Methods and compositions for DNA-based kinship analysis

Abstract

The present disclosure relates in some embodiments to performing DNA-based kinship analysis involving analysis of 5,000-50,000 SNPs, including sample preparation and sequencing techniques and methods that can be used to calculate the degree of relatedness of a DNA profile to one or more reference DNA profiles. In some embodiments, provided herein are methods, compositions, devices and systems for providing a comprehensive, accessible and complete DNA-based analysis profile using forensically curated single nucleotide polymorphism (SNP) marker sets.

Description

[Technical field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority to U.S. Provisional Application No. 63 / 149,071, filed February 12, 2021, entitled "Methods and Compositions for DNA Based Kinship Analysis," the entire contents of which are incorporated herein by reference.

[0002] Field The present disclosure relates in some aspects to methods and compositions for DNA-based kinship analysis in a sample. [Background technology]

[0003] background Current methods for generating DNA profiles for comparison in genetic databases include genotyping using high-density SNP microarrays and whole genome sequencing (WGS), followed by linking evidentiary samples to distant relatives in databases, which require large amounts of high-quality DNA samples and are not designed for family search or forensic purposes. Forensic casework samples are generally small and low-quality samples, and data from current methods require extensive imputation to generate results that can be uploaded to search databases. Thus, new and improved methods for generating DNA-based profile analyses are needed. Summary of the Invention [Means for solving the problem]

[0004] Abstract In some embodiments, provided herein are methods, compositions, devices and systems for providing comprehensive, accessible and complete DNA-based analytical profiles using forensically curated single nucleotide polymorphism (SNP) marker sets.

[0005] Provided herein is a method for performing DNA-based kinship analysis, comprising: providing a nucleic acid sample; amplifying the nucleic acid sample with a plurality of primers that specifically hybridize to a plurality of target sequences collectively comprising at least or about 5,000-50,000 single nucleotide polymorphisms (SNPs), thereby generating amplification products, wherein the amplification is performed in one or more multiplex PCR reactions; generating a nucleic acid library from the amplification products; sequencing the nucleic acid library generated from the amplification products; analyzing the sequences of the amplification products; genotyping the plurality of SNPs, thereby generating a DNA profile; and calculating a degree of relationship between the DNA profile and one or more reference DNA profiles.

[0006] Also provided herein is a method for performing DNA-based kinship analysis, comprising: providing a nucleic acid sample; amplifying the nucleic acid sample with a plurality of primers that specifically hybridize to a plurality of target sequences collectively comprising at least or about 5,000-50,000 single nucleotide polymorphisms (SNPs), thereby generating amplification products, wherein the amplification is performed in one or more multiplex PCR reactions; generating a nucleic acid library from the amplification products; sequencing the nucleic acid library generated from the amplification products; genotyping the plurality of SNPs, thereby generating a DNA profile; and calculating a degree of relatedness between the DNA profile and one or more reference DNA profiles.

[0007] In some of such embodiments, the sequencing is performed using massively parallel sequencing (MPS). In some of such embodiments, the sequencing does not include whole genome sequencing (WGS).

[0008] In some of any such embodiments, the method further includes generating a family tree that includes DNA profiles related to the one or more DNA profiles.

[0009] Also provided herein is a method of constructing a nucleic acid library, the method comprising: providing a nucleic acid sample; and amplifying the nucleic acid sample with a plurality of primers that specifically hybridize to a plurality of target sequences that collectively comprise a plurality of at least or about 5,000-50,000 single nucleotide polymorphisms (SNPs), thereby generating a nucleic acid library comprising amplified products, wherein the amplification is performed in one or more multiplex PCR reactions.

[0010] In some of such embodiments, the nucleic acid sample comprises genomic DNA.In some of such embodiments, the nucleic acid sample comprises one or more enzyme inhibitors.In some of such embodiments, the one or more enzyme inhibitors comprise one or more inhibitors selected from the group consisting of hematin, heme, humic acid, indigo and tannic acid.

[0011] In some of such embodiments, the nucleic acid sample contains low quality and / or low abundance nucleic acid molecules. In some of such embodiments, the low quality nucleic acid molecules are degraded and / or fragmented genomic DNA. In some of such embodiments, the low quality nucleic acid molecules are 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195, or 200 A degradation index (DI) or a degradation index (DI) of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195 or 200. In some of any of such embodiments, the low quality nucleic acid molecules have a DI of at least 1 and up to or less than 158.3.

[0012] In some of any such embodiments, the nucleic acid sample comprises high quality nucleic acid molecules. In some of such embodiments, the high quality nucleic acid molecules have a DI of less than 1.

[0013] In some of such embodiments, the nucleic acid sample is a forensic sample. In some of such embodiments, the nucleic acid sample is derived from saliva, blood, semen, hair, teeth, or bone. In some of such embodiments, the nucleic acid sample is derived from saliva, blood, or semen. In some of such embodiments, the nucleic acid sample is derived from a buccal swab, paper, fabric, or other substrate impregnated with saliva, blood, semen, or other bodily fluid.

[0014] In some of such embodiments, the nucleic acid sample comprises at or about 50 pg to 100 ng of genomic DNA. In some of such embodiments, the nucleic acid sample comprises at or about 100 pg to 5 ng of genomic DNA or at or about 50 pg to 5 ng of genomic DNA. In some of such embodiments, the nucleic acid sample comprises at or about 1 ng of genomic DNA.

[0015] In some of any of such embodiments, the plurality of SNPs comprises kinship SNPs (kiSNPs). In some of such embodiments, the plurality of SNPs comprises kiSNPs, biogeographic ancestry SNPs (aiSNPs), identity SNPs (iiSNPs), phenotypic SNPs (piSNPs), x-chromosome SNPs (xSNPs), and y-chromosome SNPs (ySNPs). In some of such embodiments, the plurality of SNPs comprises SNPs selected from one or more of the group consisting of kiSNPs, aiSNPs, iiSNPs, piSNPs, xSNPs, and ySNPs. In some of any of such embodiments, at least or at least about 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98% or 99% of the plurality of SNPs are related SNPs.

[0016] Also provided herein is a method for calculating degree of relatedness, the method comprising obtaining a DNA profile comprising genotypes for at least or about 5,000-50,000 SNPs, and calculating the degree of relatedness of the DNA profile to one or more reference DNA profiles.

[0017] Also provided herein is a method for calculating degree of relatedness, the method comprising generating a DNA profile comprising genotypes for at least or about 5,000-50,000 SNPs, and calculating a degree of relatedness between the DNA profile and one or more reference DNA profiles.

[0018] In some of any of such embodiments, calculating the relatedness includes (1) performing KING-Robust relatedness estimation between all pairs of a sample set that includes one or more reference DNA profiles, where pairings with a relatedness coefficient >0.01 are identified as closely related and pairings with a relatedness coefficient <-0.025 are identified as ancestrally divergent; (2) removing all reference DNA profiles with ≥5% missing data; and (3) ranking all reference DNA profiles by identifying each reference DNA profile with a ranking value, where the ranking value is the number of pairs of the full set of reference DNA profiles ranked from smallest to largest. The large-scale cohort method includes a method for determining the number of related reference DNA profiles, where ties are broken by the number of ancestral reference DNA profiles in the full set of reference DNA profiles ranked from largest to smallest, and for each reference DNA profile, iteratively through the ranked reference DNA profiles: (i) if the reference DNA profile is not already in the related sample set, add it to the unrelated sample set and add all related reference DNA profiles to the related sample set; and (ii) if the reference DNA profile is already in the related sample set, skip to the next reference DNA profile and repeat starting from step (3)(i).

[0019] In some of any of such embodiments, the one or more reference DNA profiles may include any of the following: 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,50 0,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or about 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 90 0,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or at least 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000 or 400,000 , 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or at least about 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000 reference DNA profiles. In some of any of such embodiments, the one or more reference DNA profiles may include 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 100,000, 120,000, 140,000, 160,000, 180,000, 190,000, 210,000, 225,000, 230,000, 240,000, 250,000, 260,000, 275,000, 300,000, 400,000, 500,000, 325,000, 330,000, 340,000, 350,000, 360,000, 370,000, 380,000, 390,000, 400,000, 400,000, 400,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 100,000, 110,000, 120 ,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or about 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300 ,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or at least 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 25,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or at least about 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 60 The nucleic acid library may include 0,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000, or 10,000,000 reference DNA profiles. Also provided herein are nucleic acid libraries constructed using any of the methods described herein.

[0020] Also provided herein are a plurality of primers that specifically hybridize to a plurality of target sequences, including at least or about 5,000-50,000 single nucleotide polymorphisms (SNPs) in a nucleic acid sample, and amplifying the nucleic acid sample using the plurality of primers in one or more multiplex PCR reactions to obtain an amplification product. In some embodiments, the nucleic acid sample comprises genomic DNA.

[0021] In some of such embodiments, the nucleic acid sample comprises one or more enzyme inhibitors. In some of such embodiments, the one or more enzyme inhibitors comprise one or more inhibitors selected from the group consisting of hematin, heme, humic acid, indigo, and tannic acid.

[0022] In some of such embodiments, the nucleic acid sample contains low quality and / or low abundance nucleic acid molecules. In some of such embodiments, the low quality nucleic acid molecules are degraded and / or fragmented genomic DNA. In some of such embodiments, the low quality nucleic acid molecules are 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195, or 200 A degradation index (DI) or a degradation index (DI) of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195 or 200. In some of any of such embodiments, the low quality nucleic acid molecules have a DI of at least 1 and up to or less than 158.3.

[0023] In some of any such embodiments, the nucleic acid sample comprises high quality nucleic acid molecules. In some of such embodiments, the high quality nucleic acid molecules have a DI of less than 1.

[0024] In some of such embodiments, the nucleic acid sample is a forensic sample. In some of such embodiments, the nucleic acid sample is derived from a buccal swab, paper, fabric or other substrate impregnated with saliva, blood or other bodily fluid. In some of such embodiments, the nucleic acid sample comprises 50 pg to 100 ng or about 50 pg to 100 ng of genomic DNA. In some of such embodiments, the nucleic acid sample comprises 100 pg to 5 ng or about 100 pg to 5 ng of genomic DNA or 50 pg to 5 ng or about 50 pg to 5 ng of genomic DNA. In some of such embodiments, the nucleic acid sample comprises 1 ng or about 1 ng of genomic DNA.

[0025] In some of any of such embodiments, the plurality of SNPs comprises kinship SNPs (kiSNPs). In some of such embodiments, the plurality of SNPs comprises kiSNPs, biogeographic ancestry SNPs (aiSNPs), identity SNPs (iiSNPs), phenotypic SNPs (piSNPs), x-chromosome SNPs (xSNPs), and y-chromosome SNPs (ySNPs). In some of such embodiments, the plurality of SNPs comprises SNPs selected from one or more of the group consisting of kiSNPs, aiSNPs, iiSNPs, piSNPs, xSNPs, and ySNPs. In some of any of such embodiments, at least or at least about 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98% or 99% of the plurality of SNPs are related SNPs.

[0026] Also provided herein is a method for constructing a DNA profile, comprising: providing a nucleic acid sample; amplifying the nucleic acid sample with a plurality of primers that specifically hybridize to a plurality of target sequences that collectively comprise a plurality of at least or about 5,000-50,000 single nucleotide polymorphisms (SNPs), thereby generating an amplification product, wherein the amplification is performed in one or more multiplex PCR reactions; sequencing the amplification product; and genotyping the plurality of SNPs, thereby generating a DNA profile.

[0027] In some of any such embodiments, the sequencing does not include whole genome sequencing (WGS). In some of such embodiments, the nucleic acid sample comprises genomic DNA.

[0028] In some of such embodiments, the nucleic acid sample comprises one or more enzyme inhibitors. In some of such embodiments, the one or more enzyme inhibitors comprise one or more inhibitors selected from the group consisting of hematin, heme, humic acid, indigo, and tannic acid.

[0029] In some of such embodiments, the nucleic acid sample contains low quality and / or low abundance nucleic acid molecules. In some of such embodiments, the low quality nucleic acid molecules are degraded and / or fragmented genomic DNA. In some of such embodiments, the low quality nucleic acid molecules are 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195, or 200 A degradation index (DI) or a degradation index (DI) of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195 or 200. In some of any of such embodiments, the low quality nucleic acid molecules have a DI of at least 1 and up to or less than 158.3.

[0030] In some of any such embodiments, the nucleic acid sample comprises high quality nucleic acid molecules. In some of such embodiments, the high quality nucleic acid molecules have a DI of less than 1.

[0031] In some of any such embodiments, the nucleic acid sample is a forensic sample. In some of any such embodiments, the nucleic acid sample is derived from a buccal swab, paper, fabric or other substrate impregnated with saliva, blood or other bodily fluid.

[0032] In some of such embodiments, the nucleic acid sample comprises at or about 50 pg to 100 ng of genomic DNA. In some of such embodiments, the nucleic acid sample comprises at or about 100 pg to 5 ng of genomic DNA or at or about 50 pg to 5 ng of genomic DNA. In some of such embodiments, the nucleic acid sample comprises at or about 1 ng of genomic DNA.

