Ancient Genomes Reveal the Origins and Kinship Organisation of Late Bronze Age Populations in Northeastern China

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We present genome-wide data from 11 individuals from two co-burial graves (M6, M7) at the Late Bronze Age Dongshantou (DST) site in Jilin Province, Northeast China. Using uniparental genetic markers in combination with multiple relatedness estimators, we identify three first-degree, several second-degree and third-degree relationships connect the two graves. All males share the same Y-chromosome lineages (C2b), while mitochondrial haplotypes vary across graves, and lack of close-kin unions. DST individuals derive most of their ancestry from Amur River and West Liao River populations, indicating both long-term regional continuity and low-level external gene flow. We propose that DST was a patrilineal family cemetery, with burials organized around nuclear family co-burials, though exceptions—such as M7:5, who shares a mitochondrial haplotype with M6:4 despite being third-degree related to M7 members—suggest maternal connections or inter-family alliances. This pattern contrasts with recently reported matrilineal organization at the Neolithic Fujia site and aligns with patrilocal, female-exogamous systems documented in Bronze Age Europe. DST provides the first genome-wide evidence for lineage-based co-burial, sex-structured mortuary space, regionally integrated genetic structure in Late Bronze Age Northeast Asia. Ancient DNA Kinship Patrilineal society Female exogamy Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Kinship is a primary axis of social organization in small-scale and early complex societies and has long underpinned comparative social theory (Ning et al., 2021 ). Within archaeology, cemeteries provide a uniquely informative arena for testing hypotheses about kinship, household composition, and mortuary recruitment, yet traditional inferences based on skeletal traits and material culture often lack the resolution to diagnose close biological relationships (Binford, 1962 ; Ning et al., 2021 ; Vai, Eduardo G Amorim, Lari, & Caramelli, 2020). Non-metric phenotypes may be rare or environmentally plastic, and patterned burial arrangements or grave-good assemblages can reflect social roles rather than descent (Alt & Vach, 1998 ; Hassett, 2006 ; Ricaut et al., 2010 ; Stojanowski & Hubbard, 2017 ). The advent of ancient DNA (aDNA) analysis has transformed this field by enabling direct reconstruction of pedigrees and recent biological relatedness among excavated individuals. Studies now routinely integrate genome-wide data with uniparental markers, identity-by-descent (IBD) segments, and runs of homozygosity (ROH) to test kinship models at cemetery scale. Examples include patrilocal farmstead groups in Bronze Age central Europe revealed by combined isotopic and genomic evidence (Csáky et al., 2020 ), dynamic household and descent structures across third-millennium BCE Bohemia (Papac et al., 2021 ), extreme endogamy within an elite Neolithic lineage at Newgrange, Ireland (Cassidy et al., 2020 ), and a matrilineal dynasty at Chaco Canyon in the American Southwest (Kennett et al., 2017 ). In East Asia, site-level pedigrees have begun to refine mortuary interpretations, from an Eastern Han cliff-tomb nuclear family in the Sichuan Basin (Zhang et al., 2024 ) to the recently documented two-clanned matrilineal community at the Neolithic Fujia site in Shandong (Wang et al., 2025 ). Methodological advances such as robust ROH detection in low-coverage datasets and IBD calling tailored to aDNA (for example, ancIBD) further strengthen inference (Ringbauer, Novembre, & Steinrücken, 2021 ). Despite this progress, high-resolution kinship analyses remain empty for northeastern China, a frontier region with complex cultural trajectories and long-standing interaction between local populations and groups to the south and west. The DST site in Daan City, Jilin Province, dates to the Late Bronze Age and contains multiple collective burials, each interring two to nine individuals (Fig. 1 A). Archaeologists have hypothesized that these graves reflect family relationships, but this has not been assessed with genomic data. Here we analyze genome-wide data from 11 individuals recovered from two co-burial graves at DST (M7 and M6; Fig. 1 B). We pursue three objectives. First, we place DST in its regional genetic context by quantifying affinities to contemporaneous populations from the Amur River and West Liao River regions and by explicitly modeling admixture, including potential steppe-related contributions. Second, we reconstruct degrees of relatedness within and across graves using complementary approaches (READ, KIN, pairwise mismatch rates and IBD tracts), together with uniparental markers. Third, we integrate ROH, Y-chromosome and mitochondrial diversity, and the spatial composition of co-burials to evaluate sex-biased residence, descent and mortuary recruitment. This framework allows us to test alternative, data-driven models for kinship organization at DST and to situate local social practice within broader narratives of population interaction in Late Bronze Age Northeast Asia. Materials and Methods Archaeological and anthropological information The DST site (45°41′N, 124°01′E) is located in Daan City, Jilin Province, within the Nenjiang River basin of northeastern China. It was first identified during an archaeological survey in 1960, which uncovered three burials containing stone tools and pottery. Based on these findings, the site was initially attributed to the Spring and Autumn–Warring States period (ca. 770–221 BCE). Subsequent radiocarbon dating indicates an age of approximately 2500 BP, consisent with the archaeological pbservation (Supplementary Data 1). Renewed excavations in 2023 yielded additional artifacts, allowing for a refined attribution to the Han Shu Phase II cultural horizon. The DST site lies within the so-called “Yuelianghu Lake Region,” an area rich in prehistoric archaeological remains. This region includes Neolithic sites such as Houtaomuga and Shuangta, as well as numerous Bronze Age sites associated with the Han Shu Phase II culture, including Pingyang, Fuyuxiaodengke and Nehe Dagudui. In contrast to the farming-based societies of the Central Plains and the West Liao River (WLR) regions, the Han Shu Phase II populations appear to have relied primarily on hunting, fishing and gathering, supplemented by small-scale cultivation and animal husbandry. This subsistence strategy reflects a distinctive regional adaptation and cultural tradition within the Nenjiang basin (Wang & Sebillaud, 2019 ). Physical anthropological analysis In this study, conventional morphological assessments were employed to evaluate the human remains. Age-at-death was primarily estimated using the standards proposed by Buikstra and Ubelaker (Buikstra & Ubelaker, 1994 ), which integrate dental eruption and wear patterns, epiphyseal fusion, and cranial and postcranial skeletal development. DNA extraction and Sequencing Prior to extraction, all the samples were subjected to UV irradiation and bleach cleaning in a cleanroom at the ancient DNA lab of Peking University, China to reduce external contamination. DNA was extracted according to the published protocols for DNA extraction, half UDG-treatment and library preparation (Dabney et al., 2013 ; Korlević et al., 2015 ; Ning et al., 2020 ). Double-stranded libraries was prepared from a 20 µL aliquot of each extract. Blunt-end-repair of DNA fragments was incubated at 25°C for 15 min. The final fill-in step was performed by incubating at 37°C for 30 min and then at 80°C for 10 min. DNA libraries were qualified using a Qubit 2.0 (Thermo Fisher) and sequenced on an Illumina HiSeq X10 instrument at the Sangon Biotech (Shanghai) Co., Ltd, China in the 200 bp paired-end sequencing design, using paired-end 2 × 150 cycle runs. Base calling and filtering of exact index sequences were conducted using CASAVA 1.8.2 software. Low-quality reads, defined as having an average or 50% Phred quality value ≤ 30, were discarded to ensure the integrity of the sequencing data. In-solution ancient DNA capture Enrichment for the 1240k SNP panel and mtDNA was performed at the Key Laboratory of Archaeological Science, Peking University. The 1240k probes were synthesized based on previously published datasets and subsequently reverse-transcribed into RNA probes (Wang et al., 2025 ). These were combined with commercial human mtDNA probes (TargetSeq One Kit, iGeneTech; lot TC1NTC2N, diluted 1:100) for simultaneous enrichment. For each capture reaction, 500 ng of DNA library was mixed with blocking oligonucleotides (Hyb Human Block and Universal Block, iGeneTech), biotinylated RNA probes (1240k and mtDNA), RNase block and hybridization buffer. The mixture was denatured at 85°C for 5 min and hybridized at 50°C for 24 h. Hybridized products were captured with streptavidin-coated beads, washed once at room temperature with Wash Buffer 1 (15 min), and subsequently subjected to three high-temperature washes with TargetSeq One Wash Buffer at 50°C (10 min each). Beads were then washed with ethanol, dried and resuspended in Q5 High-Fidelity Polymerase Master Mix for amplification using P5 and P7 primers. Amplification was carried out with the following profile: 98°C for 3 min; 15 cycles of 98°C for 15 s, 60°C for 30 s and 72°C for 30 s; and a final extension at 72°C for 5 min. Post-capture libraries were purified with VAHTS DNA Clean beads, quantified using a Qubit fluorometer (Thermo Fisher), assessed by fragment analysis, and sequenced on an Illumina NextSeq 500 platform (paired-end, 2 × 75 cycles). Ancient DNA data processing and quality control We clipped the Illumina sequencing adapters by AdapterRemoval v2.2.0 (Schubert, Lindgreen, & Orlando), and mapped merged reads to the human reference genome (hs37d5; GRCh37 with decoy sequences) using BWA v0.7.12 with the parameters -n and -l set to 0.01 and 1024, respectively (Li & Durbin, 2010 ). The reads with phred mapping quality of less than 30 were then discarded using -q (q30-reads) in Samtools v1.9 (Li et al., 2009 ). We removed PCR duplicates using DeDup v0.12.2 (Peltzer et al., 2016 ). To minimize the impact of postmortem DNA damage on genotyping, we used the trim bam function on bamUtils v1.0.13 by trimming the first and last four bases of each read (Jun, Wing, Abecasis, & Kang, 2015 ) based on the DNA damage pattern of each library. Ancient DNA authentication We used multiple methods to assess the quality of the ancient genomes. (1) We tabulated patterns of post-mortem chemical modifications expected for ancient DNA using mapDamage v2.0.6 (Jónsson, Ginolhac, Schubert, Johnson, & Orlando, 2013 ); (2) We estimated mitochondrial contamination rates for all individuals using Schmutzi v1.5.1(Renaud, Slon, Duggan, & Kelso, 2015 ); (3) We measured the nuclear genome contamination rate in males based on X chromosome data as implemented in ANGSDv0.910 (Korneliussen, Albrechtsen, & Nielsen, 2014 ). As male individuals possess only one X chromosome, discrepancies between bases aligned to the same polymorphic position, exceeding the threshold of sequencing error, were interpreted as indicators of contamination. Population structure analysis To characterize the genetic profile of DST population, we first prepared a dataset by merging the newly generated data with previously published worldwide present-day and ancient populations (Supplementary Data 2). We performed principal components analysis (PCA) as implemented in the smartpca v16000 in EIGENSOFT package (Patterson, Price, & Reich, 2006 ) using a set of 2077 present day Eurasian individuals from the “HumanOrigins” dataset and a subset of 266 East Asian individuals using the “1240k” dataset with the option “lsqproject: YES” and “shrinkmode: YES.” We also performed unsupervised admixture analysis with ADMIXTURE v1.3.0 (Kimura et al., 2009 ). We used outgroup- f 3 statistics (Patterson et al., 2012 ; Raghavan et al., 2014 ) to obtain a measurement of genetic relationship between two populations. We calculated f 4 statistics with the “ f 4 mode: YES” function in the admixtools (Patterson et al., 2012 ). F 3 and f 4 statistics were calculated using qp3Pop v435 and qpDstatv755 in the admixtools package, and the Mbuti population from Africa was used as the outgroup. We modeled our populations using the qpAdm framework (qpAdmv810) (Haak et al., 2015 ). We used the following 8 populations in both “HumanOrigins” and “1240k” datasets as outgroup (“OG”): including Mbuti.DG (Central African hunter-gatherers), Israel_Natufian (Neolithic agricultural population from Levant), Villabruna (West European Hunter-Gatherer), Iran_Ganj_Dareh_Neolithic (Neolithic agricultural population from Iran), Mixe.DG (Native Americans), Ami.DG (an indigenous Austronesian ethnic group native to Taiwan), Onge.DG (indigenous Andamanese islanders), Anatolia_Neolithic (Neolithic farmers from the Anatolia region). Genetic sexing and Genetic relatedness analysis We assigned the molecular sex of our ancient samples by comparing the ratio of X and Y chromosome coverages with autosomes (Fu et al., 2016). We generated the mtDNA consensus sequences of our ancient individuals using the Geneious v11.1.3 software (Kearse et al., 2012), and then determined their mtDNA haplogroups using HaploGrep2 (Weissensteiner et al., 2016). We determined the male Y chromosome haplogroup by examining a set of positions on the 25,660 diagnostic positions on the ISOGG database, and assigned the final haplogroups by the most downstream derived SNPs. We used pairwise mismatch rate (PMR), Relationship Estimation from Ancient DNA (READ), KIN and ancIBD to determine the genetic relatedness between ancient individuals (Auton et al., 2015; Lipatov, Sanjeev, Patro, & Veeramah, 2015; Monroy, Jose, Jakobsson, & Günther, 2018). 