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Results for “genetics”

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bioRxiv2019

A Phenome-wide Mendelian Randomisation study on genetically determined serum urate levels in UK Biobank cohort

IntroductionThe role of serum urate level has been extensively investigated in observational studies. However, the extent of any causal effect remains unclear, making it difficult to evaluate its clinical relevance.\n\nObjectivesTo explore any causal or pleiotropic association between serum urate level and a broad spectrum of disease outcomes.\n\nMethodsPhenome-wide association study (PheWAS) together with a Bayesian analysis of tree-structured phenotypic models (TreeWAS) was performed to examine disease outcomes related to genetically determined serum urate levels in 339,256 UK Biobank participants. Mendelian Randomisation (MR) analyses were performed to replicate significant findings using various GWAS consortia data. Sensitivity analyses were conducted to examine possible pleiotropic effects on metabolic traits of the genetic variants used as instruments for serum urate.\n\nResultsPheWAS analysis, examining the association with 1,431 disease outcomes, identified a multitude of disease outcomes including gout, hypertension, hypercholesterolemia, and heart diseases (e.g., coronary atherosclerosis, myocardial infarction, and ischaemic heart disease) that were associated (p<3.35e-04) with genetically determined serum urate levels. TreeWAS analysis, examining 10,750 ICD-10 diagnostic terms, identified more sub-phenotypes of cardiovascular and cerebrovascular diseases (e.g., angina pectoris, heart failure, cerebral infarction). MR analysis successfully replicated the association with gout, hypertension, heart diseases and blood lipid levels, but indicated the existence of genetic pleiotropy. Sensitivity analyses support an inference that pleiotropic effects of genetic variants on urate and metabolic traits contribute to the observational associations with cardiovascular diseases.\n\nConclusionsHigh serum urate levels are associated with different types of cardiac events. The finding of genetic pleiotropy indicates the existence of common upstream pathological elements influencing both urate and metabolic traits, and this may suggest new opportunities and challenges for developing drugs targeting a more distal mediator that would be beneficial for both the treatment of gout and the prevention of cardiovascular comorbidities.

epidemiology↗

bioRxiv2019

Old Meets New: Combining Herbarium Databases with Genetic Methods to Evaluate the Invasion Status of Baby’s Breath (Gypsophila paniculata) in North America

AimThis paper aims to inform our knowledge of common babys breaths (Gypsophila paniculata) current population structure and invasion status using a combination of contemporary genetic methods and historical herbarium data.\n\nTaxonGypsophila paniculata (Angiosperms: Eudicot, Caryophyllaceae)\n\nLocationSamples were collected from seven locations spanning a portion of the plants North American range: Washington, North Dakota, Minnesota, and Michigan, United States.\n\nMethodsTo analyze contemporary population structure, individuals of G. paniculata from 7 distinct sampling locations were collected and genotyped at 14 microsatellite loci. Population structure was inferred using both Bayesian and multivariate methods. To investigate G. paniculatas invasion status, public herbarium databases were searched for mention of the species. Records were combined, resulting in a database of 307 herbarium collections dating from the late 1800s to current day. Using this database, invasion curves were created at different geospatial scales.\n\nResultsResults of genetic analyses suggest the presence of at least two genetic clusters spanning our seven sampling locations. Sampling locations in Washington, North Dakota, Minnesota, and northwestern Michigan form one genetic cluster, distinct from our two more southern sampling locations in Michigan, which form a second cluster with increased relative genetic diversity. Invasion curves created for these two clusters show different time periods of invasion. An invasion curve created for North America suggests G. paniculatas range may still be expanding.\n\nMain conclusionsGypsophila paniculata has likely undergone at least two distinct invasions in North America, and its range may still be expanding. Restricted genetic diversity seen across a wide geographic area could be a signature of limited seed distributors present during the early period of this garden ornamentals invasion.

evolutionary biology↗

bioRxiv2019

Genetic paths to evolutionary rescue and the distribution of fitness effects along them

