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Cross-platform genetic discovery of small molecule products of metabolism and application to clinical outcomes

Circulating levels of small molecules or metabolites are highly heritable, but the impact of genetic differences in metabolism on human health is not well understood. In this cross-platform, genome-wide meta-analysis of 174 metabolite levels across six cohorts including up to 86,507 participants (70% unpublished data), we identify 499 (362 novel) genome-wide significant associations (p<4.9×10-10) at 144 (94 novel) genomic regions. We show that inheritance of blood metabolite levels in the general population is characterized by pleiotropy, allelic heterogeneity, rare and common variants with large effects, non-linear associations, and enrichment for nonsynonymous variation in transporter and enzyme encoding genes. The majority of identified genes are known to be involved in biochemical processes regulating metabolite levels and to cause monogenic inborn errors of metabolism linked to specific metabolites, such as ASNS (rs17345286, MAF=0.27) and asparagine levels. We illustrate the influence of metabolite-associated variants on human health including a shared signal at GLP2R (p.Asp470Asn) associated with higher citrulline levels, body mass index, fasting glucose-dependent insulinotropic peptide and type 2 diabetes risk, and demonstrate beta-arrestin signalling as the underlying mechanism in cellular models. We link genetically-higher serine levels to a 95% reduction in the likelihood of developing macular telangiectasia type 2 [odds ratio (95% confidence interval) per standard deviation higher levels 0.05 (0.03-0.08; p=9.5×10-30)]. We further demonstrate the predictive value of genetic variants identified for serine or glycine levels for this rare and difficult to diagnose degenerative retinal disease [area under the receiver operating characteristic curve: 0.73 (95% confidence interval: 0.70-0.75)], for which low serine availability, through generation of deoxysphingolipids, has recently been shown to be causally relevant. These results show that integration of human genomic variation with circulating small molecule data obtained across different measurement platforms enables efficient discovery of genetic regulators of human metabolism and translation into clinical insights.Competing Interest StatementA.S.B. has received grants from AstraZeneca, Biogen, Bioverativ, Merck, Novartis, and Sanofi. J. D. sits on the International Cardiovascular and Metabolic Advisory Board for Novartis (since 2010), the Steering Committee of UK Biobank (since 2011), the MRC International Advisory Group (ING) member, London (since 2013), the MRC High Throughput Science Omics Panel Member, London (since 2013), the Scientific Advisory Committee for Sanofi (since 2013), the International Cardiovascular and Metabolism Research and Development Portfolio Committee for Novartis and the Astra Zeneca Genomics Advisory Board (2018). E.B.F. is an employee and stock holder of Pfizer.View Full Text

genetics↗

Genetic Disruption of Serine Biosynthesis is a Key Driver of Macular Telangiectasia Type 2 Etiology and Progression

PurposeMacular telangiectasia type 2 (MacTel) is a rare, heritable and largely untreatable retinal disorder, often comorbid with diabetes. Genetic risk loci subtend retinal vascular calibre, and glycine/serine/threonine metabolism genes. Serine deficiency may contribute to MacTel via neurotoxic deoxysphingolipid production, however, an independent vascular contribution is also suspected. Here we use statistical genetics to dissect the causal mechanisms underpinning this complex disease. O_TBL View this table: org.highwire.dtl.DTLVardef@1c529f3org.highwire.dtl.DTLVardef@1451baforg.highwire.dtl.DTLVardef@1ca0a9org.highwire.dtl.DTLVardef@177efb9org.highwire.dtl.DTLVardef@11b67bf_HPS_FORMAT_FIGEXP M_TBL O_TABLECAPTIONSupplementary Table 8: C_TABLECAPTION C_TBL MethodsWe integrated genetic markers for MacTel, vascular, and metabolic traits, and applied Mendelian randomization, MTAG, and conditional/interaction genome-wide association analysis to discover causal contributors to both disease, and spatial retinal imaging sub-phenotypes. ResultsSerine was a key causal driver of disease occurrence and progression, with a lesser contribution to type 2 diabetes risk. Conversely, glycine, threonine and retinal vascular traits are unlikely to be causal for MacTel. Conditional regression analysis resolved three novel disease loci independent of endogenous serine biosynthetic capacity. By aggregating retinal phenotypes into endophenotypes, we demonstrate that SNPs constituting independent risk loci act via related endophenotypes. DiscussionOur findings will aid in early diagnosis and accurate prognosis of MacTel, and improve prospects for effective therapeutic intervention. Our integrative genetics approach also serves as a useful template for post-GWAS analyses in other disorders.

