Measures Of Genetic Similarity Research Articles

An explanation for the sister repulsion phenomenon in Patterson's f-statistics.

Patterson's f-statistics are among the most heavily utilized tools for analyzing genome-wide allele frequency data for demographic inference. Beyond studying admixture, f3- and f4-statistics are also used for clustering populations to identify groups with similar histories. However, previous studies have noted an unexpected behavior of f-statistics: multiple populations from a certain region systematically show higher genetic affinity to a more distant population than to their neighbors, a pattern that is mismatched with alternative measures of genetic similarity. We call this counter-intuitive pattern "sister repulsion". We first present a novel instance of sister repulsion, where genomes from Bronze Age East Anatolian sites show higher affinity toward Bronze Age Greece rather than each other. This is observed both using f3- and f4-statistics, contrasts with archaeological/historical expectation, and also contradicts genetic affinity patterns captured using principal components analysis or multidimensional scaling on genetic distances. We then propose a simple demographic model to explain this pattern, where sister populations receive gene flow from a genetically distant source. We calculate f3- and f4-statistics using simulated genetic data with varying population genetic parameters, confirming that low-level gene flow from an external source into populations from 1 region can create sister repulsion in f-statistics. Unidirectional gene flow between the studied regions (without an external source) can likewise create repulsion. Meanwhile, similar to our empirical observations, multidimensional scaling analyses of genetic distances still cluster sister populations together. Overall, our results highlight the impact of low-level admixture events when inferring demographic history using f-statistics.

Comparison of Six Measures of Genetic Similarity of Interspecific Brassicaceae Hybrids F2 Generation and Their Parental Forms Estimated on the Basis of ISSR Markers

Comparison of Six Measures of Genetic Similarity of Interspecific Brassicaceae Hybrids F2 Generation and Their Parental Forms Estimated on the Basis of ISSR Markers

IS ANONYMITY GONE? DIRECT-TO-CONSUMER ANCESTRY TESTING REVEALS OLD SECRETS IN FERTILITY CARE: LEGAL CASE REVIEW

To heighten awareness of potential ethical and legal pitfalls when providing fertility care in the age of direct-to-consumer (DTC) ancestry tests. Legal issues and court cases against fertility clinics due to DTC ancestry testing were queried using the Nexis Uni (legal search engine of state and federal cases) and Google search engines. Local county courts were queried for court documents pertaining to specific cases. The following search terms were used: IVF, fertility, 23andMe, and Ancestry.com. Many DTC ancestry tests utilize microarray chips and look at hundreds of thousands of single nucleotide polymorphisms (snp’s) as a measure of genetic similarity, thus mapping customers to others in their database. Six legal cases were found filed between years 2018-2021. In 2019, a physician brought charges against a University IVF facility for misuse of sperm he had donated when he was a medical student. He donated sperm with the conditions that it would be used by women living outside the state and to father only five children. Through DTC ancestry testing, he later identified 19 individuals were conceived with his donated sperm and several of these individuals live in his community. This resulted in a high-profile case for breach of consent, and he sued the clinic for $5.25 million. The case is still ongoing. Another case resulted after a mother found a relative of her daughter’s sperm donor through a 23andMe DNA test. The mother made unwelcome contact to a relative of the anonymous sperm donor. The sperm bank sent the recipient a “cease-and-desist” letter stating she had violated the terms of their contract by contacting the family of the sperm donor and seized the remaining vials of the sperm she had purchased. The recipient sued the sperm bank, however in January 2020, the judge dismissed the woman’s claims and sided in favor of protecting the anonymity and rights of gamete donors. DTC ancestry testing has also revealed cases where reproductive endocrinologists have acted unethically and used their own sperm to inseminate patients without disclosure and informed consent. A woman brought eight causes of action against her parents’ fertility doctor in 2018 after using Ancestry.com DNA kit and finding out their doctor was her biological father. The charges include medical malpractice, lack of informed consent, fraud, battery, intentional infliction of emotional distress, negligent infliction of emotional distress, breach of contract, and violation of Idaho's Consumer Protection Act. The reproductive endocrinologist admitted that he breached the applicable standard of care when he inseminated his patient with his own semen. The trial is anticipated to begin May 17, 2021. With the rapid growth in popularity for DTC, donor anonymity can no longer be reasonably presumed. Individuals who are donor-conceived can more easily identify their biologic oocyte or sperm donors who intended to be anonymous.