The past century has seen substantial theoretical and empirical progress on the genetic basis of adaptation. Over this same period a pressing need to prevent the evolution of drug resistance has uncovered much about the potential genetic basis of persistence in declining populations. However, we have little theory to predict and generalize how persistence - by sufficiently rapid adaptation - might be realized in this explicitly demographic scenario. Here we use Fishers geometric model with absolute fitness to begin a line of theoretical inquiry into the genetic basis of evolutionary rescue, focusing here on asexual populations that adapt through de novo mutations. We show how the dominant genetic path to rescue switches from a single mutation to multiple as mutation rates and the severity of the environmental change increase. In multi-step rescue, intermediate genotypes that themselves go extinct provide a springboard to rescue genotypes. Comparing to a scenario where persistence is assured, our approach allows us to quantify how a race between evolution and extinction leads to a genetic basis of adaptation that is composed of fewer loci of larger effect. We hope this work brings awareness to the impact of demography on the genetic basis of adaptation.

evolutionary biology↗

bioRxiv2019

Estimates of genetic load in small populations suggest extensive purging of deleterious alleles

It is commonly thought that declining populations will experience negative genetic consequences as a result of increased inbreeding. Here we estimated the average deleteriousness of derived alleles in a range of mammals and found that species with historically small population size and low genetic diversity often have lower genetic load than species with large population sizes. This is likely the result of genetic purging - the more efficient removal of partially deleterious recessive alleles from inbred populations. Our findings suggest that genetic purging occurs over long evolutionary time frames, and therefore rapid population declines are likely to dis-proportionally increase mutational load in species with high diversity, as they carry many deleterious alleles that can reach fixation before genetic purging can remove them.

genomics↗

bioRxiv2019

Separating Measured Genetic and Environmental Effects: Evidence Linking Parental Genotype and Adopted Child Outcomes

There has been widespread adoption of genome wide summary scores (polygenic scores) as tools for studying the importance of genetics and associated lifecourse mechanisms across a range of demographic and socioeconomic outcomes. However, an often unacknowledged issue with these studies is that parental genetics impact both child environments and child genetics, leaving the effects of polygenic scores difficult to interpret. This paper uses multi-generational data containing polygenic scores for parents (n=7,193) and educational outcomes for adopted (n=855) and biological (n=20,939) children, many raised in the same families, which allows us to separate the influence of parental polygenic scores on children outcomes between environmental (adopted children) and environmental and genetic (biological children) effects. Our results complement recent work on "genetic nurture" by showing associations of parental polygenic scores with adopted childrens schooling, providing additional evidence that polygenic scores combine genetic and environmental influences and that research designs are needed to separate these estimated impacts.

genomics↗

bioRxiv2019

Integration of transcriptome, proteome and phosphoproteome data elucidates the genetic control of molecular networks

Genomic variation affects cellular networks by altering diverse molecular layers such as RNA levels, protein abundance, and post-translational protein modifications. However, it remains unclear how these different layers are affected by genetic polymorphisms and give rise to complex physiological phenotypes. To address these questions, we generated high-quality transcriptome, proteome, and phosphoproteome data for a panel of 112 genetically diverse yeast strains. While genetic effects on transcript abundances were generally transmitted to the protein level, we found a significant uncoupling of the transcript-protein relationship for certain protein classes, such as subunits of protein complexes. The additional phosphoproteomics data suggests that the same genetic locus often affects distinct sets of genes within each of these layers. In particular, QTLs tended to affect upstream regulatory proteins at the phosphorylation layer, whereas downstream pathway targets were typically affected at the transcript and protein abundance layers. Underscoring the importance of regulatory protein phosphorylation in linking genetic to phenotypic variation is the finding that the number of protein phosphosites associated with a given genetic locus was more predictive for its influence on cellular growth traits than the number of transcripts or proteins.\n\nThis study shows how multi-layered molecular networks mediate the effects of genomic variants to more complex physiological traits and highlights the important role of protein phosphorylation in mediating these effects.

