OSAC 2022-S-0011 Standards for Construction 

of Multilocus Databases

1

OSAC 2022-S-0011

Standards for 

Construction of Multilocus 

Databases

Wildlife Forensics Biology

Biology Scientific Area Committee

Organization of Scientific Area Committees (OSAC) for Forensic Science
OSAC 2022-S-0011 Standards for Construction 

of Multilocus Databases

2

Draft OSAC Proposed Standard

OSAC 2022-S-0011

Standards for Construction of 

Multilocus Databases

Prepared by 

Wildlife Forensics Biology

Version: 1.0

October 2021

Disclaimer:

This OSAC Proposed Standard was written by the (subcommittee) of the Organization of Scientific Area 

Committees (OSAC) for Forensic Science following a process that includes an open comment period. 

This Proposed Standard will be submitted to a standards developing organization and is subject to 

change.

There may be references in an OSAC Proposed Standard to other publications under development by 

OSAC. The information in the Proposed Standard, and underlying concepts and methodologies, may be 

used by the forensic-science community before the completion of such companion publications.

Any identification of commercial equipment, instruments, or materials in the Proposed Standard is not a 

recommendation or endorsement by the U.S. Government and does not imply that the equipment, 

instruments, or materials are necessarily the best available for the purpose.

To be placed on the OSAC Registry, certain types of standards first must be reviewed by a Scientific and 

Technical Review Panel (STRP). The STRP process is vital to OSAC’s mission of generating and 

recognizing scientifically sound standards for producing and interpreting forensic science results. The 

STRP shall provide critical and knowledgeable reviews of draft standards or of proposed revisions of 

standards previously published by standards developing organizations (SDOs) to ensure that the 

published methods that practitioners employ are scientifically valid, and the resulting claims are 

trustworthy.

The STRP panel will consist of an independent and diverse panel, including subject matter experts, 

human factors scientists, quality assurance personnel, and legal experts, which will be tasked with 

evaluating the proposed standard based on a comprehensive list of science-based criteria.

For more information about this important process, please visit our website 

at: https://www.nist.gov/topics/organization-scientific-area-committees-forensic-science/scientifictechnical-review-panels. 
OSAC 2022-S-0011 Standards for Construction 

of Multilocus Databases

3

1 Standards for Construction of Multilocus Databases

2 Foreword

3 This standard defines the minimum requirements that shall be met when developing allele 

4 frequency and population genetic databases for wildlife forensics. 

5 The composition of a database intended for use in population genetic analyses is critical for 

6 accurate comparison among the individual subjects as well as statistically sound group 

7 assignment (e.g. individual, relatedness, population, geographic source, taxonomic grouping). 

8 Analysts must use their expert knowledge in assessing the scientific merit of results obtained 

9 from analysis of allele frequency and population genetic data, and in the subsequent reporting of 

10 these results.

11

12 Keywords: wildlife forensics, population database, population genetics, multilocus, DNA

13
OSAC 2022-S-0011 Standards for Construction 

of Multilocus Databases

4

14

15 Table of Contents

16 1 Scope 5

17 2 Normative References 5

18 3 Terms and Definitions 5-6

19 4 Requirements 6-8

20 5 Conformance 8

21 6 Annexes 8-9

22 Annex A (informative) Bibliography 9
5

23 1 Scope

24 This document provides minimum standards to guide the construction of multilocus population 

25 genetic databases. This document covers criteria for the identification and collection of samples, 

26 inclusion of associated biological data, choice and evaluation of genetic markers, and standard 

27 statistical evaluation of the reference database. This document does not cover specific 

28 applications such as individual matching, familial matching, geographic assignment, or other 

29 wildlife forensic techniques to evidence in wildlife forensic casework. This document only 

30 applies to databases generated from reference samples and does not include evidence items.

31 These minimum standards are not intended to replace standards in ISO 17025 or additional 

32 forensic laboratory standards, but are designed to guide laboratories that are working toward 

33 meeting those standards. Notes throughout this document offer clarifications and examples of 

34 how a lab may meet a specific standard.

