scholarly journals Response to a population bottleneck can be used to infer recessive selection

2014 ◽  
Author(s):  
Daniel J Balick ◽  
Ron Do ◽  
David Reich ◽  
Shamil R Sunyaev
Keyword(s):  
Transient Response ◽  
Functional Dependence ◽  
Population Bottleneck ◽  
Statistical Test ◽  
Regional Level ◽  
Large Set ◽  
Deleterious Mutations ◽  
Demographic Differences ◽  
Genome Wide ◽  
Different Populations

Here we present the first genome wide statistical test for recessive selection. This test uses explicitly non-equilibrium demographic differences between populations to infer the mode of selection. By analyzing the transient response to a population bottleneck and subsequent re-expansion, we qualitatively distinguish between alleles under additive and recessive selection. We analyze the response of the average number of deleterious mutations per haploid individual and describe time dependence of this quantity. We introduce a statistic, BR, to compare the number of mutations in different populations and detail its functional dependence on the strength of selection and the intensity of the population bottleneck. This test can be used to detect the predominant mode of selection on the genome wide or regional level, as well as among a sufficiently large set of medically or functionally relevant alleles.

scholarly journals Nowcasting Regional GDP: The Case of the Free State of Saxony

2015 ◽  
Vol 66 (1) ◽  
pp. 71-98
Author(s):  
Steffen R. Henzel ◽  
Robert Lehmann ◽  
Klaus Wohlrabe
Keyword(s):  
Data Structure ◽  
Manufacturing Sector ◽  
Regional Level ◽  
Free State ◽  
Large Set ◽  
Regional Survey ◽  
Forecasting Accuracy ◽  
Leading Indicator ◽  
Information Sets ◽  
Survey Results

Abstract We tackle the nowcasting problem at the regional level, using a large set of indicators (regional, national and international) for the years 1998 to 2013. We explicitly take into account the ragged-edge data structure and consider the different information sets faced by a regional forecaster within each quarter. It appears that regional survey results in particular improve forecasting accuracy. Among the 10% best performing models for the short forecasting horizon, one fourth contain regional indicators. Hard indicators from the German manufacturing sector and the Composite Leading Indicator for Europe also deliver useful information for the prediction of regional GDP in Saxony. Unlike national GDP forecasts, the performance of regional GDP is similar across different information sets within a quarter.

scholarly journals The Advantages of Segregation and the Evolution of Sex

Genetics ◽  
2003 ◽  
Vol 164 (3) ◽  
pp. 1099-1118 ◽  
Author(s):  
Sarah P Otto
Keyword(s):  
Sexual Reproduction ◽  
Asexual Reproduction ◽  
Deleterious Mutations ◽  
Evolution Of Sex ◽  
Beneficial Mutations ◽  
Selection Regime ◽  
Strong Selection ◽  
Genome Wide ◽  
Low Levels

AbstractIn diploids, sexual reproduction promotes both the segregation of alleles at the same locus and the recombination of alleles at different loci. This article is the first to investigate the possibility that sex might have evolved and been maintained to promote segregation, using a model that incorporates both a general selection regime and modifier alleles that alter an individual’s allocation to sexual vs. asexual reproduction. The fate of different modifier alleles was found to depend strongly on the strength of selection at fitness loci and on the presence of inbreeding among individuals undergoing sexual reproduction. When selection is weak and mating occurs randomly among sexually produced gametes, reductions in the occurrence of sex are favored, but the genome-wide strength of selection is extremely small. In contrast, when selection is weak and some inbreeding occurs among gametes, increased allocation to sexual reproduction is expected as long as deleterious mutations are partially recessive and/or beneficial mutations are partially dominant. Under strong selection, the conditions under which increased allocation to sex evolves are reversed. Because deleterious mutations are typically considered to be partially recessive and weakly selected and because most populations exhibit some degree of inbreeding, this model predicts that higher frequencies of sex would evolve and be maintained as a consequence of the effects of segregation. Even with low levels of inbreeding, selection is stronger on a modifier that promotes segregation than on a modifier that promotes recombination, suggesting that the benefits of segregation are more likely than the benefits of recombination to have driven the evolution of sexual reproduction in diploids.

