Multiple human population movements and cultural dispersal events shaped the landscape of Chinese paternal heritage.

Large-scale genomic projects and ancient DNA innovations have ushered in a new paradigm for exploring human evolutionary history. However, the genetic legacy of spatiotemporally diverse ancient Eurasians within Chinese paternal lineages remains unresolved. Here, we report an integrated Y-chromosome genomic database encompassing 15,563 individuals from both modern and ancient Eurasians, including 919 newly reported individuals, to investigate Chinese paternal genomic diversity. The high-resolution, time-stamped phylogeny reveals multiple diversification events and extensive expansions in the early and middle Neolithic. We identify four major ancient population movements, each associated with technological innovations, that have shaped the Chinese paternal landscape. Firstly, the expansion of early East Asians and millet farmers from the Yellow River Basin, predominantly carrying O2/D subclades, significantly influenced the formation of the Sino-Tibetan people and facilitated the permanent settlement of the Tibetan Plateau. Secondly, the dispersal of rice farmers from the Yangtze River Valley, carrying O1 and certain O2 sublineages, reshapes the genetic makeup of southern Han Chinese, as well as the Tai-Kadai, Austronesian, Hmong-Mien, and Austroasiatic people. Thirdly, Neolithic Siberian Q/C paternal lineages originated and proliferated among hunter-gatherers on the Mongolian Plateau and the Amur River Basin, leaving a significant imprint on the gene pools of northern China. Fourthly, J/G/R paternal lineages derived from western Eurasia, which were initially spread by Yamnaya-related steppe pastoralists, maintain their presence primarily in northwestern China. Overall, our research provides comprehensive genetic evidence elucidating the significant impact of interactions with culturally distinct ancient Eurasians on the patterns of paternal diversity in modern Chinese populations.

Population genetic admixture and evolutionary history in the Shandong Peninsula inferred from integrative modern and ancient genomic resources.

BACKGROUND: Ancient northern East Asians (ANEA) from the Yellow River region, who pioneered millet cultivation, play a crucial role in understanding the origins of ethnolinguistically diverse populations in modern China and the entire landscape of deep genetic structure and variation discovery in modern East Asians. However, the direct links between ANEA and geographically proximate modern populations, as well as the biological adaptive processes involved, remain poorly understood. RESULTS: Here, we generated genome-wide SNP data for 264 individuals from geographically different Han populations in Shandong. An integrated genomic resource encompassing both modern and ancient East Asians was compiled to examine fine-scale population admixture scenarios and adaptive traits. The reconstruction of demographic history and hierarchical clustering patterns revealed that individuals from the Shandong Peninsula share a close genetic affinity with ANEA, indicating long-term genetic continuity and mobility in the lower Yellow River basin since the early Neolithic period. Biological adaptive signatures, including those related to immune and metabolic pathways, were identified through analyses of haplotype homozygosity and allele frequency spectra. These signatures are linked to complex traits such as height and body mass index, which may be associated with adaptations to cold environments, dietary practices, and pathogen exposure. Additionally, allele frequency trajectories over time and a haplotype network of two highly differentiated genes, ABCC11 and SLC10A1, were delineated. These genes, which are associated with axillary odor and bilirubin metabolism, respectively, illustrate how local adaptations can influence the diversification of traits in East Asians. CONCLUSIONS: Our findings provide a comprehensive genomic dataset that elucidates the fine-scale genetic history and evolutionary trajectory of natural selection signals and disease susceptibility in Han Chinese populations. This study serves as a paradigm for integrating spatiotemporally diverse ancient genomes in the era of population genomic medicine.

Using simulated microhaplotype genotyping data to evaluate the value of machine learning algorithms for inferring DNA mixture contributor numbers.

Inferring the number of contributors (NoC) is a crucial step in interpreting DNA mixtures, as it directly affects the accuracy of the likelihood ratio calculation and the assessment of evidence strength. However, obtaining the correct NoC in complex DNA mixtures remains challenging due to the high degree of allele sharing and dropout. This study aimed to analyze the impact of allele sharing and dropout on NoC inference in complex DNA mixtures when using microhaplotypes (MH). The effectiveness and value of highly polymorphic MH for NoC inference in complex DNA mixtures were evaluated through comparing the performance of three NoC inference methods, including maximum allele count (MAC) method, maximum likelihood estimation (MLE) method, and random forest classification (RFC) algorithm. In this study, we selected the top 100 most polymorphic MH from the Southern Han Chinese (CHS) population, and simulated over 40 million complex DNA mixture profiles with the NoC ranging from 2 to 8. These profiles involve unrelated individuals (RM type) and related pairs of individuals, including parent-offspring pairs (PO type), full-sibling pairs (FS type), and second-degree kinship pairs (SE type). Our results indicated that how the number of detected alleles in DNA mixture profiles varied with the markers' polymorphism, kinship's involvement, NoC, and dropout settings. Across different types of DNA mixtures, the MAC and MLE methods performed best in the RM type, followed by SE, FS, and PO types, while RFC models showed the best performance in the PO type, followed by RM, SE, and FS types. The recall of all three methods for NoC inference were decreased as the NoC and dropout levels increased. Furthermore, the MLE method performed better at low NoC, whereas RFC models excelled at high NoC and/or high dropout levels, regardless of the availability of a priori information about related pairs of individuals in DNA mixtures. However, the RFC models which considered the aforementioned priori information and were trained specifically on each type of DNA mixture profiles, outperformed RFC_ALL model that did not consider such information. Finally, we provided recommendations for model building when applying machine learning algorithms to NoC inference.

