A model-based approach for analysis of spatial structure in genetic data

In the last few decades, issues related to the legal regulation of genetic research and the legal regime of genetic information derived from it have become particularly relevant both at the international level and at the level of individual countries. However, Russia has only recently come to realize the need for legislative regulation of the relevant relations. At the same time, a distinctive feature of such regulation is the emphasis on public-legal aspects, and civil-legal aspects have been left without due attention.The distinction between genetic information and genetic data is essential for the determination of the civil law regime of genetic information. Genetic information is personified genetic (genomic) information (information), because it has an individual, personal character as relating directly or indirectly to a particular or identifiable person. Genetic data is non-personalized (anonymized) genetic data, which are characterized by a formalized species, often contained in the information system and in this regard — systematized. Genetic information is an element of such an intangible good as the secret of private life, genetic data are, as a rule, an element of such a result of intellectual activity as a database. In addition, it is concluded that there is no doctrinal or legislative basis for the recognition of genetic information as an independent object of civil rights. The necessity of additional legislative regulation of activity of the biobanks carrying out storage of biomaterials, respectively, genetic data is proved. Genetic information contained in such biobanks should be subject to the legal regime of privacy.

Most ecological and genetic data show inherent structure in space, time, or phylogeny. This chapter focuses solely on spatial structure, acknowledging that the other types of dependency occur. The power of landscape genetics analyses to detect significant spatial relationships between genetic and landscape data is directly linked to the sampling design, the spatial analysis methods, and the genetic markers used. The chapter discusses the main issues of relating genetic variation to landscape predictors in the familiar context of regression analysis or, more generally, in the framework of the linear model. It then presents different approaches through which space can be incorporated into the linear model. Finally, the chapter explains two common goals of spatial analysis in landscape genetics: first, how to test for the presence of significant isolation-by-distance (IBD) and then how to account for IBD by incorporating it into the null model when testing for other landscape effects.

Various unsupervised clustering algorithms have been used to infer population structure in genetic data. The goals are to separate individuals of similar genetic characteristics into clusters and to estimate the number of clusters within each dataset. Among them, a framework called iterative pruning principal component analysis (ipPCA) have been developed. It performs PCA iteratively on subsets of data samples and clusters them using fuzzy c-mean. We believe that the choice of model-based clustering method affects the individual assignments and cluster quality, as well as the estimated number of clusters. Thus, in this paper we introduce a hierarchical tree clustering concept from graph theory, whose performance is independent of cluster shapes, into the ipPCA framework. We also add a PCA-based feature selection technique as a data pre-processing step to reduce data dimension and increase computational efficiency. The resulting algorithm is called HiClust-ipPCA. We illustrate the improved clustering results of the HiClust-ipPCA algorithm using 47-breed bovine and 28-breed sheep datasets.

Responsibility in the age of precision genomics

A novel allele frequency trajectories template to discriminate genetic similarity among populations

The genetic differences in 32 populations of Hydropsyche belonging to nine species distributed in Sicily, and central and southern Italy were assayed by horizontal starch gel electrophoresis. Larval specimens were examined. Twelve enzyme loci were assayed and allele frequencies, variability parameters, and Nei's genetic distance were calculated. The percentage of polymorphic loci ranged from 8.3 to 50.0%, the mean number of alleles per locus from 1.1 to 1.8, and the mean observed heterozygosity from 0.009 to 0.123. Nei's genetic distances values between conspecific populations ranged from 0 to 0.096; in the comparison between populations from Sicily and Calabria, H. doehleri had the highest values. Only for H. spiritoi there were differences among the Sicilian populations. From genetic distance data, a dendrogram was obtained. At interspecific level, the values of genetic distance between conspecific populations ranged from 0.201 {H. spiritoi ‐ H. gereckei) to 1.135 (H. dinarica ‐ H. klefbecki). Genetic data were in agreement with morphological data.

The rising demand to use genetic data for research goes hand in hand with an increased awareness of privacy issues related to its use. Using human genetic data in a legally compliant way requires an examination of the legal basis as well as an assessment of potential disclosure risks. Focusing on the relevant legal framework in the European Union, we discuss open questions and uncertainties around the handling of genetic data in research, which can result in the introduction of unnecessary hurdles for data sharing. First, we discuss defining features and relative disclosure risks of some DNA-related biomarkers, distinguishing between the risk for disclosure of (1) the identity of an individual, (2) information about an individual's health and behavior, including previously unknown phenotypes, and (3) information about an individual's blood relatives. Second, we discuss the European legal framework applicable to the use of DNA-related biomarkers in research, the implications of including both inherited and acquired traits in the legal definition, as well as the issue of “genetic exceptionalism”—the notion that genetic information has inherent characteristics that require different considerations than other health and medical information. Finally, by mapping the legal to specific technical definitions, we draw some initial conclusions concerning how sensitive different types of “genetic data” may actually be. We argue that whole genome sequences may justifiably be considered “exceptional” and require special protection, whereas other genetic data that do not fulfill the same criteria should be treated in a similar manner to other clinical data. This kind of differentiation should be reflected by the law and/or other governance frameworks as well as agreed Codes of Conduct when using the term “genetic data.”

