Concepts Of Population Genetics Research Articles

CSGA: A DUAL POPULATION GENETIC ALGORITHM BASED ON MEXICAN CAVEFISH GENETIC DIVERSITY

Genetic algorithms (GAs) are search algorithms based on population genetics and natural selection concepts. Maintaining population variety in GAs is critical for ensuring global exploration and mitigating the risks of premature convergence. Rapid convergence to local optima is one such challenge in the application of genetic algorithms. To address this issue, we provide Cave-Surface GA (CSGA), an alternative method based on the Dual Population Genetic Algorithm and inspired by the genetic variety observed in Mexican cavefish. Through inter-population crossbreeding, CSGA increases diversity via a secondary population (Cave population) and facilitates the exchange of information between populations, effectively counteracting premature convergence. Several experiments are carried out utilizing benchmark instances of the Traveling Salesman Problem (TSP) obtained from TSPLIB, a well-known TSP problem library. Our experimental results over many TSP instances show that CSGA outperforms both classic GAs and other GAs that use diversity preservation techniques, such as Multipopulation GA (MPGA). CSGA has the potential to give promising solutions to challenging optimization issues like TSP.

Boosting life sciences research in Brazil: building a case for a local Drosophila stock center.

Drosophila melanogaster is undoubtedly one of the most useful model organisms in biology. Initially used in solidifying the principles of heredity, and establishing the basic concepts of population genetics and of the synthetic theory of evolution, it can currently offer scientists much more: the possibility of investigating a plethora of cellular and biological mechanisms, from development and function of the immune system to animal neurogenesis, tumorigenesis and beyond. Extensive resources are available for the community of Drosophila researchers worldwide, including an ever-growing number of mutant, transgenic and genomically-edited lines currently carried by stock centers in North America, Europe and Asia. Here, we provide evidence for the importance of stock centers in sustaining the substantial increase in the output of Drosophila research worldwide in recent decades. We also discuss the challenges that Brazilian Drosophila scientists face to keep their research projects internationally competitive, and argue that difficulties in importing fly lines from international stock centers have significantly stalled the progression of all Drosophila research areas in the country. Establishing a local stock center might be the first step towards building a strong local Drosophila community that will likely contribute to all areas of life sciences research.

Beyond simple adaptation: Incorporating other evolutionary processes and concepts into eco-evolutionary dynamics.

Studies of eco-evolutionary dynamics have integrated evolution with ecological processes at multiple scales (populations, communities and ecosystems) and with multiple interspecific interactions (antagonistic, mutualistic and competitive). However, evolution has often been conceptualised as a simple process: short-term directional adaptation that increases population growth. Here we argue that diverse other evolutionary processes, well studied in population genetics and evolutionary ecology, should also be considered to explore the full spectrum of feedback between ecological and evolutionary processes. Relevant but underappreciated processes include (1) drift and mutation, (2) disruptive selection causing lineage diversification or speciation reversal and (3) evolution driven by relative fitness differences that may decrease population growth. Because eco-evolutionary dynamics have often been studied by population and community ecologists, it will be important to incorporate a variety of concepts in population genetics and evolutionary ecology to better understand and predict eco-evolutionary dynamics in nature.