35 2 Normative References

ANSI/ASB Standard 019, Wildlife Forensics General Standards1 36

ANSI/ASB Standard 046, Wildlife Validation Standards-STR Analysis1 37

38 ANSI/ASB Standard 047, Wildlife Validation Standards-Validating New Primers for 

Sequencing1 39

ANSI/ASB Standard 048, Wildlife Forensic DNA Standard Procedures1 40

41 ANSI/ASB Best Practices Recommendations 114, Best Practice Recommendations for Internal 

Validation of Software used in Forensic DNA Laboratories1 42

43 3 Terms and Definitions

44 For purposes of this document, the following definitions apply. 

45 3.1

46 assignment

47 a method for assigning individuals to predefined categories, based on a suite of characters (e.g. 

48 multilocus genotype) measured for the individual and for samples from each category (e.g. 

49 potential source populations).

50 3.2

51 autocorrelation

52 phenomenon where samples closer in geographic space or time tend to be more similar or 

53 dissimilar to each other than expected by chance alone, for a given variable such as allele 

54 frequencies.

55
6

56 3.3

57 co-ancestry

58 identical alleles that are copies of the same ancestral allele without mutation; this is a subset of 

59 identical by state (IBS).

60

61 3.4

62 familial matching

63 a method for determining genetic family relationships such as paternity, siblingship and other 

64 kinships.

65 3.5

66 individual matching

67 a method for comparing one DNA profile to another to determine if the DNA profiles are 

68 consistent at the level of interest 

69

70 3.6

71 population

72 a group of organisms of the same species in a defined geographic area, such that any pair of 

73 members can interbreed.

74 3.7

75 probability of identity

76 the probability that two randomly drawn individuals within a given population will have 

77 identical genotypes at multiple loci (reference Waits et al 2013 or Peakall and Sykes 1996)

78

79 3.8

80 probability of siblings

81 the probability that two randomly drawn individuals within a given population will have 

82 identical genotypes at multiple loci when relatives are included in the sample.

83

84 3.9

85 statistical power 

86 the probability of a hypothesis test finding an effect if there is an effect to be found.

87

88 4 Requirements

89 The following requirements and recommendations address criteria for construction and 

90 evaluation of population databases, including identification of database components, choice of 

91 genetic markers, procedures for statistical analysis, and evaluation and interpretation of results 

92 for general population genetic analyses. Species differ based on demographic, ecological, and 

93 evolutionary factors, so quantitative values for the minimum number of individuals and genetic 

94 markers needed for a reference database are expected to vary according to the species and 

95 populations of interest. These criteria shall be addressed in laboratory validation studies 

96 according to established population genetic theory and practice.

97 4.1 Inclusion Criteria for Genetic Database Samples
7

98 4.1.1 Protocols for constructing genetic databases shall include:

99 a. sample acquisition;

100 b. establishment of parameters for inclusion of samples;

101 c. validation process for use of genetic markers;

102 d. criteria for individual sample data quality; 

103 e. quality control/curation of sample information and genetic data

104

105 4.1.2 Quality control shall include adherence to standards in ANSI/ASB 019, ANSI/ASB 046, 

106 ANSI/ASB 047, and ANSI/ASB 048

107 4.1.3 In determining database composition the laboratory shall assess, at minimum: 

108 a. sample size needed to accurately represent source population genetic diversity;

109 b. related taxonomic information, including

110 i. presence of subspecies

111 ii. evolutionary significant units (ESU)

112 iii. hybrids in the species group of interest

113 iv. geographic range of the taxa in question

114 4.1.4 Criteria shall be established for metadata associated with sample acquisition, to include at 

115 minimum: 

116 a. geographic location of source samples (e.g. sampling location, breeding location, location 

117 of death);

118 b. sex of individual, if known;

119 c. age class of individual, if known;

120 d. type of tissue sampled (e.g. fresh tissue, blood, bone, hair, antler, keratin, feces, etc);

121 e. collection information (i.e. date, collector - both name and agency/institution, method of 

122 collection).

123 4.1.5 At minimum, genetic markers shall be evaluated for the: 

124 a. number of loci required, as determined by laboratory validation.