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Dissecting the role of Amerindian genetic ancestry and ApoE ε4 allele on Alzheimer disease in an admixed Peruvian population

Alzheimer disease (AD) is the leading cause of dementia in the elderly and occurs in all ethnic and racial groups. ApoE {varepsilon}4 is the most significant genetic risk factor for late-onset AD and shows the strongest effect among East Asian populations followed by non-Hispanic White populations and has a relatively lower effect in African descent populations. Admixture analysis in the African American and Puerto Rican populations showed that the variation in{varepsilon} 4 risk is correlated with the genetic ancestral background local to the ApoE gene. Native American populations are substantially underrepresented in AD genetic studies. The Peruvian population with up to [~]80 of Amerindian ancestry provides a unique opportunity to assess the role of Amerindian ancestry in Alzheimer disease. In this study we assess the effect of the ApoE {varepsilon}4 allele on AD in the Peruvian population. A total of 78 AD cases and 128 unrelated cognitive healthy controls were included in the study. Genome-wide genotyping was performed using the Illumina Global screening array. Global ancestry and local ancestry analyses were assessed. The effect of the ApoE {varepsilon}4 allele on Alzheimer disease was tested using a logistic regression model by adjusting for age, gender, and population substructure (first three principal components). Logistic regression results showed that ApoE {varepsilon}4 allele is significantly associated with AD in Peruvian population with the high-risk effect (OR = 5.02, CI: 2.3-12.5, p-value = 2e-4). The average values of the local ancestries surrounding the ApoE gene (chr19:44Mb-46Mb) have the highest proportion of Amerindian (60.6%), followed by European (33.9%) and African (5.5%) ancestral backgrounds. Our results showed that the risk for AD from ApoE {varepsilon}4 in Peruvians is higher than we have observed in non-Hispanic White populations. Given the high admixture of Amerindian ancestry in the Peruvian population, it suggests that the Amerindian local ancestry is contributing to a strong risk for AD in ApoE {varepsilon}4 carriers. Our data also support the findings of an interaction between the genetic risk allele ApoE {varepsilon}4 and the ancestral backgrounds located around the genomic region of ApoE gene.

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Identification of 38 novel loci for systemic lupus erythematosus and genetic heterogeneity that may underly population disparities in this disease

Systemic lupus erythematosus (SLE), a worldwide autoimmune disease with high heritability, shows differences in prevalence, severity and age of onset among different ancestral groups. Previous genetic studies have focused more on European populations, which appear to be the least affected. Consequently, the genetic variations that underly the commonalities, differences and treatment options in SLE among ancestral groups have not been well elucidated. To address this, we undertook a genome-wide association study, increasing the sample size of Chinese populations to the level of existing European studies. Thirty-eight novel SLE-associated loci and incomplete sharing of genetic architecture were identified. Nine disease loci showed clear ancestral group heterogeneity and implicated antibody production as a potential mechanism for differences in disease manifestation. Polygenic risk scores performed significantly better when trained on matched ancestral data sets. These analyses help to reveal the genetic bases for disparities in SLE among ancestral groups.