systems biology↗

bioRxiv2019

Human footprint differentially impacts genetic connectivity of four wide-ranging mammals in a fragmented landscape

AimMaintaining connectivity is critical for long-term persistence of wild carnivores in landscapes fragmented due to anthropogenic activity. We examined spatial genetic structure and the impact of landscape features on connectivity in four wide-spread species- jungle cat (Felis chaus), leopard (Panthera pardus), sloth bear (Melursus ursinus) and tiger (Panthera tigris). Location Our study was carried out in the central Indian landscape, a stronghold in terms of distribution and abundance of large mammals. The landscape comprises fragmented forests embedded in a heterogeneous matrix of multiple land-use types.\n\nMethodsMicrosatellite data from non-invasively sampled individuals (90 jungle cats, 82 leopards, 104 sloth bears and 117 tigers) were used to investigate genetic differentiation. Impact of landscape features on gene flow was inferred using a multi-model landscape resistance optimization approach.\n\nResultsAll four study species revealed significant isolation by distance (IBD). The correlation between genetic and geographic distance was significant only over a short distance for jungle cat, followed by longer distances for sloth bear, leopard and tiger. Overall, human footprint had a high negative impact on geneflow in tigers, followed by leopards, sloth bears and the least on jungle cats. Individual landscape variables- land-use, human population density, density of linear features and roads- impacted the study species differently. Although land-use was found to be an important variable explaining genetic connectivity for all four species, the amount of variation explained, the optimum spatial resolution and the resistance offered by different land-use classes varied.\n\nMain conclusionsAs expected from theory, but rarely demonstrated using empirical data, the pattern of spatial autocorrelation of genetic variation scaled with dispersal ability and density of the study species. Landscape genetic analyses revealed species-specific impact of landscape features and provided insights into interactions between species biology and landscape structure. Our results emphasize the need for incorporating functional connectivity data from multiple species for landscape-level conservation planning.

ecology↗

bioRxiv2019

Genetic Associations in Four Decades of Multi-Environment Trials Reveal Agronomic Trait Evolution in Common Bean

Multi-environment trials (METs) are widely used to assess the performance of promising crop germplasm. Though seldom designed to elucidate genetic mechanisms, MET datasets are often much larger than could be duplicated for genetic research and, given proper interpretation, may offer valuable insights into the genetics of adaptation across time and space. The Cooperative Dry Bean Nursery (CDBN) is a MET for common bean (Phaseolus vulgaris) grown for over 70 years in the United States and Canada, consisting of 20 to 50 entries each year at 10 to 20 locations. The CBDN provides a rich source of phenotypic data across entries, years, and locations that is amenable to genetic analysis. To study stable genetic effects segregating in this MET, we conducted genome-wide association (GWAS) using best linear unbiased predictions (BLUPs) derived across years and locations for 21 CDBN phenotypes and genotypic data (1.2M SNPs) for 327 CDBN genotypes. The value of this approach was confirmed by the discovery of three candidate genes and genomic regions previously identified in balanced GWAS. Multivariate adaptive shrinkage (mash) analysis, which increased our power to detect significant correlated effects, found significant effects for all phenotypes. The first use of mash on an agricultural dataset discovered two genomic regions with pleiotropic effects on multiple phenotypes, likely selected on in pursuit of a crop ideotype. Overall, our results demonstrate that by applying multiple statistical genomic approaches on data mined from MET phenotypic data sets, significant genetic effects that define genomic regions associated with crop improvement can be discovered.

genomics↗

bioRxiv2019

CONSTRUTION OF A GENETIC MAP OF RILs DERIVED FROM WHEAT (T. AESTIVUM L.) VARIETIES PAMYATII AZIEVA X PARAGON USING HIGH-THROUGHPUT SNP GENOTYPING PLATFORM KASP - COMPETATIVE ALLELE SPECIFIC PCR

