渐近混合群体的混合连锁不平衡及其遗传连锁推断

在渐近混合模型中,混合现象发生在每一世代,通过对其混合连锁不平衡的理论分析,发现混合连锁不平衡与两个子群体间的基因频率差成正比。基于这一点,构造了一个对重组率严格单调的函数（△ker=△／（p1-p2）,其中△代表连锁不平衡）,进而据此推断标记基因座与疾病基因座的遗传连锁。应用人类基因组上不连锁的标记基因提供的连锁不平衡信息,基于病人组数据构造了一个准似然比统计量。模拟结果显示,此检验可用于精确的基因定位。文章亦讨论了参数对检验的影响。     

The Admixture Linkage Disequilibrium and Genetic Linkage Inference on the Gradual Admixture Population

Through the theoretical analysis of the admixture linkage disequilibrium (ALD) in the gradual admixture (GA) model, in which admixture occurs in every generation, the ALD is found to be proportional to the difference in marker allele frequencies, p₁-p₂, between two subpopulations. Based on this property, we can employ a strict monotonic function (Δ_ker=Δ/(p₁-p₂), where Δ denotes the linkage disequilibrium (LD)) of the recombination fraction between the marker locus and the disease locus to infer the true genetic linkage. We construct a quasi likelihood ratio test (LRT) for the case-only data utilizing the information of unlinked markers in the human genome. The simulation results show that our tests can be used to fine map a disease locus. The effects of parameter values in the ALD mapping are also discussed.     

Statistical software for gene mapping by admixture linkage disequilibrium

Admixture mapping is a statistical methodology that detects genetic variants in recently admixed populations that are responsible for ethnic differences in disease risk. Three software packages are now available for admixture mapping and we provide a brief overview of the statistical methods and other principal features they implement.     

Inferring Admixture Histories of Human Populations Using Linkage Disequilibrium

Long-range migrations and the resulting admixtures between populations have been important forces shaping human genetic diversity. Most existing methods for detecting and reconstructing historical admixture events are based on allele frequency divergences or patterns of ancestry segments in chromosomes of admixed individuals. An emerging new approach harnesses the exponential decay of admixture-induced linkage disequilibrium (LD) as a function of genetic distance. Here, we comprehensively develop LD-based inference into a versatile tool for investigating admixture. We present a new weighted LD statistic that can be used to infer mixture proportions as well as dates with fewer constraints on reference populations than previous methods. We define an LD-based three-population test for admixture and identify scenarios in which it can detect admixture events that previous formal tests cannot. We further show that we can uncover phylogenetic relationships among populations by comparing weighted LD curves obtained using a suite of references. Finally, we describe several improvements to the computation and fitting of weighted LD curves that greatly increase the robustness and speed of the calculations. We implement all of these advances in a software package, ALDER, which we validate in simulations and apply to test for admixture among all populations from the Human Genome Diversity Project (HGDP), highlighting insights into the admixture history of Central African Pygmies, Sardinians, and Japanese.     

Aspartate Aminotransferase Activity in Fiber Tracts of the Rat Brain

Activity of aspartate aminotransferase, an enzyme which catalyzes the interconversion of the excitatory transmitter candidates, glutamate and aspartate, has been measured in fiber tracts of rat, with an emphasis on sensory and motor systems of the brain. Most tracts had significantly higher activities than the cholinergic facial nerve root, consistent with the possibility that a component of aspartate aminotransferase activity might serve as a marker for neurons using glutamate and/or aspartate as neurotransmitter. Highest activity was in the auditory nerve root. On the other hand, a close correlation was found between aspartate aminotransferase and malate dehydrogenase activities in the fiber tracts, raising the question whether aspartate aminotransferase activity may be more closely related to energy metabolism than to transmitter metabolism.     