[0033] In some of such embodiments, the plurality of SNPs includes kinship SNPs. In some of such embodiments, the plurality of SNPs includes kiSNPs, biogeographic ancestry SNPs (aiSNPs), identity SNPs (iiSNPs), phenotypic SNPs (piSNPs), x-chromosome SNPs (xSNPs), and y-chromosome SNPs (ySNPs). In some of such embodiments, the plurality of SNPs includes SNPs selected from one or more of the group consisting of kiSNPs, aiSNPs, iiSNPs, piSNPs, xSNPs, and ySNPs. In some of any of such embodiments, at least or at least about 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98% or 99% of the plurality of SNPs are related SNPs.

[0034] Also provided herein is a method for identifying genetic relatives of a DNA profile, the method comprising calculating the degree of relatedness between a DNA profile generated using any of the methods provided herein and one or more reference DNA profiles, and generating a family tree including DNA profiles related to the one or more reference DNA profiles.

[0035] In some of any of such embodiments, the method further comprises generating a family tree comprising a DNA profile related to the one or more DNA profiles. In some of any of such embodiments, the one or more reference DNA profiles are part of a genealogy database.

[0036] In some of any of such embodiments, the one or more reference DNA profiles may include any of the following: 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,50 0,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or about 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 90 0,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or at least 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000 or 400,000 , 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or at least about 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000 reference DNA profiles. In some of any of such embodiments, the one or more reference DNA profiles may include 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 100,000, 120,000, 140,000, 160,000, 180,000, 190,000, 210,000, 225,000, 230,000, 240,000, 250,000, 260,000, 275,000, 300,000, 400,000, 500,000, 325,000, 330,000, 340,000, 350,000, 360,000, 370,000, 380,000, 390,000, 400,000, 400,000, 400,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 100,000, 110,000, 120 ,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or about 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300 ,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or at least 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 25,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or at least about 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 60 Contains 0,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000 reference DNA profiles.

[0037] Also provided herein is a method for identifying genetic relatives of a DNA profile, the method comprising: calculating a degree of relatedness between a DNA profile comprising genotypes of at least or about 5,000-50,000 SNPs and one or more reference DNA profiles; and generating a pedigree comprising the DNA profiles related to the one or more reference DNA profiles. In some embodiments, the DNA is generated by the method of any one of claims 52 to 71.

[0038] Also provided herein are kits comprising at least one container means comprising any of a plurality of primers described herein. In some of any of such embodiments, the plurality of SNPs may be from about 7,000-15,000 SNPs, 7,000-14,000 SNPs, 7,000-13,000 SNPs, 7,000-12,000 SNPs, 7,000-11,000 SNPs, 8,000-15,000 SNPs, 8,000-14,000 SNPs, or any combination thereof. In some of such embodiments, the plurality of SNPs comprises 10,230 SNPs. In some of any of such embodiments, the plurality of SNPs is about 7,000-15,000 SNPs, 7,000-14,000 SNPs, 7,000-13,000 SNPs, 7,000-12,000 SNPs, 7,000-11,000 SNPs, 8,000-15,000 SNPs, 8,000-14,000 SNPs, In some of such embodiments, the plurality of SNPs comprises 10,230 SNPs.

[0039] In some of any such embodiments, the method further includes generating a family tree that includes DNA profiles related to the one or more DNA profiles. [Brief description of the drawings]

[0040] [Figure 1]FIG. 1 shows an exemplary schematic of a method for generating a sequenceable library.

[0041] [Diagram 2] Figure 2 shows the results of the number of loci identified using various input dosage adjustments of genomic DNA including 5 ng, 2.5 ng, 1 ng, 500 pg, 250 pg, 100 pg and 50 pg.

[0042] [Diagram 3] FIG. 3 shows the percentage of loci (call rate) detected in degraded DNA using the assay described herein compared to microarray (GSA) call rate.

[0043] [Figure 4] FIG. 4 shows the number of loci detected in the presence of the inhibitors hematin, humic acid, indigo and tannic acid compared to the reference control.

[0044] [Diagram 5] FIG. 5 shows an exemplary pedigree tree generated by the methods described herein.

[0045] [Figure 6] FIG. 6 shows the expected and observed kinship coefficients calculated using the algorithm described herein.

[0046] [Figure 7] FIG. 7 shows the results of the 1:many search algorithm on an exemplary case study.

[0047] [Figure 8] FIG. 8 shows an exemplary pedigree generated from the results of the 1:multiple search algorithm.

[0048] [Figure 9]FIG. 9 is a table summarizing the number and types of loci detected using various input dosage adjustments including 5 ng, 2.5 ng, 1 ng, 500 pg, 250 pg, 100 pg and 50 pg of genomic DNA.

[0049] [Figure 10] FIG. 10 is a table summarizing the number and type of loci detected using DNA in the presence of the inhibitors hematin, humic acid, tannic acid and indigo compared to the positive amplification control in the absence of inhibitors.

[0050] [Figure 11] Figure 11 is a table summarizing the number and types of loci detected for two samples of DNA obtained 9 and 22 hours after a simulated sexual assault. DNA was isolated from the sperm fraction by differential extraction, with 500 pg of DNA input.

[0051] [Figure 12] FIG. 12 shows the number of loci detected in saliva samples with increasing phenol (a known PCR amplification inhibitor) content from the phenol-chloroform-isoamyl alcohol (PCIA) extraction method.

[0052] [Figure 13] FIG. 13 shows the number of loci detected in blood samples isolated from different substrates or methods commonly performed in forensic laboratories, including blood with rust, blood on denim, blood on a swab, and blood with varying levels of heme (a known PCR amplification inhibitor) carryover from Chelex™ extraction. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0053] Detailed Description The practice of the techniques described herein may employ conventional techniques and explanations of molecular biology, cell biology, biochemistry and sequencing techniques, unless otherwise indicated, which are within the skill of those of ordinary skill in the art. Specific illustrations of suitable techniques may be had by reference to the examples herein.

[0054] All publications, including patent documents, scientific articles, and databases, referred to in this application are incorporated by reference in their entirety for all purposes to the same extent as if each individual publication was individually incorporated by reference. To the extent that a definition set forth herein contradicts or otherwise conflicts with a definition set forth in a patent, application, published application, or other publication incorporated herein by reference, the definition set forth herein shall take precedence over the definition incorporated herein by reference.

[0055] The section headings used herein are for organizational purposes only and are not to be construed as limiting the subject matter described. overview

[0056] Provided herein are novel and improved methods for generating DNA-based profile analysis, including nucleic acid profile generation and DNA-based kinship analysis. Current methods for generating DNA profiles for comparison in genetic databases include genotyping using high-density SNP microarrays and WGS followed by linking of evidence samples with distant relatives in the database, which require large amounts and high quality DNA samples and are not designed for family search or forensic purposes. Forensic casework samples, for example from crime scenes, are generally small amounts and low quality samples, e.g., contain degraded DNA, and data from current methods require extensive imputation to generate results that can be uploaded to a search database. Additionally, forensic samples often contain drugs that are inhibitors of PCR amplification reactions. The novel and improved methods provided herein overcome these limitations by enabling the use of small amounts and low quality, e.g., degraded DNA, for the generation of nucleic acid profiles, even when the samples contain known inhibitors of PCR amplification, using primers that specifically hybridize to approximately 5,000-50,000 SNPs for more efficient genetic analysis than alternative approaches such as WGS or SNP microarrays. Additionally, the new and improved methods provided herein also include improved methods of performing kinship analysis that require fewer calculations to calculate accurate kinship. Finally, in some embodiments, the new and improved methods provided herein also exclude SNPs with known medical associations or low minor allele frequencies, thereby limiting privacy concerns and protecting genetic health data.

[0057] Disclosed herein is a method of performing DNA-based kinship analysis, comprising providing a nucleic acid sample, and subsequently amplifying the nucleic acid sample with a plurality of primers that specifically hybridize to a plurality of target sequences that collectively comprise a plurality of at least or about 5,000-50,000 single nucleotide polymorphisms (SNPs), thereby generating amplification products, where the amplification is performed in one or more multiplex PCR reactions. In some embodiments, a nucleic acid library (e.g., a DNA library) is generated from the amplification products. In some embodiments, the nucleic acid library generated from the amplification products is sequenced to determine the genotype of the plurality of SNPs. In some embodiments, the amplification products are sequenced, amplified, and the genotype of the plurality of SNPs is determined. In some embodiments, the genotype of the plurality of SNPs is used to generate a DNA profile. In some embodiments, the degree of association of the DNA profile with one or more reference DNA profiles is determined.

[0058] In some embodiments, the methods disclosed herein include performing a DNA-based kinship analysis, which includes providing a nucleic acid sample, followed by amplifying the nucleic acid sample with a plurality of primers that specifically hybridize to a plurality of target sequences collectively comprising at least or about 5,000-50,000 single nucleotide polymorphisms (SNPs), thereby generating an amplification product, where the amplification is performed in one or more multiplex PCR reactions. In some embodiments, a nucleic acid library, e.g., a DNA library, is generated from the amplification products. In some embodiments, the nucleic acid library, e.g., a DNA library, generated from the amplification products is sequenced to determine the genotype of the plurality of SNPs. In some embodiments, the amplification products are sequenced to determine the genotype of the plurality of SNPs. In some embodiments, the genotype of the plurality of SNPs is used to generate a DNA profile. In some embodiments, the degree of association of the DNA profile with one or more reference DNA profiles is determined.

[0059] Also provided herein, in some embodiments, are a plurality of primers that specifically hybridize to a plurality of target sequences that collectively comprise at least or about 5,000-50,000 single nucleotide polymorphisms (SNPs) in a nucleic acid sample, and amplifying the nucleic acid sample using the plurality of primers in one or more multiplex reactions to obtain amplification products.

[0060] In some embodiments, the methods disclosed herein include constructing a nucleic acid library, which includes providing a nucleic acid sample, followed by amplifying the nucleic acid sample with a plurality of primers that specifically hybridize to a plurality of target sequences collectively comprising at least or about 5,000-50,000 single nucleotide polymorphisms (SNPs), thereby generating amplification products, where the amplification is performed in one or more multiplex PCR reactions. In some embodiments, the amplification products are sequenced to determine the genotypes of the plurality of SNPs. In some embodiments, the genotypes of the plurality of SNPs are used to generate a DNA profile.

[0061] In some embodiments, the methods disclosed herein include constructing a DNA profile, which includes providing a nucleic acid sample, followed by amplifying the nucleic acid sample with a plurality of primers that specifically hybridize to a plurality of target sequences collectively comprising at least or about 5,000-50,000 single nucleotide polymorphisms (SNPs), thereby generating amplification products, where the amplification is performed in one or more multiplex PCR reactions. In some embodiments, the amplification products are sequenced to determine the genotypes of the plurality of SNPs. In some embodiments, the genotypes of the plurality of SNPs are used to generate a DNA profile.

[0062] In some embodiments, the methods disclosed herein include identifying genetic relatives of a DNA profile, which includes calculating the degree of relatedness of a DNA profile comprising genotypes for at least or about 5,000-50,000 SNPs to one or more reference DNA profiles, and generating a pedigree tree comprising DNA profiles related to the one or more reference DNA profiles. Samples and sample processing

[0063] In some aspects, the sample disclosed herein can be or comprise any suitable biological sample, or a sample derived therefrom.In some aspects, the sample described herein is processed and amplified using any known suitable method to complement the method described herein.Exemplary samples, sample processing methods and sample amplification methods are described below. A. Nucleic Acid Samples

[0064] The nucleic acid sample disclosed herein may be derived from any biological sample. The biological sample may be derived from blood, buccal swabs, hair, teeth, bones and / or semen. In some embodiments, the nucleic acid sample is derived from a biological sample that is or contains blood, hair, teeth, bones, semen or sperm. In some embodiments, the biological sample is a DNA sample. In some embodiments, the nucleic acid sample comprises DNA. In some embodiments, the DNA is genomic DNA (gDNA). The DNA from which the nucleic acid sample can be obtained may be intact or partially degraded. The DNA from which the nucleic acid sample can be obtained may be damaged, degraded or inhibited due to, but not limited to, degradation of raw materials, variability in extraction, storage procedures or environmental exposure. In some embodiments, the DNA is damaged due to calcium inhibition, cremation, incineration and embalming.

[0065] In some embodiments, the DNA from which the nucleic acid sample can be obtained is a low-volume and / or low-quality DNA sample. In some embodiments, the DNA from which the nucleic acid sample can be obtained is a low-volume and low-quality DNA sample. In some embodiments, the low-quality DNA sample comprises low-quality nucleic acid molecules. In some embodiments, the low-quality nucleic acid molecules are degraded DNA, such as genomic DNA, and / or fragmented DNA, such as genomic DNA.

[0066] The quality of a nucleic acid, e.g., DNA, sample can be determined by calculating the Degradation Index (DI). DI is calculated by dividing the concentration of the small DNA target by the concentration of the large DNA target (DI=concentration of small DNA target / concentration of large DNA target). In general, a DI value less than 1 typically indicates that the nucleic acid, e.g., DNA, is not degraded, is not a low quality sample, and / or is a high quality sample, a DI value between 1 and 10 typically indicates that the nucleic acid, e.g., DNA, has a small to moderate amount of degradation, and a DI value greater than 10 typically indicates that the nucleic acid, e.g., DNA, is highly degraded.