1.PMR method (Kennett et al., 2017) estimates kinship by calculating the proportion of mismatched alleles at shared SNP sites between two individuals. PMR is defined as the number of SNP where the individuals carry different alleles divided by the total number of overlapping sites. Under this model, the PMR value for identical individuals (r = 1) is expected to be half of the population baseline PMR (r = 0, representing unrelated individuals without inbreeding), while first-degree relatives (r = 0.5) and second-degree relatives (r = 0.25) are expected to have PMR values of approximately 3/4 and 7/8 of the baseline, respectively. 2.READ (Monroy et al., 2018) further estimates relatedness by computing the proportion of non-matching alleles (P₀) within non-overlapping 1 Mb genomic windows. P₀ values are normalized against the expected P₀ of unrelated individuals from the same population to account for within-population genetic diversity. Lower P₀ values indicate greater sharing of chromosomal segments identical-by-descent, allowing for the detection of close relatives even in low-coverage ancient genomes. 3.KIN (Popli, Peyrégne, & Peter, 2023) estimates genetic relatedness and identity-by-descent (IBD) from low-coverage ancient DNA using genotype likelihoods within a maximum likelihood framework, accounting for genotype uncertainty, missing data, and sequencing errors. This likelihood-based approach allows robust inference of kinship coefficients (k 0 , k 1 , k 2 ). KIN can accurately classify relationships up to third-degree relatives and distinguish between full siblings and parent-offspring pairs with as little as 0.05× coverage. The method assumes a homogeneous population; significant substructure may affect its accuracy. 4.ancIBD (Ringbauer et al., 2021) was used to detect long genomic segments shared identical-by-descent, which are indicative of recent common ancestry. This method leverages phased genotype data and is robust to genotype uncertainty, making it suitable for low-coverage ancient DNA. The total length and number of shared IBD tracts allow for inference of relatedness degrees, with closer relatives sharing longer and more numerous IBD segments. Run of homozygosity analysis Runs of homozygosity (ROH) blocks were identified in our ancient individuals using the hapROH v0.64 python package ( https://pypi.org/project/hapROH/ ), utilizing default settings. The hapROH method was specifically designed for analyzing low-coverage ancient genomes (> 0.5x) (Ringbauer et al., 2021 ). To perform the analysis, we first prepared pseudo-haploid genotyping data on 1240k SNPs by pileupCaller program, ran the hapROH, and further extracted the results from the output CSV files. Finally, we employed the plot functions within the hapROH package to visualize the obtained results. Results Ancient genome data production Initial shallow sequencing indicated adequate endogenous human DNA in all samples, with human endogenous DNA ranging from 0.89% to 80.54%. We then produced deep sequencing data for population and kinship analyses, yielding autosomal coverages from 0.017× to 0.613× and genotype calls at 189,957 to 713,781 SNPs on the 1.24 million SNP panel (Table 1 ). All individuals show characteristic ancient DNA misincorporation profiles consistent with post-mortem cytosine deamination (Supplementary Fig. 1). Mitochondrial contamination estimates are below 5% for all individuals and X-chromosome–based nuclear contamination estimates for males are also below 5% (Supplementary Data 1). Newly generated data were merged with a curated reference panel based on the 1.24 million SNP dataset for downstream analyses (PCA, f -statistics, kinship and qpAdm). Table 1 A summary of DST samples reported in this study. Sample ID age bio. Sex mn.Cov Yhap. mtHap. cont.nolen n1240K M6:1 35± F 0.6129 - B4b1a3a 0.01 622613 M6:2 18–21 F 0.1097 - B4b1a3a 0.01 699130 M6:3 35–45 M 0.0349 C2b D4 0.05 237821 M6:4 35–55 M 0.4322 C2b F1b1e 0.01 493059 M7:1 20–30 F 0.5457 - C4a1a4a 0.01 577011 M7:2 40± M 0.1317 C2b1a1b1 D2 0.01 713781 M7:3 30–35 M 0.0925 C2b1a1b D2 0.01 625838 M7:4 40± F 0.0013 - B4b1a3a 0.01 2016 M7:5 8–11 M 0.0933 C2b1a1b F1b1b 0.01 614396 M7:6 2± M 0.0037 C2b1a1b B4c1a2 0.01 5694 M7:7 >18 M 0.0166 C2b D2 0.01 189957 Individuals in bold in the table indicate autosomal coverages below 0.01× and were excluded from downstream analyses. Sex determination and analysis of uniparental markers We first determined the genetic sex of all DST individuals and analyzed mitochondrial DNA (mtDNA) for all individuals, as well as Y-chromosomal haplogroups for males (Supplementary Data 1 and Table 1 ). Genetic sex was inferred by calculating the ratio of reads mapped to the X and Y chromosomes relative to autosomal coverage (X-ratio and Y-ratio, respectively). Individuals with an X-ratio 0.26 were classified as male, while those with an X-ratio > 0.68 and a Y-ratio < 0.02 were assigned as female (Ning et al., 2021 ). According to these criteria, 6 individuals were identified as male (M6:3, M6:4, M7:2, M7:3, M7:5 and M7:7), and 3 as female (M6:1, M6:2 and M7:1). All male individuals belong to Y-chromosomal haplogroup C2b, which is widely distributed across East Asia (Yan et al., 2014 ) and is found at high frequencies in nearly all Chinese Han populations, indicating a shared paternal lineage. C2b and its downstream clades are prevalent across Northeast Asia, the Mongolian Plateau and Siberia, are widely associated with Tungusic, Mongolic and several ancient northern nomadic populations. C2b1a1 and its derived subclades are frequently found among Mongolic-speaking populations (Wang, Wang, Hu, He, & Nie, 2024 ). Mitochondrial haplotypes further illuminate maternal relationships. The mitochondrial haplotypes of the DST individuals include haplogroups D (D2 and D4), C, F and B, all belonging to the East Eurasian mtDNA lineage pool (Kivisild et al., 2002 ; Yao, Kong, Bandelt, Kivisild, & Zhang, 2002 ). Among them, haplogroups C and D are characteristic of northern East Asian populations (Bai et al., 2018 ), whereas haplogroups B and F are more commonly found in southern East Asian groups (Wen et al., 2004 ). M7:2, M7:3 and M7:7 share haplogroup D2, suggesting a common maternal ancestry. M6:3 carries haplogroup D4, one of the most common mitochondrial lineages in modern northern East Asian populations, including Japanese, Koreans, northern Han, Mongolic, Tungusic speakers and Native American populations. M7:5 and M6:4 harbor haplogroup F1b1, found in northern Asian populations such as Yakut, Uyghur, Turkic-speaking Even and Koreans. M6:1 and M6:2 share haplogroup B4b1a3a, which is observed in Han Chinese and northern Asian groups such as Altai Kizhi, Shor, Uyghur and Yakut. M7:1 share haplogroup C4a1a4a, which is predominantly found among indigenous populations of the Russian Far East, particularly the Evenk and Shor peoples (Bai et al., 2018 ; Kivisild et al., 2002 ; Yao et al., 2002 ). Both paternal and maternal lineages of the DST individuals consistently trace their origins to northern East Asia, potentially with close affinities to Tungusic-speaking ancestral groups. The genetic origin of the DST population To characterize the genetic profile of the DST individuals (hereafter DST_total), we conducted principal component analysis (PCA) using their autosomal genotypes (Fig. 2 A and 2 B). The DST genomes, along with a broad panel of relevant ancient individuals, were projected onto a reference space constructed from present-day Eurasian populations (Supplementary Data 2). The PCA results demonstrate that DST individuals cluster closely with Northeast Asian populations, particularly those from the Amur River (AR) and West Liao River (WLR) regions. DST individuals fall near the Late Neolithic and Iron Age groups from the Amur River region, including AR_LN and AR_Xianbei_IA, as well as Middle and Late Neolithic populations from the West Liao River region such as WLR_LN and HMMH_MN. This genetic affinity is geographically consistent with the location of DST on the Songnen Plain, situated between the AR and WLR regions in Northeast Asia. Outgroup f 3 -statistics further support this observation by quantitatively assessing the shared genetic drift between DST_total and various ancient populations ( f 3 (Mbuti; X, DST_total), where X represents other ancient populations) (Fig. 2 C). The highest f 3 values are observed with WLR_BA_o ( f 3 = 0.3327, Z = 108.8), followed by AR_LN ( f 3 = 0.3258, Z = 84.5) and AR_Xianbei_IA ( f 3 = 0.3232, Z = 101.2), suggesting substantial shared ancestry between DST_total and both West Liao River and Amur River ancient populations. Boisman_MN, DevilsCave_N represent ancient Northeast Asian populations, also show high f 3 values (all above 0.319), indicating broader genetic continuity across Northeast Asia. Populations from the Yellow River (YR) basin in the Central Plains of China such as Shandong_EN exhibit slightly lower f 3 values with DST_total (around 0.309), suggesting a relatively weaker genetic connection (Supplementary Data 3). To further evaluate differential genetic affinities between DST and Northeast Asian versus Central Plain populations, we performed f 4 -statistics of the form f 4 (Mbuti, X; ancient and present-day East Asian populations, DST_total), where X represents various northern East Asian populations. The results reveal a pronounced excess of allele sharing between DST_total and multiple Northeast Asian groups compared with populations from the Central Plains or western Eurasia. For instance, DST_total shows strong affinity with Baikal_EN ( f 4 = 0.0522, Z = 100), Mongolia_N_North ( f 4 = 0.0528, Z = 100), Boisman_MN ( f 4 = 0.0544, Z = 100), and Oroqen.DG ( f 4 = 0.0533, Z = 98.1). Similar signals are observed with other northern East Asian populations, including Ulchi.DG ( f 4 = 0.0535, Z = 94.7), AR_LN ( f 4 = 0.0553, Z = 63.4), AR_Xianbei_IA ( f 4 = 0.0548, Z = 81.1), WLR_LN ( f 4 = 0.0514, Z = 91.1) and WLR_BA_o ( f 4 = 0.0565, Z = 89.5). By contrast, DST_total exhibits lower affinity with ancient populations from the Central Plains, such as YR_LN ( f 4 = 0.0515, Z = 97.3) and YR_LBIA ( f 4 = 0.0514, Z = 97.2), and much weaker affinity with western Eurasian groups including BMAC ( f 4 = 0.0196, Z = 64.2) and Anatolia_Neolithic ( f 4 = 0.0205, Z = 62.9). These results are consistent with PCA and outgroup- f 3 analyses, indicating that DST individuals share substantial ancestry with ancient Northeast Asian populations from the Amur River and West Liao River regions, while exhibiting only limited genetic contribution from the Central Plains and western Eurasian sources (Supplementary Data 4). To further quantify the ancestral composition of DST_total, we performed qpAdm analyses using both one-way and two-way models with Northeast Asian and Central Plain populations as sources. In one-way models, DST_total can be adequately modeled as descending from a single Northeast Asian source, including DevilsCave_N (P = 0.798), AR_LN (P = 0.731) and AR_Xianbei_IA (P = 0.451), whereas models using Central Plain populations as the sole source do not fit, such as Miaozigou_MN (P = 0.045), Shimao_LN (P = 0.001). These results suggest that DST_total derives predominantly from Northeast Asian ancestry (Supplementary Data 5). Two-way qpAdm models further indicate that DST_total can be modeled as a mixture of two Northeast Asian sources, for example AR_LN and HMMH_MN (P = 0.979, 65% AR_LN, 35% HMMH_MN), or AR_Xianbei_IA and DevilsCave_N (P = 0.741, 25% AR_Xianbei_IA, 75% DevilsCave_N). These results reinforce that the DST individuals primarily descend from ancient Northeast Asian populations (Supplementary Data 5). Estimation of kinship To investigate potential genetic relatedness among individuals co-buried within single graves at the DST site, we estimated genetic relatedness among 11 individuals recovered from two burials, while M7:4 and M7:6 were excluded from the kinship analysis due to coverage below 0.01× (Table 