Abstract P5-13-01: TUMOR PROGRESSION MODEL IN BREAST CANCER WITH BRAIN METASTASIS

Abstract INTRODUCTION: Breast cancer are the main cause of related deaths cancer among women, corresponding to 25% of new cases each year. When diagnosed at early stages, it has an overall five-year survival rate of up to 90%. However, in more advanced stages, survival is reduced to about 24%, with 90% of women in stage IV dying as a result of complications related to metastases. Considering that brain metastasis is an unfavorable prognostic site, and the identification of genetic-molecular profiles in primary tumors and in metastatic sites are a subject poorly described in the literature, we understand that the identification of mutational profiles may contribute to elucidate the genetic-molecular mechanisms associated with tumor progression. AIM: The aim of this study was to identify clonal and subclonal driver mutations that lead to evolution of metastatic clones from a breast cancer progression model. MATERIAL AND METHODS: For tumor progression model, automated extraction of DNA from buffy coat and paraffin samples of breast tumors and paired brain metastases (n=9) was performed. In the present work, we used a subclonal reconstruction model based on the combination of machine learning and population genetics concepts. This proposal is based on the frequency spectrum of each somatic mutation (SNVs or indels), considering VAF (Variant Allele Frequency - ratio of mapped reads of the mutant allele) in relation to the coverage of variant locus, as known as CCF (Cancer Cell Fraction). CCF is defined as the proportion of neoplastic cells that have a certain set of mutations and then is normalized considering the sample purity and the segments with changes in number of DNA copies (Copy Number Alterations). Then, a statistical model based on finite Dirichlet mixtures with mixed distributions is applied. In this model, Beta components capture clonal expansions and population genetics concepts were applied to mutant alleles in each population considering principles of cancer evolution. Finally, confidence was computed using both parametric and non-parametric bootstraps. The functions for building the model are implemented at https://caravagnalab.github.io/mobster/, and for visualization and construction of graphs, packages in R statistical-mathematical environment were used, such as ggplot2, sads, cli, clisymbols, cowplot, crayon, ctree, dndscv, dplyr, magrittr, reshape2, and tidyr. RESULTS: With this model was possible to identify the distribution of clones according to somatic alterations in patients with breast cancer and brain metastasis. It was possible to observe common patterns, such as alterations of the SF3B1 gene as a common ancestral clone in both conditions and the frequency of the AKT1 gene in a subclonal condition. Other genes relevant to breast cancer carcinogenesis, such as PIK3CA and TP53, are found in a different clonal hierarchical pattern between the two conditions. CONCLUSION: This data suggests a model of clonal evolution capable to identify which drivers clones and subclones are involved in the metastatic process. Citation Format: Muriele B. Varuzza, Adriane F. Evangelista, Cristiano P. Souza, Márcia C. Marques. TUMOR PROGRESSION MODEL IN BREAST CANCER WITH BRAIN METASTASIS [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P5-13-01.

How much do we know and how much do we care about genetic diversity of threatened plants ? A case study from the French flora

ABSTRACT Small demographic size and reduced genetic diversity increase the extinction probability of a population. Genetic diversity within populations for neutral markers is an heuristic parameter, as it reflects past and ongoing processes acting on populations, and informs on possible futures. This study presents a synthesis of the knowledge on neutral genetic diversity for threatened plants in metropolitan France and the use of such data in management actions. Pairing threatened species with the closest non-threatened species for which we could find appropriate genetic data, we collected information on genetic diversity for 25 threatened species and non-threatened controls. We found that threatened species in France have on average a lower within-population genetic diversity than non-threatened controls and thus are exposed to risks linked to genetic erosion. Combining an analysis of recovery plans and a survey addressed to practitioners, we concluded that genetic diversity is rarely integrated in management actions. The integration of such information into applied conservation remains a challenge. We provide some guidelines to collect biological traits impacting within-population genetic diversity and some specific recommendations for a better incorporation of population genetics concepts into conservations actions.

Genie: an interactive real-time simulation for teaching genetic drift

Neutral evolution is a fundamental concept in evolutionary biology but teaching this and other non-adaptive concepts is especially challenging. Here we present Genie, a browser-based educational tool that demonstrates population-genetic concepts such as genetic drift, population isolation, gene flow, and genetic mutation. Because it does not need to be downloaded and installed, Genie can scale to large groups of students and is useful for both in-person and online instruction. Genie was used to teach genetic drift to Evolution students at Arizona State University during Spring 2016 and Spring 2017. The effectiveness of Genie to teach key genetic drift concepts and misconceptions was assessed with the Genetic Drift Inventory developed by Price et al. (CBE Life Sci Educ 13(1):65–75, 2014). Overall, Genie performed comparably to that of traditional static methods across all evaluated classes. We have empirically demonstrated that Genie can be successfully integrated with traditional instruction to reduce misconceptions about genetic drift.

