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Results for “genetics”

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bioRxiv2017

Bivariate Gaussian Mixture Model of GWAS (BGMG)quantifies polygenic overlap between complex traitsbeyond genetic correlation

Accumulating evidence from genome wide association studies (GWAS) suggests an abundance of shared genetic influences among complex human traits and disorders, such as mental disorders. While current cross-trait analytical methods focus on genetic correlation between traits, we developed a novel statistical tool (MiXeR), which quantifies polygenic overlap independent of genetic correlation, using summary statistics from GWAS. MiXeR results can be presented as a Venn diagram of unique and shared polygenic components across traits. At 90% of SNP-heritability explained for each phenotype, MiXeR estimates that more than 9K variants causally influence schizophrenia, 7K influence bipolar disorder, and out of those variants 6.9K are shared between these two disorders, which have high genetic correlation. Further, MiXeR uncovers extensive polygenic overlap between schizophrenia and educational attainment. Despite a genetic correlation close to zero, these traits share more than 9K causal variants, while 3K additional variants only influence educational attainment. By considering the polygenicity, heritability and discoverability of complex phenotypes, MiXeR provides a more complete quantification of shared genetic architecture than offered by other available tools.

genetics↗

bioRxiv2018

Accounting for Errors in Low Coverage High-Throughput Sequencing Data when Constructing Genetic Maps using Biparental Outcrossed Populations

Next generation sequencing is an efficient method that allows for substantially more markers than previous technologies, providing opportunities for building high density genetic linkage maps, which facilitate the development of non-model species genomic assemblies and the investigation of their genes. However, constructing genetic maps using data generated via high-throughput sequencing technology (e.g., genotyping-by-sequencing) is complicated by the presence of sequencing errors and genotyping errors resulting from missing parental alleles due to low sequencing depth. If unaccounted for, these errors lead to inflated genetic maps. In addition, map construction in many species is performed using full-sib family populations derived from the outcrossing of two individuals, where unknown parental phase and varying segregation types further complicate construction. We present a new methodology for modeling low coverage sequencing data in the construction of genetic linkage maps using full-sib populations of diploid species, implemented in a package called GUSMap. Our model is based on an extension of the Lander-Green hidden Markov model that accounts for errors present in sequencing data. Results show that GUSMap was able to give accurate estimates of the recombination fractions and overall map distance, while most existing mapping packages produced inflated genetic maps in the presence of errors. Our results demonstrate the feasibility of using low coverage sequencing data to produce genetic maps without requiring extensive filtering of potentially erroneous genotypes, provided that the associated errors are correctly accounted for in the model.

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bioRxiv2018

Investigating the shared genetics of non-syndromic cleft lip/palate and facial morphology

There is increasing evidence that genetic risk variants for non-syndromic cleft lip/palate (nsCL/P) are also associated with normal-range variation in facial morphology. However, previous analyses are mostly limited to candidate SNPs and findings have not been consistently replicated. Here, we used polygenic risk scores (PRS) to test for genetic overlap between nsCL/P and seven biologically relevant facial phenotypes. Where evidence was found of genetic overlap, we used bidirectional Mendelian randomization (MR) to test the hypothesis that genetic liability to nsCL/P is causally related to implicated facial phenotypes. Across 5,804 individuals of European ancestry from two studies, we found strong evidence, using PRS, of genetic overlap between nsCL/P and philtrum width; a 1 S.D. increase in nsCL/P PRS was associated with a 0.10 mm decrease in philtrum width (95% C.I. 0.054, 0.146; P = 0.00002). Follow-up MR analyses supported a causal relationship; genetic variants for nsCL/P homogeneously cause decreased philtrum width. In addition to the primary analysis, we also identified two novel risk loci for philtrum width at 5q22.2 and 7p15.2 in our Genome-wide Association Study (GWAS) of 6,136 individuals. Our results support a liability threshold model of inheritance for nsCL/P, related to abnormalities in development of the philtrum.