The common chaffinch Fringilla coelebs is the extant avian species with the highest level of differentiation across North Atlantic archipelagos. Such a degree of diversification has been traditionally recognised within the subspecies category, with one endemic subspecies occurring in Azores ( F. c. moreletti ), one in Madeira ( F. c. maderensis ), and three in the Canary Islands ( F. c. canariensis , F. c. palmae and F. c. ombriosa ). Recent genetic, acoustic, and sperm morphology studies informed us about the significant differentiation of the Gran Canaria population, which is traditionally included within F. c. canariensis subspecies. The goal of this study is to examine the similarity of the Canarian chaffinches, with the objective of determining if the Gran Canaria chaffinches represent an isolated and distinct population. In order to achieve this aim, we used a double approach: 1) we analysed new morphological and genetic data from the Canary Islands, and 2) we reviewed and synthesised the vast acoustic, morphological and genetic information available for these taxa in Macaronesia, with special emphasis on the Canary Islands. Genetic, acoustic, and sperm morphological data, and to a lesser extent phenotypic data, strongly support the existence of a cryptic taxon in Gran Canaria. Moreover, our findings also reveal an incipient speciation process on going in the Canary Islands, mostly driven by genetic differentiation. Overall, our synthesis suggests that individuals occurring in Gran Canaria should be considered as a novel taxon that we formally described as Fringilla coelebs bakeri ssp. nov.

Hybridization between domestic and wild animals is a major concern for biodiversity conservation, and as habitats become increasingly fragmented, conserving biodiversity at all levels, including genetic, becomes increasingly important. Except for tropical forests and true deserts, African wildcats occur across the African continent; however, almost no work has been carried out to assess its genetic status and extent of hybridization with domestic cats. For example, in South Africa it has been argued that the long-term viability of maintaining pure wildcat populations lies in large protected areas only, isolated from human populations. Two of the largest protected areas in Africa, the Kgalagadi Transfrontier and Kruger National Parks, as well as the size of South Africa and range of landscape uses, provide a model situation to assess how habitat fragmentation and heterogeneity influences the genetic purity of African wildcats. Using population genetic and home range data, we examined the genetic purity of African wildcats and their suspected hybrids across South Africa, including areas within and outside of protected areas. Overall, we found African wildcat populations to be genetically relatively pure, but instances of hybridization and a significant relationship between the genetic distinctiveness (purity) of wildcats and human population pressure were evident. The genetically purest African wildcats were found in the Kgalagadi Transfrontier Park, while samples from around Kruger National Park showed cause for concern, especially combined with the substantial human population density along the park's boundary. While African wildcat populations in South Africa generally appear to be genetically pure, with low levels of hybridization, our genetic data do suggest that protected areas may play an important role in maintaining genetic purity by reducing the likelihood of contact with domestic cats. We suggest that approaches such as corridors between protected areas are unlikely to remain effective for wildcat conservation, as the proximity to human settlements around these areas is projected to increase the wild/domestic animal interface. Thus, large, isolated protected areas will become increasingly important for wildcat conservation and efforts need to be made to prevent introduction of domestic cats into these areas.

Over the past decade, the development of genetic and genomic tools for conservation management has come forward in leaps and bounds. Once considered a ‘nice to have’, genetic data are fast becoming an essential tool for informing and managing translocations. However, due to the complexity of the field, easily using genetic data for decision‐making and monitoring remains beyond the reach of most managers and conservation biologists. In May 2020, we launched the Threatened Species Initiative (TSI), a programme designed to generate genomic resources for Australia's threatened species. Critical to the project is not only the generation of reference genomes and population genetic data but an online toolkit for conservation managers. The toolkit is a ‘one stop shop’ from collecting samples, to generating and analysing genetic data, to an easily interpretable genetic management report. A series of workflows and pipelines have been developed, including the TSI Biodiversity Portal, that uses point and click web interfaces to easily transfer raw sequence data and assemble genomes, transcriptomes and soon population genetics for management decisions. Here we present how the current toolkit works and provide case study examples for how it is being used to inform translocations and the management of threatened species.

