differentiation comparisons involving previously reported groups were conducted.

1 案 例 1.1 简要案情 某年7月,本鉴定中心受当事人孔某文的委托,受理了孔某文及其双胞胎孩子孔某萌(女)和孔某祥(男)有无血缘关系的案件.采集孔某文、孔某萌和孔某祥的血样进行STR基因座分型检测.

1 案例 1.1 简要案情 委托人熊某自述其与熊某亮为姑侄关系,因需要更改户口信息,委托本单位证明二人为非母子关系.本中心采集熊某与熊某亮的口腔拭子和血痕,因二联体亲子鉴定未能排除母子关系,本中心又补采了熊某亮亲生父亲熊某明的血痕及头发.

ABSTRACT:Objective To apply Demirjian's and Cameriere's method for dental age estimation of adolescents from Hunan Han nationality, and compare the accuracy of the two methods. Methods A total of 480 orthopantomograms of?8-16 year?old adolescents from Hunan Han nationality?with no special diseases and good nutritional status were collected?by Xiangya Stomatological Hospital of Central South University from January, 2016 to July, 2017, among them 236 males and 244 females. The dental age of each adolescent was determined by Demirjian's method and Cameriere's method, respectively, and the paired t-test of the estimated dental age and the chronological age determined by the two methods was conducted by SPSS 20.0 software to compare the difference between estimated dental age and chronological age. Results Mean chronological age of males and females was 11.91 and 11.88 years, respectively. The estimated dental age determined by Demirjian's method showed an underestimate of chronological age by an average of 0.11 years （males） and 0.15 years （females）, while the estimated dental age determined by Cameriere's method showed an underestimate of chronological age by an average of 0.83 years （males） and 0.72 years （females）. Conclusion Demirjian's method is more accurate than Cameriere's method in dental age estimation of adolescents from Hunan Han nationality, therefore more suitable for dental age estimation of adolescents in this region.

Goldeneye™ DNA ID 22NC Kit is a novel short tandem repeat (STR) genotyping system that investigate 20 non-CODIS loci (D4S2366, D6S477, D22GATA198B05, D15S659, D8S1132, D3S3045, D14S608, D17S1290, D3S1744, D2S441, D18S535, D13S325, D7S1517, D10S1435, D11S2368, D19S253, D1S1656, D7S3048, D10S148, and D5S2500), a CODIS locus (D3S1358), and a sex-determining locus amelogenin in one assay. In the present study, this STR genotyping system was validated according to the guidelines of “Validation Guidelines for DNA Analysis Methods (2016)” updated by the Scientific Working Group on DNA Analysis Methods. A series of tests, such as polymerase chain reaction-based studies, sensitivity, inhibitors, DNA mixture, species specificity, precision and accuracy evaluation, stutter percentage, and peak height ratio, was conducted. The genetic polymorphism of 21 STR loci that included in the 22NC system was also investigated in the Chinese Hunan Han population. The validation results demonstrated that Goldeneye™ DNA ID 22NC Kit is a robust and reliable identification assay as required for genotyping in kinship analysis and forensic investigation. The 21 STR loci in this kit also showed a high level of genetic polymorphism for the Hunan Han population. Therefore, it can be used for forensic applications and population studies.

1 简要案例 当事人刘某因需要了解自己与孩子之间是否有父子关系,委托我中心进行亲缘关系鉴定.本中心采集两位被鉴定人的手指尖血样进行 STR 分型检测.使用常规 Chelex-100 法提取被鉴定人血样DNA[1].在 9700 型扩增仪(美国 AB 公司)上分别采用 AGCU EX22、AGCU 21+1(无锡中德美联生物技术有限公司)、Investigator HDplex 试剂盒(德国 Qiagen 公司)对被鉴定人 DNA 样本进行扩增.使用 310 型基因分析仪(美国 AB 公司)对扩增产物进行毛细管电泳,使用 GeneMapper v3.2 软件(美国 Thermo Fisher Scientific 公司)对数据进行分析处理.结果发现同一个体在试剂盒 AGCU 21+1与 Investigator HDplex 间出现了基因座 D5S2500 和D6S474 等位基因分型结果不一致现象(表 1).为查明原因并明确被鉴定人正确的基因分型,我们重新设计了基因座 D5S2500 和 D6S474 的引物,PCR扩增后进行Sanger测序及TA克隆后进行测序分析.

The aim of this study was to compare the accuracy of the Demirjian method and the Demirjian method as revised by Willems for age estimation based on orthopantomograms from central southern Chinese Han population aged 8–16 years. Discrepancies between chronological and estimated ages were statistically evaluated by analyzing 1249 orthopantomograms from 603 girls and 646 boys. Using the Demirjian method, the mean age estimates underestimated chronological age by 0.03 years (p = 0.48) for girls and overestimated it by 0.03 years (p = 0.59) for boys; these differences with respect to chronological age were not statistically significant. In contrast, the Willems method underestimated chronological age by 0.54 years (p < 0.01) for girls and 0.44 years (p < 0.01) for boys; these differences with respect to chronological age were statistically significant. Compared to the Demirjian method, the overall mean absolute error generated using the Willems method was slightly higher (0.85 and 0.86 years, respectively). Since the Demirjian method was more accurate, we highly recommend that it should be applied when estimating dental age in the Chinese Han population. Further modifications of these two methods for populations from other regions and additional studies of other age groups are warranted.

Some representatives of flesh flies visiting/colonizing the decomposed remains demonstrated their values in estimating the minimal postmortem interval (PMImin) since death. However, the utility of sarcophagid flies has been seriously hampered by limited ecological, biological and taxonomic knowledge of them. Although mitochondrial genes have been proposed as a potential DNA barcode for the species-level identification of sarcophagids, some defects still remain such as the substantial memory and processing time taken for homologous comparisons online. Moreover, species identification is mainly achieved by Sanger sequencing based on PCR with genus-specific primers. In the present study we characterized 24 single nucleotide polymorphisms (SNPs) as robust markers of genetic variation for identifying different sarcophagids based on available cytochrome c oxidase I (COI) data and verified them through pyrosequencing (PSQ) technology to establish a SNP-based genotyping system. The system provides a preliminary foundation for developing a rapid, reliable, and high-throughput assay so as to efficiently and accurately identify the sarcophgid flies. Furthermore, the PSQ approach is proved to be faster, more cost-effective as well as more sensitive and specific than custom Sanger sequencing.