1 ). Pairwise mismatch rates (PMR) were first calculated based on psedo-haploid genotypes based on the “1240K” SNP panel. The PMR results suggest the presence of both first- and second-degree relationships between the DST individuals (Supplementary Data 6). We applied READ to independently assess the genetic kinship relationships among these individuals based on normalized P0 values. Our analysis identified multiple closely related pairs. M6:1-M6:2 was classified as first-degree relatives (Parent-offspring; P0 = 0.7565), while M6:3-M7:3 (P0 = 0.8058), M6:3-M7:7 (P0 = 0.8123), M7:2-M7:3 (P0 = 0.8061) and M7:2-M7:7 (P0 = 0.8097) were also assigned as first-degree relatives. M7:3-M7:7 and M7:1-M7:2 was identified as genetically identical (P0 values were all around 0.49), suggesting either identical twins or the same individual. Osteological analysis identified M7:3-M7:7 as adult males. Considering that M7:7 lacked a cranium, exhibited disarticulated postcranial elements, and was located near M7:3 (Fig. 1 C), we infer that M7:3 and M7:7 likely represent the same individual; M7:1 was a 20-30-year-old female and M7:2 an approximately 40-year-old male. Both tooth samples were collected from the mandible, reducing the likelihood of mixup, thus we infer that these two individuals were twins. M6:2-M7:5 and M6:3-M7:2 both share a second-degree kinship relationship, there are also multiple third-degree relative pairs. (Supplementary Data 7). Third-degree or closer kinship relationships exist both within and between the M6 and M7 co-buried graves. Considering that all males from both burials belong to the Y-chromosome haplogroup C2b and that all were primary co-burials, it is likely that the two burial clusters represent a single extended family, closely connected through paternal lineage, indicative of a patrilineal social structure. To further clarify the kinship relationships between individuals, we applied the KIN method. Consistent with these findings, KIN analysis further confirmed the first-degree parent-offspring relationship between M6:1-M6:2, as well as sibling relationships between M7:2-M7:3/M7:7. M7:3-M7:7 (LogLikelihoodRatio = 92.659) was again confirmed as genetically identical (Supplementary Data 8). Several additional pairs (e.g., M6:3 with M7:3) exhibited kinship coefficients and IBD segment counts consistent with second-degree or third-degree relationships. The highly concordant results across PMR, READ and KIN analyses robustly confirm the presence of multiple close kinships within this population. To further refine the degree of genetic relatedness, we applied ancIBD to detect pairwise identity-by-descent (IBD) segments along the genome. The IBD patterns are highly consistent with previous kinship inferences. The pair M6:1 and M6:2 exhibited extensive genome-wide IBD sharing, with nearly continuous segments distributed across all autosomes, consistent with a first-degree relationship (parent-offspring or full siblings). The pair M7:2 and M7:3 also demonstrated substantial IBD sharing, characterized by numerous long IBD segments interspersed with non-shared regions, indicative of a full sibling relationship (Fig. 3 ). To reconstruct the most probable pedigree structure, we integrated autosomal kinship analyses, uniparental genetic markers, biological sex and age-at-death estimates. The results indicate that the M6 and M7 burials belong to a single extended family centered on paternal lineage. Within this group, M7:2 and M7:3 form a pair of full siblings, sharing both parents; while M6:1 and M6:2 represent a mother–daughter pair. M6:3 shows a second-degree relationship with M7:2 and M7:3, and a third-degree relationship with M6:2. In addition, M6:4-M7:2 and M7:5-M6:2 share a second-degree relationship. As the maternal identity between individuals M6:1 and M6:2 cannot yet be conclusively determined, we propose two alternative pedigree models (Fig. 4 A and 4 B), wherein M6:1 is assumed to be the mother in Fig. 4 A, and M6:2 is assumed to be the mother in Fig. 4 B. The two co-burials are located close to each other along a north–south axis, suggesting that they may have formed part of a single, closely related kin group. The results reveal the presence of two core nuclear families within the DST site. Individuals with the same border color share an identical mtDNA haplotype. We further applied hapROH to evaluate runs of homozygosity (ROH) across the DST individuals (Fig. 5 ). ROH are extended stretches of homozygous segments in the genome, and the total length and distribution of ROH segments can reflect the levels of parental relatedness and population size. Our analysis reveals that all DST individuals possess only limited amounts of ROH longer than 4 cM, with most ROH segments being short (< 12 cM), and with few segments exceeding 20 cM. The absence of long ROH segments suggests that none of the DST individuals are recent inbred offspring and that their parents were not closely related. Discussion In this study, we combined genome-wide data, uniparental markers and multiple relatedness utalities to investigate how biological relationships shaped mortuary practices at the DST site. From a population perspective, DST individuals align most closely with ancient groups from the Amur River and West Liao River regions, which is geographically consistent with the site’s position on the Songnen Plain. Outgroup f 3 and f 4 statistics indicate greater allele sharing with northern East Asian populations than with Yellow River basin groups, and qpAdm modeling indicates that DST individuals derive the majority of their ancestry from ancient Northeast Asian populations. These findings support a scenario of long-term genetic continuity in Northeast Asia, with only limited external gene flow during the Late Bronze Age. The uniparental and autosomal evidence together indicate that the excavated individuals represent closely related members of extended families. Two core family units can be reconstructed with high confidence. M6:1 and M6:2 form a mother and daughter pair, supported by both their shared mitochondrial haplogroup B4b1a3a and first-degree autosomal relatedness. M7:2 and M7:3 form a full-sibling pair, sharing mitochondrial haplogroup D2 and Y haplogroup C2b1a1b, with extensive autosomal IBD segments that are characteristic of full siblings. M6:3 shows a second-degree relationship with M7:2 and M7:3, and a third-degree relationship with M6:2. In addition, M6:4-M7:2 and M7:5-M6:2 share a second-degree relationship. M7:3 and M7:7 are genetically indistinguishable and likely represent a duplicate sampling of the same individual. These cross-grave links indicate that co-burial at DST encompassed not only nuclear families but also intergenerational lineages, implying a burial organization coordinated at the lineage level rather than at the level of a single household. A notable sex pattern characterizes the two chambers. In our view, the most plausible explanation is a sex-structured co-burial within a patrilineal framework. Under this model, the low diversity of Y-chromosome lineages among males indicates a persistent paternal line, whereas the heterogeneous mitochondrial haplotypes reflect female in-marriage from outside groups. This pattern parallels that observed in Bronze Age cemeteries of central Europe, where repeated male-line continuity and isotopic evidence for non-local women suggest patrilocal residence and female exogamy (Haak et al., 2015 ; Knipper et al., 2017 ). The DST pattern also contrasts with the Neolithic Fujia site in eastern China, where two cemeteries were organized by maternal clans with low mitochondrial diversity and diverse Y lineages (Wang et al., 2025 ). Given the modest sample size at DST, both models should be treated as hypotheses. The following tests are diagnostic and feasible with additional material: (i) replicate the low Y and higher mtDNA diversity in more chambers; (ii) test for sex-biased mobility using strontium and oxygen isotopes; (iii) evaluate X-to-autosome allele-sharing asymmetries; and (iv) assess whether kinship networks cluster by chamber beyond the two graves studied here. ROH profiles lack long segments and are dominated by short tracts, which is inconsistent with recent consanguinity. This supports out-marriage and a relatively large effective population size, and provides a counterpoint to elite contexts that show extreme inbreeding. The combination of outbred ROH signatures, limited Y diversity, and cross-chamber second-degree relatedness supports a model of a lineage-based community that maintained a local paternal line while incorporating occasional non-local individuals, plausibly through marriage alliances. Integrating ancestry and kinship clarifies how population processes intersected with social organization. The ancestry profile places DST within a Northeast Asian continuum connected to Amur and West Liao River groups. Historical and archaeogenomic research documents repeated pulses of interaction across the Northeast Asia during the second millennium BCE. In this context, the DST pattern is consistent with a community anchored by local male descent that occasionally integrated external ancestry. Such integration is expected to be mediated by women under patrilocal residence, which aligns with the observed mitochondrial diversity. Our interpretations remain constrained by sample size, uneven coverage across individuals, and the focus on two chambers. Nonetheless, the DST case strengthens the emerging view that prehistoric East Asia featured diverse descent rules and mortuary systems. DST falls on the patrilineal side of this spectrum, whereas Fujia represents a matrilineal end member. Additional genome-wide data from further DST chambers, high-resolution radiocarbon modeling, isotopic mobility data, and formal tests on the X chromosome will enable stronger evaluation of residence rules, the spatial extent of the lineage, and the temporal depth of the paternal line at the cemetery scale. Conclusion This study integrates genome-wide data, uniparental markers, identity-by-descent tracts, and runs of homozygosity to evaluate kinship organization and population history at DST site in Late Bronze Age Northeast Asia. Two first-degree dyads occur within chambers (a mother and daughter in M6; full brothers in M7), and a paternal half-sibling link bridges the graves. Together with low Y-chromosome diversity among males (C2b-related lineages) and heterogeneous mitochondrial haplotypes, as well as the absence of long ROH in all individuals, these findings indicate mortuary recruitment structured by biological kinship, persistence of a local paternal line at cemetery scale, and out-marriage rather than recent consanguinity. A parsimonious interpretation is a patrilineal system with female exogamy and sex-structured co-burials. From a population perspective, DST individuals fall within a Northeast Asian genetic continuum most closely related to Amur River and West Liao River groups. qpAdm models that fit the data best contain AR/WLR-related source, which situates DST within known second-millennium BCE networks of interaction across Northeast Asia. Under patrilocal residence, limited external ancestry would be expected to enter predominantly via in-marrying women, consistent with the observed mitochondrial diversity. This configuration contrasts with the Neolithic Fujia site in eastern China, where two cemeteries were organized by maternal clans with low mtDNA diversity and diverse Y lineages, and it parallels Bronze Age central European cemeteries that show male-line continuity alongside isotopic evidence for non-local women. We acknowledge limitations arising from sample size, uneven coverage, and the focus on two chambers. Future work should expand genomic sampling across additional DST burials, incorporate high-resolution radiocarbon modeling, and pair genetic analyses with strontium and oxygen isotopes to test sex-biased mobility. X-to-autosome allele-sharing tests provide an additional genetics-only check for sex-biased gene flow. These data will allow stronger evaluation of the spatial extent and temporal depth of the DST lineage and will refine the balance between descent rules and marriage practices in structuring mortuary space. Declarations Competing interests The authors declare no competing interests. Conflict of interest The authors declare no conflict of interest. Funding This work was supported by the Major Projects of Key Research Bases of Humanities and Social Sciences of the Ministry of Education of China (Grant No. 22JJD780009), the National Social Science Fund of China (Grant No. 23VLS007 and 23VRC034) and the National Natural Science Foundation of China (Grant No. 42472029). Author Contribution Danyang Ge, Ruiqi Zou and Jiaqi Jin wrote the main manuscript text. Danyang Ge performed the experiment and data analysis. Xiaoxuan Shi, Xiaoming Wang, Di Zhang and Xinghan Zhang provided the archaeological samples and information. Chao Ning and Quanchao Zhang contributed to review and editing of the manuscript. Acknowledgments We thank all the volunteers who participated in the DST excavations and appreciate the support from Jilin Provincial Institute of Cultural Relics and Archaeology for this research. Data Availability The basemap used in Figure 1 is in the public domain and accessible through the Natural Earth website (https://www.naturalearthdata.com/downloads/10m-raster-data/). The genotyping for the newly sequenced individuals will be publicly available upon the publication of the manuscript. References Alt KW, Vach W (1998) Kinship Studies in Skeletal Remains — Concepts and Examples. 