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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↗

bioRxiv2018

Genetic basis of transgressive segregation in rice heading phenotypes

Transgressive segregation produces hybrid progeny phenotypes that exceed parental phenotypes. Unlike heterosis, extreme phenotypes caused by transgressive segregation are heritably stable. We examined transgressive phenotypes of flowering time in rice. Our previous study examined days to flowering (heading; DTH) in six F2 populations for which the parents had distal DTH, and found very few transgressive phenotypes. Here, we demonstrate that transgressive segregation in F2 populations occurred between parents with proximal DTH. DTH phenotypes of the A58 x Kitaake F2 progenies frequently exceeded those of both parents. Both A58 and Kitaake are japonica rice cultivars adapted to Hokkaido, Japan, which is a high-latitude region, and have short DTH. Among the four known loci required for short DTH, three loci had common alleles in A58 and Kitaake, and only the one locus had different alleles. This result indicates that there is a similar genetic basis for DTH between the two varieties. We identified five new quantitative trait loci (QTLs) associated with transgressive DTH phenotypes by genome-wide single nucleotide polymorphism (SNP) analysis. Each of these QTLs showed different degrees of additive effects on DTH, and two QTLs had epistatic effect on each other. These results demonstrated that genome-wide SNP analysis facilitated detection of genetic loci associated with the extreme phenotypes and revealed that the transgressive phenotypes were produced by exchanging complementary alleles of a few minor QTLs in the similar parental genotypes.

genetics↗

bioRxiv2018

Genetic variants associated with Alzheimer's disease confer different cerebral cortex cell-type population structure

Alzheimers disease (AD) is characterized by neuronal loss and astrocytosis in the cerebral cortex. However, the effects of brain cellular composition are often ignored in high-throughput molecular studies. We developed and optimized a cell-type specific expression reference panel and employed digital deconvolution methods to determine brain cellular distribution in three independent transcriptomic studies. We found that neuronal and astrocyte proportions differ between healthy and diseased brains and also among AD cases that carry specific genetic risk variants. Brain carriers of pathogenic mutations in APP, PSEN1 or PSEN2 presented lower neurons and higher astrocytes proportions compared to sporadic AD. Similarly, the APOE {varepsilon}4 allele also showed decreased neurons and increased astrocytes compared to AD non-carriers. On the contrary, carriers of variants in TREM2 risk showed a lower degree of neuronal loss than matched AD cases in multiple independent studies. These findings suggest that genetic risk factors associated with AD etiology have a specific imprinting in the cellular composition of AD brains. Our digital deconvolution reference panel provides an enhanced understanding of the fundamental molecular mechanisms underlying neurodegeneration, enabling the analysis of large bulk RNA-seq studies for cell composition, and suggests that correcting for the cellular structure when performing transcriptomic analysis will lead to novel insights of AD.

genetics↗

bioRxiv2018

A Genetic Program Mediates Cold-warming Response and Promotes Stress-induced Phenoptosis in C. elegans

How multicellular organisms respond to and are impacted by severe hypothermic stress is largely unknown. From C. elegans screens for mutants abnormally responding to cold-warming stimuli, we identify a molecular genetic pathway comprising ISY-1, a conserved uncharacterized protein, and ZIP-10, a bZIP-type transcription factor. ISY-1 gatekeeps the ZIP-10 transcriptional program by regulating the microRNA mir-60. Downstream of ISY-1 and mir-60, zip-10 levels rapidly and specifically increase upon transient cold-warming response. Prolonged zip-10 up-regulation induces several protease-encoding genes and promotes stress-induced organismic death, or phenoptosis, of C. elegans. zip-10 deficiency confers enhanced resistance to prolonged cold-warming stress, more prominently in adults than larvae. We conclude that the ZIP-10 genetic program mediates cold-warming response and may have evolved to promote wild population kin selection under resource-limiting and thermal stress conditions.

genetics↗

bioRxiv2018

Subset-based genomic prediction provides insights into the genetic architecture of free amino acid levels in dry Arabidopsis thaliana seeds

