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Genetic testing of dogs predicts problem behaviors in clinical and nonclinical samples

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Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.08.13.249805v1?rss=1 Authors: Zapata, I., Lilly, M. L., Herron, M. E., Alvarez, C. E. Abstract: Very little is known about the etiology of personality and psychiatric disorders. Because the core neurobiology of many such traits is evolutionarily conserved, dogs present a powerful model. We previously reported genome scans of breed averages of ten traits related to fear, anxiety, aggression and social behavior in multiple cohorts of pedigree dogs. As a second phase of that discovery, here we tested the ability of markers at 13 of those loci to predict canine behavior in a community sample of 397 pedigree and mixed-breed dogs with individual-level genotype and phenotype data. We found support for all markers and loci. By including 122 dogs with veterinary behavioral diagnoses in our cohort, we were able to identify eight loci associated with those diagnoses. Logistic regression models showed subsets of those loci could predict behavioral diagnoses. We corroborated our previous findings that small body size is associated with many problem behaviors and large body size is associated with increased trainability. Children in the home were associated with anxiety traits; illness and other animals in the home with coprophagia; working-dog status with increased energy and separation-related problems; and competitive dogs with increased aggression directed at familiar dogs, but reduced fear directed at humans and unfamiliar dogs. Compared to other dogs, Pit Bull-type dogs were not defined by a set of our markers and were not more aggressive; but they were strongly associated with pulling on the leash. Using severity-threshold models, Pit Bull-type dogs showed reduced risk of owner-directed aggression (75th quantile) and increased risk of dog-directed fear (95th quantile). Our findings have broad utility, including for clinical and breeding purposes, but we caution that thorough understanding is necessary for their interpretation and use. Copy rights belong to original authors. Visit the link for more info

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    The Nature of Genetic Susceptibility to Multiple Sclerosis

    Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.08.13.249920v1?rss=1 Authors: Goodin, D. S., Khankhanian, P., Gourraud, P.-A., Vince, N. Abstract: OBJECTIVE: To explore the nature of MS-susceptibility and, by extension, other complex-genetic diseases. BACKGROUND Basic-epidemiological parameters of MS (e.g., prevalence, recurrence-risks for siblings and twins, time-dependent changes in sex-ratio, etc.) are well-established. Moreover, >200 genetic-loci are unequivocally MS-associated, especially the HLA-DRB1*15:01~HLA-DQB1*06:02~a1 haplotype-association. DESIGN/METHODS: We define the genetically-susceptible subset-(G) to include everyone with any non-zero life-time chance of developing MS. We analyze, mathematically, the implications that these epidemiological observations have regarding genetic susceptibility. In addition, we use the sex-ratio change (observed over a 35-year interval), to derive the relationship between MS-probability and an increasing likelihood of a suitable environmental-exposure. RESULTS: We demonstrate that genetic-susceptibitly is restricted to less than 4.7% of populations across Europe and North America. Among carriers of the HLA-DRB1*15:01~HLA-DQB1*06:02~a1 haplotype, fewer than 20% are even in the subset-(G). Women are less likely to be susceptible than men although their MS-penetrance is considerably greater. Response-curves for MS-probability increase with an increasing likelihood of a suitable environmental-exposure, especially among women. These environmental response-curves plateau at under 50% for women and at a significantly lower level for men. CONCLUSIONS: MS is fundamentally a genetic disorder. Despite this, a suitable environmental-exposure is also critical for disease-pathogenesis. Genetic-susceptibility requires specific combinations of non-additive genetic risk-factors. For example, the HLA-DRB1*15:01~HLA-DQB1*06:02~a1 haplotype, by itself, poses no MS-risk. Moreover, the fact that environmental-response-curves plateau below 50%, indicates that disease-pathogenesis is partly stochastic. By extension, other diseases for which monozygotic-twin recurrence-risks greatly exceed disease-prevalence (e.g., rheumatoid arthritis, diabetes, and celiac disease), must have a similar genetic basis. Copy rights belong to original authors. Visit the link for more info
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    Genetic testing of dogs predicts problem behaviors in clinical and nonclinical samples

    Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.08.13.249805v1?rss=1 Authors: Zapata, I., Lilly, M. L., Herron, M. E., Alvarez, C. E. Abstract: Very little is known about the etiology of personality and psychiatric disorders. Because the core neurobiology of many such traits is evolutionarily conserved, dogs present a powerful model. We previously reported genome scans of breed averages of ten traits related to fear, anxiety, aggression and social behavior in multiple cohorts of pedigree dogs. As a second phase of that discovery, here we tested the ability of markers at 13 of those loci to predict canine behavior in a community sample of 397 pedigree and mixed-breed dogs with individual-level genotype and phenotype data. We found support for all markers and loci. By including 122 dogs with veterinary behavioral diagnoses in our cohort, we were able to identify eight loci associated with those diagnoses. Logistic regression models showed subsets of those loci could predict behavioral diagnoses. We corroborated our previous findings that small body size is associated with many problem behaviors and large body size is associated with increased trainability. Children in the home were associated with anxiety traits; illness and other animals in the home with coprophagia; working-dog status with increased energy and separation-related problems; and competitive dogs with increased aggression directed at familiar dogs, but reduced fear directed at humans and unfamiliar dogs. Compared to other dogs, Pit Bull-type dogs were not defined by a set of our markers and were not more aggressive; but they were strongly associated with pulling on the leash. Using severity-threshold models, Pit Bull-type dogs showed reduced risk of owner-directed aggression (75th quantile) and increased risk of dog-directed fear (95th quantile). Our findings have broad utility, including for clinical and breeding purposes, but we caution that thorough understanding is necessary for their interpretation and use. Copy rights belong to original authors. Visit the link for more info
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    A Statistical Framework for QTL Hotspot Detection

    Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.08.13.249342v1?rss=1 Authors: Kao, C.-H., Wu, P.-Y., Yang, M.-H. Abstract: Quantitative trait loci (QTL) hotspots (genomic locations enriched in QTL) are a common and notable feature when collecting many QTL for various traits in many areas of biological studies. The QTL hotspots are important and attractive since they are highly informative and may harbor genes for the quantitative traits. So far, the current statistical methods for QTL hotspot detection use either the individual-level data from the genetical genomics experiments or the summarized data from public QTL databases to proceed with the detection analysis. These detection methods attempt to address some of the concerns, including the correlation structure among traits, the magnitude of LOD scores within a hotspot and computational cost, that arise during the process of QTL hotspot detection. In this article, we describe a statistical framework that can handle both types of data as well as address all the concerns at a time for QTL hotspot detection. Our statistical framework directly operates on the QTL matrix and hence has a very cheap computation cost, and is deployed to take advantage of the QTL mapping results for assisting the detection analysis. Two special devices, trait grouping and top profile, are introduced into the framework. The trait grouping attempts to group the closely linked or pleiotropic traits together to take care of the true linkages and cope with the underestimation of hotspot thresholds due to non-genetic correlations (arising from ignoring the correlation structure among traits), so as to have the ability to obtain much stricter thresholds and dismiss spurious hotspots. The top profile is designed to outline the LOD-score pattern of a hotspot across the different hotspot architectures, so that it can serve to identify and characterize the types of QTL hotspots with varying sizes and LOD score distributions. Real examples, numerical analysis and simulation study are performed to validate our statistical framework, investigate the detection properties, and also compare with the current methods in QTL hotspot detection. The results demonstrate that the proposed statistical framework can effectively accommodate the correlation structure among traits, identify the types of hotspots and still keep the notable features of easy implementation and fast computation for practical QTL hotspot detection. Copy rights belong to original authors. Visit the link for more info
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    eIF2B extends lifespan through inhibition of the integrated stress response

    Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.08.13.244970v1?rss=1 Authors: Derisbourg, M., Wester, L., Baddi, R., Denzel, M. S. Abstract: Protein homeostasis is modulated by stress response pathways and its deficiency is a hallmark of aging. The integrated stress response (ISR) is a conserved stress-signaling pathway that tunes mRNA translation via phosphorylation of the translation initiation factor eIF2. ISR activation and translation initiation are finely balanced by eIF2 kinases and by the eIF2 guanine nucleotide exchange factor eIF2B. However, the role of the ISR during aging remains unexplored. Using a genomic screen in Caenorhabditis elegans, we discovered a role of eIF2B and the eIF2 kinases in longevity. By limiting the ISR, these mutations enhanced protein homeostasis and increased lifespan. Consistently, full ISR inhibition using phosphorylation-defective eIF2 or pharmacological ISR inhibition prolonged lifespan. Lifespan extension through ISR inhibition occurred without changes in overall protein synthesis, and depended on enhanced translational efficiency of the kinase KIN-35. Evidently, lifespan is limited by the ISR and its inhibition may provide an intervention in aging. Copy rights belong to original authors. Visit the link for more info
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    Extensive Genetic Diversity and Host Range of Rodent-borne Coronaviruses

    Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.08.11.245415v1?rss=1 Authors: Wang, W., Lin, X.-D., Zhang, H.-L., Wang, M.-R., Guan, X.-Q., Holmes, E. C., Zhang, Y.-Z. Abstract: 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. Copy rights belong to original authors. Visit the link for more info
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    Pleiotropy in FOXC1-attributable phenotypes involves altered ciliation and cilia-dependent signaling

    Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.08.13.249334v1?rss=1 Authors: Havrylov, S., Chrystal, P., van Baarle, S., French, C. R., MacDonald, I. M., Avasarala, J. R., Rogers, R. C., Berry, F. B., Kume, T., Waskiewicz, A. J., Lehmann, O. J. Abstract: Alterations to cilia are responsible for a wide range of severe disease; however, understanding of the transcriptional control of ciliogenesis remains incomplete. We evaluated whether ciliary dysfunction contributed to the pleiotropic phenotypes caused by the Forkhead transcription factor FOXC1. Here, we show that patients with FOXC1-attributable Axenfeld-Rieger Syndrome (ARS) have a prevalence of ciliopathy-associated phenotypes comparable to syndromic ciliopathies. We demonstrate that altering the level of Foxc1, via shRNA mediated inhibition and mRNA overexpression, modifies cilia length in vitro. These structural changes were associated with substantially perturbed cilia-dependent signaling [Hedgehog (Hh) and PDGFRalpha] and the altered ciliary compartmentalization of a major Hh pathway transcription factor, Gli2. Analyses of two Foxc1 murine mutant strains demonstrated altered axonemal length in the choroid plexus with the increased expression of an essential regulator of multi-ciliation, Foxj1. The novel complexity revealed in ciliation of the choroid plexus indicates a partitioning of function between these Forkhead transcription factors. Collectively, these results support a contribution from ciliary dysfunction to some FOXC1-induced phenotypes. Copy rights belong to original authors. Visit the link for more info
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    The SOD-2 protein is the single active SOD enzyme in C. elegans

    Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.08.12.247973v1?rss=1 Authors: Fernando, L. M., Adeel, S., Basar, M. A., Allen, A. K., Duttaroy, A. Abstract: The nematode C. elegans has a contingent of five sod genes, one of the largest among aerobic organism. Earlier studies revealed each of the five sod genes is capable of making perfectly active SOD proteins in heterologous expressions systems therefore none appears to be a pseudogene. Yet deletion of the entire contingent of sod genes fails to impose any effect on the survival of C. elegans except these animals appear more sensitive to extraneously applied oxidative stress condition. We asked how many of the five sod genes are actually active in C. elegans through an in-gel SOD activity analysis. Here we provide evidence that out of the five genes only the mitochondrial SOD gene is active in C. elegans, albeit at a much lesser amount compared to D. melanogaster and E. coli. Mutant analysis further confirmed that among the mitochondrial forms, SOD-2 is the only naturally active SOD in C. elegans. Copy rights belong to original authors. Visit the link for more info
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    Visualizing Population Structure with Variational Autoencoders

    Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.08.12.248278v1?rss=1 Authors: Kern, A. D., Coffing, G. C., Battey, C. J. Abstract: Dimensionality reduction is a common tool for visualization and inference of population structure from genotypes, but popular methods either return too many dimensions for easy plotting (PCA) or fail to preserve global geometry (t-SNE and UMAP). Here we explore the utility of variational autoencoders (VAEs) -- generative machine learning models in which a pair of neural networks seek to first compress and then recreate the input data -- for visualizing population genetic variation. VAEs incorporate non-linear relationships, allow users to define the dimensionality of the latent space, and in our tests preserve global geometry better than t-SNE and UMAP. Our implementation, which we call popvae, is available as a command-line python program at github.com/kr-colab/popvae. The approach yields latent embeddings that capture subtle aspects of population structure in humans and Anopheles mosquitoes, and can generate artificial genotypes characteristic of a given sample or population. Copy rights belong to original authors. Visit the link for more info
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    Why are rare variants hard to impute? Coalescent models reveal theoretical limits in existing algorithms.

    Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.08.10.245043v1?rss=1 Authors: Si, Y., Zoellner, S. Abstract: Genotype imputation is an indispensable step in human genetic studies. Large reference panels with deeply sequenced genomes now allow interrogating variants with minor allele frequency <1% without sequencing. While it is critical to consider limits of this approach, imputation methods for rare variants have only done so empirically; the theoretical basis of their imputation accuracy has not been explored. To provide theoretical consideration of imputation accuracy under the current imputation framework, we develop a coalescent model of imputing rare variants, leveraging the joint genealogy of the sample to be imputed and reference individuals. We show that broadly used imputation algorithms includes model miss-specifications about this joint genealogy that limit the ability to correctly impute rare variants. We develop closed-form solutions for the probability distribution of this joint genealogy and quantify the inevitable error rate resulting from the model miss-specification across a range of allele frequencies and reference sample sizes. We show that the probability of a falsely imputed minor allele decreases with reference sample size, but the proportion of falsely imputed minor alleles mostly depends on the allele count in the reference sample. We summarize the impact of this error on genotype imputation on association tests by calculating the r2 between imputed and true genotype and show that even when modeling other sources of error, the impact of the model miss-specification have a significant impact on the r2 of rare variants. These results provide a framework for developing new imputation algorithms and for interpreting rare variant association analyses. Copy rights belong to original authors. Visit the link for more info
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    Chemical-genetic interactions with the proline analog L-azetidine-2-carboxylic acid in Saccharomyces cerevisiae

    Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.08.10.245191v1?rss=1 Authors: Berg, M. D., Zhu, Y., Isaacson, J., Genereaux, J., Loll-Krippleber, R., Brown, G. W., Brandl, C. J. Abstract: Non-proteinogenic amino acids, such as the proline analog L-azetidine-2-carboxylic acid (AZC), are detrimental to cells because they are mis-incorporated into proteins and lead to proteotoxic stress. Our goal was to identify genes that show chemical-genetic interactions with AZC in Saccharomyces cerevisiae and thus also potentially define the pathways cells use to cope with amino acid mis-incorporation. Screening the yeast deletion and temperature sensitive collections, we found 72 alleles with negative synthetic interactions with AZC treatment and 12 alleles that suppress AZC toxicity. Many of the genes with negative synthetic interactions are involved in protein quality control pathways through the proteasome. Genes involved in actin cytoskeleton organization and endocytosis also had negative synthetic interactions with AZC. Related to this, the number of actin patches per cell increases upon AZC treatment. Many of the same cellular processes were identified to have interactions with proteotoxic stress caused by two other amino acid analogs, canavanine and thialysine, or a mistranslating tRNA variant that mis-incorporates serine at proline codons. Alleles that suppressed AZC-induced toxicity functioned through the amino acid sensing TOR pathway or controlled amino acid permeases required for AZC uptake. Copy rights belong to original authors. Visit the link for more info

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