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bioRxiv2017

Fast and Powerful Genome Wide Association Analysis of Dense Genetic Data with High Dimensional Imaging Phenotypes

Genome wide association (GWA) analysis of brain imaging phenotypes can advance our understanding of the genetic basis of normal and disorder-related variation in the brain. GWA approaches typically use linear mixed effect models to account for non-independence amongst subjects due to factors such as family relatedness and population structure. The use of these models with high-dimensional imaging phenotypes presents enormous challenges in terms of computational intensity and the need to account multiple testing in both the imaging and genetic domain. Here we present method that makes mixed models practical with high-dimensional traits by a combination of a transformation applied to the data and model, and the use of a non-iterative variance component estimator. With such speed enhancements permutation tests are feasible, which allows inference on powerful spatial tests like the cluster size statistic.

genetics↗

bioRxiv2017

Genetic Analysis of Lodging in Diverse Maize Hybrids

Damage caused by lodging is a significant problem in corn production that results in estimated annual yield losses of 5-20%. Over the past 100 years, substantial maize breeding efforts have increased lodging resistance by artificial selection. However, less research has focused on understanding the genetic architecture underlying lodging. Lodging is a problematic trait to evaluate since it is greatly influenced by environmental factors such as wind, rain, and insect infestation, which make replication difficult. In this study over 1,723 diverse inbred maize genotypes were crossed to a common tester and evaluated in five environments over multiple years. Natural lodging due to severe weather conditions occurred in all five environments. By testing a large population of genetically diverse maize lines in multiple field environments, we detected significant correlations for this highly environmentally influenced trait across environments and with important agronomic traits such as yield and plant height. This study also permitted the mapping of quantitative trait loci (QTL) for lodging. Several QTL identified in this study overlapped with loci previously mapped for stalk strength in related maize inbred lines. QTL intervals mapped in this study also overlapped candidate genes implicated in the regulation of lignin and cellulose synthesis.

genetics↗

bioRxiv2017

Sodium valproate rescues expression of TRANK1 in iPSC-derived neural cells that carry a genetic variant associated with serious mental illness

Biological characterization of genetic variants identified in genome-wide association studies (GWAS) remains a substantial challenge. Here we used human induced pluripotent stem cells (hiPSC) and their neural derivatives to characterize common variants on chromosome 3p22 that have been associated by GWAS with major mental illnesses. HiPSC-derived neural progenitor cells carrying the risk allele of the single nucleotide polymorphism (SNP), rs9834970, displayed lower baseline TRANK1 expression that was rescued by chronic treatment with therapeutic dosages of valproic acid (VPA). Although rs9834970 has no known function, we demonstrated that a nearby SNP, rs90832, strongly affects binding by the transcription factor, CTCF, and that the high-affinity allele usually occurs on haplotypes carrying the rs9834970 risk allele. Decreased expression of TRANK1 perturbed expression of many genes involved in neural development and differentiation. These findings have important implications for the pathophysiology of major mental illnesses and the development of novel therapeutics.\n\nHighlightsO_LIhiPSC-derived neural cells carrying a mental illness risk allele showed lower expression of TRANK1\nC_LIO_LIValproic acid rescued TRANK1expression in cells carrying the risk allele\nC_LIO_LIRisk haplotypes usually carry an allele that increased CTCF binding\nC_LIO_LIReduced expression of TRANK1 perturbed genes involved in neural development and differentiation\nC_LI\n\nIn BriefUsing neural derivatives of human induced pluripotent stem cells, Jiang et al. demonstrate that genetic variants associated with mental illness alter transcription factor binding and decrease expression of a nearby gene, an effect which is rescued by valproic acid.

genetics↗

bioRxiv2017

Leveraging lung tissue transcriptome to uncover candidate causal genes in COPD genetic associations

We collated 129 non-overlapping risk loci for chronic obstructive pulmonary disease (COPD) from the GWAS literature. Using recent and complementary integrative genomics approaches, combining GWAS and lung eQTL results, we identified 12 novel COPD loci and corresponding causal genes. In addition, we mapped candidate causal genes for 60 out of the 129 GWAS-nominated loci as well as for four sub-genome-wide significant COPD risk loci derived from the largest GWAS on COPD. Mapping causal genes in lung tissue represents an important contribution on the genetics of COPD, enriches our biological interpretation of GWAS findings, and brings us closer to clinical translation of genetic associations.