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Supplementary Files SupplementaryData1Asummaryofalltheancientindividualsscreenedinthisstudy..xlsx SupplementaryData2Alistofpreviouslypublishedgenomicdatafrompresentdayandancienthumansusedforthegeneticanalysesinthisstudy..xlsx SupplementaryData3Thef3statistcsresultofDSTpopulation..xlsx SupplementaryData4Thef4statistcsresultofDSTpopulation..xlsx SupplementaryData5QpAdmmodelingoftheDSTpopulationsinourstudy..xlsx SupplementaryData6TheestimationofkinshiponautosomesusingPMRmethods..xlsx SupplementaryData7TheresultsofREADanalysisofancientDSTindividuals.xlsx SupplementaryData8TheresultsofKINanalysisofancientDSTindividuals.xlsx SupplementaryFigure1Postmortemmodificationsatthe5and3ends..docx Cite Share Download PDF Status: Published Journal Publication published 20 Apr, 2026 Read the published version in Archaeological and Anthropological Sciences → Version 1 posted Editorial decision: Revision requested 10 Mar, 2026 Reviews received at journal 27 Feb, 2026 Reviews received at journal 26 Feb, 2026 Reviewers agreed at journal 09 Feb, 2026 Reviewers agreed at journal 09 Feb, 2026 Reviewers invited by journal 09 Feb, 2026 Editor assigned by journal 22 Oct, 2025 Submission checks completed at journal 21 Oct, 2025 First submitted to journal 20 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7908178","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":588651189,"identity":"e4fed54a-1f61-4c9e-9b1b-c3cbc0059dd7","order_by":0,"name":"Danyang Ge","email":"","orcid":"","institution":"Jilin University","correspondingAuthor":false,"prefix":"","firstName":"Danyang","middleName":"","lastName":"Ge","suffix":""},{"id":588651190,"identity":"c5261f5f-9584-455d-9b59-0be20375c5a9","order_by":1,"name":"Ruiqi Zou","email":"","orcid":"","institution":"Jilin University","correspondingAuthor":false,"prefix":"","firstName":"Ruiqi","middleName":"","lastName":"Zou","suffix":""},{"id":588651191,"identity":"dc642184-a328-491f-a150-a0b1b4ae19a2","order_by":2,"name":"Jiaqi Jin","email":"","orcid":"","institution":"Jilin University","correspondingAuthor":false,"prefix":"","firstName":"Jiaqi","middleName":"","lastName":"Jin","suffix":""},{"id":588651192,"identity":"dbd9f8a2-4692-4621-b238-29d45223de9f","order_by":3,"name":"Xiaoxuan Shi","email":"","orcid":"","institution":"Jilin Provincial Institute of Cultural Relics and Archaeology","correspondingAuthor":false,"prefix":"","firstName":"Xiaoxuan","middleName":"","lastName":"Shi","suffix":""},{"id":588651193,"identity":"358c0079-8489-43b1-a3e5-8c77e76f8f39","order_by":4,"name":"Xiaoming Wang","email":"","orcid":"","institution":"Jilin Provincial Institute of Cultural Relics and Archaeology","correspondingAuthor":false,"prefix":"","firstName":"Xiaoming","middleName":"","lastName":"Wang","suffix":""},{"id":588651194,"identity":"9d8598f5-8c5a-4a0c-83e8-af7fd4e0f8f2","order_by":5,"name":"Di Zhang","email":"","orcid":"","institution":"Jilin Provincial Institute of Cultural Relics and Archaeology","correspondingAuthor":false,"prefix":"","firstName":"Di","middleName":"","lastName":"Zhang","suffix":""},{"id":588651195,"identity":"2b074677-69b2-4fe8-8667-b04afef65987","order_by":6,"name":"Xinghan Zhang","email":"","orcid":"","institution":"Jilin Provincial Institute of Cultural Relics and Archaeology","correspondingAuthor":false,"prefix":"","firstName":"Xinghan","middleName":"","lastName":"Zhang","suffix":""},{"id":588651196,"identity":"648c880e-f341-448d-bdf8-3713bc38cbcf","order_by":7,"name":"Quanchao Zhang","email":"","orcid":"","institution":"Jilin University","correspondingAuthor":false,"prefix":"","firstName":"Quanchao","middleName":"","lastName":"Zhang","suffix":""},{"id":588651197,"identity":"580c889a-f5e5-41e6-b7fa-2dc592888607","order_by":8,"name":"Chao Ning","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuElEQVRIiWNgGAWjYFACxgYGhgoGAxBTggQtZ0jTAtLVRooW/tnNbQ+/zrtjbHCA+eBtHga7PIJaJO4cbDeW3fbMzOAAW7I1D0NyMUEtBhKJbdKS2w7bGBzgMZPmYTiQ2ECcljkgLfzfiNci+bHhMNBhPGzEaZG4AbSF4dgzY8nDbMaWcwySCWvhn5H+TPJHzR3DvuPND2+8qbAjrAUEmIHuAZJgdxKjHggYf4C0jIJRMApGwSjABQCEgzrMzVYXPQAAAABJRU5ErkJggg==","orcid":"","institution":"Peking University","correspondingAuthor":true,"prefix":"","firstName":"Chao","middleName":"","lastName":"Ning","suffix":""}],"badges":[],"createdAt":"2025-10-20 18:23:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7908178/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7908178/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s12520-026-02466-w","type":"published","date":"2026-04-20T15:59:19+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":102745812,"identity":"7627dc27-7a87-4790-a8a7-86f05bfc995c","added_by":"auto","created_at":"2026-02-16 08:54:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":537494,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA. Geographical location of the DST site, B.Distribution of co-burial tombs (M7 and M6), C. and D. are the individuals in the burial chambers of M7 and M6, respectively\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7908178/v1/40527bb0bd33cab6179d2a53.png"},{"id":102448359,"identity":"b4587a37-5324-4a3b-84d0-1d04ad5c320f","added_by":"auto","created_at":"2026-02-11 18:10:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":342543,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA and B.The PCA results of the DST populations in our study; C. The top 20 populations who share the closest relationship with the DST populations\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7908178/v1/76b5e5a6cfdcaa52ee58df12.png"},{"id":102448309,"identity":"f5f47d5d-005a-4ad5-af82-cf29a77b8ff6","added_by":"auto","created_at":"2026-02-11 18:10:11","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":174578,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe result of ancIBD among M6:1-M6:2 and M7:2-M7:3\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7908178/v1/7a20c8cb147085d64fb2426f.png"},{"id":102448369,"identity":"e19bc3a4-f6e5-45a1-a4bc-6b425d9af120","added_by":"auto","created_at":"2026-02-11 18:10:18","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":371830,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAlternative pedigree models for the DST individuals. (A) M6:1 designated as the mother. (B) M6:2 designated as the mother.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIndividuals with the same border color share an identical mtDNA haplotype.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7908178/v1/da013ca63d7a2d6ced5e7c60.jpeg"},{"id":102448375,"identity":"7154d720-5736-441b-b234-e83acec63a16","added_by":"auto","created_at":"2026-02-11 18:10:24","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":101393,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe results of the ROH analysis\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7908178/v1/cb3d3c4b961e679fe55dc60a.png"},{"id":107928045,"identity":"8e6482c3-e6b3-4ece-916f-db047d010e3e","added_by":"auto","created_at":"2026-04-27 16:06:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1867695,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7908178/v1/952371a1-ad15-4c7a-9c2c-c31387afe373.pdf"},{"id":102448389,"identity":"5be66742-8288-4638-a643-3119150ed31b","added_by":"auto","created_at":"2026-02-11 18:10:34","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":12204,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryData1Asummaryofalltheancientindividualsscreenedinthisstudy..xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7908178/v1/6caa192723f483d3b12adc97.xlsx"},{"id":102448362,"identity":"e278394e-b66f-4f1b-a008-ad34e413315a","added_by":"auto","created_at":"2026-02-11 18:10:17","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":12941,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryData2Alistofpreviouslypublishedgenomicdatafrompresentdayandancienthumansusedforthegeneticanalysesinthisstudy..xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7908178/v1/9721ad66147ee08068c78de7.xlsx"},{"id":102448310,"identity":"60266bd1-5e79-48c5-80c1-43690574ce39","added_by":"auto","created_at":"2026-02-11 18:10:12","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":18664,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryData3Thef3statistcsresultofDSTpopulation..xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7908178/v1/b9b09b0218771d42c8b48155.xlsx"},{"id":102448312,"identity":"2e2d972c-e032-46f0-b0f0-cd20be98f403","added_by":"auto","created_at":"2026-02-11 18:10:13","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":195694,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryData4Thef4statistcsresultofDSTpopulation..xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7908178/v1/3a0fe83c7854f075ee0debc0.xlsx"},{"id":102745938,"identity":"4ecbeff2-f656-4c46-9c35-50b36b4488eb","added_by":"auto","created_at":"2026-02-16 08:54:48","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":12094,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryData5QpAdmmodelingoftheDSTpopulationsinourstudy..xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7908178/v1/946961805ca6858183e86a7f.xlsx"},{"id":102448393,"identity":"1871ef9b-e020-4e0a-8984-9c792e26e041","added_by":"auto","created_at":"2026-02-11 18:10:38","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":10644,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryData6TheestimationofkinshiponautosomesusingPMRmethods..xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7908178/v1/76bfb08ee2a1eb07ebfe17e1.xlsx"},{"id":102448379,"identity":"86a0fabd-0f64-41f7-8996-e3c1357797ee","added_by":"auto","created_at":"2026-02-11 18:10:26","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":14742,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryData7TheresultsofREADanalysisofancientDSTindividuals.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7908178/v1/71964fa051a225c6254eda12.xlsx"},{"id":102448315,"identity":"aa161898-fb41-46c7-badb-3752ae1e095e","added_by":"auto","created_at":"2026-02-11 18:10:14","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":13673,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryData8TheresultsofKINanalysisofancientDSTindividuals.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7908178/v1/cccc5b964c1220b4df5c2e4a.xlsx"},{"id":102448358,"identity":"40e29412-8a16-4e06-99d2-0fd4dc83c9f3","added_by":"auto","created_at":"2026-02-11 18:10:15","extension":"docx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":667426,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure1Postmortemmodificationsatthe5and3ends..docx","url":"https://assets-eu.researchsquare.com/files/rs-7908178/v1/44791b84f34131a26a391a59.