[0067] In some embodiments, low quality nucleic acid molecules have a D of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195, or 200 or more. I or has a DI of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195 or 200 or more. In some embodiments, the low quality nucleic acid molecules are at least 1 and 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195 or 200 or more. In some embodiments, low quality nucleic acid molecules have a DI of 1-200. In some embodiments, low quality nucleic acid molecules have a DI of at least 1 and less than 158.3 or 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195, or 200 or more. In some embodiments, low quality nucleic acid molecules have a DI of at least 1 and less than 158.3 or 158.3.

[0068] In some embodiments, the DNA from which the nucleic acid sample is obtained is a high quality nucleic acid sample. In some embodiments, a high quality nucleic acid sample has a DI of less than 1.

[0069] In some embodiments, the nucleic acid sample comprises one or more enzyme inhibitors. In some embodiments, the one or more enzyme inhibitors comprise one or more inhibitors selected from the group consisting of hematin, humic acid, indigo and tannic acid. In some embodiments, the one or more enzyme inhibitors comprise heme.

[0070] In some embodiments, the nucleic acid sample is a forensic sample. In some embodiments, the nucleic acid sample is derived from a buccal swab, paper, fabric, such as denim, or other substrate impregnated with saliva, blood, sperm, or other bodily fluid.

[0071] In some embodiments, the nucleic acid sample is from a crime scene, such as a murder, an assault, such as a sexual assault, or a burglary, or any other crime where identification of participants is required. In some embodiments, the nucleic acid sample is from a sexual assault.

[0072] In some embodiments, the nucleic acid sample is obtained at or about 30 minutes, at or about 1 hour, or at or about 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, or 24 hours or more after a sample containing the nucleic acid sample is deposited by its source, e.g., a human subject. In some embodiments, the nucleic acid sample is isolated from the human subject within about 3 hours, 9 hours, 12 hours, 15 hours, 18 hours, 21 hours, 22 hours, 24 hours, 36 hours, 48 ​​hours, 3 days, 4 days, 5 days, 6 days, 7 days, 2 weeks, 3 weeks, 4 weeks, 1 month, 2 months, 3 months, 4 months, 5 months, 6 months, 7 months, 8 months, 9 months, 10 months, 11 months, 1 year after the sample containing the nucleic acid sample is deposited by its source, e.g., a human subject. , 2, 3 or 4 years or more, or less than about 3 hours, 9 hours, 12 hours, 15 hours, 18 hours, 21 hours, 22 hours, 24 hours, 36 hours, 48 ​​hours, 3 days, 4 days, 5 days, 6 days, 7 days, 2 weeks, 3 weeks, 4 weeks, 1 month, 2 months, 3 months, 4 months, 5 months, 6 months, 7 months, 8 months, 9 months, 10 months, 11 months, 1 year, 2 years, 3 years or 4 years or more. In some embodiments, the nucleic acid sample is obtained 24 hours or less, e.g., 22 hours or less, after a sample containing the nucleic acid sample is deposited by its source, e.g., a human subject.

[0073] In some embodiments, the nucleic acid sample comprises at or about 50 pg to 100 ng of DNA, e.g., genomic DNA. In some embodiments, the nucleic acid sample comprises at or about 100 pg to 5 ng of DNA, e.g., genomic DNA. In some embodiments, the nucleic acid sample comprises at or about 1 ng of DNA, e.g., genomic DNA.

[0074] In some embodiments, the nucleic acid sample comprises 10 pg or about 10 pg to 100 ng or about 100 ng of DNA, e.g., genomic DNA, or 10 pg or about 10 pg to 5 ng or about 5 ng of DNA, e.g., genomic DNA. In some embodiments, the nucleic acid sample comprises 10 pg to 10 ng or about 10 pg to 10 ng, 10 pg to 5 ng or about 10 pg to 5 ng, 25 pg to 10 ng or about 25 pg to 10 ng, 25 pg to 5 ng or about 25 pg to 5 ng, 50 pg to 10 ng or about 50 pg to 10 ng, or 50 pg to 5 ng or about 50 pg to 5 ng of DNA, e.g., genomic DNA.

[0075] In some embodiments, the nucleic acid sample contains between or about 50 pg and 5 ng or about 5 ng of DNA, e.g., genomic DNA. In some embodiments, the nucleic acid sample contains between or about 10 pg, 15 pg, 20 pg, 25 pg, 30 pg, 35 pg, 40 pg, 45 pg, 50 pg, 55 pg, 60 pg, 70 pg, 75 pg, 80 pg, 85 pg, 90 pg, 95 pg, 100 pg, 125 pg, 150 pg, 175 pg, 200 pg, 225 pg, 250 pg, 275 pg, 300 pg, 325 pg, 350 pg, 375 pg, 400 pg, 420 pg, 425 ... 0pg, 475pg, 500pg, 600pg, 700pg, 800pg, 900pg, 1ng, 1.1ng, 1.2ng, 1.3ng, 1.4ng, 1.5ng, 1.6ng, 1.7ng, 1.8ng, 1.9ng, 2ng, 2.1ng, 2.2ng, 2.3ng, 2.4ng, 2.5ng, 2.6ng, 2.7ng, 2.8ng, 2.9ng, 3ng, 3.25ng, 3.5ng, 3.75ng, 4ng, 4.25ng, 4.5ng, 4.75ng or 5ng, or about 10pg, 15pg, 20pg, 25pg, 30pg, 35pg, 40pg, 45pg, 50pg, 55pg, 60pg, 70pg, 75pg, 80pg, 85pg, 90pg, 95pg, 100pg, 125pg, 150pg, 175pg, 200pg, 225pg, 250pg, 275pg, 300pg, 325pg, 350pg, 375pg, 400pg, 420pg, 425pg, 450pg g, 475pg, 500pg, 600pg, 700pg, 800pg, 900pg, 1ng, 1.1ng, 1.2ng, 1.3ng, 1.4ng, 1.5ng, 1.6ng, 1.7ng, 1.8ng, 1.9ng, 2n g, 2.1ng, 2.2ng, 2.3ng, 2.4ng, 2.5ng, 2.6ng, 2.7ng, 2.8ng, 2.9ng, 3ng, 3.25ng, 3.5ng, 3.75ng, 4ng, 4.25ng, 4.5ng, 4.In some embodiments, the nucleic acid sample comprises 75 ng or 5 ng of DNA, e.g., genomic DNA, or between any of the aforementioned values. In some embodiments, the nucleic acid sample comprises 10 pg to 10 ng or about 10 pg to 10 ng, 10 pg to 5 ng or about 10 pg to 5 ng, 10 pg to 4 ng or about 10 pg to 4 ng, 10 pg to 3 ng or about 10 pg to 3 ng, 10 pg to 2 ng or about 10 pg to 2 ng, 25 pg to 10 ng or about 25 pg to 10 ng, 25 pg to 5 ng or about 25 pg to 5 ng, 25 pg to 4 ng or about 25 pg to 4 ng, 25 pg to 3 ng or about 25 pg to 3 ng, 25 pg to 2 ng or about 25 pg to 2 ng, is about 25pg~2ng, 40pg~10ng or about 40pg~10ng, 40pg~5ng or about 40pg~5ng, 40pg~4ng or about 40pg~4ng, 40pg~3ng or about 40pg~3ng, 40pg~2ng or about 40pg~2ng, 50pg~10ng or about 50pg~10ng, 50pg~5ng or about 50pg~5ng, 50pg~4ng or about 50pg~4ng, 50pg~3ng or about 50pg~3ng, 50pg~2ng or about 50pg~2ng g, 10pg~2ng or about 10pg~2ng, 10pg~1.5ng or about 10pg~1.5ng, 10pg~1ng or about 10pg~1ng, 20pg~2ng or about 20pg~2ng, 20pg~1.5ng or about 20pg~1.5ng, 20pg~1ng or about 20pg~1ng, 25pg~2ng or about 25pg~2ng, 25pg~1.5ng or about 25pg~1.5ng, 25pg~1ng or about 25pg~1ng, 30pg~2ng or about 30pg~2ng , 30pg~1.5ng or about 30pg~1.5ng, 30pg~1ng or about 30pg~1ng, 35pg~2ng or about 35pg~2ng, 35pg~1.5ng or about 35pg~1.5ng, 35pg~1ng or about 35pg~1ng, 40pg~2ng or about 40pg~2ng, 40pg~1.5ng or about 40pg~1.5ng, 40pg~1ng or about 40pg~1ng, 45pg~2ng or about 45pg~2ng, 45pg~1.5ng or about 45pg~1.5ng, 45pg to 1ng or about 45pg to 1ng, 50pg to 2ng or about 50pg to 2ng, 50pg to 1.5ng or about 50pg to 1.5ng, 50pg to 1ng or about 50pg to 1ng. B. Sample Processing and Amplification

[0076] Various steps were performed to prepare or process the nucleic acid sample for and / or during the assay. Unless otherwise indicated, the preparation or processing steps described below can generally be combined in any manner and in any order to appropriately prepare or process a particular sample for analysis and / or sequencing as disclosed herein.

[0077] In some embodiments, the amount of nucleic acid sample provided is 1 ng of genomic DNA, about 1 ng of genomic DNA, or less than 1 ng of genomic DNA. In some embodiments, the methods disclosed herein include amplification of genomic DNA. In some embodiments, the amplification of genomic DNA includes one or more multiplex polymerase chain reactions (PCRs) including multiple primers, thereby generating an amplification product. In some embodiments, the amplification of genomic DNA includes a single multiplex PCR reaction. In some embodiments, the amplification of genomic DNA includes two multiplex PCR reactions. In some embodiments, the amplification of genomic DNA includes three multiplex PCR reactions. In some embodiments, the amplification of genomic DNA includes four multiplex PCR reactions.

[0078] In some embodiments, one or more primers in the plurality of primers are designed according to the non-existent design strategy described in WO 2015 / 126766, which is incorporated herein by reference in its entirety. In some embodiments, one or more primers in the plurality of primers are at least 24 nucleotides in length, and / or have a melting temperature of less than 60°C, and / or are AT-rich with an AT content of at least 60%. In some embodiments, one or more primers in the plurality of primers comprise at least 24 nucleotides in length that hybridize to the target sequence, and / or have a melting temperature of 50°C to 60°C, and / or are AT-rich with an AT content of at least 60%. In some embodiments, one or more primers in the plurality of primers have a melting temperature of less than 58°C or less than 54°C.

[0079] In some embodiments, genomic DNA may be amplified for multiple cycles using multiple primers that hybridize to and / or tag multiple target sequences that collectively contain a plurality of at least or about 5,000-50,000 single nucleotide polymorphisms (SNPs). In some embodiments, genomic DNA may be amplified for multiple cycles using multiple primers that hybridize to and / or tag multiple target sequences that collectively comprise a plurality of at least or about 5,000-15,000, 20,000, 25,000, 30,000, 35,000, 40,000, 45,000, or 50,000 SNPs. In some embodiments, genomic DNA can be amplified for multiple cycles using multiple primers that hybridize to and / or tag multiple target sequences that collectively contain at least or about 10,000-11,000 SNPs.In some embodiments, the genomic DNA contains at least 7,000-15,000 SNPs, 7,000-14,000 SNPs, 7,000-13,000 SNPs, 7,000-12,000 SNPs, 7,000-11,000 SNPs, 8,000-15,000 SNPs, 8,000-14,000 SNPs, 8,000-15,000 SNPs, 8,000-16,000 SNPs, 8,000-17,000 SNPs, 8,000-18,000 SNPs, 8,000-19,000 SNPs, 8,000-20,000 SNPs, 8,000-21,000 SNPs, 8,000-22,000 SNPs, 8,000-23,000 SNPs, 8,000-24,000 SNPs, 8,000-25,000 SNPs, 8,000-26,000 SNPs, 8,000-27,000 SNPs, 8,000-28,000 SNPs, 8,000-29,000 SNPs, 8,000-30,000 SNPs, 8,000-31,000 SNPs, 8,000-32,000 SNPs, 8,000-33,000 SNPs, 8,000-34,000 SNPs, 8,000-35,000 SNPs, 8,000-36,000 SNPs, 8,000 13,000 SNPs, 8,000-12,000 SNPs, 8,000-11,000 SNPs, 9,000-15,000 SNPs, 9,000-14,000 SNPs, 9,000-13,000 SNPs, 9,000-12,000 SNPs, 9,000-11,000 SNPs or about 7,000-15,000 SNPs , 7,000-14,000 SNPs, 7,000-13,000 SNPs, 7,000-12,000 SNPs, 7,000-11,000 SNPs, 8,000-15,000 SNPs, 8,000-14,000 SNPs, 8,000-13,000 SNPs, 8,000-12,000 SNPs, 8,000-11,000 In some embodiments, the genomic DNA may be amplified multiple cycles using multiple primers that hybridize and / or tag multiple target sequences collectively comprising at least 10,230 or about 10,230 SNPs.