The mutation effect reaction norm (mu-rn) highlights environmentally dependent mutation effects and epistatic interactions.

Since the modern synthesis, the fitness effects of mutations and epistasis have been central yet provocative concepts in evolutionary and population genetics. Studies of how the interactions between parcels of genetic information can change as a function of environmental context have added a layer of complexity to these discussions. Here, I introduce the "mutation effect reaction norm" (Mu-RN), a new instrument through which one can analyze the phenotypic consequences of mutations and interactions across environmental contexts. It embodies the fusion of measurements of genetic interactions with the reaction norm, a classic depiction of the performance of genotypes across environments. I demonstrate the utility of the Mu-RN through a case study: the signature of a "compensatory ratchet" mutation that undermines reverse evolution of antimicrobial resistance. In closing, I argue that the mutation effect reaction norm may help us resolve the dynamism and unpredictability of evolution, with implications for theoretical biology, biotechnology, and publichealth.

Genetic Analysis of Plant Pathogens Natural Populations.

Population genetics allow to address fundamental questions about the biology of plant pathogens. By testing specific hypotheses, population genetics provide insights into the population genetic variability of pathogens across different geographical areas, time, and associated plant hosts, as well as on the structure and differentiation of populations, and on the possibility that a population is introduced and from where it has originated. In this chapter, basic concepts of population genetics are introduced, as well as the five evolutionary factors affecting populations, that is, mutations, recombination, variation in population size, gene flow, and natural selection. A step-by-step workflow, from sampling to data analysis, on how to perform a genetic analysis of natural populations of plant pathogens is discussed. Increased knowledge of the population biology of pathogens is pivotal to improve management strategies of diseases in agricultural and forest ecosystems.

A spectral theory for Wright's inbreeding coefficients and related quantities.

Wright’s inbreeding coefficient, FST, is a fundamental measure in population genetics. Assuming a predefined population subdivision, this statistic is classically used to evaluate population structure at a given genomic locus. With large numbers of loci, unsupervised approaches such as principal component analysis (PCA) have, however, become prominent in recent analyses of population structure. In this study, we describe the relationships between Wright’s inbreeding coefficients and PCA for a model of K discrete populations. Our theory provides an equivalent definition of FST based on the decomposition of the genotype matrix into between and within-population matrices. The average value of Wright’s FST over all loci included in the genotype matrix can be obtained from the PCA of the between-population matrix. Assuming that a separation condition is fulfilled and for reasonably large data sets, this value of FST approximates the proportion of genetic variation explained by the first (K − 1) principal components accurately. The new definition of FST is useful for computing inbreeding coefficients from surrogate genotypes, for example, obtained after correction of experimental artifacts or after removing adaptive genetic variation associated with environmental variables. The relationships between inbreeding coefficients and the spectrum of the genotype matrix not only allow interpretations of PCA results in terms of population genetic concepts but extend those concepts to population genetic analyses accounting for temporal, geographical and environmental contexts.

CfDNA deconvolution via NIPT of a pregnant woman after bone marrow transplant and donor egg IVF

Cell-free DNA is known to be a mixture of DNA fragments originating from various tissue types and organs of the human body and can be utilized for several clinical applications and potentially more to be created. Non-invasive prenatal testing (NIPT), by high throughput sequencing of cell-free DNA (cfDNA), has been successfully applied in the clinical screening of fetal chromosomal aneuploidies, with more extended coverage under active research.In this study, via a quite unique and rare NIPT sample, who has undergone both bone marrow transplant and donor egg IVF, we investigated the sources of oddness observed in the NIPT result using a combination of molecular genetics and genomic methods and eventually had the case fully resolved. Along the process, we devised a clinically viable process to dissect the sample mixture.Eventually, we used the proposed scheme to evaluate the relatedness of individuals and the demultiplexed sample components following modified population genetics concepts, exemplifying a noninvasive prenatal paternity test prototype. For NIPT specific applicational concern, more thorough and detailed clinical information should therefore be collected prior to cfDNA-based screening procedure like NIPT and systematically reviewed when an abnormal report is obtained to improve genetic counseling and overall patient care.

