Methods and Research Hotspots of Forensic Kinship Testing / 法医学杂志

Kinship testing is widely needed in forensic science practice. This paper reviews the definitions of common concepts, and summarizes the basic principles, advantages and disadvantages, and application scope of kinship analysis methods, including identity by state (IBS) method, likelihood ratio (LR) method, method of moment (MoM), and identity by descent (IBD) segment method. This paper also discusses the research hotspots of challenging kinship testing, complex kinship testing, forensic genetic genealogy analysis, and non-human biological samples.

Identification Strategy of Biological Half Sibling Relationship / 法医学杂志

OBJECTIVES@#To compare the application value of the likelihood ratio (LR) method and identity by state (IBS) method in the identification involving half sibling relationships, and to provide a reference for the setting of relevant standards for identification of half sibling relationship.@*METHODS@#(1) Based on the same genetic marker combinations, the reliability of computer simulation method was verified by comparing the distributions of cumulated identity by state score (CIBS) and combined full sibling index in actual cases with the distributions in simulated cases. (2) In different numbers of three genetic marker combinations, the simulation of full sibling, half sibling and unrelated individual pairs, each 1 million pairs, was obtained; the CIBS, as well as the corresponding types of cumulative LR parameters, were calculated. (3) The application value of LR method was compared with that of IBS method, by comparing the best system efficiency provided by LR method and IBS method when genetic markers in different amounts and of different types and accuracy were applied to distinguish the above three relational individual pairs. (4) According to the existing simulation data, the minimum number of genetic markers required to distinguish half siblings from the other two relationships using different types of genetic markers was estimated by curve fitting.@*RESULTS@#(1) After the rank sum test, under the premise that the real relationship and the genetic marker combination tested were the same, there was no significant difference between the simulation method and the results obtained in the actual case. (2) In most cases, under the same conditions, the system effectiveness obtained by LR method was greater than that by IBS method. (3) According to the existing data, the number of genetic markers required for full-half siblings and half sibling identification could be obtained by curve fitting when the system effectiveness reached 0.95 or 0.99.@*CONCLUSIONS@#When distinguishing half sibling from full sibling pairs or unrelated pairs, it is recommended to give preference to the LR method, and estimate the required number of markers according to the identification types and the population data, to ensure the identification effect.

Calculation of the Probability Distribution of CIBS Score in Different Relationships and Its Application / 法医学杂志

Objective To derive the probability distribution formula of combined identity by state （CIBS） score among individuals with different relationships based on population data of autosomal multiallelic genetic markers. Methods The probabilities of different identity by state （IBS） scores occurring at a single locus between two individuals with different relationships were derived based on the principle of ITO method. Then the distribution probability formula of CIBS score between two individuals with different relationships when a certain number of genetic markers were used for relationship identification was derived based on the multinomial distribution theory. The formula was compared with the CIBS probability distribution formula based on binomial distribution theory. Results Between individuals with a certain relationship, labelled as RS, the probabilities of IBS=2, 1 and 0 occurring at a certain autosomal genetic marker x （that is, p2（RSx）, p1（RSx） and p0（RSx））, can be calculated based on the allele frequency data of that genetic marker and the probability of two individuals with the corresponding RS relationship sharing 0, 1 or 2 identity by descent （IBD） alleles （that is, φ0, φ1 and φ2）. For a genotyping system with multiple independent genetic markers, the distribution of CIBS score between pairs of individuals with relationships other than parent-child can be deducted using the averages of the 3 probabilities of all genetic markers （that is, p2（RS）, p1（RS） and p0（RS））, based on multinomial distribution theory. Conclusion The calculation of CIBS score distribution formula can be extended to all kinships and has great application value in case interpretation and system effectiveness evaluation. In most situations, the results based on binomial distribution formula are similar to those based on the formula derived in this study, thus, there is little difference between the two methods in actual work.