[0080] In some embodiments, the plurality of SNPs comprises at least, or about, 5,000-15,000, 20,000, 25,000, 30,000, 35,000, 40,000, 45,000, or 50,000 SNPs. In some embodiments, the plurality of SNPs is at least 7,000-15,000 SNPs, 7,000-14,000 SNPs, 7,000-13,000 SNPs, 7,000-12,000 SNPs, 7,000-11,000 SNPs, 8,000-15,000 SNPs, 8,000-14,000 SNPs, 8,000-13,000 SNPs, 8,000-12,000 SNPs, 8,000-11,000 SNPs, 9,000-15,000 SNPs, 9,000-14,000 SNPs, 9,000-13,000 SNPs, 9,000-12,000 SNPs, or 9,000-1 1,000 or approximately 7,000-15,000 SNPs, 7,000-14,000 SNPs, 7,000-13,000 SNPs, 7,000-12,000 SNPs, 7,000-11,000 SNPs, 8,000-15,000 SNPs, 8,000-14,000 SNPs, 8,000- In some embodiments, the plurality of SNPs comprises at or about 10,230 SNPs. In some embodiments, the plurality of SNPs is at least 5,000-50,000 SNPs, 5,000-45,000 SNPs, 5,000-40,000 SNPs, 5,000-35,000 SNPs, 5,000-30,000 SNPs, 5,000-25,000 SNPs, 5,000-20,000 SNPs, 6,000-50,000 SNPs, 6,000-45,000 SNPs, 6,000-40,000 SNPs, 6,000-35,000 SNPs, 6,000-30,000 SNPs, 6,000-25,000 SNPs, 6,000-20,000 SNPs, 7,000-50,000 SNPs, 7,000-45,000 SNPs, 7,000-40,000 SNPs, 7,000-35,000 SNPs, 7,000-30,000 SNPs, 7,000-25,000 SNPs, 7,000-20,000 SNPs, 8,000-50,000 SNPs, 8,000-45,000 SNPs, 8,000 ~40,000 SNPs, 8,000-35,000 SNPs, 8,000-30,000 SNPs, 8,000-25,000 SNPs, 8,000-20,000 SNPs, 9,000-50,000 SNPs, 9,000-45,000 SNPs, 9,000-40,000 SNPs, 9,000-35,000 SNPs, 9,000-30,000 SNPs, 9,000-25,000 SNPs or 9,000-20,000 SNPs, or at least about 5,000-50,000 SNPs, 5,000-45 ,000 SNPs, 5,000-40,000 SNPs, 5,000-35,000 SNPs, 5,000-30,000 SNPs, 5,000-25,000 SNPs, 5,000-20,000 SNPs, 6,000-50,000 SNPs, 6,000-45,000 SNPs, 6,000-40,000 SNPs, 6,000-35,000 SNPs, 6,000-30,000 SNPs, 6,000-25,000 SNPs, 6,000-20,000 SNPs, 7,000-50,000 SNPs, 7,000 ~45,000 SNPs, 7,000-40,000 SNPs, 7,000-35,000 SNPs, 7,000-30,000 SNPs, 7,000-25,000 SNPs, 7,000-20,000 SNPs, 8,000-50,000 SNPs, 8,000-45,000 SNPs, 8,000-40,000 SNPs, 8,000-35,000 SNPs, 8,000-30,000 SNPs, 8,000-25,000 SNPs, 8,000-20,000 SNPs, 9,000-50,000 SNPs, 9,000-45,000 SNPs, 9,000-40,000 SNPs, 9,000-35,000 SNPs, 9,000-30,000 SNPs, 9,000-25,000 SNPs or 9,000-20,000 SNPs.

[0081] In some embodiments, the plurality of SNPs comprises SNPs selected from one or more of the group consisting of consanguineous SNPs, ancestral SNPs, identity SNPs, phenotypic SNPs, X-SNPs, and Y-SNPs. In some embodiments, the plurality of SNPs comprises consanguineous SNPs, ancestral SNPs, identity SNPs, phenotypic SNPs, X-SNPs, and Y-SNPs. In some embodiments, the plurality of SNPs comprises consanguineous SNPs.

[0082] In some embodiments, the SNPs do not include SNPs with known medical associations, e.g., SNPs associated with known medical conditions, or SNPs with low minor allele frequency. By excluding SNPs with known medical associations, e.g., SNPs associated with known medical conditions, or SNPs with low minor allele frequency, privacy concerns are limited and genetic health data is protected.

[0083] In some embodiments, the SNPs include SNPs filtered in a plurality of genotype samples. In some embodiments, the SNPs are selected from categories including ancestral SNPs, identity SNPs, kinship SNPs, phenotypic SNPs, X-SNPs, and Y-SNPs. In some embodiments, the ancestral SNPs include 10-100 or about 10-100 SNPs. In some embodiments, the identity SNPs include 10-200 or about 10-200 SNPs. In some embodiments, the kinship SNPs include 7,000-12,000 or about 7,000-12,000 SNPs. In some embodiments, the phenotypic SNPs include 1-50 or about 1-50 SNPs. In some embodiments, the X-SNPs include 10-200 or about 10-200 SNPs. In some embodiments, the Y-SNPs include 10-200 or about 10-200 SNPs. In some embodiments, ancestral SNPs comprise at or about 0-10% of the total number of SNPs. In some embodiments, identity SNPs comprise at or about 0-10% of the total number of SNPs. In some embodiments, consanguineous SNPs comprise at or about 80-100% of the total number of SNPs. In some embodiments, at least or at least about 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98% or 99% of the plurality of SNPs are related SNPs. In some embodiments, 100% of the plurality of SNPs are related SNPs. In some embodiments, the phenotypic SNPs comprise 0-5% or about 0-5% of the total number of SNPs. In some embodiments, the X-SNPs comprise 0-5% or about 0-5% of the total number of SNPs. In some embodiments, the Y-SNPs comprise 0-5% or about 0-5% of the total number of SNPs. In some embodiments, the SNPs do not include medically informative SNPs or minor allele frequency SNPs.The tag region can be any sequence, such as a universal tag region, a capture tag region, an amplification tag region, a sequencing tag region, a UMI tag region, and the like.

[0084] In some embodiments, the target sequences are purified and enriched to generate a library of the original DNA sample, also called a nucleic acid library. In some embodiments, purification combines purification beads with enzymes to purify the amplified target from other reaction components. In some embodiments, the purified target sequences are enriched by amplifying the DNA and adding UDI adapters and sequences required for cluster generation. The UDI adapters can tag the DNA with a unique combination of sequences that identify each sample for analysis.

[0085] In some embodiments, a nucleic acid library is generated from the amplification products, including amplification products produced by any of the methods or embodiments described herein. Thus, in some embodiments, the nucleic acid library comprises amplification products generated by amplifying a nucleic acid sample with a plurality of primers that specifically hybridize to a plurality of target sequences that collectively comprise a plurality of at least or about 5,000-50,000 SNPs.

[0086] In some embodiments, nucleic acid or DNA libraries are normalized for quantification and quality check, and pooled by combining equal amounts of normalized libraries to create a pool of libraries that can be sequenced together on the same flow cell. In some embodiments, quantification comprises the use of fluorescent quantification methods. In some embodiments, quantification comprises quantitative PCR methods. After pooling DNA libraries, they can be denatured and diluted using sodium hydroxide (NaOH)-based methods, and sequencing controls can be added.

[0087] In some embodiments, the nucleic acid library is quantified, normalized, denatured and diluted according to the instructions set forth in the Forenseq Kintelligence kit user guide (Verogen PN: V16000120, the contents of which are incorporated herein by reference in their entirety).

[0088] In some embodiments, the nucleic acid library of the DNA library is prepared for sequencing using massively parallel sequencing using any known suitable method to complement the methods described herein. Sequencing and analysis

[0089] In some embodiments, the nucleic acid library or DNA library described in Section II of this specification can be sequenced using any known suitable method to complement the method described herein, and is not limited to any particular sequencing platform.In some embodiments, the sample disclosed herein can be analyzed using any known suitable method to complement the method described herein.The exemplary method of sequencing and method analysis is described below. A. Sequencing

[0090] In some embodiments, techniques for sequencing the nucleic acid or DNA libraries generated by performing the methods described herein include the use of polymerase-based sequencing by synthesis, ligation-based sequencing, pyrosequencing, or polymerase-based sequencing methods.

[0091] In some embodiments, the nucleic acid library is sequenced according to the instructions in the MiSeq FGx Sequencing System Reference Guide (Document No. VD2018006, the entire contents of which are incorporated herein by reference). In some embodiments, the nucleic acid library to be sequenced is denatured according to the instructions in the MiSeq FGx Sequencing System Reference Guide (Document No. VD2018006).

[0092] In some embodiments, the sequencing method disclosed herein comprises the use of massively parallel sequencing (MPS).In some embodiments, the sequencing method disclosed herein comprises the use of whole genome sequencing (WGS).In some embodiments, the sequencing method disclosed herein comprises the use of microarray.

[0093] In some embodiments, the sequencing methods disclosed herein detect 90% or about 90% of the SNP loci.

[0094] In some embodiments, the sequencing methods disclosed herein generate an output report that includes the results of sequencing the amplification product that contains multiple SNPs. B. Analysis

[0095] In some aspects, the methods disclosed herein involve the use of an analysis module that automatically initiates analysis upon completion of sequencing of a sample (i.e., an amplified product). In some embodiments, the analysis module comprises Universal Analysis Software (UAS).

[0096] In some embodiments, the analytical methods disclosed herein generate an output report that includes the results of sequencing the amplification products that contain multiple SNPs.

[0097] In some embodiments, the sequencing results are analyzed using any suitable sequence analysis software available in the art.

[0098] In some embodiments, the sequencing results are analyzed using Forenseq Universal Analysis Software, such as version 2.1 or 2.2 or later (Verogen, San Diego, CA), following the instructions outlined in the Forenseq Universal Analysis Software Reference Guide, e.g., Document No. VD2019002, the contents of which are incorporated herein by reference in their entirety. Genotype and DNA profile determination

[0099] In some embodiments, the output report containing the results of sequencing the amplification products containing multiple SNPs generated by any of the methods described herein can be used to genotype the sample using any known suitable method to complement the methods described herein. In some embodiments, the output report containing the results of sequencing the amplification products containing multiple SNPs generated by any of the methods described herein can be used to generate a DNA profile using any known suitable method to complement the methods described herein.

[0100] In some embodiments, the DNA profile comprises the genotype for each of a plurality of SNPs. In some embodiments, the DNA profile comprises at least 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98% or 99% of the genotypes of a plurality of SNPs, or at least about 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98% or 99%. In some embodiments, the DNA profile comprises at least 99% or at least about 99% or about 100% of the genotypes of SNPs.

[0101] In some embodiments, the methods disclosed herein include determining hair color, eye color, and biogeographic ancestry. Determining relevance

[0102] In some embodiments, the relevance of the DNA profiles described in Section IV herein can be calculated with reference to one or more reference DNA profiles using any known suitable method to complement the methods described herein.

[0103] In some embodiments, the DNA-based kinship analysis described herein includes the use of GEDmatch PRO. In some embodiments, the DNA-based kinship analysis described herein allows for the generation of reports with minimal user input. In some embodiments, the DNA-based kinship analysis described herein includes the use of an algorithm to calculate a kinship coefficient. In some embodiments, the kinship coefficient determines the relatedness status of a sample or DNA profile with a reference DNA profile on a database. For example, in some embodiments, the kinship coefficient indicates whether each of one or more identified genetic relatives is likely to be a great-great-grandmother, great-great-grandfather, great-grandfather, great-grandmother, grandmother, grandfather, cousin, child of a cousin, or second cousin based on the relative value of the kinship coefficient. In some embodiments, the reference DNA profile is part of a genealogy database.

[0104] In some embodiments, the DNA-based kinship analysis described herein includes identifying genetic relatives to the first, second, third, fourth or fifth degree of kinship or about the first, second, third, fourth or fifth degree of kinship. In some embodiments, the DNA-based kinship analysis described herein includes identifying genetic relatives to more than the first, second, third, fourth or fifth degree of kinship.

[0105] In some embodiments, the DNA-based kinship analysis described herein comprises generating a family tree comprising one or more DNA profiles related to the DNA profile. The family tree can be generated using any available means or methodology.

[0106] In some embodiments, the DNA-based kinship analysis described herein involves identifying suspects through common ancestry.

[0107] In some embodiments, calculating relatedness comprises using a principal component analysis (PCA) method. In some embodiments, calculating relatedness comprises using a PC-Relate method. See, for example, Conomos et al., Model-free Estimation of Recent Genetic Relatedness, Am. J. Hum. Genet., 98(1):127-148 (2016). In some embodiments, calculating relatedness comprises using a principal component analysis on related samples (PC-AiR).