genomics↗

bioRxiv2017

Genetic Analysis of Deep Phenotyping Projects in Common Disorders

Several studies of complex psychotic disorders with large numbers of neurobiological phenotypes are currently under way, in living patients and controls, and on assemblies of brain specimens. Genetic analyses of such data typically present challenges, because of the choice of underlying hypotheses on genetic architecture of the studied disorders and phenotypes, large numbers of phenotypes, the appropriate multiple testing corrections, limited numbers of subjects, imputations required on missing phenotypes and genotypes, and the cross-disciplinary nature of the phenotype measures. Advances in genotype and phenotype imputation, and in genome-wide association (GWAS) methods, are useful in dealing with these challenges. As compared with the more traditional single-trait analyses, deep phenotyping with simultaneous genome-wide analyses serves as a discovery tool for previously unsuspected relationships of phenotypic traits with each other, and with specific molecular involvements.

genetics↗

bioRxiv2017

Large-scale screening of rare genetic variants in humans reveals frequent splicing disruptions

Any individuals genome contains [~]4-5 million genetic variants that differ from reference, and understanding how these variants give rise to trait diversity and disease susceptibility is a central goal of human genetics1. A vast majority (96-99%) of an individuals variants are common, though at a population level the overwhelming majority of variants are rare2-5. Because of their scarcity in an individuals genome, rare variants that play important roles in complex traits are likely to have large functional effects6,7. Mutations that cause an exon to be skipped can have severe functional consequences on gene function, and many known disease-causing mutations reduce or eliminate exon recognition8. Here we explore the extent to which rare genetic variation in humans results in near complete loss of exon recognition. We developed a Multiplexed Functional Assay of Splicing using Sort-seq (MFASS) that allows us to measure exon inclusion in thousands of human exons and surrounding intronic sequence simultaneously. We assayed 27,733 extant variants in the Exome Aggregation Consortium (ExAC)9 within or adjacent to 2,339 human exons, and found that 3.8% (1,050) of the variants, almost all of which were extremely rare, led to large-effect defects in exon recognition. Importantly, we find that 83% of these splice-disrupting variants (SDVs) are located outside of canonical splice sites, are distributed evenly across distinct exonic and intronic regions, and are difficult to predict a priori. Our results indicate that loss of exon recognition is an important and underappreciated means by which rare variants exert large functional effects, and that MFASS enables their empirical assessment for splicing defects at scale.

genetics↗

bioRxiv2017

Modernized tools for streamlined genetic manipulation of wild and diverse symbiotic bacteria

The capacity to associate symbiotic bacteria with vital aspects of plant and animal biology is outpacing our understanding of the mechanisms shaping these interactions. A major barrier to mechanistic studies is the paucity of tools for genetically manipulating wild and diverse bacterial isolates. Solving this problem is crucial to elucidating the cellular and molecular rules that govern symbiotic relationships and ultimately harnessing them for agricultural and biomedical applications. Therefore, we constructed a series of vectors that expedite genetic knock-in and knock-out procedures across a range of bacterial lineages. This was accomplished by developing strategies for domestication-free bacterial conjugation, designing plasmids with customizable features, and streamlining allelic exchange using visual markers of homologous recombination. These tools enabled a comparative study based on live imaging of diverse bacterial symbionts native to the zebrafish intestine, with which we discovered heterogeneous colonization patterns and a striking correlation between bacterial population biogeography and cellular behavior.

genetics↗

bioRxiv2017

Predicting the genetic loci of past evolution

Repetitions in the mutations found to be responsible for independent evolution of similar phenotypes in various taxa have led some biologists to propose that for certain evolutionary changes the causal mutations are predictable. We examine here the nature of the predictions that have been made and their associated arguments. Predictions about the loci of past evolution are retrodictions, i.e. inferences about events that occurred in the past. They are not based on elaborate models and they derive mainly from the observation of repeated cases of genetic evolution. Predictions at the nucleotide level or at the gene level have a higher inference gain than those for broader categories of genetic changes such as cis-regulatory mutations.

genetics↗

bioRxiv2017

Sharing genetic admixture and diversity of public biomedical datasets

Genetic ancestry and admixture are critical co-factors to study phenotype-genotype associations using cohorts of human subjects. Most publically available molecular datasets - genomes, exomes or transcriptomes - are however missing this information or only share self-reported ancestry. This represents a limitation to identify and re-purpose datasets to investigate the contribution of race and ethnicity to diseases and traits. we propose an analytical framework to enrich the meta-data from publically available cohorts with admixture information and a resulting diversity score at continental resolution, calculated directly from the data. We illustrate the utility and versatility of the framework using The Cancer Genome Atlas datasets indexed and searched through the DataMed Data Discovery Index. Data repositories or data contributors can use this framework to provide, as metadata, admixture for controlled access datasets, minimizing the work involved in requesting a dataset that may ultimately prove inadequate for a researchers purpose. With the increasingly global scale of human genetics research, research on disease risk and susceptibility would benefit greatly from the adequate estimation and sharing of admixture data following a framework such as the one presented.