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Ancient Genomes Reveal the Origins and Kinship Organisation of Late Bronze Age Populations in Northeastern China","fulltext":[{"header":"Introduction","content":"\u003cp\u003eKinship is a primary axis of social organization in small-scale and early complex societies and has long underpinned comparative social theory (Ning et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Within archaeology, cemeteries provide a uniquely informative arena for testing hypotheses about kinship, household composition, and mortuary recruitment, yet traditional inferences based on skeletal traits and material culture often lack the resolution to diagnose close biological relationships (Binford, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1962\u003c/span\u003e; Ning et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Vai, Eduardo G Amorim, Lari, \u0026amp; Caramelli, 2020). Non-metric phenotypes may be rare or environmentally plastic, and patterned burial arrangements or grave-good assemblages can reflect social roles rather than descent (Alt \u0026amp; Vach, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Hassett, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Ricaut et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Stojanowski \u0026amp; Hubbard, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe advent of ancient DNA (aDNA) analysis has transformed this field by enabling direct reconstruction of pedigrees and recent biological relatedness among excavated individuals. Studies now routinely integrate genome-wide data with uniparental markers, identity-by-descent (IBD) segments, and runs of homozygosity (ROH) to test kinship models at cemetery scale. Examples include patrilocal farmstead groups in Bronze Age central Europe revealed by combined isotopic and genomic evidence (Cs\u0026aacute;ky et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), dynamic household and descent structures across third-millennium BCE Bohemia (Papac et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), extreme endogamy within an elite Neolithic lineage at Newgrange, Ireland (Cassidy et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and a matrilineal dynasty at Chaco Canyon in the American Southwest (Kennett et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In East Asia, site-level pedigrees have begun to refine mortuary interpretations, from an Eastern Han cliff-tomb nuclear family in the Sichuan Basin (Zhang et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) to the recently documented two-clanned matrilineal community at the Neolithic Fujia site in Shandong (Wang et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Methodological advances such as robust ROH detection in low-coverage datasets and IBD calling tailored to aDNA (for example, ancIBD) further strengthen inference (Ringbauer, Novembre, \u0026amp; Steinr\u0026uuml;cken, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Despite this progress, high-resolution kinship analyses remain empty for northeastern China, a frontier region with complex cultural trajectories and long-standing interaction between local populations and groups to the south and west.\u003c/p\u003e \u003cp\u003eThe DST site in Daan City, Jilin Province, dates to the Late Bronze Age and contains multiple collective burials, each interring two to nine individuals (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Archaeologists have hypothesized that these graves reflect family relationships, but this has not been assessed with genomic data.\u003c/p\u003e \u003cp\u003eHere we analyze genome-wide data from 11 individuals recovered from two co-burial graves at DST (M7 and M6; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). We pursue three objectives. First, we place DST in its regional genetic context by quantifying affinities to contemporaneous populations from the Amur River and West Liao River regions and by explicitly modeling admixture, including potential steppe-related contributions. Second, we reconstruct degrees of relatedness within and across graves using complementary approaches (READ, KIN, pairwise mismatch rates and IBD tracts), together with uniparental markers. Third, we integrate ROH, Y-chromosome and mitochondrial diversity, and the spatial composition of co-burials to evaluate sex-biased residence, descent and mortuary recruitment. This framework allows us to test alternative, data-driven models for kinship organization at DST and to situate local social practice within broader narratives of population interaction in Late Bronze Age Northeast Asia.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eArchaeological and anthropological information\u003c/h2\u003e \u003cp\u003eThe DST site (45\u0026deg;41\u0026prime;N, 124\u0026deg;01\u0026prime;E) is located in Daan City, Jilin Province, within the Nenjiang River basin of northeastern China. It was first identified during an archaeological survey in 1960, which uncovered three burials containing stone tools and pottery. Based on these findings, the site was initially attributed to the Spring and Autumn\u0026ndash;Warring States period (ca. 770\u0026ndash;221 BCE). Subsequent radiocarbon dating indicates an age of approximately 2500 BP, consisent with the archaeological pbservation (Supplementary Data 1). Renewed excavations in 2023 yielded additional artifacts, allowing for a refined attribution to the Han Shu Phase II cultural horizon.\u003c/p\u003e \u003cp\u003eThe DST site lies within the so-called \u0026ldquo;Yuelianghu Lake Region,\u0026rdquo; an area rich in prehistoric archaeological remains. This region includes Neolithic sites such as Houtaomuga and Shuangta, as well as numerous Bronze Age sites associated with the Han Shu Phase II culture, including Pingyang, Fuyuxiaodengke and Nehe Dagudui. In contrast to the farming-based societies of the Central Plains and the West Liao River (WLR) regions, the Han Shu Phase II populations appear to have relied primarily on hunting, fishing and gathering, supplemented by small-scale cultivation and animal husbandry. This subsistence strategy reflects a distinctive regional adaptation and cultural tradition within the Nenjiang basin (Wang \u0026amp; Sebillaud, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePhysical anthropological analysis\u003c/h3\u003e\n\u003cp\u003eIn this study, conventional morphological assessments were employed to evaluate the human remains. Age-at-death was primarily estimated using the standards proposed by Buikstra and Ubelaker (Buikstra \u0026amp; Ubelaker, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1994\u003c/span\u003e), which integrate dental eruption and wear patterns, epiphyseal fusion, and cranial and postcranial skeletal development.\u003c/p\u003e\n\u003ch3\u003eDNA extraction and Sequencing\u003c/h3\u003e\n\u003cp\u003ePrior to extraction, all the samples were subjected to UV irradiation and bleach cleaning in a cleanroom at the ancient DNA lab of Peking University, China to reduce external contamination. DNA was extracted according to the published protocols for DNA extraction, half UDG-treatment and library preparation (Dabney et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Korlević et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Ning et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Double-stranded libraries was prepared from a 20 \u0026micro;L aliquot of each extract. Blunt-end-repair of DNA fragments was incubated at 25\u0026deg;C for 15 min. The final fill-in step was performed by incubating at 37\u0026deg;C for 30 min and then at 80\u0026deg;C for 10 min. DNA libraries were qualified using a Qubit 2.0 (Thermo Fisher) and sequenced on an Illumina HiSeq X10 instrument at the Sangon Biotech (Shanghai) Co., Ltd, China in the 200 bp paired-end sequencing design, using paired-end 2 \u0026times; 150 cycle runs. Base calling and filtering of exact index sequences were conducted using CASAVA 1.8.2 software. Low-quality reads, defined as having an average or 50% Phred quality value\u0026thinsp;\u0026le;\u0026thinsp;30, were discarded to ensure the integrity of the sequencing data.\u003c/p\u003e\n\u003ch3\u003eIn-solution ancient DNA capture\u003c/h3\u003e\n\u003cp\u003eEnrichment for the 1240k SNP panel and mtDNA was performed at the Key Laboratory of Archaeological Science, Peking University. The 1240k probes were synthesized based on previously published datasets and subsequently reverse-transcribed into RNA probes (Wang et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). These were combined with commercial human mtDNA probes (TargetSeq One Kit, iGeneTech; lot TC1NTC2N, diluted 1:100) for simultaneous enrichment.\u003c/p\u003e \u003cp\u003eFor each capture reaction, 500 ng of DNA library was mixed with blocking oligonucleotides (Hyb Human Block and Universal Block, iGeneTech), biotinylated RNA probes (1240k and mtDNA), RNase block and hybridization buffer. The mixture was denatured at 85\u0026deg;C for 5 min and hybridized at 50\u0026deg;C for 24 h. Hybridized products were captured with streptavidin-coated beads, washed once at room temperature with Wash Buffer 1 (15 min), and subsequently subjected to three high-temperature washes with TargetSeq One Wash Buffer at 50\u0026deg;C (10 min each). Beads were then washed with ethanol, dried and resuspended in Q5 High-Fidelity Polymerase Master Mix for amplification using P5 and P7 primers.\u003c/p\u003e \u003cp\u003eAmplification was carried out with the following profile: 98\u0026deg;C for 3 min; 15 cycles of 98\u0026deg;C for 15 s, 60\u0026deg;C for 30 s and 72\u0026deg;C for 30 s; and a final extension at 72\u0026deg;C for 5 min. Post-capture libraries were purified with VAHTS DNA Clean beads, quantified using a Qubit fluorometer (Thermo Fisher), assessed by fragment analysis, and sequenced on an Illumina NextSeq 500 platform (paired-end, 2 \u0026times; 75 cycles).\u003c/p\u003e\n\u003ch3\u003eAncient DNA data processing and quality control\u003c/h3\u003e\n\u003cp\u003eWe clipped the Illumina sequencing adapters by AdapterRemoval v2.2.0 (Schubert, Lindgreen, \u0026amp; Orlando), and mapped merged reads to the human reference genome (hs37d5; GRCh37 with decoy sequences) using BWA v0.7.12 with the parameters -n and -l set to 0.01 and 1024, respectively (Li \u0026amp; Durbin, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The reads with phred mapping quality of less than 30 were then discarded using -q (q30-reads) in Samtools v1.9 (Li et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). We removed PCR duplicates using DeDup v0.12.2 (Peltzer et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). To minimize the impact of postmortem DNA damage on genotyping, we used the trim bam function on bamUtils v1.0.13 by trimming the first and last four bases of each read (Jun, Wing, Abecasis, \u0026amp; Kang, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) based on the DNA damage pattern of each library.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eAncient DNA authentication\u003c/h2\u003e \u003cp\u003eWe used multiple methods to assess the quality of the ancient genomes. (1) We tabulated patterns of post-mortem chemical modifications expected for ancient DNA using mapDamage v2.0.6 (J\u0026oacute;nsson, Ginolhac, Schubert, Johnson, \u0026amp; Orlando, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e); (2) We estimated mitochondrial contamination rates for all individuals using Schmutzi v1.5.1(Renaud, Slon, Duggan, \u0026amp; Kelso, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2015\u003c/span\u003e); (3) We measured the nuclear genome contamination rate in males based on X chromosome data as implemented in ANGSDv0.910 (Korneliussen, Albrechtsen, \u0026amp; Nielsen, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). As male individuals possess only one X chromosome, discrepancies between bases aligned to the same polymorphic position, exceeding the threshold of sequencing error, were interpreted as indicators of contamination.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePopulation structure analysis\u003c/h3\u003e\n\u003cp\u003eTo characterize the genetic profile of DST population, we first prepared a dataset by merging the newly generated data with previously published worldwide present-day and ancient populations (Supplementary Data 2). We performed principal components analysis (PCA) as implemented in the smartpca v16000 in EIGENSOFT package (Patterson, Price, \u0026amp; Reich, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) using a set of 2077 present day Eurasian individuals from the \u0026ldquo;HumanOrigins\u0026rdquo; dataset and a subset of 266 East Asian individuals using the \u0026ldquo;1240k\u0026rdquo; dataset with the option \u0026ldquo;lsqproject: YES\u0026rdquo; and \u0026ldquo;shrinkmode: YES.\u0026rdquo; We also performed unsupervised admixture analysis with ADMIXTURE v1.3.0 (Kimura et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). We used outgroup-\u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e statistics (Patterson et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Raghavan et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) to obtain a measurement of genetic relationship between two populations. We calculated \u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sub\u003e statistics with the \u0026ldquo;\u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sub\u003e mode: YES\u0026rdquo; function in the admixtools (Patterson et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). \u003cem\u003eF\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sub\u003e statistics were calculated using qp3Pop v435 and qpDstatv755 in the admixtools package, and the Mbuti population from Africa was used as the outgroup.\u003c/p\u003e \u003cp\u003eWe modeled our populations using the qpAdm framework (qpAdmv810) (Haak et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). We used the following 8 populations in both \u0026ldquo;HumanOrigins\u0026rdquo; and \u0026ldquo;1240k\u0026rdquo; datasets as outgroup (\u0026ldquo;OG\u0026rdquo;): including Mbuti.DG (Central African hunter-gatherers), Israel_Natufian (Neolithic agricultural population from Levant), Villabruna (West European Hunter-Gatherer), Iran_Ganj_Dareh_Neolithic (Neolithic agricultural population from Iran), Mixe.DG (Native Americans), Ami.DG (an indigenous Austronesian ethnic group native to Taiwan), Onge.DG (indigenous Andamanese islanders), Anatolia_Neolithic (Neolithic farmers from the Anatolia region).