Plant growth, development, and nutritional quality depends upon amino acid homeostasis, especially in seeds. However, our understanding of the underlying genetics influencing amino acid content and composition remains limited, with only a few candidate genes and quantitative trait loci identified to date. Improved knowledge of the genetics and biological processes that determine amino acid levels will enable researchers to use this information for plant breeding and biological discovery. Towards this goal, we used genomic prediction to identify biological processes that are associated with, and therefore potentially influence, free amino acid (FAA) composition in seeds of the model plant Arabidopsis thaliana. Markers were split into categories based on metabolic pathway annotations and fit using a genomic partitioning model to evaluate the influence of each pathway on heritability explained, model fit, and predictive ability. Selected pathways included processes known to influence FAA composition, albeit to an unknown degree, and spanned four categories: amino acid, core, specialized, and protein metabolism. Using this approach, we identified associations for pathways containing known variants for FAA traits, in addition to finding new trait-pathway associations. Markers related to amino acid metabolism, which are directly involved in the FAA regulation, improved predictive ability for branched chain amino acids and histidine. The use of genomic partitioning also revealed patterns across biochemical families, in which serine-derived FAAs were associated with protein related annotations and aromatic FAAs were associated with specialized metabolic pathways. Taken together, these findings provide evidence that genomic partitioning is a viable strategy to uncover the relative contributions of biological processes to FAA traits in seeds, offering a promising framework to guide hypothesis testing and narrow the search space for candidate genes.

genetics↗

bioRxiv2018

GWAS in 446,118 European adults identifies 78 genetic loci for self-reported habitual sleep duration supported by accelerometer-derived estimates

Sleep is an essential homeostatically-regulated state of decreased activity and alertness conserved across animal species, and both short and long sleep duration associate with chronic disease and all-cause mortality1,2. Defining genetic contributions to sleep duration could point to regulatory mechanisms and clarify causal disease relationships. Through genome-wide association analyses in 446,118 participants of European ancestry from the UK Biobank, we discover 78 loci for self-reported sleep duration that further impact accelerometer-derived measures of sleep duration, daytime inactivity duration, sleep efficiency and number of sleep bouts in a subgroup (n=85,499) with up to 7-day accelerometry. Associations are enriched for genes expressed in several brain regions, and for pathways including striatum and subpallium development, mechanosensory response, dopamine binding, synaptic neurotransmission, catecholamine production, synaptic plasticity, and unsaturated fatty acid metabolism. Genetic correlation analysis indicates shared biological links between sleep duration and psychiatric, cognitive, anthropometric and metabolic traits and Mendelian randomization highlights a causal link of longer sleep with schizophrenia.

genetics↗

bioRxiv2018

Novel susceptibility loci and genetic regulation mechanisms for type 2 diabetes

We conducted a meta-analysis of genome-wide association studies (GWAS) with [~]16 million genotyped/imputed genetic variants in 62,892 type 2 diabetes (T2D) cases and 596,424 controls of European ancestry. We identified 139 common and 4 rare (minor allele frequency < 0.01) variants associated with T2D, 42 of which (39 common and 3 rare variants) were independent of the known variants. Integration of the gene expression data from blood (n = 14,115 and 2,765) and other T2D-relevant tissues (n = up to 385) with the GWAS results identified 33 putative functional genes for T2D, three of which were targeted by approved drugs. A further integration of DNA methylation (n = 1,980) and epigenomic annotations data highlighted three putative T2D genes (CAMK1D, TP53INP1 and ATP5G1) with plausible regulatory mechanisms whereby a genetic variant exerts an effect on T2D through epigenetic regulation of gene expression. We further found evidence that the T2D-associated loci have been under purifying selection.

genetics↗

bioRxiv2018

Better estimation of SNP heritability from summary statistics provides a new understanding of the genetic architecture of complex traits

LD Score Regression (LDSC) has been widely applied to the results of genome-wide association studies. However, its estimates of SNP heritability are derived from an unrealistic model in which each SNP is expected to contribute equal heritability. As a consequence, LDSC tends to over-estimate confounding bias, under-estimate the total phenotypic variation explained by SNPs, and provide misleading estimates of the heritability enrichment of SNP categories. Therefore, we present SumHer, software for estimating SNP heritability from summary statistics using more realistic heritability models. After demonstrating its superiority over LDSC, we apply SumHer to the results of 24 large-scale association studies (average sample size 121 000). First we show that these studies have tended to substantially over-correct for confounding, and as a result the number of genome-wide significant loci has under-reported by about 20%. Next we estimate enrichment for 24 categories of SNPs defined by functional annotations. A previous study using LDSC reported that conserved regions were 13-fold enriched, and found a further twelve categories with above 2-fold enrichment. By contrast, our analysis using SumHer finds that conserved regions are only 1.6-fold (SD 0.06) enriched, and that no category has enrichment above 1.7-fold. SumHer provides an improved understanding of the genetic architecture of complex traits, which enables more efficient analysis of future genetic data.

genetics↗