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Sleep Deficits and Cannabis Use Behaviors: An Analysis of Shared Genetics Using Linkage Disequilibrium Score Regression and Polygenic Risk Prediction

Study ObjectivesEstimate the genetic relationship of cannabis use with sleep deficits and eveningness chronotype. MethodsWe used linkage disequilibrium score regression (LDSC) to analyze genetic correlations between sleep deficits and cannabis use behaviors. Secondly, we generated sleep deficit polygenic risk scores (PRSs) and estimated their ability to predict cannabis use behaviors using logistic regression. Summary statistics came from existing genome wide association studies (GWASs) of European ancestry that were focused on sleep duration, insomnia, chronotype, lifetime cannabis use, and cannabis use disorder (CUD). A target sample for PRS prediction consisted of high-risk participants and participants from twin/family community-based studies (n = 796, male = 66%; mean age = 26.81). Target data consisted of self-reported sleep (sleep duration, feeling tired, and taking naps) and cannabis use behaviors (lifetime use, number of lifetime uses, past 180-day use, age of first use, and lifetime CUD symptoms). ResultsSignificant genetic correlation between lifetime cannabis use and eveningness chronotype (rG = 0.24, p < 0.01), as well as between CUD and both short sleep duration (<7 h) (rG = 0.23, p = 0.02) and insomnia (rG = 0.20, p = 0.02). Insomnia PRS predicted earlier age of first cannabis use ({beta} = -0.09, p = 0.02) and increased lifetime CUD symptom count use ({beta} = 0.07, p = 0.03). ConclusionCannabis use is genetically associated with both sleep deficits and an eveningness chronotype, suggesting that there are genes that predispose individuals to both cannabis use and sleep deficits.

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Genoppi: an open-source software for robust and standardized integration of proteomic and genetic data

Combining genetic and cell-type-specific proteomic datasets can lead to new biological insights and therapeutic hypotheses, but a technical and statistical framework for such analyses is lacking. Here, we present an open-source computational tool called Genoppi that enables robust, standardized, and intuitive integration of quantitative proteomic results with genetic data. We used Genoppi to analyze sixteen cell-type-specific protein interaction datasets of four proteins (TDP-43, MDM2, PTEN, and BCL2) involved in cancer and neurological disease. Through systematic quality control of the data and integration with published protein interactions, we show a general pattern of both cell-type-independent and cell-type-specific interactions across three cancer and one human iPSC-derived neuronal type. Furthermore, through the integration of proteomic and genetic datasets in Genoppi, our results suggest that the neuron-specific interactions of these proteins are mediating their genetic involvement in neurodevelopmental and neurodegenerative diseases. Importantly, our analyses indicate that human iPSC-derived neurons are a relevant model system for studying the involvement of TDP-43 and BCL2 in amyotrophic lateral sclerosis.

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Genetic and environmental determinants of variation in the plasma lipidome of older Australian twins

The critical role of blood lipids in a broad range of health and disease states is well recognised, while an understanding of the complex genetic regulation of lipid homeostasis is emerging. Traditional blood lipids (LDL-C, HDL-C and triglycerides) are known to be substantially regulated by genetic variation. Less well explored is the interplay of genetics and environment within the broader blood lipidome. Here we use the twin model to examine heritability of the plasma lipidome among healthy older aged twins and explore gene expression and epigenetic (DNA methylation) associations of these lipids. Heritability of 209 plasma lipids quantified by liquid chromatography coupled mass spectrometry (LC-MS) was assessed in 75 monozygotic and 55 dizygotic twin pairs enrolled in the Older Australian Twins Study (OATS), aged 69-93 years. Only 27/209 lipids (13.3%) were significantly heritable under the classical ACE twin model (h2 = 0.28-0.59). Ceramides (Cer) and triglycerides (TG) were most heritable, while sphingomyelins (SM) and most phospholipids, especially lysophospholipids, were not significantly heritable. Lipid levels correlated with 3731 transcripts. Relative to non-significantly heritable TGs, heritable TGs had a greater number of associations with gene transcripts, which were not directly associated with lipid metabolism, but with immune function, signalling and transcriptional regulation. Genome-wide average DNA methylation (GWAM) levels accounted for a proportion of variability in some non-heritable lipids, especially lysophosphatidylcholine (LPC). We found a complex interplay of genetic and environmental influences on the ageing plasma lipidome, with most of the variation controlled by unique environmental influences.

