scholarly journals Ethnic Identity and Genome Wide Runs of Homozygosity

2021 ◽  
Author(s):  
Martin Fieder ◽  
Brittany L. Mitchell ◽  
Scott Gordon ◽  
Susanne Huber ◽  
Nicholas G. Martin
Keyword(s):  
Ethnic Identity ◽  
Longitudinal Data ◽  
Ethnic Group ◽  
Statistical Power ◽  
Sequence Variants ◽  
Runs Of Homozygosity ◽  
Twin Data ◽  
Data Set ◽  
Total N ◽  
Genome Wide

AbstractIt is long known that inbreeding increases the detrimental effects of recessive sequence variants in “Runs of Homozygosity” (ROHs). However, although the phenotypic association of ROH has been investigated for a variety of traits, the statistical power of the results often remains limited as a sufficiently high number of cases are available for only a restricted number of traits. In the present study, we aim to analyze the association of runs of homozygosity with the trait “in-group ethnic favoritism”. This analysis assumes that if ethnic identity is important for an individual, that individual may tend to marry more frequently within their own group and therefore ROH are expected to increase. We hypothesize that an attitude preferring one’s own ethnic group may be associated with a stronger tendency of inbreeding and, as a result, with more and longer ROHs. Accordingly, we investigated the association between the attitude to someone’s own ethnicity and ROH, using the Wisconsin Longitudinal data (WLS, total N ~ 9000) as discovery data set and the Brisbane Twin data as replication data set (N ~ 8000). We find that both the number as well as the total length of homozygous segments are significantly positively associated with “in-group ethnic favoritism”, independent of the method used for ROH calculation.

scholarly journals Meta-Analytic Use of Balanced Identity Theory to Validate the Implicit Association Test

2020 ◽  
pp. 014616722091663 ◽  
Author(s):  
Dario Cvencek ◽  
Andrew N. Meltzoff ◽  
Craig D. Maddox ◽  
Brian A. Nosek ◽  
Laurie A. Rudman ◽  
...  
Keyword(s):  
Implicit Association Test ◽  
Statistical Power ◽  
Identity Theory ◽  
Meta Analysis ◽  
Association Test ◽  
Self Report ◽  
Implicit Association ◽  
Individual Subject ◽  
Data Set ◽  
Total N

This meta-analysis evaluated theoretical predictions from balanced identity theory (BIT) and evaluated the validity of zero points of Implicit Association Test (IAT) and self-report measures used to test these predictions. Twenty-one researchers contributed individual subject data from 36 experiments (total N = 12,773) that used both explicit and implicit measures of the social–cognitive constructs. The meta-analysis confirmed predictions of BIT’s balance–congruity principle and simultaneously validated interpretation of the IAT’s zero point as indicating absence of preference between two attitude objects. Statistical power afforded by the sample size enabled the first confirmations of balance–congruity predictions with self-report measures. Beyond these empirical results, the meta-analysis introduced a within-study statistical test of the balance–congruity principle, finding that it had greater efficiency than the previous best method. The meta-analysis’s full data set has been publicly archived to enable further studies of interrelations among attitudes, stereotypes, and identities.

scholarly journals State Networks and Intra-Ethnic Group Variation in the 2011 Syrian Uprising

2018 ◽  
Vol 52 (7) ◽  
pp. 995-1027
Author(s):  
Kevin Mazur
Keyword(s):  
Ethnic Identity ◽  
Social Structure ◽  
Ethnic Group ◽  
Original Data ◽  
The State ◽  
Social Boundaries ◽  
Group Level ◽  
Data Set ◽  
Ethnic Exclusion ◽  
Group Variation

The 2011 Syrian uprising looks, from afar, like a paradigmatic example of ethnically exclusive rule giving way to civil war. The ruling regime is drawn almost exclusively from the Alawi minority, and the challengers were drawn heavily from the Sunni majority. But many Sunnis remained quiescent or actively supported the regime. This article argues that variation in revolutionary participation among members of an excluded ethnic group is best explained in terms of the networks states construct across ethnic boundaries. It identifies several forms of linkage that regimes can develop with their subject populations and relates them to variations in local social structure. Drawing on an original data set of ethnic identity and challenge events in the Syrian uprising, the article quantitatively tests the state networks hypothesis. Its findings suggest that the mechanisms commonly associated with ethnic identity and “ethnic exclusion” frequently operate upon social boundaries below the ethnic group level.