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bioRxiv2018

Trans-ancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders

Liability to alcohol dependence (AD) is heritable, but little is known about its complex polygenic architecture or its genetic relationship with other disorders. To discover loci associated with AD and characterize the relationship between AD and other psychiatric and behavioral outcomes, we carried out the largest GWAS to date of DSM - IV diagnosed AD. Genome - wide data on 14,904 individuals with AD and 37,944 controls from 28 case / control and family - based studies were meta - analyzed, stratified by genetic ancestry (European, N = 46,568; African; N = 6,280). Independent, genome - wide significant effects of different ADH1B variants were identified in European (rs1229984; p = 9.8E - 13) and African ancestries (rs2066702; p = 2.2E - 9). Significant genetic correlations were observed with schizophrenia, ADHD, depression, and use of cigarettes and cannabis. There was only modest genetic correlation with alcohol consumption and inconsistent associations with problem drinking. The genetic underpinnings of AD only partially overlap with those for alcohol consumption, underscoring the genetic distinction between pathological and non - pathological drinking behaviors.

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bioRxiv2018

Evidence for genetic correlations and bidirectional, causal effects between smoking and sleep behaviours

IntroductionCigarette smokers are at increased risk of poor sleep behaviours. However, it is largely unknown whether these associations are due to shared (genetic) risk factors and/or causal effects (which may be bi-directional).\n\nMethodsWe obtained summary-level data of genome-wide association studies of smoking (smoking initiation (n=74,035), cigarettes per day (n=38,181) and smoking cessation (n=41,278)) and sleep behaviours (sleep duration and chronotype, or morningness) (n=128,266) and insomnia (n=113,006)). Using LD score regression, we calculated genetic correlations between smoking and sleep behaviours. To investigate causal effects, we employed Mendelian randomization (MR), both with summary-level data and individual level data (n=333,581 UK Biobank participants). For MR with summary-level data, individual genetic variants were combined with inverse-variance weighted meta-analysis, weighted median regression and MR Egger regression methods.\n\nResultsWe found positive genetic correlations between insomnia and smoking initiation (rg=0.27, 95% CI 0.06 to 0.49) and insomnia and cigarettes per day (rg=0.15, 0.01 to 0.28), and negative genetic correlations between sleep duration and smoking initiation (rg=-0.14, -0.26 to -0.01) and chronotype and smoking cessation (rg=-0.18, -0.31 to -0.06). MR analyses provided strong evidence that smoking more cigarettes per day causally decreases the odds of being a morning person, and weak evidence that insomnia causally increases smoking heaviness and decreases smoking cessation odds.\n\nConclusionsSmoking and sleep behaviours show moderate genetic correlation. Heavier smoking seems to causally affect circadian rhythm and there is some indication that insomnia increases smoking heaviness and hampers cessation. Our findings point to sleep as a potentially interesting smoking treatment target.

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bioRxiv2018

Genetic meta-analysis identifies 10 novel loci and functional pathways for Alzheimer’s disease risk

Late onset Alzheimers disease (AD) is the most common form of dementia with more than 35 million people affected worldwide, and no curative treatment available. AD is highly heritable and recent genome-wide meta-analyses have identified over 20 genomic loci associated with AD, yet only explaining a small proportion of the genetic variance indicating that undiscovered loci exist. Here, we performed the largest genome-wide association study of clinically diagnosed AD and AD-by-proxy (71,880 AD cases, 383,378 controls). AD-by-proxy status is based on parental AD diagnosis, and showed strong genetic correlation with AD (rg=0.81). Genetic meta analysis identified 29 risk loci, of which 9 are novel, and implicating 215 potential causative genes. Independent replication further supports these novel loci in AD. Associated genes are strongly expressed in immune-related tissues and cell types (spleen, liver and microglia). Furthermore, gene-set analyses indicate the genetic contribution of biological mechanisms involved in lipid-related processes and degradation of amyloid precursor proteins. We show strong genetic correlations with multiple health-related outcomes, and Mendelian randomisation results suggest a protective effect of cognitive ability on AD risk. These results are a step forward in identifying more of the genetic factors that contribute to AD risk and add novel insights into the neurobiology of AD to guide new drug development.

