Variant-to-gene-mapping followed by cross-species genetic screening identifies GPI-anchor biosynthesis as novel regulator of sleep

Sleep is nearly ubiquitous throughout the animal kingdom, with deficiencies in sleep having been linked to a wide range of human disorders and diseases. While genome wide association studies (GWAS) in humans have been identified loci robustly associated with several heritable diseases or traits, little is known about the functional roles of the underlying causal variants in regulating sleep duration or quality. We applied an ATAC-seq/promoter focused Capture C methodology in iPSC-derived neural progenitors to carry out a variant-to-gene mapping campaign that identified 88 candidate sleep effector genes connected to relevant GWAS signals. To functionally validate the role of the implicated effector genes in sleep regulation, we performed a neuron-specific RNAi screen in the fruit fly, Drosophila melanogaster. This approach identified a number of genes that regulated sleep, including phosphatidylinositol N-acetylglucosaminyltransferase subunit Q (PIG-Q). This gene encodes an enzyme involved in the first step of glycosylphosphatidylinositol (GPI)-anchor biosynthesis. We show that flies deficient for PIG-Q have longer sleep during both the day and night due to an increase in the total number of sleep bouts. Subsequent systematic investigation of other PIG-family genes identified increased sleep in flies for multiple different genes within the PIG pathway. We then mutated the PIG-Q locus in zebrafish and identified similar increases in sleep to those observed in Drosophila, confirming deep homology of PIG-Q mediated sleep regulation. These results provide the first physical variant-to-gene mapping of human sleep genes, and reveals a novel and conserved role for GPI-anchor biosynthesis in sleep regulation.

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Genome-wide association study implicates novel loci and reveals candidate effector genes for longitudinal pediatric bone accrual through variant-to-gene mapping

10.1101/2020.02.17.20024133 ◽

2020 ◽

Cited By ~ 2

Author(s):

Diana L. Cousminer ◽

Yadav Wagley ◽

James A. Pippin ◽

Ahmed Elhakeem ◽

Gregory P. Way ◽

...

Keyword(s):

Gene Mapping ◽

Cell Fate ◽

Target Genes ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Gene Promoters ◽

Skeletal Health ◽

Effector Genes ◽

Genome Wide

Introductory paragraphBone accrual impacts lifelong skeletal health, but genetic discovery has been hampered by cross-sectional study designs and uncertainty about target effector genes. Here, we captured this dynamic phenotype by modeling longitudinal bone accrual across 11,000 bone scans followed by genome-wide association studies (GWAS). We revealed 40 loci (35 novel), half residing in topological associated domains harboring known bone genes. Variant-to-gene mapping identified contacts between GWAS loci and nearby gene promoters, and siRNA knockdown of gene expression clarified the putative effector gene at three specific loci in two osteoblast cell models. The resulting target genes highlight the cell fate decision between osteogenic and adipogenic lineages as important in normal bone accrual.

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Strong Association between Serotonin Transporter 5-HTTVNTR Variant and Psychoactive Substance (Nicotine) Use in the Turkish Cypriot Population

Current Drug Metabolism ◽

10.2174/1389200221666200620201348 ◽

2020 ◽

Vol 21 (6) ◽

pp. 466-470

Author(s):

Emine Kandemis ◽

Gulten Tuncel ◽

Ozen Asut ◽

Sehime G. Temel ◽

Mahmut C. Ergoren

Keyword(s):