MORPHOLOGICAL DESCRIPTORS FOR THE CHARACTERISATION OF TEAK CLONES CUTTINGS (Tectona grandis L.F.)

ABSTRACT Teak (Tectona grandis) is a forest species cultivated in tropical regions worldwide, due to the traits of its wood and its great economic value on the market. In Brazil, original plantations are being replaced by selected clonal forests, which generate the need and interest to protect this genetic material based on the current legislation. The legal requirements for cultivar protection are that the genotype must result from genetic improvement and provide distinguishability, homogeneity, and stability (DHS). This work identifies morphological descriptors in teak cuttings to assist the clone protection process of the species. The study was conducted in a completely randomized design with the evaluation of 7 clones and 15 cuttings per clone, at 30, 60, 90, and 120 days old. The information was also organized based on the arrays of presence and absence of variations for each clone, for 21 morphological traits. Subsequently, genetic similarity measures were estimated using the Jaccard index and the UPGMA clustering method. The clones with the 12, 7, 9, and 11 morphological traits formed the morphological descriptors for the 30, 60, 90, and 120 days old cuttings, respectively. The traits of the leaf blade: length, width, length/width ratio, green intensity, and the brightness of the leaf, were common for all the evaluated ages, but their respective levels of expression were different.

Morphological descriptors for the characterization of teak clones (Tectona grandis L.f.) in plantations

Aim of study: The objective of this work was to identify possible morphological descriptors for teak clones, in order to support the cultivars protection process of this species.Area of study: This experiment was carried out in ‘São José dos Quatro Marcos’, Mato Grosso, midwest Brazil.Material and methods: A teak clonal test, assessing 18 clones, was evaluated at the ages of 29 and 41 months by means of 41 morphological characteristics, related mainly to the branches, leaves and trunk. The clonal test was established in a randomized block design composed by three blocks, each block containing 18 plots, one for each clone. Each plot had 36 plants, but only the innermost five individuals were selected and evaluated. The information was organized in a presence and absence matrix. Subsequently, genetic similarity measures were estimated, by means of the Jaccard index, and a clustering was performed by the Unweighted Pair Group Method using the Arithmetic averages (UPGMA) method.Main results: A total of 26 and 28 morphological characteristic that exhibited DHS (distinction, homogeneity and stability) were identified at the ages of 29 and 41 months, respectively. Of these, 17 characteristics showed the same behavior at 29 and 41 months of age. However, it is important to emphasize that the evaluation must be performed under the same planting conditions in which these descriptors were developed.Research highlights: These 17 morphological characteristics can compose the list of potential morphological descriptors to be used in the process of teak clones/cultivars protection.Keywords: cultivars protection; morphological characteristics; distinction, homogeneity; stability.

The Most Popular Measures of Genetic Similarity Based on Analyses of DNA Polymorphism

The Most Popular Measures of Genetic Similarity Based on Analyses of DNA Polymorphism

Genetic Characterization of Cleveland Bay Horse Breed

The Cleveland Bay (CB) is the United Kingdom’s oldest established horse breed. In this study we analyzed the genetic variability in CB horses and investigated its genetic relationships with other horse breeds. We examined the genetic variability among 90 CB horses sampled in the USA compared to a total of 3447 horses from 59 other breeds. Analysis of the genetic diversity and population structure was carried out using 15 microsatellite loci. We found that genetic diversity in CB horses was less than that for the majority of other tested breeds. The genetic similarity measures showed no direct relationship between the CB and Thoroughbred but suggested the Turkman horses (likely in the lineage of ancestors of the Thoroughbred) as a possible ancestor. Our findings reveal the genetic uniqueness of the CB breed and indicate its need to be preserved as a genetic resource.