\u003c/p\u003e\n\u003ch3\u003eGenetic sexing and Genetic relatedness analysis\u003c/h3\u003e\n\u003cp\u003eWe assigned the molecular sex of our ancient samples by comparing the ratio of X and Y chromosome coverages with autosomes (Fu et al., 2016). We generated the mtDNA consensus sequences of our ancient individuals using the Geneious v11.1.3 software (Kearse et al., 2012), and then determined their mtDNA haplogroups using HaploGrep2 (Weissensteiner et al., 2016). We determined the male Y chromosome haplogroup by examining a set of positions on the 25,660 diagnostic positions on the ISOGG database, and assigned the final haplogroups by the most downstream derived SNPs. We used pairwise mismatch rate (PMR), Relationship Estimation from Ancient DNA (READ), KIN and ancIBD to determine the genetic relatedness between ancient individuals (Auton et al., 2015; Lipatov, Sanjeev, Patro, \u0026amp; Veeramah, 2015; Monroy, Jose, Jakobsson, \u0026amp; Günther, 2018).\u003c/p\u003e\n\u003cp\u003e1.PMR method (Kennett et al., 2017) estimates kinship by calculating the proportion of mismatched alleles at shared SNP sites between two individuals. PMR is defined as the number of SNP where the individuals carry different alleles divided by the total number of overlapping sites. Under this model, the PMR value for identical individuals (r = 1) is expected to be half of the population baseline PMR (r = 0, representing unrelated individuals without inbreeding), while first-degree relatives (r = 0.5) and second-degree relatives (r = 0.25) are expected to have PMR values of approximately 3/4 and 7/8 of the baseline, respectively.\u003c/p\u003e\n\u003cp\u003e2.READ (Monroy et al., 2018) further estimates relatedness by computing the proportion of non-matching alleles (P₀) within non-overlapping 1 Mb genomic windows. P₀ values are normalized against the expected P₀ of unrelated individuals from the same population to account for within-population genetic diversity. Lower P₀ values indicate greater sharing of chromosomal segments identical-by-descent, allowing for the detection of close relatives even in low-coverage ancient genomes.\u003c/p\u003e\n\u003cp\u003e3.KIN (Popli, Peyrégne, \u0026amp; Peter, 2023) estimates genetic relatedness and identity-by-descent (IBD) from low-coverage ancient DNA using genotype likelihoods within a maximum likelihood framework, accounting for genotype uncertainty, missing data, and sequencing errors. This likelihood-based approach allows robust inference of kinship coefficients (k\u003csub\u003e0\u003c/sub\u003e, k\u003csub\u003e1\u003c/sub\u003e, k\u003csub\u003e2\u003c/sub\u003e). KIN can accurately classify relationships up to third-degree relatives and distinguish between full siblings and parent-offspring pairs with as little as 0.05× coverage. The method assumes a homogeneous population; significant substructure may affect its accuracy.\u003c/p\u003e\n\u003cp\u003e4.ancIBD (Ringbauer et al., 2021) was used to detect long genomic segments shared identical-by-descent, which are indicative of recent common ancestry. This method leverages phased genotype data and is robust to genotype uncertainty, making it suitable for low-coverage ancient DNA. The total length and number of shared IBD tracts allow for inference of relatedness degrees, with closer relatives sharing longer and more numerous IBD segments.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eRun of homozygosity analysis\u003c/h2\u003e \u003cp\u003eRuns of homozygosity (ROH) blocks were identified in our ancient individuals using the hapROH v0.64 python package (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pypi.org/project/hapROH/\u003c/span\u003e\u003cspan address=\"https://pypi.org/project/hapROH/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), utilizing default settings. The hapROH method was specifically designed for analyzing low-coverage ancient genomes (\u0026gt;\u0026thinsp;0.5x) (Ringbauer et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). To perform the analysis, we first prepared pseudo-haploid genotyping data on 1240k SNPs by pileupCaller program, ran the hapROH, and further extracted the results from the output CSV files. Finally, we employed the plot functions within the hapROH package to visualize the obtained results.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eAncient genome data production\u003c/h2\u003e \u003cp\u003eInitial shallow sequencing indicated adequate endogenous human DNA in all samples, with human endogenous DNA ranging from 0.89% to 80.54%. We then produced deep sequencing data for population and kinship analyses, yielding autosomal coverages from 0.017\u0026times; to 0.613\u0026times; and genotype calls at 189,957 to 713,781 SNPs on the 1.24\u0026nbsp;million SNP panel (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). All individuals show characteristic ancient DNA misincorporation profiles consistent with post-mortem cytosine deamination (Supplementary Fig.\u0026nbsp;1). Mitochondrial contamination estimates are below 5% for all individuals and X-chromosome\u0026ndash;based nuclear contamination estimates for males are also below 5% (Supplementary Data 1). Newly generated data were merged with a curated reference panel based on the 1.24\u0026nbsp;million SNP dataset for downstream analyses (PCA, \u003cem\u003ef\u003c/em\u003e-statistics, kinship and qpAdm).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eA summary of DST samples reported in this study.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ebio. Sex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003emn.Cov\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYhap.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003emtHap.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003econt.nolen\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003en1240K\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM6:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.6129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eB4b1a3a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e622613\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM6:2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eB4b1a3a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e699130\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM6:3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35\u0026ndash;45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eC2b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eD4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e237821\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM6:4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35\u0026ndash;55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.4322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eC2b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eF1b1e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e493059\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM7:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.5457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eC4a1a4a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e577011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM7:2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eC2b1a1b1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eD2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e713781\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM7:3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026ndash;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eC2b1a1b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eD2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e625838\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eM7:4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e40\u0026plusmn;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.0013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eB4b1a3a\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e2016\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM7:5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u0026ndash;11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eC2b1a1b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eF1b1b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e614396\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eM7:6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2\u0026plusmn;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eM\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.0037\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eC2b1a1b\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eB4c1a2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e5694\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM7:7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eC2b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eD2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e189957\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIndividuals in bold in the table indicate autosomal coverages below 0.01\u0026times; and were excluded from downstream analyses.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eSex determination and analysis of uniparental markers\u003c/h2\u003e \u003cp\u003eWe first determined the genetic sex of all DST individuals and analyzed mitochondrial DNA (mtDNA) for all individuals, as well as Y-chromosomal haplogroups for males (Supplementary Data 1 and Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Genetic sex was inferred by calculating the ratio of reads mapped to the X and Y chromosomes relative to autosomal coverage (X-ratio and Y-ratio, respectively). Individuals with an X-ratio\u0026thinsp;\u0026lt;\u0026thinsp;0.42 and a Y-ratio\u0026thinsp;\u0026gt;\u0026thinsp;0.26 were classified as male, while those with an X-ratio\u0026thinsp;\u0026gt;\u0026thinsp;0.68 and a Y-ratio\u0026thinsp;\u0026lt;\u0026thinsp;0.02 were assigned as female (Ning et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). According to these criteria, 6 individuals were identified as male (M6:3, M6:4, M7:2, M7:3, M7:5 and M7:7), and 3 as female (M6:1, M6:2 and M7:1). All male individuals belong to Y-chromosomal haplogroup C2b, which is widely distributed across East Asia (Yan et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) and is found at high frequencies in nearly all Chinese Han populations, indicating a shared paternal lineage. C2b and its downstream clades are prevalent across Northeast Asia, the Mongolian Plateau and Siberia, are widely associated with Tungusic, Mongolic and several ancient northern nomadic populations. C2b1a1 and its derived subclades are frequently found among Mongolic-speaking populations (Wang, Wang, Hu, He, \u0026amp; Nie, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMitochondrial haplotypes further illuminate maternal relationships. The mitochondrial haplotypes of the DST individuals include haplogroups D (D2 and D4), C, F and B, all belonging to the East Eurasian mtDNA lineage pool (Kivisild et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Yao, Kong, Bandelt, Kivisild, \u0026amp; Zhang, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Among them, haplogroups C and D are characteristic of northern East Asian populations (Bai et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), whereas haplogroups B and F are more commonly found in southern East Asian groups (Wen et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). M7:2, M7:3 and M7:7 share haplogroup D2, suggesting a common maternal ancestry. M6:3 carries haplogroup D4, one of the most common mitochondrial lineages in modern northern East Asian populations, including Japanese, Koreans, northern Han, Mongolic, Tungusic speakers and Native American populations. M7:5 and M6:4 harbor haplogroup F1b1, found in northern Asian populations such as Yakut, Uyghur, Turkic-speaking Even and Koreans. M6:1 and M6:2 share haplogroup B4b1a3a, which is observed in Han Chinese and northern Asian groups such as Altai Kizhi, Shor, Uyghur and Yakut. M7:1 share haplogroup C4a1a4a, which is predominantly found among indigenous populations of the Russian Far East, particularly the Evenk and Shor peoples (Bai et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Kivisild et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Yao et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Both paternal and maternal lineages of the DST individuals consistently trace their origins to northern East Asia, potentially with close affinities to Tungusic-speaking ancestral groups.