Genetic information is crucial for species identification, population genetics structure, evolutionary relationships, and biodiversity monitoring. It helps address biodiversity gaps related to Linnean (taxonomic uncertainty) and Darwinian (phylogenetic knowledge) shortfalls. Understanding these gaps can guide data collection to reduce these shortfalls. This study focuses on compiling genetic data for 748 fish species in the Tocantins-Araguaia basin, examining the number of unique genomic regions and the individual regions sampled per species. We also investigated the factors that determine genetic data availability by linking it with macroecological predictors. Our findings reveal that fewer than one-third of endemic species have genetic resources available. The Darwinian shortfall - the lack of phylogenetic knowledge - is a key factor limiting genetic data, with species experiencing more of this shortfall having less genetic information. The study underscores the need for increased genetic sampling of endemic species and more sampling of individual regions to better assess biological information like population structure.

Background The inflammatory response plays a key role at different stages of cancer development. Allelic variants of the interleukin 1A (IL1A), interleukin 4 (IL4), nuclear factor kappa B1 (NFKB1) and protease-activated receptor 1 (PAR1) genes may influence not only the inflammatory response but also susceptibility to cancer development. Among major ethnic or continental groups, these polymorphic variants present different allelic frequencies. In admixed populations, such as the Brazilian population, data on distribution of these polymorphisms are limited. Here, we collected samples of cancer-free individuals from the north, northeast, midwest, south and southeast regions of Brazil and from the three main groups that gave rise to the Brazilian population: Native Americans from the Brazilian Amazon, Africans and Europeans. We describe the allelic distributions of four IL1A (rs3783553), IL4 (rs79071878), NFKB1 (rs28362491) and PAR1 (rs11267092) gene polymorphisms, which the literature describes as polymorphisms with a risk of cancer or worse prognosis for cancer.ResultsThe genotypic distribution of the four polymorphisms was statistically distinct between Native Americans, Africans and Europeans. For the allelic frequency of these polymorphisms, the Native American population was the most distinct among the three parental populations, and it included the greatest number of alleles with a risk of cancer or worse prognosis for cancer. The PAR1 gene polymorphism allelic distribution was similar among all Brazilian regions. For the other three markers, the northern region population was statistically distinct from other Brazilian region populations.ConclusionThe IL1A, IL4, NFKB1 and PAR1 gene polymorphism allelic distributions are homogeneous among the regional Brazilian populations, except for the northern region, which significantly differs from the other four Brazilian regions. Among the parental populations, the Native American population exhibited a higher incidence of alleles with risk of cancer or worse prognosis for cancer, which can indicate greater susceptibility to this disease. These genetic data may be useful for future studies on the association between these polymorphisms and cancer in the investigated populations.

Small populations are prone to loss of genetic variation and hence to a reduction in their evolutionary potential. Therefore, studying the mating system of small populations and its potential effects on genetic drift and genetic diversity is of high importance for their viability assessments. The traditional method for studying genetic mating systems is paternity analysis. Yet, as small populations are often rare and elusive, the genetic data required for paternity analysis are frequently unavailable. The endangered Asiatic wild ass (Equus hemionus), like all equids, displays a behaviourally polygynous mating system; however, the level of polygyny has never been measured genetically in wild equids. Combining noninvasive genetic data with stochastic modelling of shifts in allele frequencies, we developed an alternative approach to paternity analysis for studying the genetic mating system of the re-introduced Asiatic wild ass in the Negev Desert, Israel. We compared the shifts in allele frequencies (as a measure of genetic drift) that have occurred in the wild ass population since re-introduction onset to simulated scenarios under different proportions of mating males. We revealed a strongly polygynous mating system in which less than 25% of all males participate in the mating process each generation. This strongly polygynous mating system and its potential effect on the re-introduced population's genetic diversity could have significant consequences for the long-term persistence of the population in the Negev. The stochastic modelling approach and the use of allele-frequency shifts can be further applied to systems that are affected by genetic drift and for which genetic data are limited.