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Disentangling selection on genetically correlated polygenic traits using whole-genome genealogies

We present a full-likelihood method to estimate and quantify polygenic adaptation from contemporary DNA sequence data. The method combines population genetic DNA sequence data and GWAS summary statistics from up to thousands of nucleotide sites in a joint likelihood function to estimate the strength of transient directional selection acting on a polygenic trait. Through population genetic simulations of polygenic trait architectures and GWAS, we show that the method substantially improves power over current methods. We examine the robustness of the method under uncorrected GWAS stratification, uncertainty and ascertainment bias in the GWAS estimates of SNP effects, uncertainty in the identification of causal SNPs, allelic heterogeneity, negative selection, and low GWAS sample size. The method can quantify selection acting on correlated traits, fully controlling for pleiotropy even among traits with strong genetic correlation (|rg| = 80%; c.f. schizophrenia and bipolar disorder) while retaining high power to attribute selection to the causal trait. We apply the method to study 56 human polygenic traits for signs of recent adaptation. We find signals of directional selection on pigmentation (tanning, sunburn, hair, P=5.5e-15, 1.1e-11, 2.2e-6, respectively), life history traits (age at first birth, EduYears, P=2.5e-4, 2.6e-4, respectively), glycated hemoglobin (HbA1c, P=1.2e-3), bone mineral density (P=1.1e-3), and neuroticism (P=5.5e-3). We also conduct joint testing of 137 pairs of genetically correlated traits. We find evidence of widespread correlated response acting on these traits (2.6-fold enrichment over the null expectation, P=1.5e-7). We find that for several traits previously reported as adaptive, such as educational attainment and hair color, a significant proportion of the signal of selection on these traits can be attributed to correlated response, vs direct selection (P=2.9e-6, 1.7e-4, respectively). Lastly, our joint test uncovers antagonistic selection that has acted to increase type 2 diabetes (T2D) risk and decrease HbA1c (P=1.5e-5).

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SLE non-coding Genetic Risk Variant Determines the Epigenetic Dysfunction of an Immune Cell Specific Enhancer that Controls Disease-critical microRNA Expression

The human genome contains millions of putative regulatory elements, which regulate gene expression. We are just beginning to understand the functional consequences of genetic variation within these regulatory elements. Since the bulk of common genetic variation impacting polygenic disease phenotypes localizes to these non-coding regions of the genome, understanding the consequences will improve our understanding of the mechanisms mediating genetic risk in human disease. Here, we define the systemic lupus erythematosus (SLE) risk variant rs2431369 as likely causal for SLE and show that it is located in a functional regulatory element that modulates miR-146a expression. We use epigenomic analysis and genome-editing to show that the rs2431697-containing region is a distal enhancer that specifically regulates miR-146a expression in a cell-type dependent manner. 3D chromatin structure analysis demonstrates physical interaction between the rs2431697-containing region and the miR-146a promoter. Further, our data show that NF-kB binds the disease protective allele in a sequence-specific manner, leading to increased expression of this immunoregulatory microRNA. Our work provides a strategy for using disease-associated variants to define the functional regulatory elements of non-coding RNA molecules such as miR-146a and provides mechanistic links between autoimmune disease risk genetic variation and disease etiology.

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Natural Genetic Variation in Drosophila melanogaster Reveals Genes Associated with Coxiella burnetii Infection