Serotonin Transporter ◽

Association Studies ◽

Strong Association ◽

Smoking Behavior ◽

Population Based ◽

Genome Wide Association Studies ◽

Genotype Distribution ◽

Psychological Traits ◽

Wide Range ◽

Turkish Cypriot

Background: The use of psychoactive substances is one of the most dangerous social problems worldwide. Nicotine dependence results from the interaction between neurobiological, environmental and genetic factors. Serotonin is a neurotransmitter that has a wide range of central nervous system activities. The serotonin transporter gene has been previously linked to psychological traits. Objective: A variable number of tandem repeats within the serotonin transporter-linked polymorphic gene region are believed to alter the transcriptional efficiency of the 5-HTT gene. Therefore, we aimed to investigate the association between this polymorphic site and smoking behavior in the Turkish Cypriot population. Methods: A total of 259 (100 smokers, 100 non-smokers and 59 ex-smokers) Turkish Cypriots were included in this population-based cross-sectional study. Genomic DNA was extracted from peripheral blood samples and the 5-HTTVNTR2 polymorphisms were determined by the PCR-RFLP. Results: The allelic frequency and genotype distribution results of this study showed a strong association (P<0.0001) between smokers and non-smokers. No statistical significance was found between non-smokers and ex-smokers. Conclusion: This is the first genetic epidemiology study to investigate the allelic frequencies of 5-HTTVNTR2 polymorphisms associated with smoking behavior in the Turkish Cypriot population. Based on the results of this study, genome-wide association studies should be designed for preventive medicine in this population.

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Systems genetics in diversity outbred mice inform BMD GWAS and identify determinants of bone strength

Nature Communications ◽

10.1038/s41467-021-23649-0 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Basel M. Al-Barghouthi ◽

Larry D. Mesner ◽

Gina M. Calabrese ◽

Daniel Brooks ◽

Steven M. Tommasini ◽

...

Keyword(s):

Cortical Bone ◽

Bone Strength ◽

Human Genetics ◽

Association Studies ◽

Systems Genetics ◽

Genome Wide Association Studies ◽

Mineral Density ◽

Diversity Outbred ◽

Wide Range ◽

Genetics Of Osteoporosis

AbstractGenome-wide association studies (GWASs) for osteoporotic traits have identified over 1000 associations; however, their impact has been limited by the difficulties of causal gene identification and a strict focus on bone mineral density (BMD). Here, we use Diversity Outbred (DO) mice to directly address these limitations by performing a systems genetics analysis of 55 complex skeletal phenotypes. We apply a network approach to cortical bone RNA-seq data to discover 66 genes likely to be causal for human BMD GWAS associations, including the genes SERTAD4 and GLT8D2. We also perform GWAS in the DO for a wide-range of bone traits and identify Qsox1 as a gene influencing cortical bone accrual and bone strength. In this work, we advance our understanding of the genetics of osteoporosis and highlight the ability of the mouse to inform human genetics.

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Role of Genetic Interactions in Lung Diseases Detection using Computational Approaches: A Review

Current Chinese Computer Science ◽

10.2174/2665997201666210125091915 ◽

2021 ◽

Vol 01 ◽

Author(s):

S Priya ◽

R Manavalan

Keyword(s):

Lung Cancer ◽

Lung Diseases ◽

Computational Models ◽

Association Studies ◽

Genetic Interactions ◽

Genome Wide Association Studies ◽

Computational Approaches ◽

Genome Wide ◽

Human Disorders ◽

Brca1 Brca2

: Genome-wide Association Studies (GWAS) give special insight into genetic differences and environmental influences that are part of different human disorders and provide prognostic help to increase the survival of patients. Lung diseases such as lung cancer, asthma, and tuberculosis are detected by analyzing Single Nucleotide Polymorphism (SNP) genetic variations. The key causes of lung-related diseases are genetic factors, environmental and social behaviors. The epistasis effects act as a blueprint for the researchers to observe the genetic variation associated with lung diseases. The manual examination of the enormous genetic interactions is complicated to detect the lungs syndromes for diagnosis of acute respiratory. Due to its importance, several computational approaches have been modeled to infer epistasis effects. This article includes a comprehensive and multifaceted review of all relevant genetic studies published between 2006 and 2020. In this critical review, various computational approaches are extensively discussed in detecting respondent Epistasis effects for various lung diseases such as Asthma, Tuberculosis, lung cancer, and Nicotine drug dependence. The analysis shows that different computational models identified candidate genes such as CHRNA4, CHRNB2, BDNF, TAS2R16, TAS2R38, BRCA1, BRCA2, RAD21, IL4Ra, IL-13 and IL-1β, have important causes for genetic variants linked to pulmonary disease. These computational approaches' strengths and limitations are described. The issues behind the computational methods while identifying the lung diseases through epistasis effects and the parameters used by various researchers for their evaluation are presented.

