Reconstructing complex admixture history using a hierarchical model.

Various methods have been proposed to reconstruct admixture histories by analyzing the length of ancestral chromosomal tracts, such as estimating the admixture time and number of admixture events. However, available methods do not explicitly consider the complex admixture structure, which characterizes the joining and mixing patterns of different ancestral populations during the admixture process, and instead assume a simplified one-by-one sequential admixture model. In this study, we proposed a novel approach that considers the non-sequential admixture structure to reconstruct admixture histories. Specifically, we introduced a hierarchical admixture model that incorporated four ancestral populations and developed a new method, called HierarchyMix, which uses the length of ancestral tracts and the number of ancestry switches along genomes to reconstruct the four-way admixture history. By automatically selecting the optimal admixture model using the Bayesian information criterion principles, HierarchyMix effectively estimates the corresponding admixture parameters. Simulation studies confirmed the effectiveness and robustness of HierarchyMix. We also applied HierarchyMix to Uyghurs and Kazakhs, enabling us to reconstruct the admixture histories of Central Asians. Our results highlight the importance of considering complex admixture structures and demonstrate that HierarchyMix is a useful tool for analyzing complex admixture events.

MultiWaverX: modeling latent sex-biased admixture history.

Sex-biased gene flow has been common in the demographic history of modern humans. However, the lack of sophisticated methods for delineating the detailed sex-biased admixture process prevents insights into complex admixture history and thus our understanding of the evolutionary mechanisms of genetic diversity. Here, we present a novel algorithm, MultiWaverX, for modeling complex admixture history with sex-biased gene flow. Systematic simulations showed that MultiWaverX is a powerful tool for modeling complex admixture history and inferring sex-biased gene flow. Application of MultiWaverX to empirical data of 17 typical admixed populations in America, Central Asia, and the Middle East revealed sex-biased admixture histories that were largely consistent with the historical records. Notably, fine-scale admixture process reconstruction enabled us to recognize latent sex-biased gene flow in certain populations that would likely be overlooked by much of the routine analysis with commonly used methods. An outstanding example in the real world is the Kazakh population that experienced complex admixture with sex-biased gene flow but in which the overall signature has been canceled due to biased gene flow from an opposite direction.

AdmixSim 2: a forward-time simulator for modeling complex population admixture.

BACKGROUND: Computer simulations have been widely applied in population genetics and evolutionary studies. A great deal of effort has been made over the past two decades in developing simulation tools. However, there are not many simulation tools suitable for studying population admixture. RESULTS: We here developed a forward-time simulator, AdmixSim 2, an individual-based tool that can flexibly and efficiently simulate population genomics data under complex evolutionary scenarios. Unlike its previous version, AdmixSim 2 is based on the extended Wright-Fisher model, and it implements many common evolutionary parameters to involve gene flow, natural selection, recombination, and mutation, which allow users to freely design and simulate any complex scenario involving population admixture. AdmixSim 2 can be used to simulate data of dioecious or monoecious populations, autosomes, or sex chromosomes. To our best knowledge, there are no similar tools available for the purpose of simulation of complex population admixture. Using empirical or previously simulated genomic data as input, AdmixSim 2 provides phased haplotype data for the convenience of further admixture-related analyses such as local ancestry inference, association studies, and other applications. We here evaluate the performance of AdmixSim 2 based on simulated data and validated functions via comparative analysis of simulated data and empirical data of African American, Mexican, and Uyghur populations. CONCLUSIONS: AdmixSim 2 is a flexible simulation tool expected to facilitate the study of complex population admixture in various situations.

Detecting fitness epistasis in recently admixed populations with genome-wide data.