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bioRxiv2018

Expanding the genetic toolkit of Tribolium castaneum

The red flour beetle, Tribolium castaneum, is an important model insect and agricultural pest.However, many standard genetic tools are lacking or underdeveloped in this system. Here, we present a set of new reagents to augment existing Tribolium genetic tools. We demonstrate a new GAL4 driver line that employs the promoter of a ribosomal protein gene to drive expression of a UAS responder in the fat body. We also present a novel dual fluorescent reporter that labels cell membranes and nuclei with different fluorophores for the analysis of cellular morphology. This approach also demonstrates the functionality of the viral T2A peptide for bicistronic gene expression in Tribolium. To facilitate classical genetic analysis, we created lines with visible genetic markers by CRISPR-mediated disruption of the yellow and ebony body color loci with a cassette carrying an attP site, enabling future {varphi}C31-mediated integration. Together,the reagents presented here will facilitate more robust genetic analysis in Tribolium and serve as a blueprint for the further development of this powerful models genetic toolkit.

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bioRxiv2018

Genetic Determinants of Telomere Length in African American Youth

Telomere length (TL) is associated with numerous disease states and is affected by genetic and environmental factors. However, TL has been mostly studied in adult populations of European or Asian ancestry. These studies have identified 34 TL-associated genetic variants recently used as genetic proxies for TL. The generalizability of these associations to pediatric populations and racially diverse populations, specifically of African ancestry, remains unclear. Furthermore, six novel variants associated with TL in a population of European children have been identified but not validated. We measured TL from whole blood samples of 492 healthy African American youth (children and adolescents between 8 and 20 years old) and performed the first genome-wide association study of TL in this population. We were unable to replicate neither the 34 reported genetic associations found in adults nor the six genetic associations found in European children. However, we discovered a novel genome-wide significant association between TL and rs1483898 on chromosome 14. Our results underscore the importance of examining these genetic associations with TL in diverse pediatric populations such as African Americans.

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bioRxiv2018

The complex genetic architecture of shoot growth natural variation in Arabidopsis thaliana

One of the main outcome of quantitative genetics approaches to natural variation is to reveal the genetic architecture underlying the phenotypic space. Complex genetic architectures are described as including numerous loci (or alleles) with small-effect and/or low-frequency in the populations, interactions with the genetic background, environment or age... Linkage or association mapping strategies will be more or less sensitive to this complexity, so that we still have an unclear picture of its extent. By combining high-throughput phenotyping under two environmental conditions with classical QTL mapping approaches in multiple Arabidopsis thaliana segregating populations as well as advanced near isogenic lines construction and survey, we have attempted to push back the limits of our understanding of quantitative phenotypic variation. Integrative traits such as those related to vegetative growth used in this work (highlighting either cumulative growth, growth rate or morphology) all showed complex and dynamic genetic architecture with respect to the segregating population and condition. The more resolutive our mapping approach, the more complexity we uncover, with several instances of QTLs visible in near isogenic lines but not detected with the initial QTL mapping, indicating that our phenotyping resolution was less limiting than the mapping resolution with respect to the underlying genetic architecture. In an ultimate approach to resolve this complexity, we intensified our phenotyping effort to target specifically a 3Mb-region known to segregate for a major quantitative trait gene, using a series of selected lines recombined every 100kb. We discovered that at least 3 other independent QTLs had remained hidden in this region, some with trait- or condition-specific effects, or opposite allelic effects. If we were to extrapolate the figures obtained on this specific region in this particular cross to the genome- and species-scale, we would predict hundreds of causative loci of detectable phenotypic effect controlling these growth-related phenotypes.

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bioRxiv2018

Combinatorial Genetic Control of Rpd3S through histone H3K4 and H3K36 Methylation in Budding Yeast

Much of euchromatin regulation occurs through reversible methylation of histone H3 lysine-4 and lysine-36 (H3K4me and H3K36me). Using the budding yeast Saccharomyces cerevisiae, we previously found that levels of H3K4me modulated temperature sensitive alleles of the transcriptional elongation complex Spt6-Spn1 through an unknown H3K4me effector pathway. Here we identify the Rpd3S histone deacetylase complex as the H3K4me effector underlying these Spt6-Spn1 genetic interactions. Exploiting these Spt6-Spn1 genetic interactions, we show that H3K4me and H3K36me collaboratively impact Rpd3S function in an opposing manner. H3K36me is deposited by the histone methyltransferase Set2 and is known to promote Rpd3S function at RNA PolII transcribed open reading frames. Using genetic epistasis experiments, we find that mutations perturbing the Set2-H3K36me-Rpd3S pathway suppress the growth defects caused by temperature sensitive alleles of SPT6 and SPN1, illuminating that this pathway antagonizes Spt6-Spn1. Using these sensitive genetic assays, we also identify a role for H3K4me in antagonizing Rpd3S that functions through the Rpd3S subunit Rco1, which is known to bind H3 N-terminal tails in a manner that is prevented by H3K4me. Further genetic experiments reveal that the H3K4 and H3K36 demethylases JHD2 and RPH1 mediate this combinatorial control of Rpd3S. Finally, our studies also show that the Rpd3L complex, which acts at promoter-proximal regions of PolII transcribed genes, counters Rpd3S for genetic modulation of Spt6-Spn1, and that these two Rpd3 complexes balance the activities of each other. Our findings present the first evidence that H3K4me and H3K36me act combinatorially to control Rpd3S.