Learning deep compact similarity metric for kinship verification from face images

Recent advances in kinship verification have shown that learning an appropriate kinship similarity metric on human faces plays a critical role in this problem. However, most of existing distance metric learning (DML) based solutions rely on linearity assumption of the kinship metric model, and the domain knowledge of large cross-generation discrepancy (e.g., large age span and gender difference between parent and child images) has not been considered in metric learning, leading to degraded performance for genetic similarity measure on human faces. To address these limitations, we propose in this work a new kinship metric learning (KML) method with a coupled deep neural network (DNN) model. KML explicitly models the cross-generation discrepancy inherent on parent-child pairs, and learns a coupled deep similarity metric such that the image pairs with kinship relation are pulled close, while those without kinship relation (but with high appearance similarity) are pushed as far away as possible. Moreover, by imposing the intra-connection diversity and inter-connection consistency over the coupled DNN, we introduce the property of hierarchical compactness into the coupled network to facilitate deep metric learning with limited amount of kinship training data. Empirically, we evaluate our algorithm on several kinship benchmarks against the state-of-the-art DML alternatives, and the results demonstrate the superiority of our method.

Genotype confidence percentage of SSR HRM profiles as a measure of genetic similarity in Rosmarinus officinalis

Rosemary (Rosmarinus officinalis L.) is a highly allogamous plant with few genomic resources available. Among these, a discrete set of nuclear and cytoplasmic microsatellite markers is counted. High resolution melting (HRM) is a closed-tube technique widely used for sequence polymorphism detection. Until now, HRM data analysis in plants has been conducted reporting melting profiles to known allelic assets. Even for preliminary studies on general genetic diversity, laborious workflows have been proposed for HRM genotyping of microsatellite's indels as well as of SNPs. Genotype confidence percentage (GCP) of HRM curves is the most commonly used statistical transformation of Euclidean distance between HRM curves to determine whether two curves are identical or not. In the present study we tested an analysis workflow that implies the use of GCPs of HRM profiles as a direct measure of the genetic similarities on SSR loci, bypassing therefore genotyping. The comparison between capillary electrophoresis and HRM-GCPs data demonstrates the efficiency of this new technique in detecting genetic differences between rosemary populations. This method can be used for determining overall genomic similarity in phylogenetic and ecological studies. It is cost and time effective, suitable to complete automation and can be used in other allogamous plants as well.

Bounding measures of genetic similarity and diversity using majorization

The homozygosity and the frequency of the most frequent allele at a polymorphic genetic locus have a close mathematical relationship, so that each quantity places a tight constraint on the other. We use the theory of majorization to provide a simplified derivation of the bounds on homozygosity J in terms of the frequency M of the most frequent allele. The method not only enables simpler derivations of known bounds on J in terms of M, it also produces analogous bounds on entropy statistics for genetic diversity and on homozygosity-like statistics that range in their emphasis on the most frequent allele in relation to other alleles. We illustrate the constraints on the statistics using data from human populations. The approach suggests the potential of the majorization method as a tool for deriving inequalities that characterize mathematical relationships between statistics in population genetics.