Supporting the Learning of Evolution Theory Using an Educational Simulator

This paper analyzes Sim-Evolution, an educational simulator designed to help teachers presenting three basic principles of the theory of evolution by natural selection (TENS): the trait variation within a population, the heritability of trait variation, and the selective survival based on heritable traits. Sim-Evolution focuses on high school students, so its interface was designed to be joyful, helping to engage them. Although it was designed based on the concept of population genetics, knowing it is not a requirement for exploring TENS. Sim-Evolution models the population of a hypothetic bird species in two possible vegetations: forest or veld. Individuals of this bird species vary over two characteristics (color and beak type), with three possible phenotypes for each one. The user can choose individuals to form an initial population and monitor variation through successive generations. Birds breed independently of their phenotype, and natural selection (based on the fitness of each trait) was the only driven factor of population variation. Sim-Evolution was evaluated with high school students during a biology class. Students were able to describe and analyze the simulation process from a scientific perspective, observing the phenomenon associated with TENS. They correctly associated the bird's evolution with different survivor rates associated with the different traits and identified evolution by natural selection as a population and not an individual/organism process. Our proposal opens the possibility that TENS simulator does not obligatorily require users to be familiar with population genetics concepts, which is especially interestingly for high school pedagogical uses.

Population Genomics on the Fly: Recent Advances in Drosophila.

Drosophila melanogaster, a small dipteran of African origin, represents one of the best-studied model organisms. Early work in this system has uniquely shed light on the basic principles of genetics and resulted in a versatile collection of genetic tools that allow to uncover mechanistic links between genotype and phenotype. Moreover, given its worldwide distribution in diverse habitats and its moderate genome-size, Drosophila has proven very powerful for population genetics inference and was one of the first eukaryotes whose genome was fully sequenced. In this book chapter, we provide a brief historical overview of research in Drosophila and then focus on recent advances during the genomic era. After describing different types and sources of genomic data, we discuss mechanisms of neutral evolution including the demographic history of Drosophila and the effects of recombination and biased gene conversion. Then, we review recent advances in detecting genome-wide signals of selection, such as soft and hard selective sweeps. We further provide a brief introduction to background selection, selection of noncoding DNA and codon usage and focus on the role of structural variants, such as transposable elements and chromosomal inversions, during the adaptive process. Finally, we discuss how genomic data helps to dissect neutral and adaptive evolutionary mechanisms that shape genetic and phenotypic variation in natural populations along environmental gradients. In summary, this book chapter serves as a starting point to Drosophila population genomics and provides an introduction to the system and an overview to data sources, important population genetic concepts and recent advances in the field.

Malaria Molecular Epidemiology: An Evolutionary Genetics Perspective.

Malaria is a vector-borne disease that involves multiple parasite species in a variety of ecological settings. However, the parasite species causing the disease, the prevalence of subclinical infections, the emergence of drug resistance, the scale-up of interventions, and the ecological factors affecting malaria transmission, among others, are aspects that vary across areas where malaria is endemic. Such complexities have propelled the study of parasite genetic diversity patterns in the context of epidemiologic investigations. Importantly, molecular studies indicate that the time and spatial distribution of malaria cases reflect epidemiologic processes that cannot be fully understood without characterizing the evolutionary forces shaping parasite population genetic patterns. Although broad in scope, this review in the Microbiology Spectrum Curated Collection: Advances in Molecular Epidemiology highlights the need for understanding population genetic concepts when interpreting parasite molecular data. First, we discuss malaria complexity in terms of the parasite species involved. Second, we describe how molecular data are changing our understanding of malaria incidence and infectiousness. Third, we compare different approaches to generate parasite genetic information in the context of epidemiologically relevant questions related to malaria control. Finally, we describe a few Plasmodium genomic studies as evidence of how these approaches will provide new insights into the malaria disease dynamics. *This article is part of a curated collection.