The main purposes of the study were i) to develop a first mapping population for bread wheat grown in Kazakhstan, ii) to construct its genetic map for further identification of genes associated with important agronomic traits.\n\nTo the best of our knowledge this is the first segregating population and genetic map developed for Kazakh bread wheat. The work is an example of how plant breeding programs in Kazakhstan have started successfully deploying next generation plant breeding methods.\n\nThe KASP (Compatative Allele Specific PCR) technology of LGC Group and SNP DNA-markers have been exploited to genotype and build a genetic map of the segregating population. The total length of the map was 1376 cM. A total 157 out of initial 178 SNP markers used formed 26 linkage groups leaving 1 duplicated and 20 unassigned markers. The threshold distance between markers was set [≤] 30 cM. Therefore, two linkage groups were obtained for chromosomes such as 2A, 2B, 2D, 3A, 5A, 6B and 7A. Despite one duplicated and 20 unassigned markers, the 157 KASP SNP markers that were mapped spanned A, B and D genomes of wheat. Kosambi Mapping function was employed to calculate recombination units between makers. RILs were developed through SSD method up to F4 generation. Almost 97% of identified alleles were useful in evaluating the populations genetic diversity; the remaining 3% showed no outcome. As a result, 77 DNA markers were mapped for A, 74 for B and 27 for D genomes. The mapping population will be genotyped using high marker density array planform such as Illumina iSelect to obtain a genetic map with a relatively high coverage. Then, the population and high-resolution genetic map will be used to identify genes influencing wheat adaptation in Kazakhstan.

genomics↗

bioRxiv2019

Accumulation of genetic variants associated with immunity in the selective breeding of broilers

To satisfy an increasing demand for dietary protein, the poultry industry has employed genetic selection to increase the growth rate of broilers by over 400% in the past 50 years. Although modern broilers reach a marketable weight of [~]2 kg in a short span of 35 days, a speed twice as fast as a broiler 50 years ago, the expedited growth has been associated with several negative detrimental consequences. Aside from heart and musculoskeletal problems, which are direct consequences of additional weight, the immune response is also thought to be altered in modern broilers. Given that identifying the underlying genetic basis responsible for a less sensitive innate immune response would be economically beneficial for poultry breeding, we decided to compare the genomes of two unselected meat control strains that are representative of broilers from 1957 and 1978, and a current commercial broiler line. Through analysis of genetic variants, we developed a custom prioritization strategy to identify genes and pathways that have accumulated genetic changes and are biologically relevant to immune response and growth performance. Our results highlight two genes, TLR3 and PLIN3, with genetic variants that are predicted to enhance growth performance at the expense of immune function. Placing these new genomes in the context of other chicken lines, reveal genetic changes that have specifically arisen in selective breeding programs that were implemented in the last 50 years.

genomics↗

bioRxiv2019

Predicting the genetic ancestry of 2.6 million New York City patients using clinical data

Ancestry is an essential covariate in clinical genomics research. When genetic data are available, dimensionality reduction techniques, such as principal components analysis, are used to determine ancestry in complex populations. Unfortunately, these data are not always available in the clinical and research settings. For example, electronic health records (EHRs), which are a rich source of temporal human disease data that could be used to enhance genetic studies, do not directly capture ancestry. Here, we present a novel algorithm for predicting genetic ancestry using only variables that are routinely captured in EHRs, such as self-reported race and ethnicity, and condition billing codes. Using patients that have both genetic and clinical information at Columbia University/ New York-Presbyterian Irving Medical Center, we developed a pipeline that uses only clinical data to predict the genetic ancestry of all patients of which more than 80% identify as other or unknown. Our ancestry estimates can be used in observational studies of disease inheritance, to guide genetic cohort studies, or to explore health disparities in clinical care and outcomes.

bioinformatics↗

bioRxiv2019

Genetic changes of P. vivax tempers host tissue-specific responses in Anopheles stephensi