BackgroundThe Tohoku Medical Megabank Organization (ToMMo) is a prospective genome cohort study and biobank established in 2012 in Northern Japan’s Miyagi Prefecture following the Great East Japan Earthquake and Tsunami. ToMMo has enrolled 120,000 healthy male and female adults aged over 20, plus 30,000 children in a longitudinal study designed to identify diverse biological, psychological, and lifestyle characteristics associated with mainly common diseases and support additional innovative research. Baseline information includes brain MRI, genetic data, physiological measurements, several cognitive and psychological screening tests, and health/lifestyle assessments. Alzheimer’s disease (AD) is a key research focus; goals include using MRI, genomic and other data in combination to identify predictive biomarkers. This communication reports initial progress.MethodMRI: MP‐RAGE, PCASL, FLAIR and DTI sequences were performed. Following quality checks and pre‐processing, Freesurfer (2.1.0) was used with the Destrieux or Desikan‐Killiany atlas to parcellate multiple anatomical brain regions and derive cortical thickness data. The digitized data were archived; raw data was preserved. Genetics: whole genome sequencing (WGS) and/or DNA array data were obtained for participants; apolipoprotein E (APOE) genotype was identified. Blood, urine, stool, saliva and dental plaque samples were collected and stored for biomarker identification and other studies.ResultUsable MRI data exist for >12,000 participants (4,000 for FLAIR); approximately half the scans are of participants aged ≥50 (see Table). The quality exclusion rate was <5%. WGS and DNA array data have so far been prepared for 800 participants who had MRI scans; APOE genotype information exists for all participants with MRI scans. The MRI and genetic data, plus demographic, cognitive screening and relevant health data are currently being readied for use in combination to identify valuable biomarkers, e.g., those predicting incipient cognitive impairment in preclinical AD. The frequency of major known AD risk alleles in the ToMMo sample will also be determined and compared to that in external GWAS studies.ConclusionToMMo’s MRI, WGS/DNA array, biospecimen repository and other data represent a powerful resource for AD research. Specifically, the combination of MRI and genetic data will support unique disease progression analyses and investigations to elucidate AD pathophysiology.

It is in the present decade that quanntitative-geographical studies began to undergo a marked development based on a new viewpoint in geography. In geography, too, mathematical and statistical techniques have been utilized since a long while ago as well as in other sciences. Those techniques of late are however characterized by the quantitative-geographical viewpoint as to the ‘nomothetic’ subjects in pursuit of some general law concerning the spatial regularities of various phenomena on the earth. In this respect, it should be clearly distinct from the ‘ideographic’ viewpoint in regional geography, which is interested in unique items to put emphasis on the intensive studies of individual cases, if the mathematical and statistical techniques are employed as a mere means for description of regions.The studies from quantitative-geographical viewpoint pay further attention to spatial aspects of the phenomena on the earth, make models derived from some hypothesis, put them to practical tests, and formulate the theories on which the hypothesis is based. The models used there range from deterministic to probabilistic, and static to dynamic models.The quantitative geography is assumed to contain the following seven branches of research: (1) Point Pattern Analysis, (2) Network Analysis, (3) Trend-Surface Analysis, (4) Regionalization Analysis, (5) Spatial Interaction Analysis, (6) Spatial Diffusion Analysis, and (7) Spatial Behavior Analysis. A large number of studies have added to the literatures of quantitative geography. Among the abovelisted seven branches of quantitative geography, the spatial diffusion analysis seems to show more sufficient development in connection with a theoretical formulation.The spatial diffusion analysis has been studied in a considerable number of geographical papers, since a Swedish geographer Torsten Hägerstrand understood the diffusion of information and innovation as a spatial process. The significance of Hagerstrand's studies seem to be briefly summarized in two sentences as follows: (1) the spatial process of diffusion in a geographic space was approached through his analysis of the diffusion of information and innovation, and (2) the Monte Carlo simulation technique was first employed for the analysis of geographic space. His diffusion theory of information and innovation might be regarded as comparable to the Christaller's central-place theory.The present writer attempted an analysis of the intra-urban migration in the pursuit of a theoretical formulation of geographic space, assuming the geographic space as a system of purely spatial components. And the geographic space is assumed to organize a ‘geographic field’ as probability surface given in form of ‘Mean Migration Field’ for the intra-urdan migration. Thus the MMF as a geographic field organized rationally for a given geographic space may probabilistically control the intra-urban migration as a spatial and geographic phenomenon. An example was drawn from an analysis of intra-urban migation on the built-up area, defined as a Densely Inhabited District by the national population census, of Fukaya city (approximately 60, 000 population), Saitama prefecture. The following four stochastic models were formulated to test the hypotheses concerning geographic space considered for the intra-urban migration by means of the Hägerstrand type of Monte Carlo simulation: (1) MODEL I to simulate the migration under a complete random process on a hypothesis of the completely uniform geographic space, ‘Isotropic Plain’, (2) MODEL II for a simulation of the migration pattern within a geographic space assuming the friction effect of distance involved, (3) MODEL III by which simulation is attempted for the intra-urban migration within a geographic space characterized by the uneven distribution of population or the densities effect