Measures Collected on the USMA Class of 1998 as Part of the Baseline Officer Longitudinal Data Set (BOLDS)

2002 ◽  
Author(s):  
Lynn M. Milan ◽  
Dennis R. Bourne ◽  
Michelle M. Zazanis ◽  
Paul T. Bartone
Keyword(s):  
Longitudinal Data ◽  
Data Set

Ethnic Group Status Differences in the Ethnic Identity--> Prejudice Relationship

2006 ◽  
Author(s):  
Wendy Soto ◽  
Dawn Fassih ◽  
Debby Martin ◽  
James Hsiao ◽  
Michele Wittig
Keyword(s):  
Ethnic Identity ◽  
Ethnic Group ◽  
Group Status ◽  
Status Differences

scholarly journals Soil carbon and nutrient stocks under Scots pine plantations in comparison to European beech forests: a paired-plot study across forests with different management history and precipitation regimes

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Marco Diers ◽  
Robert Weigel ◽  
Heike Culmsee ◽  
Christoph Leuschner
Keyword(s):  
Scots Pine ◽  
Tree Species ◽  
European Beech ◽  
Organic Layer ◽  
Species Identity ◽  
Data Set ◽  
Nutrient Pools ◽  
Total N ◽  
Precipitation Regimes ◽  
Pine Stands

Abstract Background Organic carbon stored in forest soils (SOC) represents an important element of the global C cycle. It is thought that the C storage capacity of the stable pool can be enhanced by increasing forest productivity, but empirical evidence in support of this assumption from forests differing in tree species and productivity, while stocking on similar substrate, is scarce. Methods We determined the stocks of SOC and macro-nutrients (nitrogen, phosphorus, calcium, potassium and magnesium) in nine paired European beech/Scots pine stands on similar Pleistocene sandy substrates across a precipitation gradient (560–820 mm∙yr− 1) in northern Germany and explored the influence of tree species, forest history, climate, and soil pH on SOC and nutrient pools. Results While the organic layer stored on average about 80% more C under pine than beech, the pools of SOC and total N in the total profile (organic layer plus mineral soil measured to 60 cm and extrapolated to 100 cm) were greater under pine by about 40% and 20%, respectively. This contrasts with a higher annual production of foliar litter and a much higher fine root biomass in beech stands, indicating that soil C sequestration is unrelated to the production of leaf litter and fine roots in these stands on Pleistocene sandy soils. The pools of available P and basic cations tended to be higher under beech. Neither precipitation nor temperature influenced the SOC pool, whereas tree species was a key driver. An extended data set (which included additional pine stands established more recently on former agricultural soil) revealed that, besides tree species identity, forest continuity is an important factor determining the SOC and nutrient pools of these stands. Conclusion We conclude that tree species identity can exert a considerable influence on the stocks of SOC and macronutrients, which may be unrelated to productivity but closely linked to species-specific forest management histories, thus masking weaker climate and soil chemistry effects on pool sizes.

scholarly journals A likelihood ratio approach for identifying three-quarter siblings in genetic databases

Heredity ◽  
2021 ◽  
Author(s):  
Iván Galván-Femenía ◽  
Carles Barceló-Vidal ◽  
Lauro Sumoy ◽  
Victor Moreno ◽  
Rafael de Cid ◽  
...  
Keyword(s):  
Likelihood Ratio ◽  
Family Relationships ◽  
Genetic Research ◽  
Data Set ◽  
Scientific Disciplines ◽  
Genome Wide ◽  
Standard Quality ◽  
Control Procedures ◽  
Identity By State ◽  
Second Degree

AbstractThe detection of family relationships in genetic databases is of interest in various scientific disciplines such as genetic epidemiology, population and conservation genetics, forensic science, and genealogical research. Nowadays, screening genetic databases for related individuals forms an important aspect of standard quality control procedures. Relatedness research is usually based on an allele sharing analysis of identity by state (IBS) or identity by descent (IBD) alleles. Existing IBS/IBD methods mainly aim to identify first-degree relationships (parent–offspring or full siblings) and second degree (half-siblings, avuncular, or grandparent–grandchild) pairs. Little attention has been paid to the detection of in-between first and second-degree relationships such as three-quarter siblings (3/4S) who share fewer alleles than first-degree relationships but more alleles than second-degree relationships. With the progressively increasing sample sizes used in genetic research, it becomes more likely that such relationships are present in the database under study. In this paper, we extend existing likelihood ratio (LR) methodology to accurately infer the existence of 3/4S, distinguishing them from full siblings and second-degree relatives. We use bootstrap confidence intervals to express uncertainty in the LRs. Our proposal accounts for linkage disequilibrium (LD) by using marker pruning, and we validate our methodology with a pedigree-based simulation study accounting for both LD and recombination. An empirical genome-wide array data set from the GCAT Genomes for Life cohort project is used to illustrate the method.

scholarly journals Common genetic variants with fetal effects on birth weight are enriched for proximity to genes implicated in rare developmental disorders