Autosomal Admixture Levels Are Informative About Sex Bias in Admixed Populations

Sex-biased admixture has been observed in a wide variety of admixed populations. Genetic variation in sex chromosomes and functions of quantities computed from sex chromosomes and autosomes have often been examined to infer patterns of sex-biased admixture, typically using statistical approaches that do not mechanistically model the complexity of a sex-specific history of admixture. Here, expanding on a model of Verdu and Rosenberg (2011) that did not include sex specificity, we develop a model that mechanistically examines sex-specific admixture histories. Under the model, multiple source populations contribute to an admixed population, potentially with their male and female contributions varying over time. In an admixed population descended from two source groups, we derive the moments of the distribution of the autosomal admixture fraction from a specific source population as a function of sex-specific introgression parameters and time. Considering admixture processes that are constant in time, we demonstrate that surprisingly, although the mean autosomal admixture fraction from a specific source population does not reveal a sex bias in the admixture history, the variance of autosomal admixture is informative about sex bias. Specifically, the long-term variance decreases as the sex bias from a contributing source population increases. This result can be viewed as analogous to the reduction in effective population size for populations with an unequal number of breeding males and females. Our approach suggests that it may be possible to use the effect of sex-biased admixture on autosomal DNA to assist with methods for inference of the history of complex sex-biased admixture processes.     

Robust estimation of local genetic ancestry in admixed populations using a nonparametric bayesian approach

We present a new haplotype-based approach for inferring local genetic ancestry of individuals in an admixed population. Most existing approaches for local ancestry estimation ignore the latent genetic relatedness between ancestral populations and treat them as independent. In this article, we exploit such information by building an inheritance model that describes both the ancestral populations and the admixed population jointly in a unified framework. Based on an assumption that the common hypothetical founder haplotypes give rise to both the ancestral and the admixed population haplotypes, we employ an infinite hidden Markov model to characterize each ancestral population and further extend it to generate the admixed population. Through an effective utilization of the population structural information under a principled nonparametric Bayesian framework, the resulting model is significantly less sensitive to the choice and the amount of training data for ancestral populations than state-of-the-art algorithms. We also improve the robustness under deviation from common modeling assumptions by incorporating population-specific scale parameters that allow variable recombination rates in different populations. Our method is applicable to an admixed population from an arbitrary number of ancestral populations and also performs competitively in terms of spurious ancestry proportions under a general multiway admixture assumption. We validate the proposed method by simulation under various admixing scenarios and present empirical analysis results from a worldwide-distributed dataset from the Human Genome Diversity Project.     

Ancient Admixture in Human History

Population mixture is an important process in biology. We present a suite of methods for learning about population mixtures, implemented in a software package called ADMIXTOOLS, that support formal tests for whether mixture occurred and make it possible to infer proportions and dates of mixture. We also describe the development of a new single nucleotide polymorphism (SNP) array consisting of 629,433 sites with clearly documented ascertainment that was specifically designed for population genetic analyses and that we genotyped in 934 individuals from 53 diverse populations. To illustrate the methods, we give a number of examples that provide new insights about the history of human admixture. The most striking finding is a clear signal of admixture into northern Europe, with one ancestral population related to present-day Basques and Sardinians and the other related to present-day populations of northeast Asia and the Americas. This likely reflects a history of admixture between Neolithic migrants and the indigenous Mesolithic population of Europe, consistent with recent analyses of ancient bones from Sweden and the sequencing of the genome of the Tyrolean “Iceman.”     

The analysis of disease biomarker data using a mixed hidden Markov model (Open Access publication)

A mixed hidden Markov model (HMM) was developed for predicting breeding values of a biomarker (here, somatic cell score) and the individual probabilities of health and disease (here, mastitis) based upon the measurements of the biomarker. At a first level, the unobserved disease process (Markov model) was introduced and at a second level, the measurement process was modeled, making the link between the unobserved disease states and the observed biomarker values. This hierarchical formulation allows joint estimation of the parameters of both processes. The flexibility of this approach is illustrated on the simulated data. Firstly, lactation curves for the biomarker were generated based upon published parameters (mean, variance, and probabilities of infection) for cows with known clinical conditions (health or mastitis due to Escherichia coli or Staphylococcus aureus). Next, estimation of the parameters was performed via Gibbs sampling, assuming the health status was unknown. Results from the simulations and mathematics show that the mixed HMM is appropriate to estimate the quantities of interest although the accuracy of the estimates is moderate when the prevalence of the disease is low. The paper ends with some indications for further developments of the methodology.     