Comprehensive landscape of non-CODIS STRs in global populations provides new insights into challenging DNA profiles.

The worldwide implementation of short tandem repeats (STR) profiles in forensic genetics necessitated establishing and expanding the CODIS core loci set to facilitated efficient data management and exchange. Currently, the mainstay CODIS STRs are adopted in most general-purpose forensic kits. However, relying solely on these loci failed to yield satisfactory results for challenging tasks, such as bio-geographical ancestry inference, complex DNA mixture profile interpretation, and distant kinship analysis. In this context, non-CODIS STRs are potent supplements to enhance the systematic discriminating power, particularly when combined with the high-throughput next-generation sequencing (NGS) technique. Nevertheless, comprehensive evaluation on non-CODIS STRs in diverse populations was scarce, hindering their further application in routine caseworks. To address this gap, we investigated genetic variations of 178 historically available non-CODIS STRs from ethnolinguistically different worldwide populations and studied their characteristics and forensic potentials via high-coverage whole genome sequencing (WGS) data. Initially, we delineated the genomic properties of these non-CODIS markers through sequence searching, repeat structure scanning, and manual inspection. Subsequent population genetics analysis suggested that these non-CODIS STRs had comparable polymorphism levels and forensic utility to CODIS STRs. Furthermore, we constructed a theoretical next-generation sequencing (NGS) panel comprising 108 STRs (20 CODIS STRs and 88 non-CODIS STRs), and evaluated its performance in inferring bio-geographical ancestry origins, deconvoluting complex DNA mixtures, and differentiating distant kinships using real and simulated datasets. Our findings demonstrated that incorporating supplementary non-CODIS STRs enabled the extrapolation of multidimensional information from a single STR profile, thereby facilitating the analysis of challenging forensic tasks. In conclusion, this study presents an extensive genomic landscape of forensic non-CODIS STRs among global populations, and emphasized the imperative inclusion of additional polymorphic non-CODIS STRs in future NGS-based forensic systems.

Distinguished biological adaptation architecture aggravated population differentiation of Tibeto-Burman-speaking people.

Tibeto-Burman (TB) people have endeavored to adapt to the hypoxic, cold, and high-UV high-altitude environments in the Tibetan Plateau and complex disease exposures in lowland rainforests since the late Paleolithic period. However, the full landscape of genetic history and biological adaptation of geographically diverse TB-speaking people, as well as their interaction mechanism, remain unknown. Here, we generate a whole-genome meta-database of 500 individuals from 39 TB-speaking populations and present a comprehensive landscape of genetic diversity, admixture history, and differentiated adaptative features of geographically different TB-speaking people. We identify genetic differentiation related to geography and language among TB-speaking people, consistent with their differentiated admixture process with incoming or indigenous ancestral source populations. A robust genetic connection between the Tibetan-Yi corridor and the ancient Yellow River people supports their Northern China origin hypothesis. We finally report substructure-related differentiated biological adaptative signatures between highland Tibetans and Loloish speakers. Adaptative signatures associated with the physical pigmentation (EDAR and SLC24A5) and metabolism (ALDH9A1) are identified in Loloish people, which differed from the high-altitude adaptative genetic architecture in Tibetan. TB-related genomic resources provide new insights into the genetic basis of biological adaptation and better reference for the anthropologically informed sampling design in biomedical and genomic cohort research.

Evaluation of large-scale highly polymorphic microhaplotypes in complex DNA mixtures analysis using RMNE method.