The gram-negative bacterium Coxiella burnetii is the causative agent of Query (Q) fever in humans and coxiellosis in livestock. Association between host genetic background and Coxiella burnetii pathogenesis has been demonstrated both in humans and animals; however, specific genes associated with severity of infection remain unknown. We employed the Drosophila Genetics Reference Panel to perform a genome-wide association study and identify host genetic variants that affect Coxiella burnetii infection outcome. The analysis resulted in 64 genome-wide suggestive (P < 10-5) single nucleotide polymorphisms or gene variants in 25 unique genes. We examined the role of each gene in Coxiella burnetii infection using flies carrying a null mutation or RNAi knockdown of each gene and monitoring survival. Of the 25 candidate genes, 15 validated using at least one method. For many, this is the first report establishing involvement of these genes or their homologs with Coxiella burnetii susceptibility in any system. Among the validated genes, FER and tara play roles in the JAK-STAT, JNK, and decapentaplegic/TGF-{beta} signaling pathways that are associated with the innate immune response to Coxiella burnetii infection. Two other two validated genes, CG42673 and DIP-{varepsilon}, play roles in bacterial infection and synaptic signaling but no previous association with Coxiella burnetii pathogenesis. Furthermore, since the mammalian ortholog of CG13404 (PLGRKT) is an important regulator of macrophage function, CG13404 could play a role in Coxiella burnetii susceptibility through hemocyte regulation. These insights provide a foundation for further investigation of genetics of Coxiella burnetii susceptibility across a wide variety of hosts.

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Disentangling principled and opportunistic motives for reacting to injustice: A genetically-informed exploration of justice sensitivity

Moral judgments may be driven by both principled and opportunistic motivations. Being morally principled is to consistently adhere to a single set of rules about morality and justice. Opportunistic morality rather involves selectively enforcing rules when they are beneficial to ones interests. These two kinds of motivations sometimes pull in the same direction, other times not. Prior studies on moral motivations have mostly focused on principled morality. Opportunistic morality, along with its phenotypic and genetic correlates, remains largely unexamined. Here, utilizing a sample from the Norwegian Twin Registry, consisting of 312 monozygotic-and 298 dizygotic twin pairs (N = 1220), we measure peoples propensity to react to injustice as victims, observers, beneficiaries, and perpetrators of injustice, using the Justice Sensitivity scale. Our genetically informative sample allows a biometric modeling approach that provides increased stringency in inferring latent psychological traits. We find evidence for two substantially heritable traits explaining correlations between Justice Sensitivity facets, which we interpret as a principled justice sensitivity (h2 = .45) leading to increased sensitivity to injustices of all categories, and an opportunistic justice sensitivity (h2 = .69) associated with increased victim sensitivity and a decreased propensity to feel guilt from being a perpetrator. These heritable justice traits share a genetic substrate with broad strategies for cooperation (as measured by altruism and trust) and for selectively benefitting oneself over the adaptive interests of others (as measured by social dominance orientation and support for monopolizing territory and resources), and differ genetically and phenotypically from Big Five personality traits.

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Genetic Variation Regulates Opioid-Induced Respiratory Depression in Mice

In the U.S., opioid prescription for treatment of pain nearly quadrupled from 1999 to 2014, leading to an epidemic in addiction and overdose deaths. The most common cause of opioid overdose and death is opioid-induced respiratory depression (OIRD), a life-threatening depression in respiratory rate thought to be caused by stimulation of opioid receptors in the inspiratory-generating regions of the brain. Studies in mice have revealed that variation in opiate lethality is associated with strain differences, suggesting that sensitivity to OIRD is genetically determined. We first tested the hypothesis that genetic variation in inbred strains of mice influences the innate variability in opioid-induced responses in respiratory depression, recovery time and survival time. Using the founders of the advanced, high-diversity mouse populations, the Collaborative Cross (CC) and Diversity Outbred (DO), we found substantial sex and genetic effects on respiratory sensitivity and opiate lethality. To define genetic modifiers of OIRD, we then used the high precision DO population treated with morphine to map and identify quantitative trait loci (QTL) for respiratory depression, recovery time and survival time. Trait mapping and integrative functional genomic analysis in GeneWeaver has allowed us to implicate Galnt11, an N-acetylgalactosaminyltransferase, as a candidate gene that regulates OIRD.