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bioRxiv2018

Unraveling the genetic architecture of grain size in einkorn wheat through linkage and homology mapping, and transcriptomic profiling

HighlightGenome-wide linkage and homology mapping revealed 17 genomic regions through a high-density einkorn wheat genetic map constructed using RAD-seq, and transcription levels of 20 candidate genes were explored using RNA-seq.\n\nAbstractUnderstanding the genetic architecture of grain size is a prerequisite to manipulate the grain development and improve the yield potential in crops. In this study, we conducted a whole genome-wide QTL mapping of grain size related traits in einkorn wheat by constructing a high-density genetic map, and explored the candidate genes underlying QTL through homologous analysis and RNA sequencing. The high-density genetic map spanned 1873 cM and contained 9937 SNP markers assigned to 1551 bins in seven chromosomes. Strong collinearity and high genome coverage of this map were revealed with the physical maps of wheat and barley. Six grain size related traits were surveyed in five agro-climatic environments with 80% or more broad-sense heritability. In total, 42 QTL were identified and assigned to 17 genomic regions on six chromosomes and accounted for 52.3-66.7% of the phenotypic variations. Thirty homologous genes involved in grain development were located in 12 regions. RNA sequencing provided 4959 genes differentially expressed between the two parents. Twenty differentially expressed genes involved in grain size development and starch biosynthesis were mapped to nine regions that contained 26 QTL, indicating that the starch biosynthesis pathway played a vital role on grain development in einkorn wheat. This study provides new insights into the genetic architecture of grain size in einkorn wheat, the underlying genes enables the understanding of grain development and wheat genetic improvement, and the map facilitates the mapping of quantitative traits, map-based cloning, genome assembling and comparative genomics in wheat taxa.

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bioRxiv2018

Insight into the genetic architecture of back pain and its risk factors from a study of 509,000 individuals

Back pain (BP) is a common condition of major social importance and poorly understood pathogenesis. Combining data from the UK Biobank and CHARGE consortium cohorts allowed us to perform a very large GWAS (total N = 509,070) and examine the genetic correlation and pleiotropy between BP and its clinical and psychosocial risk factors. We identified and replicated three BP associated loci, including one novel region implicating SPOCK2/CHST3 genes. We provide evidence for pleiotropic effects of genetic factors underlying BP, height, and intervertebral disc problems. We also identified independent genetic correlations between BP and depression symptoms, neuroticism, sleep disturbance, overweight, and smoking. A significant enrichment for genes involved in central nervous system and skeletal tissue development was observed. The study of pleiotropy and genetic correlations, supported by the pathway analysis, suggests at least two strong molecular axes of BP genesis, one related to structural/anatomic factors such as intervertebral disk problems and anthropometrics; and another related to the psychological component of pain perception and pain processing. These findings corroborate with the current biopsychosocial model as a paradigm for BP. Overall, the results demonstrate BP to have an extremely complex genetic architecture that overlaps with the genetic predisposition to its biopsychosocial risk factors. The work sheds light on pathways of relevance in the prevention and management of LBP.