DNA mixture interpretation is one of the most challenging problems in forensics. Complex DNA mixtures are more difficult to analyze when there are more than two contributors or related contributors. Microhaplotypes (MHs) are polymorphic genetic markers recently discovered and employed in DNA mixture analysis. However, the evidentiary interpretation of the MH genotyping data needs more debate. The Random Man Not Excluded (RMNE) method analyzes DNA mixtures without using allelic peak height data or the number of contributors (NoC) assumptions. This study aimed to assess how well RMNE interpreted mixed MH genotyping data. We classified the MH loci from the 1000 Genomes Project database into groups based on their Ae values. Then we performed simulations of DNA mixtures with 2-10 unrelated contributors and DNA mixtures with a pair of sibling contributors. For each simulated DNA mixture, incorrectly included ratios were estimated for three types of non-contributors: random men, parents of contributors, and siblings of contributors. Meanwhile, RMNE probability was calculated for contributors and three types of non-contributors, allowing loci mismatch. The results showed that the MH number, the MH Ae values, and the NoC affected the RMNE probability of the mixture and the incorrectly included ratio of non-contributors. When there were more MHs, MHs with higher Ae values, and a mixture with less NoC, the RMNE probability, and the incorrectly included ratio decreased. The existence of kinship in mixtures complicated the mixture interpretation. Contributors' relatives as non-contributors and related contributors in the mixture increased the demands on the genetic markers to identify the contributors correctly. When 500 highly polymorphic MHs with Ae values higher than 5 were used, the four individual types could be distinguished according to the RMNE probabilities. This study reveals the promising potential of MH as a genetic marker for mixed DNA interpretation and the broadening of RMNE as a parameter indicating the relationship of a specific individual with a DNA mixture in the DNA database search.

Characterizing the amplification of STR markers in multiplex polymerase chain displacement reaction using massively parallel sequencing.

Polymerase chain displacement reaction (PCDR) showed advantages in forensic low-template DNA analysis with improved amplification efficiency, higher allele detection capacity, and lower stutter artifact than PCR. However, characteristics of STR markers after PCDR amplification remain unclarified for the limited resolving power of capillary electrophoresis (CE). This issue can be addressed by massively parallel sequencing (MPS) technology with higher throughput and discriminability. Here, we developed a multiplex PCDR system including 24 STRs and amelogenin. In addition, a PCR reference was established for comparison. After amplification, products were subjected to PCR-free library construction and sequenced on the Illumina NovaSeq system. We implemented a sequence-matching pipeline to separate different amplicon types of PCDR products from the combination of primers. In the sensitivity test, the PCDR multiplex obtained full STR profiles with as low as 125 pg 2800M control DNA. Based on that, single-source DNA samples were tested. First, highly concordant genotypes were observed among the PCDR multiplex, the PCR reference, and CE-based STR kits. Next, read counts of different PCDR amplicon types were investigated, showing a relative abundance of 78:12:12:1 for the shortest amplicon S, the two medium amplicons M1 and M2, and the longest amplicon L. We also analyzed the stutter artifacts for distinct amplicon types, and the results revealed the reduction of N - 1 and N - 2 contraction stutters, and the increase of N + 1 and N + 2 elongation stutters in PCDR samples. Moreover, we confirmed the feasibility of PCDR for amplifying degraded DNA samples and unbalanced DNA mixtures. Compared to the previous proof of principle study, our work took a further step to characterize the complete profile of STR markers in the PCDR context. Our results suggested that the PCDR-MPS workflow is an effective approach for forensic STR analysis. Corresponding findings in this study may help the development of PCDR-based assays and probabilistic methods in future studies.

An efficient ancestry informative SNPs panel for further discriminating East Asian populations.

In forensic genetics, the use of ancestry informative single-nucleotide polymorphisms (AISNPs) panels can narrow the direction of the investigation by estimating an individual's biogeographic ancestry. However, distinguishing subgroups within continental regions requires more specific panels. In this study, we screened 19 AISNPs from the 1000 Genomes Project (1KG) based on their FST values to distinguish target populations in East Asia and obtained genotypes through SNaPshot. The 19 AISNPs could divide the global population of the 1KG into five clusters and could further divide the East Asian population into four clusters: Japanese, Han Chinese, Dai Chinese, and Kinh in Ho Chi Minh City of Vietnam. In summary, the 19-AISNP panel may serve as a useful and cost-effective tool for forensic ancestry inference in East Asian populations at a finer scale.

A proof-of-principle study on implementing polymerase chain displacement reaction (PCDR) to improve forensic low-template DNA analysis.

Polymerase chain reaction (PCR) plays an important role in forensic DNA analysis. However, the amplification of low-template DNA (LTDNA) samples usually encounters unsatisfactory results for the limited efficiency of PCR, which would interfere with the subsequent profile interpretation. Polymerase chain displacement reaction (PCDR) is a highly-efficient technique characterized by combining PCR and strand displacement reaction into a single PCDR cycle. This study explored the feasibility of PCDR for improving forensic LTDNA analysis. STR markers commonly used in forensic genetics were subjected to PCDR amplification and capillary electrophoresis detection. The results of singleplex reactions indicated that PCDR surpassed original PCR in efficiency for STR amplification. The average peak height of alleles in PCDR profiles was linearly correlated to the number of outer primers adopted for initiating the strand displacement process. Further, we assessed the multiplexing potential of PCDR by incorporating 17 STRs included in the expanded CODIS core loci and Amelogenin gene into a multiplex PCDR system. For pristine DNA templates ranged from 200 pg to 12.5 pg, the multiplex PCDR system consistently exhibited higher allele peak height as well as less allele dropout compared to the multiplex PCR references. Meanwhile, a significant reduction of stutter ratio was extensively observed in PCDR profiles. We also tested mock casework samples to verify the practical ability of multiplex PCDR for LTDNA detection. With DNA input varying from 48.1 pg to 6.6 pg, the multiplex PCDR system consistently obtained more allelic information than multiplex PCR methods. Our data collectively suggested that it is feasible to apply PCDR in forensic LTDNA analysis.