Genetics on a maize cob: A teaching tool for schools

Genetics occupies central position in biology and directly connects with all its branches. In fact, ‘life’ and ‘non-life’ meet each other in viruses and genes. Technologies emanating from genetics have had immense impact in various areas such as healthcare, agriculture, environment etc. Recent developments in stem cell biology and gene editing technologies not only promise cures for several ailments which were hitherto unthinkable but also raise concerns of irreparable harm that can result from unbridled use of these technologies. Therefore, basic understanding of genetics is necessary for all sections of society. Hence, genetics is now introduced at the school level. However, at least in the Indian context, genetics teaching in classrooms relies largely on blackboard or chart-based explanations. Unlike physics, chemistry and to some extent basic botany and zoology where models or live/preserved specimens are available to demonstrate fundamental concepts under classroom conditions, there is a dearth of material resources for teaching genetics. Maize has a long history of basic and applied genetics where a large number of well-characterized mutant stocks are available. To make learning experience interesting and engaging, we have developed maize genetic resources for use under classroom conditions. In particular, maize cob with seeds segregating for various clearly identifiable phenotypes presents unique opportunity to demonstrate basic genetic principles including statistical and population genetic concepts. In this article we describe these resources and explain how they can be used to demonstrate different concepts.

Cell population genetics: emergence, main results and concepts (to the 50th anniversary of the foundation)

The article briefly reviews the emergence and development in Ukraine of a new scientific field — cell population genetics, which formed the theoretical basis of modern cell technologies. These include, in particular, plant biotechnologies for the improvement, preservation, and accelerated reproduction of unique genotypes in vitro; development of new genotypes (organisms) by the methods of cell and genetic engineering and cellular selection; obtaining biologically active compounds, including recombinant, from biomass of cultured cells and tissues for the needs of medicine, cosmetics and food industry; as well as the methods of cell therapy, including technologies based on the use of stem cells, etc. Cultured cells are widely used as model objects and biological systems for studying the most relevant problems of modern biology: the features of the course, signaling pathways, and mechanisms of cell proliferation, including carcinogenesis and tumor proliferation; dedifferentiation of cells, including their reversion to a pluripotent state; totipotency, pluripotency and omnipotency; regeneration of tissues, separate organs, and whole organisms, etc. The article reviews scientific prerequisites for the development of the new scientific field and presents the main concepts of cell population genetics, which have been mainly developed in the Department of cell population genetics of the Institute of Molecular Biology and Genetics of the National Academy of Sciences of Ukraine. It also presents an analysis of the features of development of the newest research areas of genetics of somatic cells of intact plants and cells in vitro, cell population genetics, genetic foundations of cell selection, cell biology, and biotechnology during the second half of the past and the beginning of this century. Keywords: history of science, cell population genetics, plant tissue and cell culture, cell selection, plant biotechnology.

Understanding the Aryan Debate:Population Genetic Concepts and Frameworks

A long-standing debate on whether ‘Aryans’ (central Asians) had entered India has recently gained momentum. The debate is polarized. In the recent set of articles, some authors have strongly criticized inferences drawn using genomic data and population genetic methods. Some criticisms are flawed. These criticisms stem from lack of clear understanding of population genetic concepts and frameworks. Such inappropriate criticisms have led to unnecessary confusion and further polarization among readers. This article attempts to place the ongoing ‘Aryan debate’ in the perspective of population genetic frameworks.

Mathematical Modeling the Biology of Single Nucleotide Polymorphisms (SNPs) in Whole Genome Adaptation

As a living information and communications system, the genome encodes patterns in single nucleotide polymorphisms (SNPs) reflecting human adaptation that optimizes population survival in differing environments. This paper mathematically models environmentally induced adaptive forces that quantify changes in the distribution of SNP frequencies between populations. We make direct connections between biophysical methods (e.g. minimizing genomic free energy) and concepts in population genetics. Our unbiased computer program scanned a large set of SNPs in the major histocompatibility complex region and flagged an altitude dependency on a SNP associated with response to oxygen deprivation. The statistical power of our double-blind approach is demonstrated in the flagging of mathematical functional correlations of SNP information-based potentials in multiple populations with specific environmental parameters. Furthermore, our approach provides insights for new discoveries on the biology of common variants. This paper demonstrates the power of biophysical modeling of population diversity for better understanding genome-environment interactions in biological phenomenon.