Investigating the Association of Genetic Admixture and Donor/Recipient Genetic Disparity with Transplant Outcomes

Disparities in survival after allogeneic hematopoietic cell transplantation have been reported for some race and ethnic groups, despite comparable HLA matching. Individuals' ethnic and race groups, as reported through self-identification, can change over time because of multiple sociological factors. We studied the effect of 2 measures of genetic similarity in 1378 recipients who underwent myeloablative first allogeneic hematopoietic cell transplantation between 1995 and 2011 and their unrelated 10 of 10 HLA-A, -B, -C, -DRB1, and-DQB1- matched donors. The studied factors were as follows (1) donor and recipient genetic ancestral admixture and (2) pairwise donor/recipient genetic distance. Increased African genetic admixture for either transplant recipients or donors was associated with increased risk of overall mortality (hazard ratio [HR], 2.26; P = .005 and HR, 3.09; P = .0002, respectively) and transplant-related mortality (HR, 3.3; P = .0003 and HR, 3.86; P = .0001, respectively) and decreased disease-free survival (HR, 1.9; P = .02 and HR, 2.46; P = .002 respectively). The observed effect, albeit statistically significant, was relevant to a small subset of the studied population and was notably correlated with self-reported African-American race. We were not able to control for other nongenetic factors, such as access to health care or other socioeconomic factors; however, the results suggest the influence of a genetic driver. Our findings confirm what has been previously reported for African-American recipients and show similar results for donors. No significant association was found with donor/recipient genetic distance.

Finding genetic overlaps among diseases based on ranked gene lists.

To understand disease relationships in terms of their genetic mechanisms, it is important to study the common genetic basis among different diseases. Although discoveries on pleiotropic genes related to multiple diseases abound, methods flexibly applicable to various types of datasets generated from different studies or experiments are needed to gain big pictures on the genetic relationships among a large number of diseases. We develop a set of genetic similarity measures to gauge the genetic overlap between diseases, as well as several estimators of the number of overlapping disease genes between diseases. These methods are based on ranked gene lists so that they could be flexibly applied to different types of data. We first investigate the performance of the genetic similarity measure for evaluating the similarity between human diseases in simulation studies. Then we apply the method to diseases in the OMIM database. We show that our proposed genetic measure achieves superior performance in explaining phenotype similarities between diseases compared to simpler methods. Furthermore, we identified common genes underlying the genetic overlap between disease pairs. With an example of five vision-related diseases, we demonstrate how our methods can provide insights into the relationships among diseases based on their shared genetic mechanisms.

Learning a Genetic Measure for Kinship Verification Using Facial Images

Motivated by the key observation that children generally resemble their parents more than other persons with respect to facial appearance, distance metric (similarity) learning has been the dominant choice for state-of-the-art kinship verification via facial images in the wild. Most existing learning-based approaches to kinship verification, however, are focused on learning a genetic similarity measure in a batch learning manner, leading to less scalability for practical applications with ever-growing amount of data. To address this, we propose a new kinship verification approach by learning a sparse similarity measure in an online fashion. Experimental results on the kinship datasets show that our approach is highly competitive to the state-of-the-art alternatives in terms of verification accuracy, yet it is superior in terms of scalability for practical applications.

Testing genetic association with rare and common variants in family data.

With the advance of next-generation sequencing technologies in recent years, rare genetic variant data have now become available for genetic epidemiology studies. For family samples, however, only a few statistical methods for association analysis of rare genetic variants have been developed. Rare variant approaches are of great interest, particularly for family data, because samples enriched for trait-relevant variants can be ascertained and rare variants are putatively enriched through segregation. To facilitate the evaluation of existing and new rare variant testing approaches for analyzing family data, Genetic Analysis Workshop 18 (GAW18) provided genotype and next-generation sequencing data and longitudinal blood pressure traits from extended pedigrees of Mexican American families from the San Antonio Family Study. Our GAW18 group members analyzed real and simulated phenotype data from GAW18 by using generalized linear mixed-effects models or principal components to adjust for familial correlation or by testing binary traits using a correction factor for familial effects. With one exception, approaches dealt with the extended pedigrees in their original state using information based on the kinship matrix or alternative genetic similarity measures. For simulated data our group demonstrated that the family-based kernel machine score test is superior in power to family-based single-marker or burden tests, except in a few specific scenarios. For real data three contributions identified significant associations. They substantially reduced the number of tests before performing the association analysis. We conclude from our real data analyses that further development of strategies for targeted testing or more focused screening of genetic variants is strongly desirable.