Evaluation of microfluidics-based droplet PCR combined with multiplex STR system in forensic science.

Because of its excellent monodispersity, high throughput, and low volume, microfluidics-based droplet PCR has become the core technology of digital PCR, next-generation sequencing, and other technology platforms. This study constructed a microfluidic water-in-oil droplet PCR system and amplified a commercially available forensic 22-plex short tandem repeat detection system. We analyzed the sensitivity, concordance, amplification efficiency of the droplet PCR, and influence factors of the above aspects. The droplet PCR showed high concordance with conventional bulk PCR and had high sensitivity as 0.125 ng. Furthermore, we observed the performance of droplet PCR in high-order mixed DNA. As the mixture ratios from 10:1 to 30:1, droplet PCR presented more mixture proportion (Mx) increased loci from 11 (57.89%) to 17 (89.47%). In the mixture ratios 20:1, 25:1, and 30:1, significant Mx differences between droplet PCR and bulk PCR were observed (p < 0.05). The results showed that the droplet PCR could improve the identification of the minor contributor's DNA in a two-person mixture and alleviate the imbalanced amplification problem. This study provides a reference and basis for the wide application of droplet PCR in forensic science.

AI-SNPs screening based on the whole genome data and research on genetic structure differences of subcontinent populations.

The genetic structure differences in population is one of the key elements in medical research involving multi-population samples. A set of ancestry-informative single nucleotide polymorphisms (AI-SNPs) can be utilized to analyze genetic component of a population, infer ancestral origin of individuals and pre-filter samples to reduce the impact of population genetic structure differences on medical research. However, most of the published studies were focused on revealing the differences between populations of continents or regions of a continent. In this paper, AI-SNPs were screened by calculating FST value in each pair of five East Asian populations: Japanese in Tokyo (JPT), Han Chinese in Beijing (CHB), Southern Han Chinese (CHS), Chinese Dai in Xishuangbanna (CDX) and Kinh in Ho Chi Minh City (KHV) in the 1000 Genomes Project phase 3 (GRCh37.p13) to analyze differences in subcontinent populations. The results demonstrate that the five East Asian populations in our study were assigned to three clusters: JPT, CHB and CHS, CDX and KHV. A set of AI-SNPs can be used for analysis of individual genetic composition and selection of representative individuals. Individuals with over 80% population representative genetic components have good representativeness of a population. This paper demonstrated the practical value of the method, which was performed to verify the ancestral composition and select representative samples with a panel of screened AI-SNPs by FST value, thereby reducing the influence of genetic structure differences in subcontinent populations on population-related medical research.

A targeted ancestry informative InDels panel on capillary electrophoresis for ancestry inference in Asian populations.

CE is the primary methodology used in forensic DNA typing. Alleles of commonly used types of genetic markers could be separated and detected via CE based on dye color and migration time. Insertion/deletion (InDel) is an ideal genetic marker for forensic DNA analysis due to their abundance in the human genome, low mutation rate, availability of their allele types via CE, and elimination of stutter peaks. Moreover, InDels could be used as ancestry informative markers since allele frequencies of InDels is different among geographically separated populations. Several ancestry informative insertion/deletion panels have been established based on CE platform to achieve the intercontinental populations distinction. However, improvements to differentiate intracontinental populations is few. In this study, 21 InDels with fixation index (FST ) > 0.15 were selected and assembled into one ancestry informative insertion/deletion panel. Using well-designed primers, those 21 InDels could be amplified successfully and genotyped on the CE platform accurately and completely. The panel showed a large FST distance distinction among the ten Asian populations. Using clustering analysis, ten Asian populations were classified into three subgroups: East Asian, Southeast Asian, and South Asian subgroups. To evaluate the panel's capability in ancestry inference, a validation experiment was undertaken with 319 individuals from four geographically separated populations in China. Four Chinese populations were classified into different ancestry subgroups and 81.8% test individuals' ancestry could be inferred correctly. Our result showed that development of high ancestry informative InDels panel based on CE platform is a potential for individual ancestry inference among intracontinental populations.