BACKGROUND: Fitness epistasis, the interaction effect of genes at different loci on fitness, makes an important contribution to adaptive evolution. Although fitness interaction evidence has been observed in model organisms, it is more difficult to detect and remains poorly understood in human populations as a result of limited statistical power and experimental constraints. Fitness epistasis is inferred from non-independence between unlinked loci. We previously observed ancestral block correlation between chromosomes 4 and 6 in African Americans. The same approach fails when examining ancestral blocks on the same chromosome due to the strong confounding effect observed in a recently admixed population. RESULTS: We developed a novel approach to eliminate the bias caused by admixture linkage disequilibrium when searching for fitness epistasis on the same chromosome. We applied this approach in 16,252 unrelated African Americans and identified significant ancestral correlations in two pairs of genomic regions (P-value< 8.11 × 10- 7) on chromosomes 1 and 10. The ancestral correlations were not explained by population admixture. Historical African-European crossover events are reduced between pairs of epistatic regions. We observed multiple pairs of co-expressed genes shared by the two regions on each chromosome, including ADAR being co-expressed with IFI44 in almost all tissues and DARC being co-expressed with VCAM1, S1PR1 and ELTD1 in multiple tissues in the Genotype-Tissue Expression (GTEx) data. Moreover, the co-expressed gene pairs are associated with the same diseases/traits in the GWAS Catalog, such as white blood cell count, blood pressure, lung function, inflammatory bowel disease and educational attainment. CONCLUSIONS: Our analyses revealed two instances of fitness epistasis on chromosomes 1 and 10, and the findings suggest a potential approach to improving our understanding of adaptive evolution.

Genetic History of Xinjiang's Uyghurs Suggests Bronze Age Multiple-Way Contacts in Eurasia.

The Uyghur people residing in Xinjiang, a territory located in the far west of China and crossed by the Silk Road, are a key ethnic group for understanding the history of human dispersion in Eurasia. Here we assessed the genetic structure and ancestry of 951 Xinjiang's Uyghurs (XJU) representing 14 geographical subpopulations. We observed a southwest and northeast differentiation within XJU, which was likely shaped jointly by the Tianshan Mountains, which traverses from east to west as a natural barrier, and gene flow from both east and west directions. In XJU, we identified four major ancestral components that were potentially derived from two earlier admixed groups: one from the West, harboring European (25-37%) and South Asian ancestries (12-20%), and the other from the East, with Siberian (15-17%) and East Asian (29-47%) ancestries. By using a newly developed method, MultiWaver, the complex admixture history of XJU was modeled as a two-wave admixture. An ancient wave was dated back to ∼3,750 years ago (ya), which is much earlier than that estimated by previous studies, but fits within the range of dating of mummies that exhibited European features that were discovered in the Tarim basin, which is situated in southern Xinjiang (4,000-2,000 ya); a more recent wave occurred around 750 ya, which is in agreement with the estimate from a recent study using other methods. We unveiled a more complex scenario of ancestral origins and admixture history in XJU than previously reported, which further suggests Bronze Age massive migrations in Eurasia and East-West contacts across the Silk Road.

Inference of multiple-wave admixtures by length distribution of ancestral tracks.

The ancestral tracks in admixed genomes are valuable for population history inference. While a few methods have been developed to infer admixture history based on ancestral tracks, these methods suffer the same flaw: only population admixture history under some specific models can be inferred. In addition, the inference of history might be biased or even unreliable if the specific model deviates from the real situation. To address this problem, we firstly proposed a general discrete admixture model to describe the admixture history with multiple ancestral populations and multiple-wave admixtures. We next deduced the length distribution of ancestral tracks under the general discrete admixture model. We further developed a new method, MultiWaver, to explore multiple-wave admixture histories. Our method could automatically determine an optimal admixture model based on the length distribution of ancestral tracks, and estimate the corresponding parameters under this optimal model. Specifically, we used a likelihood ratio test (LRT) to determine the number of admixture waves, and implemented an expectation-maximization (EM) algorithm to estimate parameters. We used simulation studies to validate the reliability and effectiveness of our method. Finally, good performance was observed when our method was applied to real data sets of African Americans and Mexicans, and new insights were gained into the admixture history of Uyghurs and Hazaras.

Reconstruct recent multi-population migration history by using identical-by-descent sharing.

Identical-by-descent (IBD) is a fundamental genomic characteristic in population genetics and has been widely used for population history reconstruction. However, limited by the nature of IBD, which could only capture the relationship between two individuals/haplotypes, existing IBD-based history inference is constrained to two populations. In this study, we propose a framework by leveraging IBD sharing in multi-population and develop a method, MatrixIBD, to reconstruct recent multi-population migration history. Specifically, we employ the structured coalescent theory to precisely model the genealogical process and then estimate the IBD sharing across multiple populations. Within our model, we establish a theoretical connection between migration history and IBD sharing. Our method is rigorously evaluated through simulations, revealing its remarkable accuracy and robustness. Furthermore, we apply MatrixIBD to Central and South Asia in the Human Genome Diversity Project and successfully reconstruct the recent migration history of three closely related populations in South Asia. By taking into account the IBD sharing across multiple populations simultaneously, MatrixIBD enables us to attain clearer and more comprehensive insights into the history of regions characterized by complex migration dynamics, providing a holistic perspective on intricate patterns embedded within the recent population migration history.