genetics↗

bioRxiv2017

Molecular genetic diversity of donkey (Equus asinus) in South Korea

The research on domestic donkey has little information and criteria comparing to other livestock, companion animal in South Korea. We analyzed genetic database of domestic donkey using microsatellite marker to clarify domestic donkey identification and paternity test. It is the first microsatellite marker analysis on domestic donkey in South Korea. We studied 179 horse samples from 50 Thoroughbred, 50 Jeju Halla horse, including 79 donkeys then analyzed 15 microsatellite marker (AHT4, AHT5, ASB2, ASB17, ASB23, CA425, HMS1, HMS2, HMS3, HMS6, HMS7, HTG4, HTG10, LEX3 and VHL20). We observed genetic diversity from biostatic analysis of them.\n\nThe number of alleles on total average is 6.08 observed from 1 (ASB17), 2 (HMS1) to 14 (AHT5). The observed heterozygosity (OHet) is from 0.0000 (ASB17, HMS1) to 0.8608 (ASB23) which is mean value of 0.4861, the expected heterozygosity (EHet) is from 0.0000 (CA425) to 0.9104 (AHT5) with mean value of 0.5915, and the Polymorphism Information Content (PIC) on each group of microsatellite marker is from 0.0000 (ASB17) to 0.8968 (AHT5) observed as a mean value of 0.5374. Among 15 markers AHT4, AHT5, ASB23, CA425, HMS2, HMS3, HTG4, HTG10, LEX3 is observed above 5.000.\n\nThe results on 15 microsatellite marker analysis of 3 horse groups is that the donkey had 0.5915 EHet, 0.4861 OHet on average, Thoroughbred had 0.6721 EHet, 0.6587 OHet on average, and the Jeju halla horse had 0.7898 EHet, 0.7093 OHet on average observed. Furthermore the mean alleles value is observed as 6.08, 4.83, 8.00 in donkey, Thoroughbred, Jeju halla horse breed in each.

genetics↗

bioRxiv2017

Heritability Informed Power Optimization (HIPO) Leads to Enhanced Detection of Genetic Associations Across Multiple Traits

Genome-wide association studies have shown that pleiotropy is a common phenomenon that can potentially be exploited for enhanced detection of susceptibility loci. We propose heritability informed power optimization (HIPO) for conducting powerful pleiotropic analysis using summary-level association statistics. We find optimal linear combinations of association coefficients across traits that are expected to maximize non-centrality parameter for the underlying test statistics, taking into account estimates of heritability, sample size variations and overlaps across the traits. Simulation studies show that the proposed method has correct type I error, robust to population stratification and leads to desired genome-wide enrichment of association signals. Application of the proposed method to publicly available data for three groups of genetically related traits, lipids (N=188,577), psychiatric diseases (Ncase=33,332, Ncontrol=27,888) and social science traits (N ranging between 161,460 to 298,420 across individual traits) increased the number of genome-wide significant loci by 12%, 200% and 50%, respectively, compared to those found by analysis of individual traits. Evidence of replication is present for many of these loci in subsequent larger studies for individual traits. HIPO can potentially be extended to high-dimensional phenotypes as a way of dimension reduction to maximize power for subsequent genetic association testing.

genetics↗

bioRxiv2017

Examining the genetic influences of educational attainment and the validity of value-added measures of progress

In this study, we estimate (i) the SNP heritability of educational attainment at three time points throughout the compulsory educational lifecourse; (ii) the SNP heritability of value-added measures of educational progress built from test data; and (iii) the extent to which value-added measures built from teacher rated ability may be biased due to measurement error. We utilise a genome wide approach using generalized restricted maximum likelihood (GCTA-GREML) to determine the total phenotypic variance in educational attainment and value-added measures that is attributable to common genetic variation across the genome within a sample of unrelated individuals from a UK birth cohort, the Avon Longitudinal Study of Parents and Children. Our findings suggest that the heritability of educational attainment measured using point score test data increases with age from 47% at age 11 to 61% at age 16. We also find that genetic variation does not contribute towards value-added measures created only from educational attainment point score data, but it does contribute a small amount to measures that additionally control for background characteristics (up to 20.09% [95%CI: 6.06 to 35.71] from age 11 to 14). Finally, our results show that value-added measures built from teacher rated ability have higher heritability than those built from exam scores. Our findings suggest that the heritability of educational attainment increases through childhood and adolescence. Value-added measures based upon fine grain point scores may be less prone to between-individual genomic differences than measures that control for students backgrounds, or those built from more subjective measures such as teacher rated ability.