[0108] The PC-AiR method allows for ancestry determination in the presence of known or cryptic relatedness. See, e.g., Conomos et al., Robust Inference of Population Structure for Ancestry Prediction and Correction of Stratification in the Presence of Relatedness, Genet Epidemiol., 2015, 39(4):276-293, the entire contents of which are incorporated herein by reference. However, PC-Relate and PC-AiR were developed at a time when researchers routinely dealt with determining relatedness using hundreds to fewer than a few thousand samples (e.g., reference DNA profiles), rather than having access to databases of, e.g., tens of thousands of samples, hundreds of thousands of samples, or even more than a million samples, e.g., about 1.5 million samples, as researchers have access to today. Thus, in building models for calculating relatedness, part of the effort was to include as many samples as possible and to place much less pressure on computational efficiency.

[0109] Although the PC-AiR method is feasible for calculating relatedness when the total number of samples (e.g., reference DNA profiles) is small, e.g., less than 5,000 samples, when scaled to a significantly larger number of samples, such as in forensic or kinship databases, it requires either (a) a large amount of calculations that scale exponentially with the number of samples, or (b) the use of different data structures to reduce computational complexity at the expense of requiring a large amount of memory, e.g., random access memory (RAM). Furthermore, the development of PC-AiR was likely driven by the need to perform analyses in GWAS studies, where users generally need to perform analyses only once or only a few times after data collection, e.g., after milestones, rather than continuous analyses as required by the ever-growing databases for forensic science. Thus, the PC-AiR method is not feasible for use with small numbers of samples, e.g., less than 5,000, more than tens of thousands of samples, hundreds of thousands of samples, or even one million or more samples, e.g., about 1.5 million samples, due to, among other things, the significant increase in computational resources and the time required to complete the analysis. Therefore, an alternative approach to the PC-AiR method is described herein for use with a large number of samples, for example at least 5,000 samples, which allows lower computational complexity than PC-AiR while providing acceptable results regarding the relatedness of DNA profile to reference DNA profile.This alternative approach is referred to herein as "large-scale cohort" method.Large-scale cohort method is intended to be used when the number of samples, for example the number of reference DNA profiles, is very large, and therefore, due to the large number of available samples, it is less necessary to include as many samples as possible when building models, thereby achieving computational efficiency.

[0110] In some embodiments, both the PC-AiR method and the large-scale cohort method described herein include an unrelated set picking process that starts and ends in the same place, with (1) an input that is a cohort of samples with genotypes at a set of selected SNPs, e.g., multiple SNPs; and (2) an output that is the identity of a set of unrelated samples within the input cohort of samples. The goal of this process is to identify a well-accepted unrelated sample set that is as close to large as possible while still adequately sampling from all ancestral backgrounds present in the cohort of samples.

[0111] In some embodiments, both the PC-AiR method and the large-scale cohort method described herein include the same first step of estimating kinship between all pairs of samples using a simplified kinship estimation method called "KING-Robust". This step is computationally complex. The PC-AiR method and the large-scale cohort method then diverge, and the PC-AiR method then proceeds to the subsequent steps, which are very complex: (1) initialize a set "U" with all samples, (2) scan the set and calculate, for each sample, the number of samples to which it is related to U (called "R") and the number of samples that are "ancestrally branched" from U (called "D"); (3) select the sample with the highest U, and if there are multiple samples with the highest U, select the sample with the highest U and the lowest D, then remove it from U, and (4) repeat from step 2. For example, using the PC-AiR method, if there are 50,000 samples, the process will be repeated for 50,000 samples in the first iteration. 2 data points, 49,999 in the second iteration 2 data points and repeat until there are no more relevant samples in the set, e.g., 20,000 2 Pieces or 10,000 2The PC-AiR method can go up to 10,000 data points. Thus, the PC-AiR method may be feasible when the total number of samples is small, e.g., 2,000, but when the total number of samples is significantly larger, e.g., 10,000, or 50,000, or 100,000 or more samples, it requires either (a) a large amount of calculations that scale exponentially with the number of samples, or (b) the use of different data structures to reduce the computational complexity at the expense of requiring a large amount of memory, e.g., RAM. Thus, the PC-AiR method is not feasible when using a large number of samples, e.g., 10,000 or more samples, where one wishes to obtain results within minutes to hours (rather than days to months), due to the computational complexity, resources, and long time required by the PC-AiR method.

[0112] Thus, in some embodiments, calculating relatedness involves the use of a large cohort method (which is an alternative approach to PC-AiR that is suitable for large sample sizes) that includes the following adjustments to the PC-AiR method: (1) redefining "related" more stringently, for example, by specifically using a KING-Robust kinship of ≧0.01 instead of ≧0.025 as in the PC-AiR method; (2) removing all samples with >5% missing genotypes (e.g., >5% of SNPs in the reference DNA profile) to ensure that each sample is sufficiently informative; and (3) adding a 100% genotype to each sample. (4) rank all samples by R (ascending) and D (descending), and (5) iterate through the list of ranked samples and either (i) if the sample is not already in the "associated" set, add it to the unassociated set and add all samples from S (i.e., reference DNA profiles associated with the DNA profile) to the associated set, or (ii) if the sample is in the "associated" set, ignore the sample and move on to the next sample. This large-cohort method is of mostly linear rather than exponential complexity (i.e., the runtime scales linearly with the number of samples), thus allowing a process that is tractable with much larger sample cohorts than those for which PC-AiR can be used, e.g., at least 5,000 or more reference DNA profiles.

[0113] In some embodiments, calculating relatedness involves using an improved version of PC-AiR that (1) redefines "related" more stringently, e.g., by specifically using a KING-Robust kinship of ≧0.01 instead of ≧0.025 as in the PC-AiR method, and (2) removes all samples with >5% missing genotypes (e.g., >5% SNPs in the reference DNA profile). In some embodiments, an improved version of PC-AiR (a) calculates for each sample ("R", the total number of related samples in all datasets, "D", the number of ancestral branch samples in the dataset, and "S", the set of related samples), (b) rank all samples by R (ascending) and D (descending), (c) iterate through the list of ranked samples, and in some embodiments, (i) if the sample is not already in the "related" set, add it to the unrelated set and add all samples from S (i.e., the reference DNA profile related to the DNA profile) to the related set, or (ii) if the sample is in the "related" set, ignore the sample and move on to the next sample.

[0114] In some embodiments, calculating relatedness comprises PC-AiR method. In some embodiments, PC-AiR method comprises: (1) performing KING-Robust kinship estimation between all pairs of sample sets comprising samples comprising one or more reference DNA profiles, wherein pairings with a kinship coefficient of >0.025 are identified as related, and pairings with a kinship coefficient of <-0.025 are identified as ancestrally diverged; (2) initializing an unrelated sample set as comprising all samples; and (3) iteratively: (i) identifying a set in the unrelated sample set that has the most related samples in the unrelated sample set, thereby designating it as X; (ii) identifying a set of samples in X that has at least ancestrally diverged pairings compared to the samples in the unrelated sample set, thereby designating it as Y; (iii) if Y has 0 samples, terminate the process, or if Y has at least 1 sample, randomly select one sample from Y and remove it from U, and repeat starting from step (3)(i).

[0115] In some embodiments, the step of calculating relatedness comprises a large-cohort method including: (1) performing KING-Robust kinship estimation between all pairs of sample sets containing one or more reference DNA profiles, where pairings with a kinship coefficient of >0.01 are identified as related and pairings with a kinship coefficient of <-0.025 are identified as ancestrally separated; (2) removing all reference DNA profiles with ≧5% missing data; and (3) ranking all reference DNA profiles by identifying each reference DNA profile with a ranking value. In some embodiments, the ranking value is determined based on the number of related reference DNA profiles in the full set of reference DNA profiles ranked from smallest to largest, and blood ties are broken by the number of ancestral reference DNA profiles in the full set of reference DNA profiles ranked from largest to smallest, and for each reference DNA profile, iteratively through the ranked reference DNA profiles: (i) if the reference DNA profile is not already in the related sample set, add it to the unrelated sample set and add all related reference DNA profiles to the related sample set; and (ii) if the reference DNA profile is already in the related sample set, skip to the next reference DNA profile and repeat starting from step (3)(i).

[0116] In some embodiments, the one or more reference DNA profiles include 1 to 10 million or more reference DNA profiles. In some embodiments, the one or more reference DNA profiles include 1, 5, 25, 50, 75, 100, 500, 1,000, 1,500, 2,000, 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1000,000, 1100,000, 1250,000, 1500,000, 1750,000, 200,000, 2250,000, 2500,000, 2750,000, 300,000, 400,000, 500,000, 600,000, 700,000, 1000,000, 1250,000, 1500,000, 1750,000, 200,000, 2250,000, 2500,000, 2750,000, 300,000 00,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or about 1, 5, 25, 50, 75, 100, 500, 1,000, 1,500, 2,000, 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125, 000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000 ,000, 1,500, 2,000, 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or at least about 1, 5, 25, 50, 75, 100, 500, 1,000, 1,500, 2,000, 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, The method comprises the steps of: 50,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000 reference DNA profiles, or a range between any two of the aforementioned values. In some embodiments, the one or more reference DNA profiles include up to 100, 500, 1,000, 1,500, 2,000, 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 1 50,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000 , 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or up to about 100, 500, 1,000, 1,500, 2,000, 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 7 5,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000 reference DNA profiles. In some embodiments, the one or more reference DNA profiles include 5,000 to 500,000, or 10,000 to 500,000, or 15,000 to 500,000, or 20,000 to 500,000, or 25,000 to 500,000, or 25,000 to 400,000, or 25,000 to 300,000, or 25,000 to 250,000, or 50,000 to 500,000, or 50,000 to 400,000, or 50,000 to 300,000, or 50,000 to 250,000 reference DNA profiles.

[0117] In some embodiments, calculating the degree of relatedness includes use of the PC-AiR method, and the one or more reference DNA profiles include at least 1 and up to 100, 200, 300, 400, 500, 600, 700, 800, 900, 1,000, 1,100, 1,200, 1,300, 1,400, 1,500, 1,600, 1,700, 1,800, 1,900, 2,000, 2,100, 2,200, 2,300, 2,400, 2,500, 2,600, 2,700, 2,800, 2,900, 3,000, 3,500, 4,000, 4,500, or 5,000 reference DNA profiles, or a range between any two of the aforementioned values.

[0118] In some embodiments, the step of calculating the degree of association comprises using a large cohort method, wherein the one or more reference DNA profiles are 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000, 0,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000 units, or about 3,000, 4,000, 5,000, 10,000, 20,000 units 0, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000 , 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or at least 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000 0, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or at least about 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000 reference DNA profiles, or a range between any two of the aforementioned values. kit

[0119] Provided herein are kits containing any of the primers, reagents or compositions described herein, which may further include instructions on how to use the kit, such as the uses described herein. The kits described herein may also include other materials desirable from a commercial and user standpoint, including other buffers, diluents, filters, and package inserts containing instructions for carrying out the methods described herein. Exemplary embodiments