Habitual Dietary Fiber Intake, Fecal Microbiota, and Hemoglobin A1c Level in Chinese Patients with Type 2 Diabetes.

High-fiber diet interventions have been proven to be beneficial for gut microbiota and glycemic control in diabetes patients. However, the effect of a low level of fiber in habitual diets remains unclear. This study aims to examine the associations of habitual dietary fiber intake with gut microbiome profiles among Chinese diabetes patients and identify differential taxa that mediated associations of dietary fiber with HbA1c level. Two cross-sectional studies and one longitudinal study were designed based on two follow-up surveys in a randomized trial conducted during 2015−2017. The study included 356 and 310 participants in the first and second follow-ups, respectively, with 293 participants in common in both surveys. Dietary fiber intake was calculated based on a 3-day 24-h diet recall at each survey and was classified into a lower or a higher group according to the levels taken based on the two surveys using 7.2 g/day as a cut-off value. HbA1c was assayed to assess glycemic status using a cut-off point of 7.0% and 8.0%. Microbiome was profiled by 16S rRNA sequencing. A high habitual dietary fiber intake was associated with a decrease in α-diversity in both the cross-sectional and longitudinal analyses. At the first follow−up, phylum Firmicutes and Fusobacteria were negatively associated with a higher dietary fiber intake (p < 0.05, Q < 0.15); at the second follow-up, genus Adlercreutzia, Prevotella, Ruminococcus, and Desulfovibrio were less abundant in patients taking higher dietary fiber (p < 0.05, Q < 0.15); genus Desulfovibrio and Ruminococcaceae (Unknown), two identified differential taxa by HbA1c level, were negatively associated with dietary fiber intake in both the cross-sectional and longitudinal analyses, and mediated the dietary fiber-HbA1c associations among patients taking dietary fiber ≥ 7.2 g/day (mediation effect ß [95%CI]: −0.019 [−0.043, −0.003], p = 0.018 and −0.019 [−0.046, −0.003], p = 0.016). Our results suggest that habitual dietary fiber intake has a beneficial effect on gut microbiota in Chinese diabetes patients. Further studies are needed to confirm our results.

Refining models of archaic admixture in Eurasia with ArchaicSeeker 2.0.

We developed a method, ArchaicSeeker 2.0, to identify introgressed hominin sequences and model multiple-wave admixture. The new method enabled us to discern two waves of introgression from both Denisovan-like and Neanderthal-like hominins in present-day Eurasian populations and an ancient Siberian individual. We estimated that an early Denisovan-like introgression occurred in Eurasia around 118.8-94.0 thousand years ago (kya). In contrast, we detected only one single episode of Denisovan-like admixture in indigenous peoples eastern to the Wallace-Line. Modeling ancient admixtures suggested an early dispersal of modern humans throughout Asia before the Toba volcanic super-eruption 74 kya, predating the initial peopling of Asia as proposed by the traditional Out-of-Africa model. Survived archaic sequences are involved in various phenotypes including immune and body mass (e.g., ZNF169), cardiovascular and lung function (e.g., HHAT), UV response and carbohydrate metabolism (e.g., HYAL1/HYAL2/HYAL3), while "archaic deserts" are enriched with genes associated with skin development and keratinization.

AdmixSim: A Forward-Time Simulator for Various Complex Scenarios of Population Admixture.

Background: Population admixture is a common phenomenon in humans, animals, and plants, and it plays a very important role in shaping individual genetic architecture and population genetic diversity. Inference of population admixture, however, is very challenging and typically relies on in silico simulation. We are aware of the lack of a computerized tool for such a purpose. A simulator capable of generating data under various complex admixture scenarios would facilitate the study of recombination, linkage disequilibrium, ancestry tracing, and admixture dynamics in admixed populations. We described such a simulator here. Results: We developed a forward-time simulator (AdmixSim) under the standard Wright Fisher model. It can simulate the following admixed populations: (1) multiple ancestral populations; (2) multiple waves of admixture events; (3) fluctuating population size; and (4) admixtures of fluctuating proportions. Analysis of the simulated data by AdmixSim showed that our simulator can quickly and accurately generate data resembling real-world values. We included in AdmixSim all possible parameters that would allow users to modify and simulate any kind of admixture scenario easily, so it is very flexible. AdmixSim records recombination break points and traces of each chromosomal segment from different ancestral populations, with which users can easily perform further analysis and comparative studies with empirical data. Conclusions: AdmixSim facilitates the study of population admixture by providing a simulation framework with the flexible implementation of various admixture models and parameters.