genetics↗

bioRxiv2017

The Anorexia Nervosa Genetics Initiative: Overview and Methods

BackgroundGenetic factors contribute to anorexia nervosa (AN); and the first genome-wide significant locus has been identified. We describe methods and procedures for the Anorexia Nervosa Genetics Initiative (ANGI), an international collaboration designed to rapidly recruit 13000 individuals with AN as well as ancestrally matched controls. We present sample characteristics and the utility of an online eating disorder diagnostic questionnaire suitable for large-scale genetic and population research.\n\nMethodsANGI recruited from the United States (US), Australia/New Zealand (ANZ), Sweden (SE), and Denmark (DK). Recruitment was via national registers (SE, DK); treatment centers (US, ANZ, SE, DK); and social and traditional media (US, ANZ, SE). All cases had a lifetime AN diagnosis based on DSM-IV or ICD-10 criteria (excluding amenorrhea). Recruited controls had no lifetime history of disordered eating behaviors. To assess the positive and negative predictive validity of the online eating disorder questionnaire (ED100K-v1), 109 women also completed the Structured Clinical Interview for DSM-IV (SCID), Module H.\n\nResultsBlood samples and clinical information were collected from 13,364 individuals with lifetime AN and from controls. Online diagnostic phenotyping was effective and efficient; the validity of the questionnaire was acceptable.\n\nConclusionsOur multipronged recruitment approach was highly effective for rapid recruitment and can be used as a model for efforts by other groups. High online presence of individuals with AN rendered the Internet/social media a remarkably effective recruitment tool in some countries. ANGI has substantially augmented Psychiatric Genomics Consortium AN sample collection. ANGI is a registered clinical trial: clinicaltrials.gov NCT01916538; https://clinicaltrials.gov/ct2/show/NCT01916538?cond=Anorexia+Nervosa&draw=1&rank=3.

genetics↗

bioRxiv2018

Genome-wide association analysis of lifetime cannabis use (N=184,765) identifies new risk loci, genetic overlap with mental health, and a causal influence of schizophrenia on cannabis use

Cannabis use is a heritable trait [1] that has been associated with adverse mental health outcomes. To identify risk variants and improve our knowledge of the genetic etiology of cannabis use, we performed the largest genome-wide association study (GWAS) meta-analysis for lifetime cannabis use (N=184,765) to date. We identified 4 independent loci containing genome-wide significant SNP associations. Gene-based tests revealed 29 genome-wide significant genes located in these 4 loci and 8 additional regions. All SNPs combined explained 10% of the variance in lifetime cannabis use. The most significantly associated gene, CADM2, has previously been associated with substance use and risk-taking phenotypes [2-4]. We used S-PrediXcan to explore gene expression levels and found 11 unique eGenes. LD-score regression uncovered genetic correlations with smoking, alcohol use and mental health outcomes, including schizophrenia and bipolar disorder. Mendelian randomisation analysis provided evidence for a causal positive influence of schizophrenia risk on lifetime cannabis use.

genetics↗

bioRxiv2017

Genetic structure and sex-biased gene flow in the history of southern African populations

ObjectivesWe investigated the genetic history of southern African populations with a special focus on their paternal history. We reexamined previous claims that the Y-chromosome haplogroup E1b1b was brought to southern Africa by pastoralists from eastern Africa, and investigated patterns of sex-biased gene flow in southern Africa.\n\nMaterial and MethodsWe analyzed previously published complete mtDNA genome sequences and ~900 kb of NRY sequences from 23 populations from Namibia, Botswana and Zambia, as well as haplogroup frequencies from a large sample of southern African populations and 23 newly genotyped Y-linked STR loci for samples assigned to haplogroup E1b1b.\n\nResultsOur results support an eastern African origin for Y-chromosome haplogroup E1b1b; however, its current distribution in southern Africa is not strongly associated with pastoralism, suggesting a more complex origin for pastoralism in this region. We confirm that the Bantu expansion had a notable genetic impact in southern Africa, and that in this region it was probably a rapid, male-dominated expansion. Furthermore, we find a significant increase in the intensity of sex-biased gene flow from north to south, which may reflect changes in the social dynamics between Khoisan and Bantu groups over time.\n\nConclusionsOur study shows that the population history of southern Africa has been very complex, with different immigrating groups mixing to different degrees with the autochthonous populations. The Bantu expansion led to heavily sex-biased admixture as a result of interactions between Khoisan females and Bantu males, with a geographic gradient which may reflect changes in the social dynamics between Khoisan and Bantu groups over time.