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eThe genetic origin of the DST population\u003c/h2\u003e \u003cp\u003eTo characterize the genetic profile of the DST individuals (hereafter DST_total), we conducted principal component analysis (PCA) using their autosomal genotypes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). The DST genomes, along with a broad panel of relevant ancient individuals, were projected onto a reference space constructed from present-day Eurasian populations (Supplementary Data 2). The PCA results demonstrate that DST individuals cluster closely with Northeast Asian populations, particularly those from the Amur River (AR) and West Liao River (WLR) regions. DST individuals fall near the Late Neolithic and Iron Age groups from the Amur River region, including AR_LN and AR_Xianbei_IA, as well as Middle and Late Neolithic populations from the West Liao River region such as WLR_LN and HMMH_MN. This genetic affinity is geographically consistent with the location of DST on the Songnen Plain, situated between the AR and WLR regions in Northeast Asia. Outgroup \u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e-statistics further support this observation by quantitatively assessing the shared genetic drift between DST_total and various ancient populations (\u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e (Mbuti; X, DST_total), where X represents other ancient populations) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). The highest \u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e values are observed with WLR_BA_o (\u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.3327, Z\u0026thinsp;=\u0026thinsp;108.8), followed by AR_LN (\u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.3258, Z\u0026thinsp;=\u0026thinsp;84.5) and AR_Xianbei_IA (\u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.3232, Z\u0026thinsp;=\u0026thinsp;101.2), suggesting substantial shared ancestry between DST_total and both West Liao River and Amur River ancient populations. Boisman_MN, DevilsCave_N represent ancient Northeast Asian populations, also show high \u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e values (all above 0.319), indicating broader genetic continuity across Northeast Asia. Populations from the Yellow River (YR) basin in the Central Plains of China such as Shandong_EN exhibit slightly lower \u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e values with DST_total (around 0.309), suggesting a relatively weaker genetic connection (Supplementary Data 3).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo further evaluate differential genetic affinities between DST and Northeast Asian versus Central Plain populations, we performed \u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sub\u003e-statistics of the form \u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sub\u003e (Mbuti, X; ancient and present-day East Asian populations, DST_total), where X represents various northern East Asian populations. The results reveal a pronounced excess of allele sharing between DST_total and multiple Northeast Asian groups compared with populations from the Central Plains or western Eurasia. For instance, DST_total shows strong affinity with Baikal_EN (\u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.0522, Z\u0026thinsp;=\u0026thinsp;100), Mongolia_N_North (\u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.0528, Z\u0026thinsp;=\u0026thinsp;100), Boisman_MN (\u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.0544, Z\u0026thinsp;=\u0026thinsp;100), and Oroqen.DG (\u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.0533, Z\u0026thinsp;=\u0026thinsp;98.1). Similar signals are observed with other northern East Asian populations, including Ulchi.DG (\u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.0535, Z\u0026thinsp;=\u0026thinsp;94.7), AR_LN (\u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.0553, Z\u0026thinsp;=\u0026thinsp;63.4), AR_Xianbei_IA (\u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.0548, Z\u0026thinsp;=\u0026thinsp;81.1), WLR_LN (\u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.0514, Z\u0026thinsp;=\u0026thinsp;91.1) and WLR_BA_o (\u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.0565, Z\u0026thinsp;=\u0026thinsp;89.5). By contrast, DST_total exhibits lower affinity with ancient populations from the Central Plains, such as YR_LN (\u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.0515, Z\u0026thinsp;=\u0026thinsp;97.3) and YR_LBIA (\u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.0514, Z\u0026thinsp;=\u0026thinsp;97.2), and much weaker affinity with western Eurasian groups including BMAC (\u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.0196, Z\u0026thinsp;=\u0026thinsp;64.2) and Anatolia_Neolithic (\u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.0205, Z\u0026thinsp;=\u0026thinsp;62.9). These results are consistent with PCA and outgroup-\u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e analyses, indicating that DST individuals share substantial ancestry with ancient Northeast Asian populations from the Amur River and West Liao River regions, while exhibiting only limited genetic contribution from the Central Plains and western Eurasian sources (Supplementary Data 4).\u003c/p\u003e \u003cp\u003eTo further quantify the ancestral composition of DST_total, we performed qpAdm analyses using both one-way and two-way models with Northeast Asian and Central Plain populations as sources. In one-way models, DST_total can be adequately modeled as descending from a single Northeast Asian source, including DevilsCave_N (P\u0026thinsp;=\u0026thinsp;0.798), AR_LN (P\u0026thinsp;=\u0026thinsp;0.731) and AR_Xianbei_IA (P\u0026thinsp;=\u0026thinsp;0.451), whereas models using Central Plain populations as the sole source do not fit, such as Miaozigou_MN (P\u0026thinsp;=\u0026thinsp;0.045), Shimao_LN (P\u0026thinsp;=\u0026thinsp;0.001). These results suggest that DST_total derives predominantly from Northeast Asian ancestry (Supplementary Data 5). Two-way qpAdm models further indicate that DST_total can be modeled as a mixture of two Northeast Asian sources, for example AR_LN and HMMH_MN (P\u0026thinsp;=\u0026thinsp;0.979, 65% AR_LN, 35% HMMH_MN), or AR_Xianbei_IA and DevilsCave_N (P\u0026thinsp;=\u0026thinsp;0.741, 25% AR_Xianbei_IA, 75% DevilsCave_N). These results reinforce that the DST individuals primarily descend from ancient Northeast Asian populations (Supplementary Data 5).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eEstimation of kinship\u003c/h2\u003e \u003cp\u003eTo investigate potential genetic relatedness among individuals co-buried within single graves at the DST site, we estimated genetic relatedness among 11 individuals recovered from two burials, while M7:4 and M7:6 were excluded from the kinship analysis due to coverage below 0.01\u0026times; (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Pairwise mismatch rates (PMR) were first calculated based on psedo-haploid genotypes based on the \u0026ldquo;1240K\u0026rdquo; SNP panel. The PMR results suggest the presence of both first- and second-degree relationships between the DST individuals (Supplementary Data 6). We applied READ to independently assess the genetic kinship relationships among these individuals based on normalized P0 values. Our analysis identified multiple closely related pairs. M6:1-M6:2 was classified as first-degree relatives (Parent-offspring; P0\u0026thinsp;=\u0026thinsp;0.7565), while M6:3-M7:3 (P0\u0026thinsp;=\u0026thinsp;0.8058), M6:3-M7:7 (P0\u0026thinsp;=\u0026thinsp;0.8123), M7:2-M7:3 (P0\u0026thinsp;=\u0026thinsp;0.8061) and M7:2-M7:7 (P0\u0026thinsp;=\u0026thinsp;0.8097) were also assigned as first-degree relatives. M7:3-M7:7 and M7:1-M7:2 was identified as genetically identical (P0 values were all around 0.49), suggesting either identical twins or the same individual. Osteological analysis identified M7:3-M7:7 as adult males. Considering that M7:7 lacked a cranium, exhibited disarticulated postcranial elements, and was located near M7:3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC), we infer that M7:3 and M7:7 likely represent the same individual; M7:1 was a 20-30-year-old female and M7:2 an approximately 40-year-old male. Both tooth samples were collected from the mandible, reducing the likelihood of mixup, thus we infer that these two individuals were twins. M6:2-M7:5 and M6:3-M7:2 both share a second-degree kinship relationship, there are also multiple third-degree relative pairs. (Supplementary Data 7). Third-degree or closer kinship relationships exist both within and between the M6 and M7 co-buried graves. Considering that all males from both burials belong to the Y-chromosome haplogroup C2b and that all were primary co-burials, it is likely that the two burial clusters represent a single extended family, closely connected through paternal lineage, indicative of a patrilineal social structure.\u003c/p\u003e \u003cp\u003eTo further clarify the kinship relationships between individuals, we applied the KIN method. Consistent with these findings, KIN analysis further confirmed the first-degree parent-offspring relationship between M6:1-M6:2, as well as sibling relationships between M7:2-M7:3/M7:7. M7:3-M7:7 (LogLikelihoodRatio\u0026thinsp;=\u0026thinsp;92.659) was again confirmed as genetically identical (Supplementary Data 8). Several additional pairs (e.g., M6:3 with M7:3) exhibited kinship coefficients and IBD segment counts consistent with second-degree or third-degree relationships. The highly concordant results across PMR, READ and KIN analyses robustly confirm the presence of multiple close kinships within this population. To further refine the degree of genetic relatedness, we applied ancIBD to detect pairwise identity-by-descent (IBD) segments along the genome. The IBD patterns are highly consistent with previous kinship inferences. The pair M6:1 and M6:2 exhibited extensive genome-wide IBD sharing, with nearly continuous segments distributed across all autosomes, consistent with a first-degree relationship (parent-offspring or full siblings). The pair M7:2 and M7:3 also demonstrated substantial IBD sharing, characterized by numerous long IBD segments interspersed with non-shared regions, indicative of a full sibling relationship (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo reconstruct the most probable pedigree structure, we integrated autosomal kinship analyses, uniparental genetic markers, biological sex and age-at-death estimates. The results indicate that the M6 and M7 burials belong to a single extended family centered on paternal lineage. Within this group, M7:2 and M7:3 form a pair of full siblings, sharing both parents; while M6:1 and M6:2 represent a mother\u0026ndash;daughter pair. M6:3 shows a second-degree relationship with M7:2 and M7:3, and a third-degree relationship with M6:2. In addition, M6:4-M7:2 and M7:5-M6:2 share a second-degree relationship. As the maternal identity between individuals M6:1 and M6:2 cannot yet be conclusively determined, we propose two alternative pedigree models (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB), wherein M6:1 is assumed to be the mother in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, and M6:2 is assumed to be the mother in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB. The two co-burials are located close to each other along a north\u0026ndash;south axis, suggesting that they may have formed part of a single, closely related kin group. The results reveal the presence of two core nuclear families within the DST site.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIndividuals with the same border color share an identical mtDNA haplotype.\u003c/p\u003e \u003cp\u003eWe further applied hapROH to evaluate runs of homozygosity (ROH) across the DST individuals (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). ROH are extended stretches of homozygous segments in the genome, and the total length and distribution of ROH segments can reflect the levels of parental relatedness and population size. Our analysis reveals that all DST individuals possess only limited amounts of ROH longer than 4 cM, with most ROH segments being short (\u0026lt;\u0026thinsp;12 cM), and with few segments exceeding 20 cM. The absence of long ROH segments suggests that none of the DST individuals are recent inbred offspring and that their parents were not closely related.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we combined genome-wide data, uniparental markers and multiple relatedness utalities to investigate how biological relationships shaped mortuary practices at the DST site. From a population perspective, DST individuals align most closely with ancient groups from the Amur River and West Liao River regions, which is geographically consistent with the site\u0026rsquo;s position on the Songnen Plain. Outgroup \u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003ef\u003c/em\u003e\u003csub\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sub\u003e statistics indicate greater allele sharing with northern East Asian populations than with Yellow River basin groups, and qpAdm modeling indicates that DST individuals derive the majority of their ancestry from ancient Northeast Asian populations. These findings support a scenario of long-term genetic continuity in Northeast Asia, with only limited external gene flow during the Late Bronze Age.