Cultural evolutionary theory: How culture evolves and why it matters

Human cultural traits—behaviors, ideas, and technologies that can be learned from other individuals—can exhibit complex patterns of transmission and evolution, and researchers have developed theoretical models, both verbal and mathematical, to facilitate our understanding of these patterns. Many of the first quantitative models of cultural evolution were modified from existing concepts in theoretical population genetics because cultural evolution has many parallels with, as well as clear differences from, genetic evolution. Furthermore, cultural and genetic evolution can interact with one another and influence both transmission and selection. This interaction requires theoretical treatments of gene–culture coevolution and dual inheritance, in addition to purely cultural evolution. In addition, cultural evolutionary theory is a natural component of studies in demography, human ecology, and many other disciplines. Here, we review the core concepts in cultural evolutionary theory as they pertain to the extension of biology through culture, focusing on cultural evolutionary applications in population genetics, ecology, and demography. For each of these disciplines, we review the theoretical literature and highlight relevant empirical studies. We also discuss the societal implications of the study of cultural evolution and of the interactions of humans with one another and with their environment.

Genetics in LGB Assisted Reproduction: Two Flipped Classroom, Progressive Disclosure Cases.

There have been several educational reforms calling for increasing lesbian, gay, bisexual, and transgender (LGBT) education materials, application of basic sciences to clinical medicine, and active engagement of students. While the amount of educational materials for LGBT clinical cases is increasing, this session for preclinical medical students uniquely combines basic science population genetics, cisgender lesbian, gay, and bisexual (LGB) cultural issues and reproductive endocrinology in a 1.5-hour flipped classroom session. Students were assigned a prediscussion video and reading. Facilitators attended a 1.5-hour training session prior to discussion. Each classroom of 30 students with small groups of six was led by a third- or fourth-year medical student facilitator who taught from a PowerPoint that included discussion questions. An audience response system was used to show aggregated, real-time anonymous responses to case questions, a pre- and postsurvey was used to analyze changes in student attitudes and knowledge of assisted reproduction services for same-sex couples, and course evaluations captured overarching student impressions. All first-year students (N = 180) attended this mandatory session. Audience response questions showed a high level of knowledge of population genetics concepts. Voluntary surveys showed a higher number of assisted reproduction recommendations for LGB patients compared to heterosexual patients before discussion, with this difference disappearing after the discussion. This may indicate a shift in student attitudes and knowledge of LGB patient barriers and assisted reproduction. Course evaluations showed appreciation of LGB material integration within the course. Educators will be able to successfully integrate the application of population genetics, assisted reproduction cases, and an examination of cultural barriers in health care for LGB patients with this session.

Is PMI the Hypothesis or the Null Hypothesis?

Over the past several decades, there have been several strident exchanges regarding whether forensic entomologists estimate the postmortem interval (PMI), minimum PMI, or something else. During that time, there has been a proliferation of terminology reflecting this concern regarding "what we do." This has been a frustrating conversation for some in the community because much of this debate appears to be centered on what assumptions are acknowledged directly and which are embedded within a list of assumptions (or ignored altogether) in the literature and in case reports. An additional component of the conversation centers on a concern that moving away from the use of certain terminology like PMI acknowledges limitations and problems that would make the application of entomology appear less useful in court-a problem for lawyers, but one that should not be problematic for scientists in the forensic entomology community, as uncertainty is part of science that should and can be presented effectively in the courtroom (e.g., population genetic concepts in forensics). Unfortunately, a consequence of the way this conversation is conducted is that even as all involved in the debate acknowledge the concerns of their colleagues, parties continue to talk past one another advocating their preferred terminology. Progress will not be made until the community recognizes that all of the terms under consideration take the form of null hypothesis statements and that thinking about "what we do" as a null hypothesis has useful legal and scientific ramifications that transcend arguments over the usage of preferred terminology.