Epidemiology characteristics of the clonal complexes of Mycobacterium tuberculosis Lineage 4 in China.

Mycobacterium tuberculosis (M. tuberculosis) Lineage 4 (L4) is frequently prevailing in Western regions of China, where the tuberculosis incidence rate is high. However, the epidemiology characteristics of M. tuberculosis L4 in China remain poorly understood. Here, the 15-loci Variable number of tandem repeats (VNTR) patterns of 975 L4 isolates from a National Survey of Tuberculosis in China were used to construct a Minimum Spanning Tree (MST), which divided the 975 isolates into 5 major clonal complexes (CC; named CC1 to CC5). We found that the CCs of M. tuberculosis L4 were nationally distributed, geographically restricted, and different in epidemiology characteristics. For example, CC1 was mainly concentrated in East and Central China and significantly related to the farmer occupation and income of an individual (>4200 yuan) (p < .05); CC5 was mainly distributed in Southwest China and was associated with ethnic minorities. Notably, using whole genome sequencing (WGS) data of 141 strains that matched our samples, we found that both CC1 and CC5 were mapped to the sublineage L4.5. Nevertheless, due to the difference of geographical distribution, the epidemiology characteristics of these CCs were largely different. We found that income and occupation significantly contributed to the odds of infection by CC1 to CC5. Consequently, our findings revealed the epidemiology characteristics of the CCs of M. tuberculosis L4, and will help in the formulation of more effective intervention measures in line with regional specifications and patient characteristics in China.

MultiWaver 2.0: modeling discrete and continuous gene flow to reconstruct complex population admixtures.

Our goal in developing the MultiWaver software series was to be able to infer population admixture history under various complex scenarios. The earlier version of MultiWaver considered only discrete admixture models. Here, we report a newly developed version, MultiWaver 2.0, that implements a more flexible framework and is capable of inferring multiple-wave admixture histories under both discrete and continuous admixture models. MultiWaver 2.0 can automatically select an optimal admixture model based on the length distribution of ancestral tracks of chromosomes, and the program can estimate the corresponding parameters under the selected model. Specifically, for discrete admixture models, we used a likelihood ratio test (LRT) to determine the optimal discrete model and an expectation-maximization algorithm to estimate the parameters. In addition, according to the principles of the Bayesian Information Criterion (BIC), we compared the optimal discrete model with several continuous admixture models. In MultiWaver 2.0, we also applied a bootstrapping technique to provide levels of support for the chosen model and the confidence interval (CI) of the estimations of admixture time. Simulation studies validated the reliability and effectiveness of our method. Finally, the program performed well when applied to real datasets of typical admixed populations, such as African Americans, Uyghurs, and Hazaras.

Network-Wide Screen Identifies Variation of Novel Precise On-Module Targets Using Conformational Modudaoism.

Modular targeting is promising in drug research at the network level, but it is challenging to quantificationally identify the precise on-modules. Based on a proposed Modudaoism (MD), we defined conserved MD (MDc) and varied MD (MDv) to quantitatively evaluate the conformational and energy variations of modules, and thereby identify the conserved and discrepant allosteric modules (AMs). Compared to the Zsummary , MDc/MDv got an optimized result of module preserved ratio and modular structure. In the mice anti-ischemic networks, 3, 5, and 1 conserved AMs as well as 4, 1, and 3 on-modules of baicalin (BA), jasminoidin (JA), and ursodeoxycholic acid (UA) were identified by MDc and MDv, 5 unique AMs and their characteristic actions were revealed. Besides, co-immunoprecipitation (Co-IP) experiments validated the representative modular structure. MDc/MDv method can quantitatively define the conformational variations of modules and screen the precise on-modules network-wide, which may provide a promising strategy for drug discovery.

Characteristics of distribution of Mycobacterium tuberculosis lineages in China.