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Genome-wide association study of flowering time reveals complex genetic heterogeneity and epistatic interactions in rice

Since domestication, rice has cultivated in a wide range of latitudes with different day lengths. Selection of diverse natural variations in heading date and photoperiod sensitivity is critical for adaptation of rice to different geographical environments. To unravel the genetic architecture underlying natural variation of rice flowering time, we conducted a genome wide association study (GWAS) using several association analysis strategies with a diverse worldwide collection of 529 O. sativa accessions. Heading date was investigated in three environments under long-day or short-day conditions, and photosensitivity was evaluated. By dividing the whole association panel into subpopulations and performing GWAS with both linear mixed models and multi-locus mixed-models, we revealed hundreds of significant loci harboring novel candidate genes as well as most of the known flowering time genes. In total, 127 hotspots were detected in at least two GWAS. Universal genetic heterogeneity was found across subpopulations. We further detected abundant interactions between GWAS loci, especially in indica. Functional gene families were revealed from enrichment analysis of the 127 hotspots. The results demonstrated a rich of genetic interactions in rice flowering time genes and such epistatic interactions contributed to the large portions of missing heritability in GWAS. It suggests the increased complexity of genetic heterogeneity might discount the power of increasing the sample sizes in GWAS.

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Systems genetic analysis of binge-like eating in a C57BL/6J x DBA/2J-F2 cross

ObjectiveBinge eating is a heritable quantitative trait associated with eating disorders (ED) and refers to the rapid consumption of a large quantity of energy-dense food that is associated with loss of control, anxiety, and depression. Binge Eating Disorder is the most common ED in adults in the US; however, the genetic basis is unknown. We previously identified robust mouse inbred strain differences between C57BL/6J and DBA/2J in binge-like eating (BLE) of sweetened palatable food (PF) in an intermittent access, conditioned place preference paradigm. MethodsTo map the genetic basis of BLE, we phenotyped and genotyped 128 C57BL/6J x DBA/2J-F2 mice. ResultsWe identified a quantitative trait locus (QTL) on chromosome 13 influencing progressive changes in body weight across training days (LOD = 5.5; 26-39 cM). We also identified two sex-combined QTLs influencing PF intake on chromosome 5 (LOD = 5.6; 1.5-LOD interval = 21-28 cM) and 6 (LOD = 5.3; 1.5-LOD interval = 50-59 cM). Furthermore, sex-specific analyses revealed that the chromosome 6 locus was driven by males (1.5-LOD interval: 52-59 cM) and identified a female-selective QTL for BLE on chromosome 18 (LOD = 4.1; 1.5-LOD interval: 23-35 cM). Systems genetic analysis of the chromosome 6 locus for BLE using GeneNetwork legacy trait datasets from BXD recombinant inbred strains identified Adipor2 and Plxnd1 as two positional, functional, biological candidate genes. DiscussionWe identified genetic loci influencing BLE. Future studies will phenotype BXD recombinant inbred strains to fine map loci and support candidate gene nomination and validation.

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The genetic paradigms of dietary restriction fail to extend life span in cep-1(gk138) mutant of C. elegans p53 due to possible background mutations

Dietary restriction (DR) increases life span and improves health in most model systems tested, including non-human primates. In C. elegans, as in other models, DR leads to reprogramming of metabolism, improvements in mitochondrial health, large changes in gene expression, including increase in expression of cytoprotective genes, better proteostasis etc. Understandably, multiple global transcriptional regulators like transcription factors FOXO/DAF-16, FOXA/PHA-4, HSF1/HSF-1 and NRF2/SKN-1 are important for DR longevity. Considering the wide-ranging effects of p53 on organismal biology, we asked whether the C. elegans ortholog, CEP-1 is required for DR-mediated longevity assurance. We employed the widely-used TJ1 strain of cep-1(gk138). We show that cep-1(gk138) suppresses the life span extension of two genetic paradigms of DR, but two non-genetic modes of DR remain unaffected in this strain. We find that in cep-1(gk138), two aspects of DR, increased autophagy and the up-regulation of expression of cytoprotective xenobiotic detoxification program (cXDP) genes are dampened. Importantly, we find that background mutation(s) in the strain may be the actual cause for the phenotypic differences that we observed and cep-1 may not be directly involved in genetic DR-mediated longevity assurance in worms. Identifying these mutation(s) may reveal a novel regulator of longevity required specifically by genetic modes of DR.