In our preceding study (Sharma et al., 2019; BioRxiv) we showed that in the gut lumen Plasmodium vivax follows a unique strategy of immuno-suppression by disabling gut flora proliferation. Here, we further demonstrate that post gut invasion, a shrewd molecular relationship with individual tissues such as midgut, hemocyte, salivary glands, and strategic changes in the genetic makeup of P. vivax favors its survival in the mosquito host. A transient suppression of metabolic machinery by early oocysts, and increased immunity against late oocysts suggested a unique mechanism of gut homeostasis restoration and Plasmodium population regulation. Though a hyper immune response of hemocyte was a key to remove free circulating sporozoites, but a strong suppression of salivary metabolic activities, may favor successful survival of invaded sporozoites. Finally, genetic alteration of P. vivax ensures evasion of mosquito responses. Conclusively, our system-wide RNAseq analysis provides first genetic evidences of direct mosquito-Plasmodium interaction and establishes a functional correlation.\n\nAuthor SummaryMalaria transmission dynamics is heavily influenced by mosquito -parasite interaction. When passing through tissue specific barriers, Plasmodium have to compromise by losing its own population, but genetic relation is unknown. To win the developmental race Plasmodium need to overcome two important immuno-physiological barriers. First one accounts an indirect 24-30hr long pre-invasive gut-microbe-parasite interaction in the gut lumen. And second one follows a direct post gut invasive 14-18 days interaction with midgut, hemocyte and salivary glands. During pre-invasive phase of interaction, we showed Plasmodium vivax follows immuno-suppression strategy by restricting microbial growth in the gut lumen. Here, we demonstrate that switch of parasite from one stage to another stage within mosquito vector is accompanied by genetic changes of parasite. Our data suggests genetic makeup change enables the parasite to manipulate the metabolism of mosquito tissues. This strategy not only clear off multifaceted mosquitos tissue specific immune responses, but also favors Plasmodium own survival and transmission. Comprehending this tissue specific interaction between host and parasite at molecular level could provide new tool to intervene the plasmodium life cycle within vector.

genomics↗

bioRxiv2019

Selection and drift determine phenotypic stasis despite genetic divergence

1Evolutionary theory suggests that phenotypic stasis is explained by natural selection and genetic drift, or by constraints imposed by mutation and recombination of standing genetic variation. We performed experimental evolution from standing genetic variation with the nematode Caenorhabditis elegans, measuring individual locomotion in outcrossing populations for 240 generations. We find that, in our constant environment, locomotion bias shows no directional divergence, due to both stabilizing and disruptive selection on specific combinations of component traits. Despite phenotypic stasis, the genetic variance-covariance structure between component traits shows clear divergence from the ancestral state and extensive differentiation among replicated populations facing the same environment. Analysis of mutation accumulation experiments and genome-sequenced recombinant inbred lines from the experimental populations indicates that the evolution of the genetic variance-covariance structure is independent of de novo mutation or major effect QTL; being instead explained by the joint action of selection and drift in generating subtle linkage disequilibrium differences between small effect QTL among replicate populations. These findings indicate that phenotypic evolution is repeatable because of selection, even if the genetic structuring of component traits within lineages is mostly contingent upon drift history.

evolutionary biology↗

bioRxiv2019

Quantifying The Individual Impact Of Artificial Barriers In Freshwaters: A Standardized And Absolute Index Of Genetic Connectivity