Physical Lengths of Meiotic and Mitotic Gene Conversion Tracts in Saccharomyces Cerevisiae

Physical lengths of gene conversion tracts for meiotic and mitotic conversions were examined, using the same diploid yeast strain in all experiments. This strain is heterozygous for a mutation in the URA3 gene as well as closely linked restriction site markers. In cells that had a gene conversion event at the URA3 locus, it was determined by Southern analysis which of the flanking heterozygous restriction sites had co-converted. It was found that mitotic conversion tracts were longer on the average than meiotic tracts. About half of the tracts generated by spontaneous mitotic gene conversion included heterozygous markers 4.2 kb apart; none of the meiotic conversions included these markers. Stimulation of mitotic gene conversion by ultraviolet light or methylmethanesulfonate had no obvious effect on the size or distribution of the tracts. Almost all conversion tracts were continuous.     

Inference of Historical Changes in Migration Rate From the Lengths of Migrant Tracts

After migrant chromosomes enter a population, they are progressively sliced into smaller pieces by recombination. Therefore, the length distribution of “migrant tracts” (chromosome segments with recent migrant ancestry) contains information about historical patterns of migration. Here we introduce a theoretical framework describing the migrant tract length distribution and propose a likelihood inference method to test demographic hypotheses and estimate parameters related to a historical change in migration rate. Applying this method to data from the hybridizing subspecies Mus musculus domesticus and M. m. musculus, we find evidence for an increase in the rate of hybridization. Our findings could indicate an evolutionary trajectory toward fusion rather than speciation in these taxa.     

Admixture of two phylogeographic lineages of the Eurasian beaver in Poland

The Eurasian beaver (Castor fiber) represents an uncommon example of an endangered species in which the restoration programs proved a spectacular success and led to enormous spatial and demographic expansion. Documented reintroduction of beavers in Poland has been conducted using animals of the eastern European origin, most likely derived from the eastern mtDNA lineage. However demographic and spatial expansion of beavers from Germany, which represent the western lineage, may have led to admixture of these two genetically distinct entities in Poland. We detected significant genetic differentiation between the populations from W and NE Poland both in mitochondrial DNA control region and microsatellites, but also substantial admixture including apparent first-generation migrants between regions. Our results indicate that beavers from the western mtDNA lineage have contributed considerably to the Polish population, particularly in W Poland. As there have been no adequately documented translocations of beavers from the western European populations to Poland, the observed situation appears to result from natural migration or range expansion from the west. In contrast to previous findings we detected a substantial diversity in mtDNA control region, which indicates that either the variation in relict populations has been underestimated, or that additional relict beaver populations survived at the end of the 19th century in Poland and Germany as indicated by considerable similarity of ancient and extant mtDNA haplotypes. The implications of our findings for beaver conservation and management are discussed.     

Admixture analysis of a rural population of the state of Guerrero, Mexico

We studied 156 individuals of Native American descent from the city of Tlapa in the state of Guerrero in western Mexico. Most individuals' ethnicity was either Nahua, Mixtec, or Tlapanec, but self-identified Mestizos and individuals of mixed ethnicities were also included in the sample. We typed 24 autosomal, one Y-chromosome, and four mitochondrial ancestry-informative markers (AIMs) to estimate group and individual admixture proportions, and determine whether the admixture process involved directional gene flow between parental groups. When genetically defined (GD) Mestizos were excluded from the analysis, Native American ancestry represented approximately 98% of the population's gene pool, while European and West African ancestry represented approximately 1% each. Maternally inherited markers also showed an exceptionally high Native American contribution (98.5%), as did the paternally inherited marker, DYS199 (90.7%). We did not detect genetic structure in this population using these AIMs, which appears consistent with the homogeneity of the sample in terms of admixture proportions. The addition of GD Mestizos to the sample did not produce a considerable change in admixture estimates, but it had a major effect on population structure. These results show that the population of Tlapa in Guerrero, Mexico, has experienced little admixture with Europeans and/or West Africans. They also show that the impact of a small number of admixed individuals on an otherwise homogeneous population might have profound implications on subsequent ancestry/phenotype analysis and mapping strategies. We suggest that heterogeneity is a major characteristic of Mexican populations and, as a consequence, should not be disregarded when designing epidemiological studies of Mexican and Mexican American populations.