The genotyping methods of Mycobacterium tuberculosis would dramatically improve our understanding of the molecular epidemiology of tuberculosis. 3,929 isolates, from a National Survey of Drug-Resistant Tuberculosis in 2007 in China, were successfully genotyped by large sequence polymorphisms and 15 loci variable number tandem repeats. We found that 2,905 (2,905/3,929, 73.9%) cases belonged to Lineage 2, dominated in the east and central regions, 975 cases (975/3,929, 24.8%) were Lineage 4, highly prevailed in the west regions, and 36 and 13 cases were Lineage 3 and Lineage 1, respectively. We also explored the associations between lineages (Lineage 2 vs. Lineage 4) and clinical characteristics by logistic regression. For Lineage 2, the risk factors were Han-ethnicity population and fever. However, for Lineage 4, they were occupation (farmer), and degree of education (non-literate). Fully understanding of the distribution of Mycobacterium tuberculosis lineage and its risk factors would play a critical role in tuberculosis prevention, control, and treatment.

Mycobacterium tuberculosis Lineage Distribution in Xinjiang and Gansu Provinces, China.

Mycobacterium tuberculosis (M. tuberculosis) genotyping has dramatically improved the understanding of the epidemiology of tuberculosis (TB). In this study, 187 M. tuberculosis isolates from Xinjiang Uygur Autonomous Region (Xinjiang) and Gansu province in China were genotyped using large sequence polymorphisms (LSPs) and variable number tandem repeats (VNTR). Ten isolates, which represent major nodes of VNTR-based minimum spanning tree, were selected and subsequently subjected to multi-locus sequence analyses (MLSA) that include 82 genes. Based on a robust lineage assignment, we tested the association between lineages and clinical characteristics by logistic regression. There are three major lineages of M. tuberculosis prevalent in Xinjiang, viz. the East Asian Lineage 2 (42.1%; 56/133), the Euro-American Lineage 4 (33.1%; 44/133), and the Indian and East African Lineage 3 (24.8%; 33/133); two lineages prevalent in Gansu province, which are the Lineage 2 (87%; 47/54) and the Lineage 4 (13%; 7/54). The topological structures of the MLSA-based phylogeny support the LSP-based identification of M. tuberculosis lineages. The statistical results suggest an association between the Lineage 2 and the hemoptysis/bloody sputum symptom, fever in Uygur patients. The pathogenicity of the Lineage 2 remains to be further investigated.

A Probabilistic Method for Estimating the Sharing of Identity by Descent for Populations with Migration.

The inference of demographic history of populations is an important undertaking in population genetics. A few recent studies have developed identity-by-descent (IBD) based methods to reveal the signature of the relatively recent historical events. Notably, Pe'er and his colleagues have introduced a novel method (named PIBD here) by employing IBD sharing to infer effective population size and migration rate. However, under island model, PIBD neglects the coalescent information before the time to the most recent common ancestor (tMRCA) which leads to apparent deviations in certain situations. In this paper, we propose a new method, MIBD, by adopting a Markov process to describe the island model and develop a new formula for estimating IBD sharing. The new formula considers the coalescent information before tMRCA and the joint effect of the coalescent and migration events. We apply both MIBD and PIBD to the genome-wide data of two human populations (Palestinian and Bedouin) obtained from the HGDP-CEPH database, and demonstrate that MIBD is competitive to PIBD. Our simulation analyses also show that the results of MIBD are more accurate than those of PIBD especially in the case of small effective population size.

Length Distribution of Ancestral Tracks under a General Admixture Model and Its Applications in Population History Inference.

The length of ancestral tracks decays with the passing of generations which can be used to infer population admixture histories. Previous studies have shown the power in recovering the histories of admixed populations via the length distributions of ancestral tracks even under simple models. We believe that the deduction of length distributions under a general model will greatly elevate the power. Here we first deduced the length distributions under a general model and proposed general principles in parameter estimation and model selection with the deduced length distributions. Next, we focused on studying the length distributions and its applications under three typical special cases. Extensive simulations showed that the length distributions of ancestral tracks were well predicted by our theoretical framework. We further developed a new method, AdmixInfer, based on the length distributions and good performance was observed when it was applied to infer population histories under the three typical models. Notably, our method was insensitive to demographic history, sample size and threshold to discard short tracks. Finally, good performance was also observed when applied to some real datasets of African Americans, Mexicans and South Asian populations from the HapMap project and the Human Genome Diversity Project.