Formula Derivation for the Probability Distribution of IBS Score in Unrelated Individual Pairs / 法医学杂志

@#Objective To derive the general equation of the probability distribution of identity by state （IBS） score among biological full sibling pairs by calculating STR allele frequency. Methods Based on the Mendelian genetics law and the hypothesis that parents of biological full siblings（FS） were unrelated individuals, the IBS score and corresponding probability of different genotype combinations in the offspring when unrelated individuals of different genotype combinations give birth to two offsprings were derived. Results Given fi （i=1, 2, …, m） as the frequency of the ith allele of a STR locus, the probability of sharing 2 alleles（p2FS）, 1 allele（p1FS） or 0 allele （p0FS） with biological full sibling pairs on the locus can be respectively expressed as follows： p2FS= 14 ×[1 + 2∑im= 1 fi2 + 2（∑im= 1 fi2）2 -∑im= 1 fi4] , p1FS= 12 ×[1 +∑im= 1 fi2 - 2（∑im= 1 fi2）2 - 2∑im= 1 fi3 + 2∑im= 1 fi4] and p0FS= 14 ×[1 - 4∑im= 1 fi2 + 2（∑im= 1 fi2）2 + 4∑im= 1 fi3 -3∑im= 1 fi4] . The sum of p2FS, p1FS and p0FS must be 1. As for the multiple genotyping system that contained n STR loci, IBS scores between biological full sibling pairs conform to binomial distribution：IBS~B（2n, π1）. The population rate π1, can be given by the formula：π1= 1n∑ln= 1 p2FSl + 21n∑ln= 1 p1FSl . Conclusion The alternative hypothesis in biological full sibling testing is that two appraised individuals are biological full siblings. The probability of the corresponding alternative hypothesis of any STR locus combination or IBS score can be directly calculated by the equations presented in this study, and the calculation results are the basis for explanations of the evidence.

Full Sibling Testing Based on NGS-SNP Genotyping Method and IBS Strategy / 法医学杂志

Objective To evaluate the effectiveness of single nucleotide polymorphism （SNP） genoty-ping in combination with identity by state （IBS） strategy in full sibling testing. Methods Thirty-five blood samples were collected from a four-generation family. Ninety autosomal SNPs were genotyped using Precision ID Identity Panel. The distribution of IBS scores for full siblings and other relationships were calculated and compared. The relationships were determined using Fisher discriminant function and threshold method, respectively. Results Based on family members and previous research, 44, 30, 111, 71 and 1 000 pairs of full siblings （FS）, grandparent-grandchild （GG）, uncle/aunt-nephew/niece （UN）, first cousins （FC） and unrelated individuals （UI） were obtained, respectively. The average IBS scores were 148, 130, 132, 124 and 120, respectively. Except for the GG and UN pairs, the distribution differences among the other relationships had statistical significance （P<0.05）. The false rates of Fisher discriminant function to determine relationships were 1.3%, 22.3%, 17.0% and 38.7% for FS, GG, UN and FC, respectively. Based on the simulation data, the thresholds t1=128 and t2=141 were recommended to determine full sibling relationships （the false rate ≤0.05%）. Conclusion The 90 SNP genetic markers included in the Precision ID Identity Panel meet the testing requirements for full sibling relationships. The threshold method based on IBS has a relatively lower false rate and is more flexible.

Equation Derivation of the Probability Distribution of IBS Score among Full Sibling Pairs / 法医学杂志

Objective To derive the general equation of the probability distribution of identity by state （IBS） score among biological full sibling pairs by calculating STR allele frequency. Methods Based on the Mendelian genetics law and the hypothesis that parents of biological full siblings （FS） were unrelated individuals, the IBS score and corresponding probability of different genotype combinations in the offspring when unrelated individuals of different genotype combinations give birth to two offsprings were derived. Results Given fi （i=1, 2, …, m） as the frequency of the ith allele of a STR locus, the probability of sharing 2 alleles （p2FS）, 1 allele （p1FS） or 0 allele （p0FS） with biological full sibling pairs on the locus can be respectively expressed as follows： (see the text). The sum of p2FS, p1FS and p0FS must be 1. As for the multiple genotyping system that contained n STR loci, IBS scores between biological full sibling pairs conform to binomial distribution： IBS~B（2n, π1）. The population rate π1, can be given by the formula： (see the text). Conclusion The alternative hypothesis in biological full sibling testing is that two appraised individuals are biological full siblings. The probability of the corresponding alternative hypothesis of any STR locus combination or IBS score can be directly calculated by the equations presented in this study, and the calculation results are the basis for explanations of the evidence.