scholarly journals A publicly available repository of ROH islands reveals signatures of selection in different livestock and pet species

2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Wim Gorssen ◽  
Roel Meyermans ◽  
Steven Janssens ◽  
Nadine Buys
Keyword(s):  
Association Studies ◽  
Genome Wide Association Studies ◽  
Single Nucleotide ◽  
Future Studies ◽  
Snp Data ◽  
Animal Populations ◽  
Genome Wide ◽  
Starting Point ◽  
Different Populations ◽  
Signatures Of Selection

Abstract Background Runs of homozygosity (ROH) have become the state-of-the-art method for analysis of inbreeding in animal populations. Moreover, ROH are suited to detect signatures of selection via ROH islands and are used in other applications, such as genomic prediction and genome-wide association studies (GWAS). Currently, a vast amount of single nucleotide polymorphism (SNP) data is available online, but most of these data have never been used for ROH analysis. Therefore, we performed a ROH analysis on large medium-density SNP datasets in eight animal species (cat, cattle, dog, goat, horse, pig, sheep and water buffalo; 442 different populations) and make these results publicly available. Results The results include an overview of ROH islands per population and a comparison of the incidence of these ROH islands among populations from the same species, which can assist researchers when studying other (livestock) populations or when looking for similar signatures of selection. We were able to confirm many known ROH islands, for example signatures of selection for the myostatin (MSTN) gene in sheep and horses. However, our results also included multiple other ROH islands, which are common to many populations and not identified to date (e.g. on chromosomes D4 and E2 in cats and on chromosome 6 in sheep). Conclusions We are confident that our repository of ROH islands is a valuable reference for future studies. The discovered ROH island regions represent a unique starting point for new studies or can be used as a reference for future studies. Furthermore, we encourage authors to add their population-specific ROH findings to our repository.

scholarly journals Leveraging polygenic enrichments of gene features to predict genes underlying complex traits and diseases

2020 ◽  
Author(s):  
Elle M Weeks ◽  
Jacob C Ulirsch ◽  
Nathan Y Cheng ◽  
Brian L Trippe ◽  
Rebecca S Fine ◽  
...  
Keyword(s):  
Complex Traits ◽  
Association Studies ◽  
Gene Prioritization ◽  
Protein Interaction Data ◽  
Large Set ◽  
Genome Wide Association Studies ◽  
Protein Protein Interaction ◽  
Genome Wide ◽  
Causal Genes ◽  
Red Blood Cell Count

Genome-wide association studies (GWAS) are a valuable tool for understanding the biology of complex traits, but the associations found rarely point directly to causal genes. Here, we introduce a new method to identify the causal genes by integrating GWAS summary statistics with gene expression, biological pathway, and predicted protein-protein interaction data. We further propose an approach that effectively leverages both polygenic and locus-specific genetic signals by combining results across multiple gene prioritization methods, increasing confidence in prioritized genes. Using a large set of gold standard genes to evaluate our approach, we prioritize 8,402 unique gene-trait pairs with greater than 75% estimated precision across 113 complex traits and diseases, including known genes such as SORT1 for LDL cholesterol, SMIM1 for red blood cell count, and DRD2 for schizophrenia, as well as novel genes such as TTC39B for cholelithiasis. Our results demonstrate that a polygenic approach is a powerful tool for gene prioritization and, in combination with locus-specific signal, improves upon existing methods.