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bioRxiv2018

Genetic variants related to antihypertensive targets inform drug efficacy and side effects

BackgroundDrug effects can be investigated through natural variation in the genes for their protein targets. We aimed to use this approach to explore the potential side effects and repurposing potential of antihypertensive drugs, which are amongst the most commonly used medications worldwide.\n\nMethodsWe identified genetic instruments for antihypertensive drug classes as variants in the gene for the corresponding target that associated with systolic blood pressure at genome-wide significance. To validate the instruments, we compared Mendelian randomisation (MR) estimates for drug effects on coronary heart disease (CHD) and stroke risk to randomised controlled trial (RCT) results. Phenome-wide association study (PheWAS) in the UK Biobank was performed to identify potential side effects and repurposing opportunities, with findings investigated in the Vanderbilt University Biobank (BioVU) and in observational analysis of the UK Biobank.\n\nFindingsWe identified suitable genetic instruments for beta-blockers (BBs) and calcium channel blockers (CCBs). MR estimates for their effect on CHD and stroke risk respectively were comparable to results from RCTs against placebo. PheWAS in the UK Biobank identified an association of the CCB genetic risk score (scaled to drug effect) with increased risk of diverticulosis (odds ratio [OR] 1.23, 95%CI 1.10-1.38), with a consistent estimate found in BioVU (OR 1.16, 95%CI 0.94-1.44). Association with diverticulosis was further supported in observational analysis of CCB use in the UK Biobank (OR 1.08, 95%CI 1.02-1.15).\n\nInterpretationWe identified valid genetic instruments for BBs and CCBs. Using genetic and observational approaches, we highlighted a previously unreported potential detrimental effect of CCBs on risk of diverticulosis. This work serves as a proof of concept that investigation of genetic variants can offer a complementary approach to exploring the efficacy and side effects of anti-hypertensive medications.\n\nFundingWellcome Trust.

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bioRxiv2018

Unraveling the layers of cryptic genetic variation in a yeast gene regulatory network

Cryptic genetic variation may be an important contributor to heritable traits, but its extent and regulation are not fully understood. Here, we investigate the cryptic variation underlying a Saccharomyces cerevisiae colony phenotype that is typically suppressed in a cross. Mapping of the traits genetic basis after induction by three different genetic perturbations identifies 21 total loci. The perturbations largely uncover distinct loci, and strongly influence additivity, epistasis, and genotype-environment interaction among these loci. Only a single locus-- the coding region of the cell surface gene FLO11--is common to all three perturbations. While the remaining loci mostly influence FLO11 transcription in cis or trans, we detect loci in different pathways and sub-pathways in the presence of each perturbation. Our work shows that complex gene regulatory networks can harbor multiple layers of cryptic variation, each of which may only be visible in highly specific genotypic and environmental contexts.\n\nArticle SummaryThe extent and regulation of cryptic genetic variation within populations is not fully understood. To address these questions, we comprehensively dissect the genetic basis of a budding yeast colony trait following its induction by three different genetic perturbations. In total, we identify 21 distinct loci, most of which show phenotypic effects that depend on particular perturbations, other segregating loci, and temperature. We find that nearly all involved loci participate in a common gene regulatory network (GRN). Thus, our work demonstrates the large amount of cryptic variation underlying a single trait and ties the visibility of this variation to GRN activity.

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bioRxiv2018

Phenome-wide investigation of health outcomes associated with genetic predisposition to loneliness

AO_SCPLOWBSTRACTC_SCPLOWHumans are social animals that experience intense suffering when they perceive a lack of social connection. Modern societies are experiencing an epidemic of loneliness. While the experience of loneliness is universally human, some people report experiencing greater loneliness than others. Loneliness is more strongly associated with mortality than obesity, emphasizing the need to understand the nature of the relationship between loneliness and health. While it is intuitive that circumstantial factors such as marital status and age influence loneliness, there is also compelling evidence of a genetic predisposition towards loneliness. To better understand the genetic architecture of loneliness and its relationship with associated outcomes, we conducted a genome-wide association (GWAS) meta-analysis of loneliness (N=475,661), report 12 associated loci (two novel) and significant genetic correlations with 34 other complex traits. The polygenic basis for loneliness was significantly enriched for evolutionary constrained genes and genes expressed in specific brain tissues: (frontal) cortex, cerebellum, anterior cingulate cortex, and substantia nigra. We built polygenic scores based on this GWAS meta-analysis to explore the genetic association between loneliness and health outcomes in an independent sample of 18,498 individuals for whom electronic health records were available. A genetic predisposition towards loneliness predicted cardiovascular, psychiatric, and metabolic disorders, and triglycerides and high-density lipoproteins. Mendelian randomization analyses showed evidence of a causal, increasing, effect of body fat on loneliness, and a similar weaker causal effect of BMI. Our results provide a framework for ongoing studies of the genetic basis of loneliness and its role in mental and physical health.