Formula Derivation for the Probability Distribution of IBS Score in Unrelated Individual Pairs / 法医学杂志

OBJECTIVES@#To derive the probability equation given by STR allele frequencies of identity by state （IBS） score shared by unrelated individual pairs.@*METHODS@#By comparing the STR genotypes of two unrelated individuals, three mutually exclusive combinations could be obtained： （1） sharing 2 identical alleles, a₂=1, otherwise a₂=0; （2） sharing 1 identical allele, a₁=1, otherwise a₁=0; （3） sharing 0 identical allele, a₀=1, otherwise a₀=0. And the IBS score of the one STR locus in this unrelated individual pair could be given by the formula： ibs=2a₂+a₁. The probability of a₂=1 （p₂）, a₁=1 （p₁） and a₀=1 （p₀） were derived and expressed in powers of the allele frequencies. Subsequently, for a genotyping system including n independent STR loci, the characteristics of binomial distribution of IBS score shared by a pair of unrelated individuals could be given by p₂l and p₁l （l=1, 2, …, n）.@*RESULTS@#All the general equations of p₂, p₁ and p₀ were derived from the basic conceptions of a₂, a₁ and a₀, respectively. Given fi （i=1, 2, …, m） as the ith allele frequency of a STR locus, the general equations of p₂, p₁ and p₀ could be respectively expressed in powers of fi： [Formula: see text],[Formula: see text] and [Formula: see text]. The sum of p₂, p₁ and p₀ must be equal to 1. Then, the binomial distribution of IBS score shared by unrelated individual pairs genotyped with n independently STR loci could be written by： IBS~B（2n, π）, and the general probability, π, could be given by the formula： [Formula: see text].@*CONCLUSIONS@#In the biological full sibling identification, the probability of null hypothesis corresponding to any specific IBS score can be directly calculated by the general equations presented in this study, which is the basement of the evidence explanation.

Full Sibling Identification by IBS Scoring Method and Establishment of the Query Table of Its Critical Value / 法医学杂志

OBJECTIVES@#To establish a query table of IBS critical value and identification power for the detection systems with different numbers of STR loci under different false judgment standards.@*METHODS@#Samples of 267 pairs of full siblings and 360 pairs of unrelated individuals were collected and 19 autosomal STR loci were genotyped by Goldeneye™ 20A system. The full siblings were determined using IBS scoring method according to the 'Regulation for biological full sibling testing'. The critical values and identification power for the detection systems with different numbers of STR loci under different false judgment standards were calculated by theoretical methods.@*RESULTS@#According to the formal IBS scoring criteria, the identification power of full siblings and unrelated individuals was 0.764 0 and the rate of false judgment was 0. The results of theoretical calculation were consistent with that of sample observation. The query table of IBS critical value for identification of full sibling detection systems with different numbers of STR loci was successfully established.@*CONCLUSIONS@#The IBS scoring method defined by the regulation has high detection efficiency and low false judgment rate, which provides a relatively conservative result. The query table of IBS critical value for identification of full sibling detection systems with different numbers of STR loci provides an important reference data for the result judgment of full sibling testing and owns a considerable practical value.

Full Sibling Identification by IBS Scoring Method and Establishment of the Query Table of Its Critical Value / 法医学杂志

Objective T o establish a query table of IB S critical value and identification pow er for the detection system s w ith different num bers of ST R loci under different false judgm ent standards. Methods Sam ples of 267 pairs of full siblings and 360 pairs of unrelated individuals w ere collected and 19 auto-som al ST R loci w ere genotyped by G oldeneyeTM 20A system . T he full siblings w ere determ ined using IB S scoring m ethod according to the 'R egulation for biological full sibling testing'. T he critical values and identification pow er for the detection system s w ith different num bers of ST R loci under different false judgm ent standards w ere calculated by theoretical m ethods. Results A ccording to the form al IB S scoring criteria, the identification pow er of full siblings and unrelated individuals w as 0.7640 and the rate of false judgm ent w as 0. T he results of theoretical calculation w ere consistent w ith that of sam ple observation. T he query table of IB S critical value for identification of full sibling detection system s w ith different num bers of ST R loci w as successfully established. Conclusion T he IB S scoring m ethod defined by the regulation has high detection efficiency and low false judgm ent rate, w hich provides a relatively conservative result. T he query table of IB S critical value for identification of full sibling detection sys-tem s w ith different num bers of ST R loci provides an im portant reference data for the result judgm ent of full sibling testing and ow ns a considerable practical value.