[0120] Among the exemplary embodiments provided herein are the following: 1. A method for performing DNA-based kinship analysis, comprising: Providing a nucleic acid sample; amplifying the nucleic acid sample with a plurality of primers that specifically hybridize to a plurality of target sequences that collectively comprise a plurality of at least or about 5,000 to 50,000 single nucleotide polymorphisms (SNPs), thereby generating amplification products, wherein the amplification is performed in one or more multiplex PCR reactions; generating a nucleic acid library from the amplification products; sequencing the nucleic acid library generated from the amplification products; and analyzing the sequence of the amplification product; genotyping the plurality of SNPs, thereby generating a DNA profile; and calculating a degree of relatedness between said DNA profile and one or more reference DNA profiles; The method includes: 2. A method for performing DNA-based kinship analysis, comprising: Providing a nucleic acid sample; amplifying the nucleic acid sample with a plurality of primers that specifically hybridize to a plurality of target sequences that collectively comprise a plurality of at least or about 5,000 to 50,000 single nucleotide polymorphisms (SNPs), thereby generating amplification products, wherein the amplification is performed in one or more multiplex PCR reactions; generating a nucleic acid library from the amplification products; sequencing the nucleic acid library generated from the amplification products; and genotyping the plurality of SNPs, thereby generating a DNA profile; and calculating a degree of relatedness between said DNA profile and one or more reference DNA profiles; The method includes: 3. The method of embodiment 1 or embodiment 2, wherein the sequencing is performed using massively parallel sequencing (MPS). 4. The method of any one of embodiments 1 to 3, wherein the sequencing does not include whole genome sequencing (WGS). 5. The method of any one of embodiments 1 to 4, further comprising generating a family tree comprising said DNA profile associated with one or more DNA profiles. 6. A method for constructing a nucleic acid library, comprising: Providing a nucleic acid sample; amplifying the nucleic acid sample with a plurality of primers that specifically hybridize to a plurality of target sequences that collectively comprise at least or about 5,000 to 50,000 single nucleotide polymorphisms (SNPs), thereby generating a nucleic acid library comprising amplified products, wherein the amplification is performed in one or more multiplex PCR reactions; The method includes: 7. The method of any one of embodiments 1 to 6, wherein the nucleic acid sample comprises genomic DNA. 8. The method of any one of embodiments 1 to 7, wherein the nucleic acid sample contains one or more enzyme inhibitors. 9. The method of embodiment 8, wherein the one or more enzyme inhibitors comprise one or more inhibitors selected from the group consisting of hematin, heme, humic acid, indigo, and tannic acid. 10. The method of any one of embodiments 1 to 9, wherein the nucleic acid sample contains low quality and / or low abundance nucleic acid molecules. 11. The method of embodiment 10, wherein the low quality nucleic acid molecules are degraded and / or fragmented genomic DNA. 12. The low quality nucleic acid molecules have a degradation index (DI) of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195 or 200, or at least 1, 2 12. The method of claim 10 or 11, wherein the decomposition index (DI) is 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195 or 200. 13. The method of embodiment 10 or embodiment 11, wherein the low quality nucleic acid molecules have a DI of at least 1 and at most 158.3 or less. 14. The method of any one of embodiments 1 to 9, wherein the nucleic acid sample contains high quality nucleic acid molecules. 15. The method of embodiment 14, wherein the high quality nucleic acid molecules have a DI of less than 1. 16. A method according to any one of embodiments 1 to 15, wherein the nucleic acid sample is a forensic sample. 17. A method according to any one of embodiments 1 to 16, wherein the nucleic acid sample is derived from saliva, blood, semen, hair, teeth or bone. 18. The method of embodiment 17, wherein the nucleic acid sample is derived from saliva, blood or semen. 19. The method of any one of embodiments 1 to 16, wherein the nucleic acid sample is derived from a buccal swab, paper, fabric or other substrate impregnated with saliva, blood, semen or other bodily fluid. 20. The method of any one of embodiments 1 to 19, wherein the nucleic acid sample comprises between 50 pg and 100 ng, or about 50 pg and 100 ng, of genomic DNA. 21. The method of any one of embodiments 1 to 20, wherein the nucleic acid sample comprises between 100 pg and 5 ng, or about 100 pg and 5 ng, of genomic DNA, or between 50 pg and 5 ng, or about 50 pg and 5 ng, of genomic DNA. 22. The method of embodiment 20 or embodiment 21, wherein the nucleic acid sample comprises 1 ng or about 1 ng of genomic DNA. 23. A method according to any one of embodiments 1 to 22, wherein the plurality of SNPs comprises kinship SNPs (kiSNPs). 24. The method of any one of embodiments 1 to 23, wherein the plurality of SNPs comprises kiSNPs, biogeographical ancestry SNPs (aiSNPs), identity SNPs (iiSNPs), phenotypic SNPs (piSNPs), x chromosome SNPs (xSNPs) and y chromosome SNPs (ySNPs). 25. The method of any one of embodiments 1 to 23, wherein the plurality of SNPs comprises SNPs selected from one or more of the group consisting of kiSNPs, aiSNPs, iiSNPs, piSNPs, xSNPs and ySNPs. 26. The method of any one of embodiments 23-25, wherein at least or at least about 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98% or 99% of the plurality of SNPs are related SNPs. 27. A method for calculating relatedness, comprising: Obtaining a DNA profile including genotypes of at least or about 5,000 to 50,000 SNPs; calculating a degree of relatedness between said DNA profile and one or more reference DNA profiles; The method includes: 28. A method for calculating relatedness, comprising: generating a DNA profile comprising genotypes for at least or about 5,000-50,000 SNPs; calculating a degree of relatedness between said DNA profile and one or more reference DNA profiles; The method includes: 29. Calculating the relevance (1) performing KING-Robust relatedness estimation between all pairs of a sample set containing one or more reference DNA profiles, where pairings with a relatedness coefficient of >0.01 are identified as closely related and pairings with a relatedness coefficient of <-0.025 are identified as ancestrally diverged; (2) removing all reference DNA profiles with ≥5% missing data; and (3) ranking all reference DNA profiles by identifying each reference DNA profile with a ranking value, where the ranking value is determined based on the number of related reference DNA profiles in the full set of reference DNA profiles ranked from smallest to largest, where the relatedness is determined based on the number of related reference DNA profiles in the full set of reference DNA profiles ranked from smallest to largest. 29. The method of any one of embodiments 1 to 28, comprising a large-scale cohort method comprising: breaking the relationship by the number of ancestrally branched reference DNA profiles in the full set of reference DNA profiles ranked from maximum to minimum, and for each reference DNA profile, iteratively through the ranked reference DNA profiles: (i) if the reference DNA profile is not already in the associated sample set, add it to an unassociated sample set and add all associated reference DNA profiles to the associated sample set; and (ii) if the reference DNA profile is already in the associated sample set, skip to the next reference DNA profile and repeat starting from step (3)(i). 30. The one or more reference DNA profiles are 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2, 000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or about 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, ,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or at least 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or at least about 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,30,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000 reference DNA profiles. 31. The one or more reference DNA profiles are selected from the group consisting of 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 00, 5,000,000 or 10,000,000 or about 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4, 000,000, 5,000,000 or 10,000,000 or at least 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3, 000,000, 4,000,000, 5,000,000 or 10,000,000, or at least about 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000,The method according to any one of embodiments 1 to 5 and 7 to 29, comprising 0,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000 reference DNA profiles. 32. A nucleic acid library constructed using the method of any one of embodiments 6 to 31. 33. A plurality of primers that specifically hybridize to a plurality of target sequences comprising at least 5,000-50,000 or about 5,000-50,000 single nucleotide polymorphisms (SNPs) in a nucleic acid sample, wherein amplification of the nucleic acid sample using the plurality of primers in one or more multiplex PCR reactions results in amplification products. 34. The plurality of primers of embodiment 33, wherein the nucleic acid sample comprises genomic DNA. 35. The multiple primers of embodiment 33 or embodiment 34, wherein the nucleic acid sample comprises one or more enzyme inhibitors. 36. The multiple primers of embodiment 35, wherein the one or more enzyme inhibitors comprise one or more inhibitors selected from the group consisting of hematin, heme, humic acid, indigo, and tannic acid. 37. A plurality of primers described in any one of embodiments 23 to 36, wherein the nucleic acid sample comprises low quality and / or low abundance nucleic acid molecules. 38. The multiple primers of embodiment 37, wherein the low quality nucleic acid molecules are degraded and / or fragmented genomic DNA. 39. The low quality nucleic acid molecules have a degradation index (DI) of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195 or 200, or at least 1, 2, 3, 39. The plurality of primers of embodiment 37 or embodiment 38 having a degradation index (DI) of 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195 or 200. 40. A plurality of primers described in any one of embodiments 37 to 39, wherein the low quality nucleic acid molecules have a DI of at least 1 and a maximum of 158.3 or less. 41. A plurality of primers described in any one of embodiments 33 to 36, wherein the nucleic acid sample comprises high quality nucleic acid molecules. 42. The multiple primers of embodiment 41, wherein the high quality nucleic acid molecules have a DI of less than 1. 43. The plurality of primers described in any one of embodiments 33 to 42, wherein the nucleic acid sample is a forensic sample. 44. A plurality of primers described in any one of embodiments 33 to 43, wherein the nucleic acid sample is derived from a buccal swab, paper, fabric or other substrate impregnated with saliva, blood, or other bodily fluid. 45. The plurality of primers of any one of embodiments 33 to 44, wherein the nucleic acid sample comprises between 50 pg and 100 ng, or between about 50 pg and 100 ng, of genomic DNA. 46. ​​A plurality of primers according to any one of embodiments 33 to 45, wherein the nucleic acid sample comprises between 100 pg and 5 ng, or between about 100 pg and 5 ng, of genomic DNA, or between 50 pg and 5 ng, or between about 50 pg and 5 ng, of genomic DNA. 47. The plurality of primers described in embodiment 45 or embodiment 46, wherein the nucleic acid sample comprises 1 ng or about 1 ng of genomic DNA. 48. A plurality of primers described in any one of embodiments 33 to 47, wherein the plurality of SNPs comprises kinship SNPs (kiSNPs). 49. The plurality of primers described in any one of embodiments 33 to 48, wherein the plurality of SNPs comprises kiSNPs, biogeographical ancestry SNPs (aiSNPs), identity SNPs (iiSNPs), phenotypic SNPs (piSNPs), x chromosome SNPs (xSNPs) and y chromosome SNPs (ySNPs). 50. A plurality of primers described in any one of embodiments 33 to 48, wherein the plurality of SNPs comprises SNPs selected from one or more of the group consisting of kiSNPs, aiSNPs, iiSNPs, piSNPs, xSNPs and ySNPs. 51. The plurality of primers according to any one of embodiments 48 to 50, wherein at least or at least about 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98% or 99% of the SNPs of the plurality are related SNPs. 52. A method for constructing a DNA profile, comprising: Providing a nucleic acid sample; amplifying the nucleic acid sample with a plurality of primers that specifically hybridize to a plurality of target sequences that collectively comprise a plurality of at least or about 5,000 to 50,000 single nucleotide polymorphisms (SNPs), thereby generating amplification products, wherein the amplification is performed in one or more multiplex PCR reactions; sequencing the amplification products; and genotyping the plurality of SNPs, thereby generating a DNA profile; and The method includes: 53. The method of embodiment 52, wherein the sequencing does not include whole genome sequencing (WGS). 54. The method of embodiment 52 or embodiment 53, wherein the nucleic acid sample comprises genomic DNA. 55. The method of any one of embodiments 52 to 54, wherein the nucleic acid sample contains one or more enzyme inhibitors. 56. The method of embodiment 55, wherein the one or more enzyme inhibitors comprise one or more inhibitors selected from the group consisting of hematin, heme, humic acid, indigo, and tannic acid. 57. The method of any one of embodiments 52 to 56, wherein the nucleic acid sample contains low quality and / or low abundance nucleic acid molecules. 58. The method of embodiment 57, wherein the low quality nucleic acid molecules are degraded and / or fragmented genomic DNA. 59. The low quality nucleic acid molecule has a degradation index (DI) of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195 or 200, or at least 1, 2 59. The method of embodiment 57 or embodiment 58, wherein the decomposition index (DI) is 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195 or 200. 60. A method according to any one of embodiments 57 to 59, wherein the low quality nucleic acid molecules have a DI of at least 1 and at most 158.3 or less. 61. The method of any one of embodiments 52 to 56, wherein the nucleic acid sample contains high quality nucleic acid molecules. 62. The method of embodiment 61, wherein the high-quality nucleic acid molecules have a DI of less than 1. 63. The method of any one of embodiments 52 to 62, wherein the nucleic acid sample is a forensic sample. 64. The method of any one of embodiments 52 to 63, wherein the nucleic acid sample is derived from a buccal swab, paper, fabric or other substrate impregnated with saliva, blood or other bodily fluid. 65. The method of any one of embodiments 52 to 64, wherein the nucleic acid sample comprises between 50 pg and 100 ng, or about 50 pg and 100 ng, of genomic DNA. 66. The method of any one of embodiments 52 to 65, wherein the nucleic acid sample comprises between 100 pg and 5 ng, or about 100 pg and 5 ng, of genomic DNA or between 50 pg and 5 ng, or about 50 pg and 5 ng, of genomic DNA. 67. The method of embodiment 65 or embodiment 66, wherein the nucleic acid sample comprises 1 ng or about 1 ng of genomic DNA. 68. A method according to any one of embodiments 52 to 67, wherein the plurality of SNPs comprises consanguineous related SNPs. 69. The method of any one of embodiments 52 to 68, wherein the plurality of SNPs comprises kiSNPs, biogeographical ancestry SNPs (aiSNPs), identity SNPs (iiSNPs), phenotypic SNPs (piSNPs), x chromosome SNPs (xSNPs) and y chromosome SNPs (ySNPs). 70. The method of any one of embodiments 52 to 69, wherein the plurality of SNPs comprises SNPs selected from one or more of the group consisting of kiSNPs, aiSNPs, iiSNPs, piSNPs, xSNPs and ySNPs. 71. The method of any one of embodiments 68-70, wherein at least or at least about 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98% or 99% of the plurality of SNPs are related SNPs. 72. A method for identifying genetic relatives of a DNA profile, comprising: Calculating the degree of association between the DNA profile according to any one of embodiments 52 to 71 and one or more reference DNA profiles; generating a pedigree comprising said DNA profile related to said one or more reference DNA profiles; The method includes: 73. The method of embodiment 72, further comprising generating a family tree comprising the DNA profile associated with one or more DNA profiles. 74. The method of embodiment 72 or embodiment 73, wherein the one or more reference DNA profiles are part of a genealogy database. 75. The one or more reference DNA profiles are 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2, 000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or about 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, ,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or at least 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or at least about 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,75. The method of any one of embodiments 72 to 74, comprising 000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000 reference DNA profiles. 76. The one or more reference DNA profiles are selected from the group consisting of 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 00, 5,000,000 or 10,000,000 pieces, or about 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 27 5,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,0 00,000, 5,000,000 or 10,000,000 pieces, or at least 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000 ,000, 4,000,000, 5,000,000 or 10,000,000 pieces, or at least about 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,75. The method of any one of embodiments 72 to 74, comprising 1,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000 reference DNA profiles. 77. A method for identifying genetic relatives of a DNA profile, comprising: Calculating a degree of association between a DNA profile containing genotypes of at least 5,000 to 50,000 or about 5,000 to 50,000 SNPs and a reference DNA profile; generating a pedigree comprising said DNA profile related to said one or more reference DNA profiles; The method includes: 78. The method described in embodiment 77, wherein the DNA is produced by a method described in any one of embodiments 52 to 71. 79. A kit comprising at least one container means, said at least one container means comprising a plurality of the primers of any one of embodiments 33-51. 80. The plurality of SNPs is about 7,000 to 15,000 SNPs, 7,000 to 14,000 SNPs, 7,000 to 13,000 SNPs, 7,000 to 12,000 SNPs, 7,000 to 11,000 SNPs, 8,000 to 15,000 SNPs, 8,000 to 14,000 SNPs, 8,000 to 13,000 SNPs, or 8,000 to 15,000 SNPs. 80. The method according to any one of embodiments 1 to 31, 51 to 71 and 77, comprising 0 to 12,000 SNPs, 8,000 to 11,000 SNPs, 9,000 to 15,000 SNPs, 9,000 to 14,000 SNPs, 9,000 to 13,000 SNPs, 9,000 to 12,000 SNPs or 9,000 to 11,000 SNPs. 81. The method of any one of embodiments 1-31, 51-71, and 77, wherein the plurality of SNPs comprises 10,230 SNPs. 82. The plurality of SNPs may be about 7,000 to 15,000 SNPs, 7,000 to 14,000 SNPs, 7,000 to 13,000 SNPs, 7,000 to 12,000 SNPs, 7,000 to 11,000 SNPs, 8,000 to 15,000 SNPs, 8,000 to 14,000 SNPs, 8,000 to 13,000 SNPs, or 8,000 to 15,000 SNPs. 52. The plurality of primers according to any one of embodiments 33 to 51, comprising: 8,000 to 12,000 SNPs, 8,000 to 11,000 SNPs, 9,000 to 15,000 SNPs, 9,000 to 14,000 SNPs, 9,000 to 13,000 SNPs, 9,000 to 12,000 SNPs, or 9,000 to 11,000 SNPs. 83. A plurality of primers described in any one of embodiments 33 to 51, wherein the plurality of SNPs comprises 10,230 SNPs. 84. A method according to any one of embodiments 7 to 31, 52 to 71 and 77, further comprising generating a family tree comprising said DNA profile related to one or more DNA profiles. EXAMPLES