2021 ◽  
Author(s):  
Robin N Beaumont ◽  
Isabelle K Mayne ◽  
Rachel M Freathy ◽  
Caroline F Wright
Keyword(s):  
Birth Weight ◽  
Statistical Power ◽  
Developmental Disorders ◽  
Association Studies ◽  
Later Life ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
Common Genetic Variants ◽  
Causal Genes

Abstract Birth weight is an important factor in newborn survival; both low and high birth weights are associated with adverse later-life health outcomes. Genome-wide association studies (GWAS) have identified 190 loci associated with maternal or fetal effects on birth weight. Knowledge of the underlying causal genes is crucial to understand how these loci influence birth weight and the links between infant and adult morbidity. Numerous monogenic developmental syndromes are associated with birth weights at the extreme ends of the distribution. Genes implicated in those syndromes may provide valuable information to prioritize candidate genes at the GWAS loci. We examined the proximity of genes implicated in developmental disorders (DDs) to birth weight GWAS loci using simulations to test whether they fall disproportionately close to the GWAS loci. We found birth weight GWAS single nucleotide polymorphisms (SNPs) fall closer to such genes than expected both when the DD gene is the nearest gene to the birth weight SNP and also when examining all genes within 258 kb of the SNP. This enrichment was driven by genes causing monogenic DDs with dominant modes of inheritance. We found examples of SNPs in the intron of one gene marking plausible effects via different nearby genes, highlighting the closest gene to the SNP not necessarily being the functionally relevant gene. This is the first application of this approach to birth weight, which has helped identify GWAS loci likely to have direct fetal effects on birth weight, which could not previously be classified as fetal or maternal owing to insufficient statistical power.

scholarly journals Eyes of Africa: The Genetics of Blindness: Study Design and Methodology

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Olusola Olawoye ◽  
Chimdi Chuka-Okosa ◽  
Onoja Akpa ◽  
Tony Realini ◽  
Michael Hauser ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Case Control Study ◽  
African Ancestry ◽  
Collaborative Study ◽  
Data Set ◽  
Human Heredity ◽  
Genome Wide ◽  
A Genome ◽  
Multiplex Families ◽  
Control Study

Abstract Background This report describes the design and methodology of the “Eyes of Africa: The Genetics of Blindness,” a collaborative study funded through the Human Heredity and Health in Africa (H3Africa) program of the National Institute of Health. Methods This is a case control study that is collecting a large well phenotyped data set among glaucoma patients and controls for a genome wide association study. (GWAS). Multiplex families segregating Mendelian forms of early-onset glaucoma will also be collected for exome sequencing. Discussion A total of 4500 cases/controls have been recruited into the study at the end of the 3rd funded year of the study. All these participants have been appropriately phenotyped and blood samples have been received from these participants. Recent GWAS of POAG in African individuals demonstrated genome-wide significant association with the APBB2 locus which is an association that is unique to individuals of African ancestry. This study will add to the existing knowledge and understanding of POAG in the African population.

scholarly journals CADD-Splice—improving genome-wide variant effect prediction using deep learning-derived splice scores

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Philipp Rentzsch ◽  
Max Schubach ◽  
Jay Shendure ◽  
Martin Kircher
Keyword(s):  
Prediction Models ◽  
Splice Variants ◽  
Superior Performance ◽  
Data Set ◽  
Pathogenic Variants ◽  
Genome Wide ◽  
Donor And Acceptor ◽  
Human Proteins ◽  
Variant Effect ◽  
Variant Effect Prediction

Abstract Background Splicing of genomic exons into mRNAs is a critical prerequisite for the accurate synthesis of human proteins. Genetic variants impacting splicing underlie a substantial proportion of genetic disease, but are challenging to identify beyond those occurring at donor and acceptor dinucleotides. To address this, various methods aim to predict variant effects on splicing. Recently, deep neural networks (DNNs) have been shown to achieve better results in predicting splice variants than other strategies. Methods It has been unclear how best to integrate such process-specific scores into genome-wide variant effect predictors. Here, we use a recently published experimental data set to compare several machine learning methods that score variant effects on splicing. We integrate the best of those approaches into general variant effect prediction models and observe the effect on classification of known pathogenic variants. Results We integrate two specialized splicing scores into CADD (Combined Annotation Dependent Depletion; cadd.gs.washington.edu), a widely used tool for genome-wide variant effect prediction that we previously developed to weight and integrate diverse collections of genomic annotations. With this new model, CADD-Splice, we show that inclusion of splicing DNN effect scores substantially improves predictions across multiple variant categories, without compromising overall performance. Conclusions While splice effect scores show superior performance on splice variants, specialized predictors cannot compete with other variant scores in general variant interpretation, as the latter account for nonsense and missense effects that do not alter splicing. Although only shown here for splice scores, we believe that the applied approach will generalize to other specific molecular processes, providing a path for the further improvement of genome-wide variant effect prediction.

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