Fragmentation by artificial barriers is an important threat to freshwater biodiversity. Mitigating the negative aftermaths of fragmentation is of crucial importance, and it is now essential for environmental managers to benefit from a precise estimate of the individual impact of weirs and dams on river connectivity. Although the indirect monitoring of fragmentation using molecular data constitutes a promising approach, it is plagued with several constraints preventing a standardized and individual quantification of barrier effects. Indeed, observed levels of genetic differentiation depend on both the age of the obstacle and the effective size of the populations it separates, making difficult comparisons of the actual barrier effect of different obstacles. Here, we developed a standardized genetic index of fragmentation (FINDEX), allowing an absolute and independent assessment of the individual effects of obstacles on connectivity. The FINDEX is the standardized ratio (expressed as a percentage) between the observed genetic differentiation between pairs of populations located on either side of an obstacle and the genetic differentiation expected if this obstacle completely prevented gene flow. The expected genetic differentiation is calculated from simulations taking into account two nuisance parameters: the number of generations since barrier creation (the age of the obstacle) and the expected heterozygosity of the targeted populations, a proxy for effective population sizes. Using both simulated and published empirical datasets, we explored and discussed the validity and the limits of the FINDEX. We demonstrated that it allows quantifying genetic effects of fragmentation only from a few generations after barrier creation and provides valid comparisons among populations (or species) of different effective populations sizes and obstacles of different ages. The computation of the FINDEX requires a minimum amount of fieldwork and genotypic data, and solves some of the difficulties inherent to the study of artificial fragmentation in rivers and potentially in other ecosystems. This makes the FINDEX a promising and objective tool for managers aiming at at planning restoration programs and at evaluating the efficiency of these programs.

ecology↗

bioRxiv2019

How to better conserve with genetic data: origin and population structure of Brazilian locally adapted hair sheep (Ovis aries) breeds

Brazilian hair sheep constitute a genetic diversity hotspot of sheep breeds. These locally adapted genetic resources developed in harsh environments of the Brazilian Northwest (semi-arid) and maintained important traits for this region, such as parasite resistance, heat tolerance and high pelt quality. Genotypes (50K SNP chip) from seven Brazilian sheep breeds (5 hair and 2 coarse wool types) and 87 worldwide breeds were used to verify population structure, admixture and genetic diversity, using PCA and ADMIXTURE analyses. We constructed a phylogenetic tree and evaluated migration events between genetic groups using TREEMIX software. Brazilian Somali, a fat-tailed breed, was the unique breed with high relationship with East African breeds and formed a distinct cluster from other Brazilian breeds. This breed seems to contribute to formation of Santa Ines, Morada Nova and Brazilian Fat-tail breeds. Brazilian Blackbelly had a clear relationship with Barbados Blackbelly, which appeared as another group. Other Brazilian breeds seem to form a further genetic group with some recent admixtures. Morada Nova remained as a separate group, not showing a strong relationship with European or African breeds, only revealing a migration event from Sidaoun, an Algerian hair breed. Brazilian Fat-tail and Morada Nova share a common ancestor, but the first received introgressions from Brazilian Somali and Afrikaner breeds, explaining the fat-tail phenotype. Santa Ines received strong contribution from Bergamasca and had an admixed origin with recent introgressions from other breeds, mainly from Suffolk animals. In conclusion, Brazilian Somali and Brazilian Fat-tail are the most endangered sheep genetic resources in Brazil.

genomics↗

bioRxiv2019

Genetic structure at national and regional scale in a long-distance dispersing pest organism, the bird cherry-oat aphid Rhopalosiphum padi

Genetic diversity is determinant for pest species success and vector competence. Understanding the ecological and evolutionary processes that determine the genetic diversity is fundamental to help identify the spatial scale at which pest populations are best managed. In the present study, we present the first comprehensive analysis of the genetic diversity and evolution of Rhopalosiphum padi, a major pest of cereals and a main vector of the barley yellow dwarf virus (BYDV), in Great Britain. We have used a genotype by sequencing approach to study whether i) there is any underlying population genetic structure in this long distant disperser pest at a national and regional scale; ii) the populations evolve as a response to environmental change and selective pressures, and; iii) the populations comprise anholocyclic lineages. Individual R. padi were collected using the Rothamsted Insect Surveys suction-trap network at several sites across England between 2004 and 2016 as part of the RIS long-term nationwide surveillance. Results identified two genetic clusters in Great Britain that mostly paralleled a North - South division, although gene flow is ongoing between the two subpopulations. These different groups do not correspond to sexual and asexual types, sexual reproduction being predominant in Great Britain, and could correspond to ecotypes. Results also show that there is migration with gene flow across Great Britain, although there is a reduction between the northern and southern sites with the Southwestern population being the most genetically differentiated. There is no evidence for isolation-by-distance and other factors like primary host distribution could influence the migration patterns. Finally, results also show no evidence for the evolution of the R. padi population, and it is demographically stable despite the ongoing environmental change. These results are discussed in view of their relevance to pest management and the transmission of BYDV.