genetics↗

bioRxiv2017

Genetic structure of the grey side-gilled sea slug (Pleurobranchaea maculata) in coastal waters of New Zealand

Pleurobranchaea maculata is a rarely studied species of the Heterobranchia found throughout the south and western Pacific - and recently recorded in Argentina - whose population genetic structure is unknown. Interest in the species was sparked in New Zealand following a series of dog deaths caused by ingestions of slugs containing high levels of the neurotoxin tetrodotoxin. Here we describe the genetic structure and demographic history of P. maculata populations from five principle locations in New Zealand based on extensive analyses of 12 microsatellite loci and the COI and CytB regions of mitochondrial DNA (mtDNA). Microsatellite data showed significant differentiation between northern and southern populations with population structure being associated with previously described regional variations in tetrodotoxin concentrations. However, mtDNA sequence data did not support such structure, revealing a star-shaped haplotype network with estimates of expansion time suggesting a population expansion in the Pleistocene era. Inclusion of publicly available mtDNA sequence from Argentinian sea slugs did not alter the star-shaped network. We interpret our data as indicative of a single founding population that fragmented following geographical changes that brought about the present day north-south divide in New Zealand waters. Lack of evidence of cryptic species supports data indicating that differences in toxicity of individuals among regions are a consequence of differences in diet.

genetics↗

bioRxiv2018

Combining high-throughput micro-CT-RGB phenotyping and genome-wide association study to dissect the genetic architecture of tiller growth in rice

Traditional phenotyping of rice tillers is time consuming and labor intensive and lags behind the rapid development of rice functional genomics. Thus, dynamic phenotyping of rice tiller traits at a high spatial resolution and high-throughput for large-scale rice accessions is urgently needed. In this study, we developed a high-throughput micro-CT-RGB (HCR) imaging system to non-destructively extract 730 traits from 234 rice accessions at 9 time points. We used these traits to predict the grain yield in the early growth stage, and 30% of the grain yield variance was explained by 2 tiller traits in the early growth stage. A total of 402 significantly associated loci were identified by GWAS, and dynamic and static genetic components were found across the nine time points. A major locus associated with tiller angle was detected at nine time points, which contained a major gene TAC1. Significant variants associated with tiller angle were enriched in the 3'-UTR of TAC1. Three haplotypes for the gene were found and tiller angles of rice accessions containing haplotype H3 were much smaller. Further, we found two loci contained associations with both vigor-related HCR traits and yield. The superior alleles would be beneficial for breeding of high yield and dense planting.\n\nHighlightCombining high-throughput micro-CT-RGB phenotyping facility and genome-wide association study to dissect the genetic architecture of rice tiller development by using the indica subpopulation.

genetics↗

bioRxiv2018

Genetic contribution to theory of mind in adolescence

Difficulties in theory of mind (the ability to attribute mental states to oneself or others, and to make predictions about anothers behaviour based on these attributions) have been observed in several psychiatric conditions. We investigate the genetic architecture of theory of mind in 4,577 13-year-olds who completed the Emotional Triangles Task (Triangles Task), a first-order test of theory of mind. We observe a small but significant female-advantage on the Triangles Task (Cohens d = 0.19, P < 0.01), in keeping with previous work using other tests of theory of mind. Genome-wide association analyses did not identify any significant loci, and SNP heritability was small and non-significant. Polygenic scores for six psychiatric conditions (ADHD, anorexia, autism, bipolar disorder, depression, and schizophrenia), and empathy were not associated with scores on the Triangles Task. However, polygenic scores of cognitive aptitude, and cognitive empathy, a term synonymous with theory of mind and measured using the \"Reading the Mind in the Eyes\" Test, were significantly associated with scores on the Triangles Task at multiple P-value thresholds, suggesting shared genetics between different measures of theory of mind and cognition.

genetics↗