125 NOTE: The number of loci needed will vary by species/population and forensic 

126 application (e.g. individual matching, population assignment, paternity)

127 b. genotyping error rate;

128 c. genetic diversity measures, including but not limited to:

129 i. Hardy-Weinberg Equilibrium,

130 ii. linkage disequilibrium,

131 iii. allelic richness,

132 iv. allelic diversity,

133 v. heterozygosity measures within and among populations; 

134 d. presence of null alleles.
8

135 4.1.6 Quality criteria shall be established for sample inclusion when adding genetic data to 

136 species/population databases. This shall include, at minimum:

137 a. minimum acceptable completeness of genotype per sample;

138 b. minimum genotype quality measures depending on genotyping platform [e.g. capillary 

139 electrophoresis - Relative Fluorescence Units (RFU); Next-generation sequencing -

140 genotype quality score and read depth].

141 4.2 Once constructed, the database shall be evaluated for:

142 a. representative geographic coverage;

143 b. power to discriminate species/population boundaries;

144 c. power to identify natural groupings that are ecologically or biologically meaningful;

145 d. population level allele frequencies;

146 e. presence of spatial or temporal autocorrelation;

147 f. sex-related bias;

148 g. estimates for statistical power (i.e. probability of identity, probability of siblings);

149 h. presence of duplicated samples;

150 i. level of co-ancestry 

151 Note: Database composition will vary based on forensic application (e.g. individual matching, 

152 familial matching, geographic assignment techniques).

153

154 4.3 Laboratories shall have protocols for evaluation of software intended for use in statistical 

155 analysis, including commercial programs and programs developed in-house.

156 4.4 Once initially validated, databases augmented with new samples or subsetted shall be re157 evaluated as in 4.2. 

158 4.5 Laboratories shall have protocols for database archival and version control.

159 5 Conformance 

160 Conformance to the standards outlined in this document is measured by the availability of 

161 written documentation in the form of formal protocols and methods available for examination.

162

163

164

165

166

167

168

169

170

171

172
9

173 Annex A

174 (informative)

175

176 Bibliography

177

178 The following information provides a list of the literature resources that may assist in defining 

179 the breadth and scope of this standard. This list is not meant to be all inclusive. The laboratory 

180 shall develop a list tailored to its specific needs. Updated references shall be added to the 

181 laboratory’s list as new methods or technologies are incorporated into the laboratory’s protocols. 

182 1] J.M. Butler. Fundamentals of Forensic DNA Typing. Elsevier Academic Press, San Diego, CA, 2010.

183 2] Legendre P and Legendre L (1998) Numerical Ecology. 3rd ed. Elsevier, Amsterdan.

184 3] Ogden, R and A. Linacre 2015, Wildlife forensic science: A review of genetic 

185 geographic origin assignment. Forensic Science International: Genetics, 18:152 - 159. 

186 https://doi.org/10.1016/j.fsigen.2015.02.008

187 4] Rousset F., 2004. Genetic Structure and Selection in Subdivided Populations. Princeton 

188 University Press, Princeton, NJ.

189 5] Slatkin, M, and H. E. Arter. Spatial Autocorrelation Methods in Population Genetics. The 

190 American Naturalist, 138(2): 499–517. JSTOR, www.jstor.org/stable/2462484. Accessed 

191 11 Mar. 2021.

192 6] Smouse, P., R. Peakall. Spatial autocorrelation analysis of individual multiallele and 

193 multilocus genetic structure. Heredity 82:561–573 (1999). 

194 https://doi.org/10.1038/sj.hdy.6885180

195 7] Waits, L. P, G Luikart, P Taberlet 2001 Estimating the probability of identity among 

196 genotypes in natural populations: cautions and guidelines. Molecular Ecology, 10(1): 

197 249-256. https://doi..org.10.1046/j.1365-294x.2001.01185.x

198 8] Waples, R. S. 1995. Evolutionarily significant units and the conservation of biological 

199 diversity under the endangered species act: Evolution and the aquatic ecosystem: defining 

200 unique units in population conservation. American Fisheries Society Symposium, vol. 17: 

201 8-27. https://ci.nii.ac.jp/naid/10021852122/en/

202

203

204

205

206

207