Gene mobility and the concept of relatedness

Cooperation is rife in the microbial world, yet our best current theories of the evolution of cooperation were developed with multicellular animals in mind. Hamilton’s theory of inclusive fitness is an important case in point: applying the theory in a microbial setting is far from straightforward, as social evolution in microbes has a number of distinctive features that the theory was never intended to capture. In this article, I focus on the conceptual challenges posed by the project of extending Hamilton’s theory to accommodate the effects of gene mobility. I begin by outlining the basics of the theory of inclusive fitness, emphasizing the role that the concept of relatedness is intended to play. I then provide a brief history of this concept, showing how, over the past fifty years, it has departed from the intuitive notion of genealogical kinship to encompass a range of generalized measures of genetic similarity. I proceed to argue that gene mobility forces a further revision of the concept. The reason in short is that, when the genes implicated in producing social behaviour are mobile, we cannot talk of an organism’s genotype simpliciter; we can talk only of an organism’s genotype at a particular stage in its life cycle. We must therefore ask: with respect to which stage(s) in the life cycle should relatedness be evaluated? For instance: is it genetic similarity at the time of social interaction that matters to the evolution of social behaviour, or is it genetic similarity at the time of reproduction? I argue that, strictly speaking, it is neither of these: what really matters to the evolution of social behaviour is diachronic genetic similarity between the producers of fitness benefits at the time they produce them and the recipients of those benefits at the end of their life-cycle. I close by discussing the implications of this result. The main payoff is that it makes room for a possible new mechanism for the evolution of altruism in microbes that does not require correlated interaction among bearers of the genes for altruism. The importance of this mechanism in nature remains an open empirical question.

Microsatellite analysis of genetic variability in Waler horses from Australia

The Waler horse breed is an integral part of Australian history. The purposes of this study were to analyse the genetic variability in Waler horses from Australia and to investigate genetic relationships with other horse breeds. We examined the genetic diversity of 70 Waler horses sampled from seven breeding stations in Australia. Also we analysed the relationships of these horses with 11 other horse breeds. Analysis of the genetic structure was carried out using 15 microsatellite loci, genetic distances, AMOVA, factorial correspondence analysis and a Bayesian method. We found that the genetic diversity in the Waler was greater than the domestic horse mean and exceeded that of all endangered horse breeds. Our findings also revealed moderate population subdivision rather than inbreeding. All genetic similarity measures indicated that the Thoroughbred might be a key ancestor to the Waler. This study indicates that there is no immediate concern for loss of variation in Waler horses. Also, there clearly has been a strong input from the Thoroughbred into the Waler horse breed. However, the genetic evidence suggests that this input was not just direct but also came through other types of horses with a Thoroughbred cross background.

Reduction of traits for genetic evaluation of linear described traits in the Old Kladruber horse

The estimated genetic parameters were used for selection of important conformation traits and reduction in the number of the described characteristics. For reduction in the number of described traits from the original 36 to 24, the traits were selected according to: measure of genetic similarity (cluster analysis), measure of uncertainty multidimensional quantity, value of the variance of aggregate genotype, value of the variance of selection index and correlation of trait to the first principal component of the genetic matrix. Reduction in the number of the described traits was based on the value of heritability coefficient and genetic correlations matrix. The reliabilities of selection indexes were estimated between 0.41 and 0.53. Among the three multivariate analysis methods evaluated in this study, the variance of selection index had the highest reliabilities of selection indexes. The estimation of selection index variance which omitted traits with low heritability coefficient and high genetic correlation was the most suitable for the traits selection. This procedure would enable the breeders to reduce field costs (e.g. time, labour) required for obtaining the genetic parameter estimates necessary for a specific breeding programme.  