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bioRxiv2018

Who’s who in the western Hermann’s tortoise conservation: a STR toolkit and reference database for wildlife forensic genetic analyses

Illegal trade is threatening tortoise populations worldwide since decades. Nowadays, however, DNA typing and forensic genetic approaches allow to investigate geographic origin of confiscated animals and to relocate them into the wild, provided that suitable molecular tools and reference data are available. Here we assess the suitability of a small panel of microsatellite markers to investigate patterns of illegal translocations and to assist forensic genetic applications in the endangered Mediterranean land tortoise Testudo hermanni hermanni. We used the microsatellite panel to (i) increase the understanding of the population genetic structure in wild populations with new data from previously unsampled geographic areas (overall 461 wild individuals from 28 sampling sites); (ii) detect the presence of non-native individuals in wild populations; and (iii) identify the most likely geographic area of origin of 458 confiscated individuals hosted in Italian seizure and recovery centers. Our analysis initially identified six major genetic clusters corresponding to different geographic macro-areas along the Mediterranean range. Long-distance migrants among wild populations, due to translocations, were found and removed from the reference database. Assignment tests allowed us to allocate approximately 70% of confiscated individuals of unknown origin to one of the six Mediterranean macro-areas. Most of the assigned tortoises belonged to the genetic cluster corresponding to the area where the respective captivity center was located. However, we also found evidence of long-distance origin of confiscated individuals, especially in centers along the Adriatic coast and facing the Balkan regions, a well-known source of illegally traded individuals. Our results clearly show the role for reintroduction projects of the microsatellite panel, which was useful to re-assign most of the confiscated individuals to the respective macro-area of origin. At the same time, the microsatellite panel can assist future forensic genetic applications to detect illegal trade and possess of Testudo hermanni individuals.

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bioRxiv2018

Exploring contributors to variability in estimates of SNP-heritability and genetic correlations from the iPSYCH case-cohort and published meta-studies of major psychiatric disorders.

As more and more large psychiatric genetic cohorts are becoming available, more and more independent investigations into the underlying genetic architecture are performed, and an expanding set of replicates for estimates of key genetic parameters, namely, liability scale SNP heritability and genetic correlations - is amassing in the literature. In recent work, we published a set of SNP-heritability and genetic correlation estimates for major psychiatric disorders using data from the iPSYCH case-cohort study, and presented them alongside estimates gleaned from large, independently collected, analyzed and published meta-studies of the same disorders. Although in the broadest sense the estimates from iPSYCH and external meta-studies were concordant, and requiring strict statistical significance could reject the null hypothesis for few pairs, there were enough subtle trends in the differences to warrant further investigation. In this work, we consider a set of factors related to sample ascertainment, including the lifetime risks for disorders for the sampled populations, the use of age censored or partially screened controls, the sampling of extreme cases and controls, and diagnostic error rates, and attempt to assess their potential contributions to estimates of genetic parameters in the context of the difference trends observed in our previous work.

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bioRxiv2018

Partitioning the genetic architecture of amyotrophic lateral sclerosis

The genetic basis of sporadic amyotrophic lateral sclerosis (ALS) is not well understood. Using large genome-wide association studies and validated tools to quantify genetic overlap, we systematically identified single nucleotide polymorphisms (SNPs) associated with ALS conditional on genetic data from 65 different traits and diseases from >3 million people. We found strong genetic enrichment between ALS and a number of disparate traits including frontotemporal dementia, coronary artery disease, C-reactive protein, celiac disease and memory function. Beyond C9ORF72, we detected novel genetic signal within numerous loci including GIPC1, ELMO1 and COL16A and confirmed previously reported variants, such as ATXN2, KIF5A, UNC13A and MOBP. We found that ALS variants form a small-world co-expression network characterized by highly inter-connected hub genes. This network clustered into smaller sub-networks, each associated with a unique function. Altered gene expression of several sub-networks and hubs was over-represented in neuropathological samples from ALS patients and SOD1 G93A mice. Our collective findings indicate that the genetic architecture of ALS can be partitioned into distinct components where some genes are highly important for developing disease. These findings have implications for stratification and enrichment strategies for ALS clinical trials.

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