Emergence and populations genomics of the highly invasive chestnut blight pathogen

2020 ◽  
Author(s):  
◽  
Lea Stauber
Keyword(s):  
Mating Type ◽  
Fungal Genome ◽  
Chestnut Blight ◽  
Mixed Mating ◽  
Large Set ◽  
Pathogen Evolution ◽  
Invasive Pathogens ◽  
Invasive Pathogen ◽  
Genome Wide

Invasive pathogens are a threat to forest and agroecosystems, as well as animal and human health. Identifying genomic determinants of pathogen evolution, as well as investigations into the genetic structure of invasive pathogen populations provide fundamental insights to why species can emerge as invasive pathogens. In this PhD project I investigated the emergence and population genomics of the invasive chestnut blight fungus Cryphonectria parasitica, using comparative and population genomic approaches. C. parasitica recently emerged as an invasive bark pathogen on non-Asian Castanea species in North America and Europe. In the first chapter, I investigated genomic determinants of lifestyle transitions in the genus Cryphonectria, by genome comparisons of C. parasitica and its sister species. The study uncovered a striking loss of genes associated with carbohydrate metabolism in the invasive pathogen C. parasitica, which may have promoted its pathogenicity on Castanea species. The second chapter explores the emergence and diversification of a highly invasive chestnut blight lineage across south-eastern Europe. By analyzing the genome-wide diversity of a large set of C. parasitica isolates of predominantly European origin, the study showed that a highly successful clonal pathogen lineage can emerge from a recombinant bridgehead population within Europe. Interestingly, the emergence of this clonal lineage was accompanied by an evolutionary transition from mixed mating type populations to single mating type outbreak populations. Lastly, in the third chapter I investigated temporal changes in genetic diversity of established C. parasitica populations in southern Switzerland, as well as potential links between the presence of the deleterious hyperparasitic mycovirus Cryphonectria hypovirus 1 (CHV1) and fungal genome-wide diversity. The results indicate increased mating among related fungal individuals, resulting in high genetic similarity of genotypes and facilitated CHV1 transmission. There were no substantial changes in fungal population structure and after ˜30 years and no detectable impact of CHV1 presence on fungal genome-wide diversity. Although our results show stable CHV1 incidence in fungal populations over three decades, the short-term interaction dynamics are likely highly volatile. The overall findings of this PhD thesis highlight the relevance of genomic determinants facilitating pathogen emergence and invasions. C. parasitica is a useful model to study fundamental questions of pathogen evolution and invasive processes, as well as antagonistic pathogen-hyperparasite interactions.

Phenotypic Screen and Transcriptomics Approach Complement Each Other in Functional Genomics of Defensive Stink Gland Physiology

2021 ◽  
Author(s):  
Sabrina Lehmann ◽  
Bibi Atika ◽  
Daniela Grossmann ◽  
Christian Schmitt-Engel ◽  
Nadi Strohlein ◽  
...  
Keyword(s):  
Functional Genomics ◽  
Large Scale ◽  
Reverse Genetics ◽  
Expression Profiles ◽  
Forward Genetics ◽  
Large Set ◽  
Knock Down ◽  
Genome Wide ◽  
Phenotypic Screen ◽  
A Genome

Abstract Background Functional genomics uses unbiased systematic genome-wide gene disruption or analyzes natural variations such as gene expression profiles of different tissues from multicellular organisms to link gene functions to particular phenotypes. Functional genomics approaches are of particular importance to identify large sets of genes that are specifically important for a particular biological process beyond known candidate genes, or when the process has not been studied with genetic methods before. Results Here, we present a large set of genes whose disruption interferes with the function of the odoriferous defensive stink glands of the red flour beetle Tribolium castaneum. This gene set is the result of a large-scale systematic phenotypic screen using a reverse genetics strategy based on RNA interference applied in a genome-wide forward genetics manner. In this first-pass screen, 130 genes were identified, of which 69 genes could be confirmed to cause knock-down gland phenotypes, which vary from necrotic tissue and irregular reservoir size to irregular color or separation of the secreted gland compounds. The knock-down of 13 genes caused specifically a strong reduction of para-benzoquinones, suggesting a specific function in the synthesis of these toxic compounds. Only 14 of the 69 confirmed gland genes are differentially overexpressed in stink gland tissue and thus could have been detected in a transcriptome-based analysis. Moreover, of the 29 previously transcriptomics-identified genes causing a gland phenotype, only one gene was recognized by this phenotypic screen despite the fact that 13 of them were covered by the screen. Conclusion Our results indicate the importance of combining diverse and independent methodologies to identify genes necessary for the function of a certain biological tissue, as the different approaches do not deliver redundant results but rather complement each other. The presented phenotypic screen together with a transcriptomics approach are now providing a set of close to hundred genes important for odoriferous defensive stink gland physiology in beetles.