Global Genetic Variation at OAS1 Provides Evidence of Archaic Admixture in Melanesian Populations

Recent analysis of DNA extracted from two Eurasian forms of archaic human shows that more genetic variants are shared with humans currently living in Eurasia than with anatomically modern humans in sub-Saharan Africa. Although these genome-wide average measures of genetic similarity are consistent with the hypothesis of archaic admixture in Eurasia, analyses of individual loci exhibiting the signal of archaic introgression are needed to test alternative hypotheses and investigate the admixture process. Here, we provide a detailed sequence analysis of the innate immune gene OAS1, a locus with a divergent Melanesian haplotype that is very similar to the Denisova sequence from the Altai region of Siberia. We resequenced a 7-kb region encompassing the OAS1 gene in 88 individuals from six Old World populations (San, Biaka, Mandenka, French Basque, Han Chinese, and Papua New Guineans) and discovered previously unknown and ancient genetic variation. The 5' region of this gene has unusual patterns of diversity, including 1) higher levels of nucleotide diversity in Papuans than in sub-Saharan Africans, 2) very deep ancestry with an estimated time to the most recent common ancestor of >3 myr, and 3) a basal branching pattern with Papuan individuals on either side of the rooted network. A global geographic survey of >1,500 individuals showed that the divergent Papuan haplotype is nearly restricted to populations from eastern Indonesia and Melanesia. Polymorphic sites within this haplotype are shared with the draft Denisova genome over a span of ∼90 kb and are associated with an extended block of linkage disequilibrium, supporting the hypothesis that this haplotype introgressed from an archaic source that likely lived in Eurasia.

Chromosome-Wide Haplotype Sharing: A Measure Integrating Recombination Information to Reconstruct the Phylogeny of Human Populations

The vast amount of recombination information in the human genome has long been ignored or deliberately avoided in studies on human population genetic relationships. One reason is that estimation of the recombination parameter from genotyping data is computationally challenging and practically difficult. Here we propose chromosome-wide haplotype sharing (CHS) as a measure of genetic similarity between human populations, which is an indirect approach to integrate recombination information. We showed in both empirical and simulated data that recombination differences and genetic differences between human populations are strongly correlated, indicating that recombination events in different human populations are evolutionarily related. We further demonstrated that CHS can be used to reconstruct reliable phylogenies of human populations and the majority of the variation in CHS matrix can be attributed to recombination. However, for distantly related populations, the utility of CHS to reconstruct correct phylogeny is limited, suggesting that the linear correlation of CHS and population divergence could have been disturbed by recurrent recombination events over a large time scale. The CHS we proposed in this study is a practical approach without involving computationally challenging and time-consuming estimation of recombination parameter. The advantage of CHS is rooted in its integration of both drift and recombination information, therefore providing additional resolution especially for populations separated recently.

Collision probabilities for AFLP bands, with an application to simple measures of genetic similarity

AFLP is a frequently used DNA fingerprinting technique that is popular in the plant sciences. A problem encountered in the interpretation and comparison of individual plant profiles, consisting of band presence-absence patterns, is that multiple DNA fragments of the same length can be generated that eventually show up as single bands on a gel. The phenomenon of two or more fragments coinciding in a band within an individual profile is a type of homoplasy, that we call collision. Homoplasy biases estimates of genetic similarity. In this study, we show how to calculate collision probabilities for bands as a function of band length, given the fragment count, the band count, or band lengths. We also determine probabilities of higher order collisions, and estimate the total number of collisions for a profile. Since short fragments occur more often, short bands are more likely to contain collisions. For a typical plant genome and AFLP procedure, the collision probability for the shortest band is 25 times larger than for the longest. In a profile with 100 bands a quarter of the bands may contain collisions, concentrated at the shorter band lengths. All calculations require a careful estimate of the monotonically decreasing fragment length distribution. Modifications of Dice and Jaccard coefficients are proposed. The principles are illustrated on data from a phylogenetic study in lettuce.