evolutionary biology↗

bioRxiv2019

Genetic Association Study of Childhood Aggression across raters, instruments and age

Childhood aggressive behavior (AGG) has a substantial heritability of around 50%. Here we present a genome-wide association meta-analysis (GWAMA) of childhood AGG, in which all phenotype measures across childhood ages from multiple assessors were included. We analyzed phenotype assessments for a total of 328 935 observations from 87 485 children aged between 1.5 and 18 years, while accounting for sample overlap. We also meta-analyzed within subsets of the data - i.e. within rater, instrument and age. SNP-heritability for the overall meta-analysis (AGGoverall) was 3.31% (SE=0.0038). We found no genome-wide significant SNPs for AGGoverall. The gene-based analysis returned three significant genes: ST3GAL3 (P=1.6E-06), PCDH7 (P=2.0E-06) and IPO13 (P=2.5E-06). All three genes have previously been associated with educational traits. Polygenic scores based on our GWAMA significantly predicted aggression in a holdout sample of children (variance explained = 0.44%) and in retrospectively assessed childhood aggression (variance explained = 0.20%). Genetic correlations (rg) among rater-specific assessment of AGG ranged from rg =0.46 between self- and teacher-assessment to rg =0.81 between mother- and teacher-assessment. We obtained moderate to strong rgs with selected phenotypes from multiple domains, but hardly with any of the classical biomarkers thought to be associated with AGG. Significant genetic correlations were observed with most psychiatric and psychological traits (range |rg| : 0.19 - 1.00), except for obsessive-compulsive disorder. Aggression had a negative genetic correlation (rg =~ -0.5) with cognitive traits and age at first birth. Aggression was strongly genetically correlated with smoking phenotypes (range |rg| : 0.46 - 0.60). The genetic correlations between aggression and psychiatric disorders were weaker for teacher-reported AGG than for mother- and self-reported AGG. The current GWAMA of childhood aggression provides a powerful tool to interrogate the rater-specific genetic etiology of AGG.

genomics↗

bioRxiv2019

Quantifying the polygenic architecture of the human cerebral cortex: Extensive genetic overlap between cortical thickness and surface area

IntroductionThe thickness of the cerebral cortical sheet and its surface area are highly heritable traits thought to have largely distinct polygenic architectures. Despite large-scale efforts, the majority of their genetic determinants remains unknown. Our ability to identify causal genetic variants can be improved by employing better delineated, less noisy brain measures that better map onto the biology we seek to understand. Such measures may have fewer variants but with larger effects, i.e. lower polygenicity and higher discoverability. MethodsUsing Gaussian mixture modeling, we estimated the number of causal variants shared between mean cortical thickness and total surface area. We further determined the polygenicity and discoverability of regional cortical measures from five often-employed parcellation schemes. We made use of UK Biobank data from 31,312 healthy White European individuals (mean age 55.5, standard deviation (SD) 7.4, 52.1% female). ResultsContrary to previous reports, we found large genetic overlap between total surface area and mean thickness, sharing 4427 out of 7150 causal variants. Regional surface area was more discoverable (p=4.1x10-6) and less polygenic (p=.007) than regional thickness measures. We further found that genetically-informed and less granular parcellation schemes had highest discoverability, with no differences in polygenicity. ConclusionsThese findings may serve as a roadmap for improved future GWAS studies; Knowledge of which measures or parcellations are most discoverable, as well as the genetic overlap between these measures, may be used to boost identification of genetic predictors and thereby gain a better understanding of brain morphology.

neuroscience↗