\u003c/p\u003e \u003cp\u003eThe uniparental and autosomal evidence together indicate that the excavated individuals represent closely related members of extended families. Two core family units can be reconstructed with high confidence. M6:1 and M6:2 form a mother and daughter pair, supported by both their shared mitochondrial haplogroup B4b1a3a and first-degree autosomal relatedness. M7:2 and M7:3 form a full-sibling pair, sharing mitochondrial haplogroup D2 and Y haplogroup C2b1a1b, with extensive autosomal IBD segments that are characteristic of full siblings. M6:3 shows a second-degree relationship with M7:2 and M7:3, and a third-degree relationship with M6:2. In addition, M6:4-M7:2 and M7:5-M6:2 share a second-degree relationship. M7:3 and M7:7 are genetically indistinguishable and likely represent a duplicate sampling of the same individual. These cross-grave links indicate that co-burial at DST encompassed not only nuclear families but also intergenerational lineages, implying a burial organization coordinated at the lineage level rather than at the level of a single household.\u003c/p\u003e \u003cp\u003eA notable sex pattern characterizes the two chambers. In our view, the most plausible explanation is a sex-structured co-burial within a patrilineal framework. Under this model, the low diversity of Y-chromosome lineages among males indicates a persistent paternal line, whereas the heterogeneous mitochondrial haplotypes reflect female in-marriage from outside groups. This pattern parallels that observed in Bronze Age cemeteries of central Europe, where repeated male-line continuity and isotopic evidence for non-local women suggest patrilocal residence and female exogamy (Haak et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Knipper et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The DST pattern also contrasts with the Neolithic Fujia site in eastern China, where two cemeteries were organized by maternal clans with low mitochondrial diversity and diverse Y lineages (Wang et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Given the modest sample size at DST, both models should be treated as hypotheses. The following tests are diagnostic and feasible with additional material: (i) replicate the low Y and higher mtDNA diversity in more chambers; (ii) test for sex-biased mobility using strontium and oxygen isotopes; (iii) evaluate X-to-autosome allele-sharing asymmetries; and (iv) assess whether kinship networks cluster by chamber beyond the two graves studied here.\u003c/p\u003e \u003cp\u003eROH profiles lack long segments and are dominated by short tracts, which is inconsistent with recent consanguinity. This supports out-marriage and a relatively large effective population size, and provides a counterpoint to elite contexts that show extreme inbreeding. The combination of outbred ROH signatures, limited Y diversity, and cross-chamber second-degree relatedness supports a model of a lineage-based community that maintained a local paternal line while incorporating occasional non-local individuals, plausibly through marriage alliances. Integrating ancestry and kinship clarifies how population processes intersected with social organization. The ancestry profile places DST within a Northeast Asian continuum connected to Amur and West Liao River groups. Historical and archaeogenomic research documents repeated pulses of interaction across the Northeast Asia during the second millennium BCE. In this context, the DST pattern is consistent with a community anchored by local male descent that occasionally integrated external ancestry. Such integration is expected to be mediated by women under patrilocal residence, which aligns with the observed mitochondrial diversity.\u003c/p\u003e \u003cp\u003eOur interpretations remain constrained by sample size, uneven coverage across individuals, and the focus on two chambers. Nonetheless, the DST case strengthens the emerging view that prehistoric East Asia featured diverse descent rules and mortuary systems. DST falls on the patrilineal side of this spectrum, whereas Fujia represents a matrilineal end member. Additional genome-wide data from further DST chambers, high-resolution radiocarbon modeling, isotopic mobility data, and formal tests on the X chromosome will enable stronger evaluation of residence rules, the spatial extent of the lineage, and the temporal depth of the paternal line at the cemetery scale.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study integrates genome-wide data, uniparental markers, identity-by-descent tracts, and runs of homozygosity to evaluate kinship organization and population history at DST site in Late Bronze Age Northeast Asia. Two first-degree dyads occur within chambers (a mother and daughter in M6; full brothers in M7), and a paternal half-sibling link bridges the graves. Together with low Y-chromosome diversity among males (C2b-related lineages) and heterogeneous mitochondrial haplotypes, as well as the absence of long ROH in all individuals, these findings indicate mortuary recruitment structured by biological kinship, persistence of a local paternal line at cemetery scale, and out-marriage rather than recent consanguinity. A parsimonious interpretation is a patrilineal system with female exogamy and sex-structured co-burials.\u003c/p\u003e \u003cp\u003eFrom a population perspective, DST individuals fall within a Northeast Asian genetic continuum most closely related to Amur River and West Liao River groups. qpAdm models that fit the data best contain AR/WLR-related source, which situates DST within known second-millennium BCE networks of interaction across Northeast Asia. Under patrilocal residence, limited external ancestry would be expected to enter predominantly via in-marrying women, consistent with the observed mitochondrial diversity. This configuration contrasts with the Neolithic Fujia site in eastern China, where two cemeteries were organized by maternal clans with low mtDNA diversity and diverse Y lineages, and it parallels Bronze Age central European cemeteries that show male-line continuity alongside isotopic evidence for non-local women.\u003c/p\u003e \u003cp\u003eWe acknowledge limitations arising from sample size, uneven coverage, and the focus on two chambers. Future work should expand genomic sampling across additional DST burials, incorporate high-resolution radiocarbon modeling, and pair genetic analyses with strontium and oxygen isotopes to test sex-biased mobility. X-to-autosome allele-sharing tests provide an additional genetics-only check for sex-biased gene flow. These data will allow stronger evaluation of the spatial extent and temporal depth of the DST lineage and will refine the balance between descent rules and marriage practices in structuring mortuary space.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConflict of interest\u003c/strong\u003e \u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by the Major Projects of Key Research Bases of Humanities and Social Sciences of the Ministry of Education of China (Grant No. 22JJD780009), the National Social Science Fund of China (Grant No. 23VLS007 and 23VRC034) and the National Natural Science Foundation of China (Grant No. 42472029).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eDanyang Ge, Ruiqi Zou and Jiaqi Jin wrote the main manuscript text. Danyang Ge performed the experiment and data analysis. Xiaoxuan Shi, Xiaoming Wang, Di Zhang and Xinghan Zhang provided the archaeological samples and information. Chao Ning and Quanchao Zhang contributed to review and editing of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eWe thank all the volunteers who participated in the DST excavations and appreciate the support from Jilin Provincial Institute of Cultural Relics and Archaeology for this research.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe basemap used in Figure 1 is in the public domain and accessible through the Natural Earth website (https://www.naturalearthdata.com/downloads/10m-raster-data/). 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J Archaeol Science: Rep 53:104333. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jasrep.2023.104333\u003c/span\u003e\u003cspan address=\"10.1016/j.jasrep.2023.104333\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"archaeological-and-anthropological-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aasc","sideBox":"Learn more about [Archaeological and Anthropological Sciences](http://link.springer.com/journal/12517)","snPcode":"12520","submissionUrl":"https://submission.nature.com/new-submission/12520/3","title":"Archaeological and Anthropological Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Ancient DNA, Kinship, Patrilineal society, Female exogamy","lastPublishedDoi":"10.21203/rs.3.rs-7908178/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7908178/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eKinship plays a pivotal role in structuring prehistoric communities, yet direct genomic evidence worldwide is sparse, especially in northeastern China. We present genome-wide data from 11 individuals from two co-burial graves (M6, M7) at the Late Bronze Age Dongshantou (DST) site in Jilin Province, Northeast China. Using uniparental genetic markers in combination with multiple relatedness estimators, we identify three first-degree, several second-degree and third-degree relationships connect the two graves. All males share the same Y-chromosome lineages (C2b), while mitochondrial haplotypes vary across graves, and lack of close-kin unions. DST individuals derive most of their ancestry from Amur River and West Liao River populations, indicating both long-term regional continuity and low-level external gene flow. We propose that DST was a patrilineal family cemetery, with burials organized around nuclear family co-burials, though exceptions\u0026mdash;such as M7:5, who shares a mitochondrial haplotype with M6:4 despite being third-degree related to M7 members\u0026mdash;suggest maternal connections or inter-family alliances. This pattern contrasts with recently reported matrilineal organization at the Neolithic Fujia site and aligns with patrilocal, female-exogamous systems documented in Bronze Age Europe. DST provides the first genome-wide evidence for lineage-based co-burial, sex-structured mortuary space, regionally integrated genetic structure in Late Bronze Age Northeast Asia.\u003c/p\u003e","manuscriptTitle":"Ancient Genomes Reveal the Origins and Kinship Organisation of Late Bronze Age Populations in Northeastern China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-11 18:08:36","doi":"10.21203/rs.3.rs-7908178/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-10T09:51:48+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-27T18:36:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-26T11:07:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"304275346370200712447409303646241384197","date":"2026-02-10T02:51:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"35538548838457832853623914831244586407","date":"2026-02-09T09:57:07+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-09T09:35:04+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-22T10:57:59+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-21T06:24:44+00:00","index":"","fulltext":""},{"type":"submitted","content":"Archaeological and Anthropological Sciences","date":"2025-10-20T18:18:36+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"archaeological-and-anthropological-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aasc","sideBox":"Learn more about [Archaeological and Anthropological Sciences](http://link.springer.com/journal/12517)","snPcode":"12520","submissionUrl":"https://submission.nature.com/new-submission/12520/3","title":"Archaeological and Anthropological Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"803240d4-5c54-4b44-93fd-9db4e4cb6f92","owner":[],"postedDate":"February 11th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-04-27T16:04:23+00:00","versionOfRecord":{"articleIdentity":"rs-7908178","link":"https://doi.org/10.1007/s12520-026-02466-w","journal":{"identity":"archaeological-and-anthropological-sciences","isVorOnly":false,"title":"Archaeological and Anthropological Sciences"},"publishedOn":"2026-04-20 15:59:19","publishedOnDateReadable":"April 20th, 2026"},"versionCreatedAt":"2026-02-11 18:08:36","video":"","vorDoi":"10.1007/s12520-026-02466-w","vorDoiUrl":"https://doi.org/10.1007/s12520-026-02466-w","workflowStages":[]},"version":"v1","identity":"rs-7908178","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7908178","identity":"rs-7908178","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}