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Early Medieval Genetic Data from Ural Region Evaluated in the Light of Archaeological Evidence of Ancient Hungarians

The ancient Hungarians originated from the Ural region of Russia, and migrated through the Middle-Volga region and the Eastern European steppe into the Carpathian Basin during the 9th century AD. Their Homeland was probably in the southern Trans-Ural region, where the Kushnarenkovo culture disseminated. In the Cis-Ural region Lomovatovo and Nevolino cultures are archaeologically related to ancient Hungarians. In this study we describe maternal and paternal lineages of 36 individuals from these regions and nine Hungarian Conquest period individuals from todays Hungary, as well as shallow shotgun genome data from the Trans-Uralic Uyelgi cemetery. We point out the genetic continuity between the three chronological horizons of Uyelgi cemetery, which was a burial place of a rather endogamous population. Using phylogenetic and population genetic analyses we demonstrate the genetic connection between Trans-, Cis-Ural and the Carpathian Basin on various levels. The analyses of this new Uralic dataset fill a gap of population genetic research of Eurasia, and reshape the conclusions previously drawn from 10-11th century ancient mitogenomes and Y-chromosomes from Hungary.

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Genetic signatures of human brain structure: A comparison between GWAS and relatedness-based regression

Identifying the genetic variations impacting human brain structure and their further effects on cognitive functions, is important for our understanding of the fundamental bases of cognition. In this study, we take two different approaches to this issue: classical genome-wide association analysis (GWAS) and a relatedness-based regression approach (REL) to search for associations between genotype and brain structural measures of gray matter and white matter. Instead of searching genetic variants by testing the association between a phenotype trait and the genotype of each single-nucleotide polymorphism (SNP) as in GWAS, REL takes advantage of multiple SNPs within a genomic window as a single measure, which potentially find associations wherever the functional SNP is in linkage disequilibrium (LD) with SNPs that have been sampled. We also conducted a simulation analysis to systemically compare GWAS and REL with respect to different levels of LD. Both methods succeed in identifying genetic variations associated with regional and global brain structural measures and tend to give complementary results due to the different aspects of genetic properties used. Simulation results suggest that GWAS outperforms REL when the signal is relatively weak. However, the collective effects due to local LD boost the performance of REL with increasing signal strength, resulting in better performance than GWAS. Our study suggests that the optimal approach may vary across the genome and that pre-testing for LD could allow GWAS to be preferred where LD is high and REL to be used where LD is low, or the local pattern of LD is complex.

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Extensive Genetic Diversity and Host Range of Rodent-borne Coronaviruses

To better understand the genetic diversity, host association and evolution of coronaviruses (CoVs) in China we analyzed a total of 696 rodents encompassing 16 different species sampled from Zhejiang and Yunnan provinces. Based on the reverse transcriptase PCR-based CoV screening CoVs of fecal samples and subsequent sequence analysis of the RdRp gene, we identified CoVs in diverse rodent species, comprising Apodemus agrarius, Apodemus latronum, Bandicota indica, Eothenomys miletus, E. eleusis, Rattus andamanesis, Rattus norvegicus, and R. tanezumi. Apodemus chevrieri was a particularly rich host, harboring 25 rodent CoVs. Genetic and phylogenetic analysis revealed the presence of three groups of CoVs carried by a range of rodents that were closely related to the Lucheng Rn rat coronavirus (LRNV), China Rattus coronavirus HKU24 (ChRCoV_HKU24) and Longquan Rl rat coronavirus (LRLV) identified previously. One newly identified A. chevrieri-associated virus closely related to LRNV lacked an NS2 gene. This virus had a similar genetic organization to AcCoV-JC34, recently discovered in the same rodent species in Yunnan, suggesting that it represents a new viral subtype. Notably, additional variants of LRNV were identified that contained putative nonstructural NS2b genes located downstream of the NS2 gene that were likely derived from the host genome. Recombination events were also identified in the ORF1a gene of Lijiang-71. In sum, these data reveal the substantial genetic diversity and genomic complexity of rodent-borne CoVs, and greatly extend our knowledge of these major wildlife virus reservoirs.

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