[0121] The following examples are included for illustrative purposes only and are not intended to limit the scope of the invention. Example 1: Generation of sequence libraries and determination of sensitivity

[0122] This example describes a method to determine the sensitivity of the multiplex polymerase chain reaction described herein to generate a sequenceable library. Figure 1 shows an exemplary schematic diagram of the method for generating a sequenceable library described in this example. A. PCR Amplification of Genomic DNA Targets

[0123] A multiplex polymerase chain reaction was performed to amplify 10,230 individual amplicons in a genomic DNA sample. Each primer pair was designed to selectively hybridize to and promote the amplification of a specific single nucleotide polymorphism (SNP) in the genomic DNA sample. Input genomic DNA of 50ng to 50pg, more specifically, 5ng, 2.5ng, 1ng, 500pg, 250pg, 100pg and 50pg, was tested. Briefly, 18.5ml of PCR master mix containing sufficient buffer, dNTPs, MgCl2, salts and PCR additives such as glycerol was added to a single well of a 96-well PCR plate. 10,530 primer pairs, 2-4 units of DNA polymerase such as Phusion hot start DNA polymerase (Thermo Fisher, catalog no. F549L or any other thermostable DNA polymerase, 5 microliters of primer pool containing 50ng to 50pg of genomic DNA were also added.

[0124] The PCR plate was sealed and placed in a thermal cycler (Veriti 96-well thermal cycler, Thermo Fisher Scientific, 4413964) and run with the temporate profile described below to generate the amplicon library. 98°C for 3 min 18 cycles: 96°C for 45 seconds 80℃ for 10 seconds 54°C for 4 minutes, applicable lamp mode 66°C for 90 seconds, applicable lamp mode 68°C for 10 min Hold at 4°C

[0125] After cycling, the amplicon library was kept at 2-8 °C until proceeding to the purification steps outlined below. B. Purification of amplicons from input DNA and primers

[0126] Two rounds of purification using MagBind Total Pure NGS beads (Omega Biotek, M1378-02) binding, washing, and elution at 1.6x and 0.6x volume ratios were found to remove genomic DNA and unbound or excess primers. The amplification and purification steps outlined herein produce amplicons approximately 150-350 bp long. The purified amplicons are then used in a second round of PCR to add adapters for sequencing. C. Enrichment of Purified Amplicons to Generate a Sequence-Ready Library

[0127] A second round of PCR amplification is performed in a 96-well PCR plate by combining 25 ml of purified amplicons from the above step with 5 ml of adapters provided in the Forenseq Kintelligence kit (Verogen PN:V16000120) and 20 ml of KPCR2 master mix provided in the Forenseq Kintelligence kit (Verogen PN:V16000120). The PCR plate is sealed and placed in a thermal cycler (Veriti 96-well thermal cycler, Thermo Fisher Scientific, 4413964) and run with the temporate profile described below to generate the amplicon library. 98°C for 30 seconds 15 cycles: 98°C for 20 seconds 66°C for 30 seconds 72°C for 30 seconds 72°C for 1 min Hold at 4°C

[0128] The library was purified using MagBind Total Pure NGS beads (Omega Biotek, M1378-02), binding, washing, and elution at 1x. The purified library is quantified, normalized, denatured, and diluted according to the instructions provided in the Forenseq Kintelligence kit user guide (Verogen PN: V16000120, the entire contents of which are incorporated herein by reference).

[0129] The denatured libraries were sequenced according to the instructions in the MiSeq FGx Sequencing System Reference Guide (Document No. VD2018006, the entire contents of which are incorporated herein by reference). As shown in Figure 2, the number of loci detected was similar across the range of input genomic DNA dose adjustments.

[0130] Results are analyzed using Forenseq Universal Analysis Software 2.1 (Verogen, San Diego, CA) according to the instructions outlined therein and provided in reference guide document number VD2019002, the entire contents of which are incorporated herein by reference. Example 2: Generation of sequence libraries using degraded DNA

[0131] This example describes the sequencing of DNA from small and highly degraded samples. Degraded DNA A series of degraded blood DNA was obtained from Innogenomics (New Orleans, LA). The DNA samples were used to generate sequencing libraries as described in Example 1, except that in this example, primer pairs for 10,327 loci were used. Figure 3 shows the percentage of loci (call rate) detected in degraded DNA using the assay described herein compared to microarray (GSA) call rate. The degradation index (DI) is shown on the x-axis and the number of loci detected is shown on the y-axis. These results show that even in highly degraded DNA with a DI of 158.3, the assay detects 9167 loci, which is sufficient to upload to a genealogy database to search for relatives. Alternative techniques such as microarrays were unable to detect loci in samples with high degradation index. Example 3: Evaluation of inhibitor activity on library preparations

[0132] This example describes the evaluation of the effect of PCR inhibitors on the preparation of libraries disclosed herein. DNA samples from crime scenes often contain co-purifying impurities that inhibit PCR. PCR inhibition is the most common cause of PCR failure when adequate copies of DNA are present. Humic compounds are a set of substances produced during the decay process and have been considered as contaminating substances for DNA in soils, natural waters and recent sediments. Other common inhibitors include hematin (derived from blood), indigo (derived from blue jean) and tannic acid.

[0133] To assess the impact of inhibitors commonly found in forensic samples, library preparation was performed as described in Example 1, except that 200 uM hematin, 50 ng / uL humic acid, 133 uM indigo, and 16 uM tannic acid were spiked into the "amplify and tag target" step above, and primer pairs for 10380 loci were used. The results are shown in Figure 4, with the PCR reaction without any inhibitors labeled as a control. Example 4: Determining relevance

[0134] This example describes exemplary results from samples prepared as generally described in Example 1 above.

[0135] Illumina Global Screening Array (GSA) 2.0 was run on 200 ng of each of the 17 samples of Utah CEPH family 1463 DNA (Coriell Institute). SNP calls were uploaded to the GEDmatch database (Verogen). An exemplary pedigree is shown in Figure 5. One of the samples, NA12889 (paternal grandfather), was run through the library preparation protocol as described in Example 1 and run through the ForenSeq UAS 2.1 module. The report generated was uploaded to a database and searched using the 1:multi tool for searching relationships. The relatedness coefficients from the algorithm in the database were compared to the expected relatedness coefficients. The expected and observed relatedness coefficients are shown in Figure 6. Example 5: Determining kinship coefficients in an illustrative case study

[0136] This example describes the results of an exemplary case study using sample SNP profiles to determine relatedness coefficients. Ten established pedigrees with 12-28 family members in the GEDmatch database were used to test the ability of the 1:many search algorithm to detect potential relatives. The sample SNP profile from the assay disclosed herein was considered to be Mr. X = POI (person of interest / unknown crime scene profile). Candidate hits, relatedness coefficients and relative status are shown in Figure 7.

[0137] The results generated from the search algorithm were then used to generate a family tree for Mr. X, as shown in Figure 8. As shown in the family tree, Mr. X's third degree relationships, cousin (1C) and great-grandfather (G GF), were returned within the first 11 candidate hits. Mr. X's great-grandmother (GG GM), great-great-uncle (GG Uncle) and cousin's child (1C1R), were fourth degree relationships, and were returned within the first 15 candidate hits. Mr. X's fifth degree relationship, second cousin (2C), was the 12th hit. Example 6: Generation of sequence libraries and determination of sensitivity, including evaluation by locus type

[0138] This example involves a method to determine the sensitivity of the multiplex polymerase chain reaction described herein to generate a sequenceable library, including an assessment by locus type.

[0139] Sequence libraries (sequenced nucleic acid libraries), also called DNA profiles, were generated in the same manner as described in Example 1, except that the results were analyzed using Forenseq Universal Analysis Software version 2.2.

[0140] The results are shown in Figure 9, which is a table summarizing the number of loci detected (as an average of three replicates) based on the amount of input DNA (ng) for each of the different types of loci, e.g., y chromosome SNPs (ySNPs), x chromosome SNPs (xSNPs), phenotypic SNPs (piSNPs), kinship SNPs (kiSNPs), identity SNPs (iiSNPs), and biogeographical SNPs (aiSNPs), out of a total of 10,230 loci analyzed. Input dose adjustments of genomic DNA tested included 5ng, 2.5ng, 1ng, 0.5ng (500pg), 0.25ng (250pg), 0.10ng (100pg), and 0.05ng (50pg) of input genomic DNA. As shown in Figure 9, amounts of input DNA ranging from 0.05 ng to 5 ng of total detected SNPs each detected at least 98.9% (10,117) of the loci, and amounts of input DNA of 0.10 ng and greater detected at least 99.5% (10,179) of the loci.

[0141] The data demonstrate that over 10,000 loci can be detected with high efficiency and sensitivity using different types of SNPs and amounts of input DNA ranging from 0.05 ng (50 pg) to 5 ng. Example 7: Evaluation of inhibitor activity on sequence library preparations, including evaluation by locus type

[0142] This example describes the evaluation of the effect of certain inhibitors on the preparation of sequence libraries (sequenced nucleic acid libraries), also referred to as DNA profiles, as disclosed herein, including by the type of locus to be detected and sequenced. DNA samples from crime scenes often contain co-purifying impurities that inhibit amplification. Common inhibitors include hematin, humic acid, and indigo.

[0143] To assess the impact of inhibitors commonly found in forensic samples, results were analyzed using Forenseq Universal Analysis Software version 2.2. Library preparation was performed as described in Example 1, and assessment of the impact of specific inhibitors on amplification was performed as described in Example 3, except that the inhibitors tested were as follows: 200 μM hematin, 100 μM hematin, 50 ng / μL humic acid, 25 ng / μL humic acid, 16 μM tannic acid, 8 μM tannic acid, 133 μM indigo, and 66.5 μM indigo, included in the amplification step as described in Example 1, and primer pairs to the 10230 locus were used. A positive control reaction without inhibitors was also performed. 1 ng of input DNA was used.

[0144] The results are shown in Figure 10. This demonstrates that various SNPs, including kiSNPs, ySNPs, xSNPs, piSNPs, iiSNPs and aiSNPs, can be amplified and detected in combination with each other according to the methods described herein, with high efficiency and detection rate, as demonstrated by all or almost all of each type of SNP being detected even in the presence of inhibitors. For example, the number of kiSNPs, ySNPs, xSNPs, piSNPs, iiSNPs and aiSNPs detected is similar to the number detected in the positive control lacking inhibitor (Figure 10). This data demonstrates that the presence of common inhibitors in samples does not adversely affect the ability to amplify more than 10,000 SNPs in a PCR reaction using the methods described herein. Example 8: Evaluation of sequencing library preparation using DNA samples obtained after simulated sexual assault

[0145] This example describes the generation of a sequence library (sequenced nucleic acid library), also called a DNA profile, using DNA from a simulated sexual assault sample. The simulated sexual assault DNA was obtained from samples taken 9 hours and 22 hours after the occurrence of the simulated sexual assault. DNA was isolated from the sperm fraction using differential extraction methods, and sperm fractions from both time points were collected and stored for analysis. The amount of DNA from the sperm fraction that was available as input in the assay (for generation of the sequence library) was only 500 pg, half the recommended amount of 1 ng.