scholarly journals Statistical and Network-Based Analysis of Italian COVID-19 Data: Communities Detection and Temporal Evolution

2020 ◽  
Vol 17 (12) ◽  
pp. 4182 ◽  
Author(s):  
Marianna Milano ◽  
Mario Cannataro
Keyword(s):  
Temporal Evolution ◽  
Edge Length ◽  
Statistical Test ◽  
Regional Level ◽  
Analysis Pipeline ◽  
Death Rates ◽  
Detection Algorithms ◽  
Italian Regions ◽  
Similarity Relationships ◽  
Similarity Matrices

The coronavirus disease (COVID-19) outbreak started in Wuhan, China, and it has rapidly spread across the world. Italy is one of the European countries most affected by COVID-19, and it has registered high COVID-19 death rates and the death toll. In this article, we analyzed different Italian COVID-19 data at the regional level for the period 24 February to 29 March 2020. The analysis pipeline includes the following steps. After individuating groups of similar or dissimilar regions with respect to the ten types of available COVID-19 data using statistical test, we built several similarity matrices. Then, we mapped those similarity matrices into networks where nodes represent Italian regions and edges represent similarity relationships (edge length is inversely proportional to similarity). Then, network-based analysis was performed mainly discovering communities of regions that show similar behavior. In particular, network-based analysis was performed by running several community detection algorithms on those networks and by underlying communities of regions that show similar behavior. The network-based analysis of Italian COVID-19 data is able to elegantly show how regions form communities, i.e., how they join and leave them, along time and how community consistency changes along time and with respect to the different available data.

scholarly journals The Intersection between COVID-19, the Gene Family of ACE2 and Alzheimer’s Disease

2020 ◽  
Vol 15 ◽  
pp. 263310552097574
Author(s):  
Mahdi Montazer Haghighi ◽  
Erfan Ghani Kakhki ◽  
Christine Sato ◽  
Mahdi Ghani ◽  
Ekaterina Rogaeva
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Gene Family ◽  
Renin Angiotensin System ◽  
Special Focus ◽  
Angiotensin System ◽  
Regulatory Pathways ◽  
Genome Wide ◽  
Different Populations ◽  
Ace2 Gene

We reviewed factors that might influence COVID-19 outcomes (eg, neurological symptoms), including the link to Alzheimer’s disease. Since the virus triggers COVID-19 infection through binding to ACE2, we focused on the ACE2 gene family, including ACE. Both ACE2 and ACE are involved in the renin–angiotensin system (RAS). In general, ACE causes inflammation and vasoconstriction, while ACE2 leads to anti-inflammation activity and vasodilation. The disturbed balance between these counter-regulatory pathways could influence susceptibility to COVID-19. Notably, dysregulation of the RAS-equilibrium contributes to Alzheimer’s disease. Differences in the incidence and symptoms of COVID-19 in diverse populations could be attributed to variability in the human genome. For example, ACE and ACE2 variations could modify the outcome of COVID-19 in different populations. It would be important to conduct genome-wide studies to detect variants influencing COVID-19 presentation, with a special focus on variants affecting immune-related pathways and expression of RAS-related genes.

Sign in / Sign up

Export Citation Format

Share Document