[0146] The DNA samples were used to generate sequence libraries (sequenced nucleic acid libraries) as described in Example 1, except that the results were analyzed using Forenseq Universal Analysis Software version 2.2. The percentage of loci detected in the assay (call rate) as well as the number of SNPs of each type present are shown in FIG. 11. The results demonstrate that the majority of SNPs are detected with as little as 500 pg of input DNA, with 99.99% of all SNPs (10,229 of 10,230 SNPs) detected at 9 hours and 99.93% of all SNPs (10,223 of 10,230 SNPs) detected at 22 hours. Specifically, all aiSNPs, iiSNPs, piSNPs, xSNPs and ySNPs were detected at both 9 hours and 22 hours after the occurrence of the simulated sexual assault. Only 1 kiSNP out of 9,867 was detected at 9 hours, and only 7 kiSNPs out of 9,867 were detected at 22 hours. The number of loci detected is sufficient to be uploaded into a genealogy database for relative searching.

[0147] This data demonstrates that the methods described herein can be used to detect over 10,000 SNPs, including various kiSNPs, ySNPs, xSNPs, piSNPs, iiSNPs, and aiSNPs, and sequence libraries can be generated using as little as 500 pg of DNA 9 hours and 22 hours after the occurrence of a simulated sexual assault, with over 99.9% of all SNPs being detected. Thus, the methods described herein are suitable for use in generating sequence libraries containing less than the recommended amount of DNA, e.g., 500 pg, following a criminal incident involving sexual assault. Example 9: Evaluation of PCIA carryover during generation of sequence libraries from saliva samples

[0148] This example describes sequencing of a nucleic acid library (e.g., to generate a DNA profile) from DNA derived from a saliva sample extracted using organic extraction with the phenol-chloroform-isoamyl alcohol (PCIA) extraction method.

[0149] Saliva DNA was obtained from saliva samples in which a high amount of extraction reagent PCIA (e.g., no PCIA, light PCIA, medium PCIA, and heavy PCIA) was intentionally left as carryover in the extracted DNA to simulate a less than complete extraction. PCIA, which contains its component phenol, is a known inhibitor of PCR amplification.

[0150] DNA samples with no PCIA, light PCIA, medium PCIA and heavy PCIA were used to generate sequence libraries (sequenced nucleic acid libraries) as described in Example 1, except the results were analyzed using Forenseq Universal Analysis Software version 2.2. The total number of SNPs detected for each sample was determined and is shown in Figure 12. The results indicate that PCIA carryover, even at high levels with heavy PCIA carryover, does not affect the ability of the assay to detect SNPs, as over 10,170 SNPs were detected in each sample. Example 10: Generation of sequence libraries from blood samples using various substrates and evaluation of the effect of heme

[0151] This example describes sequencing of nucleic acid libraries (e.g., to generate DNA profiles) of DNA derived from blood samples deposited on different substrates typically found at crime scenes, including rust and denim, as well as blood samples on swabs where only 420 pg of DNA was available, and blood samples extracted using CheleX™ where increasing levels of heme were carried along with the DNA. Heme is a known inhibitor of PCR amplification. Denim contains indigo dye, a known inhibitor of PCR amplification.

[0152] Each of the DNA samples was used to generate sequence libraries (sequenced nucleic acid libraries) as described in Example 1, except that the results were analyzed using Forenseq Universal Analysis Software version 2.2, including the blood and rust-containing sample, the two blood samples on denim, the 420 pg blood sample on the swab, and the blood samples with low or moderate amounts of heme carried over or without heme as controls, as well as the positive control blood sample. The total number of SNPs detected for each sample and the reference control was determined and is shown in FIG. 13. The results show that blood samples deposited on different substrates still allowed the detection of more than 10,114 SNPs out of 10,230 total SNPs. 9,563 SNPs were detected in the blood sample with only 420 pg, and more than 10,000 SNPs were detected in the sample with heme, and the number of SNPs detected was not affected by the amount of heme present in the sample. This demonstrates that DNA extracted from blood samples deposited on a variety of substrates commonly found at crime scenes can be used in accordance with the methods provided herein to detect over 10,000 SNPs for forensic applications.

[0153] The present invention is not intended to be limited in scope to the specific disclosed embodiments, which are provided, for example, to illustrate various embodiments of the invention. Various modifications to the compositions and methods described will become apparent from the descriptions and teachings herein. Such variations can be made without departing from the true scope and spirit of the disclosure, and are intended to be included within the scope of the disclosure.

Claims

1. 1. A method for performing DNA-based kinship analysis, comprising: Providing a nucleic acid sample; amplifying the nucleic acid sample with a plurality of primers that specifically hybridize to a plurality of target sequences that collectively comprise a plurality of at least or about 5,000-50,000 single nucleotide polymorphisms (SNPs), thereby generating amplification products, wherein the amplification is performed in one or more multiplex PCR reactions; generating a nucleic acid library from the amplification products; sequencing the nucleic acid library generated from the amplification products; and analyzing the sequence of the amplification product; genotyping the plurality of SNPs, thereby generating a DNA profile; and calculating a degree of relatedness between said DNA profile and one or more reference DNA profiles; The method includes:

2. 1. A method for performing DNA-based kinship analysis, comprising: Providing a nucleic acid sample; amplifying the nucleic acid sample with a plurality of primers that specifically hybridize to a plurality of target sequences that collectively comprise a plurality of at least or about 5,000-50,000 single nucleotide polymorphisms (SNPs), thereby generating amplification products, wherein the amplification is performed in one or more multiplex PCR reactions; generating a nucleic acid library from the amplification products; sequencing the nucleic acid library generated from the amplification products; and genotyping the plurality of SNPs, thereby generating a DNA profile; and calculating a degree of relatedness between said DNA profile and one or more reference DNA profiles; The method includes:

3. 3. The method of claim 1 or claim 2, wherein the sequencing is performed using massively parallel sequencing (MPS).

4. The method of any one of claims 1 to 3, further comprising generating a family tree comprising said DNA profile associated with one or more DNA profiles.

5. 1. A method for constructing a nucleic acid library, comprising: Providing a nucleic acid sample; amplifying the nucleic acid sample with a plurality of primers that specifically hybridize to a plurality of target sequences that collectively comprise a plurality of at least or about 5,000-50,000 single nucleotide polymorphisms (SNPs), thereby generating a nucleic acid library comprising amplified products, wherein the amplification is performed in one or more multiplex PCR reactions; The method includes:

6. The method of any one of claims 1 to 5, wherein the nucleic acid sample comprises genomic DNA.

7. The method of any one of claims 1 to 6, wherein the nucleic acid sample contains one or more enzyme inhibitors.

8. 8. The method of claim 7, wherein the one or more enzyme inhibitors comprise one or more inhibitors selected from the group consisting of hematin, heme, humic acid, indigo, and tannic acid.

9. The method according to any one of claims 1 to 8, wherein the nucleic acid sample comprises low quality and / or low abundance nucleic acid molecules.

10. The method of claim 9, wherein the low quality nucleic acid molecules are degraded and / or fragmented genomic DNA.

11. the low quality nucleic acid molecules have a degradation index (DI) of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195 or 200, or at least 1, 11. The method of claim 9 or claim 10, wherein the soluble soluble cellulose has a Decomposition Index (DI) of 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195 or 200.

12. 11. The method of claim 9 or claim 10, wherein the low quality nucleic acid molecules have a DI of at least 1 and up to 158.3 or less.

13. The method of any one of claims 1 to 8, wherein the nucleic acid sample comprises high quality nucleic acid molecules.

14. 14. The method of claim 13, wherein the high quality nucleic acid molecules have a DI of less than 1.

15. the nucleic acid sample is a forensic sample, and / or The nucleic acid sample is derived from saliva, blood, semen, hair, teeth or bone. The method according to any one of claims 1 to 14.

16. The method of any one of claims 1 to 15, wherein the nucleic acid sample comprises at or about 50 pg to 100 ng of genomic DNA.

17. 17. The method of any one of claims 1 to 16, wherein the nucleic acid sample comprises at or about 100 pg to 5 ng or at or about 50 pg to 5 ng of genomic DNA.

18. 18. The method of any one of claims 1 to 17, wherein the plurality of SNPs comprises SNPs selected from one or more of the group consisting of kiSNPs, aiSNPs, iiSNPs, piSNPs, xSNPs and ySNPs.

19. 19. The method of claim 18, wherein at least or at least about 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98% or 99% of the plurality of SNPs are related SNPs.

20. 1. A method for calculating relatedness, comprising: obtaining a DNA profile comprising genotypes of at least or about 5,000-50,000 SNPs; calculating a degree of relatedness between said DNA profile and one or more reference DNA profiles; The method includes:

21. 1. A method for calculating relatedness, comprising: generating a DNA profile comprising genotypes of at least or about 5,000-50,000 SNPs; calculating a degree of relatedness between said DNA profile and one or more reference DNA profiles; The method includes:

22. Calculating the relevance (1) performing KING-Robust relatedness estimation between all pairs of a sample set containing one or more reference DNA profiles, where pairings with a relatedness coefficient of >0.01 are identified as closely related and pairings with a relatedness coefficient of <-0.025 are identified as ancestrally diverged; (2) removing all reference DNA profiles with ≥5% missing data; and (3) ranking all reference DNA profiles by identifying each reference DNA profile with a ranking value, where the ranking value is determined based on the number of related reference DNA profiles in the full set of reference DNA profiles ranked from smallest to largest, where the relatedness is 22. The method of any one of claims 1 to 21, comprising a large scale cohort method comprising: breaking ties by the number of ancestrally branched reference DNA profiles in the full set of reference DNA profiles ranked from largest to smallest, and for each reference DNA profile, iteratively through the ranked reference DNA profiles: (i) if the reference DNA profile is not already in the related sample set, add it to an unrelated sample set and add all related reference DNA profiles to the related sample set; and (ii) if the reference DNA profile is already in the related sample set, skip to the next reference DNA profile and repeat starting from step (3)(i).

23. The one or more reference DNA profiles are 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 0,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or about 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 12 5,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250 ,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or at least 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,000, 400,000, 500,000, 600,000, 700,000 0, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000, or at least about 3,000, 4,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 125,000, 150,000, 175,000, 200,000, 225,000, 250,000, 275,000, 300,The method according to any one of claims 1 to 4 and 6 to 22, comprising 000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000, 1,000,000, 1,250,000, 1,500,000, 1,750,000, 2,000,000, 3,000,000, 4,000,000, 5,000,000 or 10,000,000 reference DNA profiles.

24. A nucleic acid library constructed using the method according to any one of claims 5 to 24.

25. A plurality of primers that specifically hybridize to a plurality of target sequences comprising at least or about 5,000-50,000 single nucleotide polymorphisms (SNPs) in a nucleic acid sample, wherein amplification of the nucleic acid sample using the plurality of primers in one or more multiplex PCR reactions results in amplification products.

26. 1. A method for constructing a DNA profile, comprising: Providing a nucleic acid sample; amplifying the nucleic acid sample with a plurality of primers that specifically hybridize to a plurality of target sequences that collectively comprise a plurality of at least or about 5,000-50,000 single nucleotide polymorphisms (SNPs), thereby generating amplification products, wherein the amplification is performed in one or more multiplex PCR reactions; sequencing the amplification products; and genotyping the plurality of SNPs, thereby generating a DNA profile; and The method includes:

27. 1. A method for identifying genetic relatives of a DNA profile, comprising: Calculating the degree of association between the DNA profile of claim 26 and one or more reference DNA profiles; generating a pedigree comprising the DNA profile related to the one or more reference DNA profiles; The method includes:

28. 1. A method for identifying genetic relatives of a DNA profile, comprising: calculating a degree of association between a DNA profile comprising genotypes of at least or about 5,000-50,000 SNPs and one or more reference DNA profiles; generating a pedigree comprising the DNA profile related to the one or more reference DNA profiles; The method includes:

29. A kit comprising at least one container means, said at least one container means comprising a plurality of the primers according to any one of claims 25 to 28.

30. The plurality of SNPs is selected from the group consisting of about 7,000-15,000 SNPs, 7,000-14,000 SNPs, 7,000-13,000 SNPs, 7,000-12,000 SNPs, 7,000-11,000 SNPs, 8,000-15,000 SNPs, 8,000-14,000 SNPs, 8,000-13,000 SNPs, 24. The method of any one of claims 1 to 23, comprising P, 8,000 to 12,000 SNPs, 8,000 to 11,000 SNPs, 9,000 to 15,000 SNPs, 9,000 to 14,000 SNPs, 9,000 to 13,000 SNPs, 9,000 to 12,000 SNPs or 9,000 to 11,000 SNPs.

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