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Inositol 1,4,5-Trisphosphate Receptors in Human Disease: A Comprehensive Update

Journal of Clinical Medicine ◽

10.3390/jcm9041096 ◽

2020 ◽

Vol 9 (4) ◽

pp. 1096

Author(s):

Jessica Gambardella ◽

Angela Lombardi ◽

Marco Bruno Morelli ◽

John Ferrara ◽

Gaetano Santulli

Keyword(s):

Human Disease ◽

Calcium Release ◽

Current Knowledge ◽

Association Studies ◽

Genome Wide Association Studies ◽

Loss Of Function ◽

Genome Wide ◽

Inositol 1,4,5 Trisphosphate ◽

Human Disorders

Inositol 1,4,5-trisphosphate receptors (ITPRs) are intracellular calcium release channels located on the endoplasmic reticulum of virtually every cell. Herein, we are reporting an updated systematic summary of the current knowledge on the functional role of ITPRs in human disorders. Specifically, we are describing the involvement of its loss-of-function and gain-of-function mutations in the pathogenesis of neurological, immunological, cardiovascular, and neoplastic human disease. Recent results from genome-wide association studies are also discussed.

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Qtlizer: comprehensive QTL annotation of GWAS results

Scientific Reports ◽

10.1038/s41598-020-75770-7 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Matthias Munz ◽

Inken Wohlers ◽

Eric Simon ◽

Tobias Reinberger ◽

Hauke Busch ◽

...

Keyword(s):

Association Studies ◽

Housekeeping Genes ◽

R Package ◽

Genome Wide Association Studies ◽

Protein Abundance ◽

Base Pairs ◽

Link Type ◽

Genome Wide ◽

Wide Range ◽

Distance Limit

AbstractExploration of genetic variant-to-gene relationships by quantitative trait loci such as expression QTLs is a frequently used tool in genome-wide association studies. However, the wide range of public QTL databases and the lack of batch annotation features complicate a comprehensive annotation of GWAS results. In this work, we introduce the tool “Qtlizer” for annotating lists of variants in human with associated changes in gene expression and protein abundance using an integrated database of published QTLs. Features include incorporation of variants in linkage disequilibrium and reverse search by gene names. Analyzing the database for base pair distances between best significant eQTLs and their affected genes suggests that the commonly used cis-distance limit of 1,000,000 base pairs might be too restrictive, implicating a substantial amount of wrongly and yet undetected eQTLs. We also ranked genes with respect to the maximum number of tissue-specific eQTL studies in which a most significant eQTL signal was consistent. For the top 100 genes we observed the strongest enrichment with housekeeping genes (P = 2 × 10–6) and with the 10% highest expressed genes (P = 0.005) after grouping eQTLs by r2 > 0.95, underlining the relevance of LD information in eQTL analyses. Qtlizer can be accessed via https://genehopper.de/qtlizer or by using the respective Bioconductor R-package (https://doi.org/10.18129/B9.bioc.Qtlizer).

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Systems genetics analyses in Diversity Outbred mice inform human bone mineral density GWAS and identify Qsox1 as a novel determinant of bone strength

10.1101/2020.06.24.169839 ◽

2020 ◽

Author(s):

Basel Al-Barghouthi ◽

Larry D. Mesner ◽

Gina M. Calabrese ◽

Daniel Brooks ◽

Steve M. Tommasini ◽

...

Keyword(s):

Bone Mineral Density ◽

Cortical Bone ◽

Bone Strength ◽

Bone Mineral ◽

Association Studies ◽

Systems Genetics ◽

Genome Wide Association Studies ◽

Mineral Density ◽

Diversity Outbred ◽

Wide Range

ABSTRACTGenome-wide association studies (GWASs) for osteoporotic traits have identified over 1000 associations; however, their impact has been limited by the difficulties of causal gene identification and a strict focus on bone mineral density (BMD). Here, we used Diversity Outbred (DO) mice to directly address these limitations by performing the first systems genetics analysis of over 50 complex skeletal phenotypes. We applied a network approach to cortical bone RNA-seq data to discover 46 genes likely to be causal for human BMD GWAS associations, including the novel genes SERTAD4 and GLT8D2. We also performed GWAS in the DO for a wide-range of bone traits and identified Qsox1 as a novel gene influencing cortical bone accrual and bone strength. Our results provide a new perspective on the genetics of osteoporosis and highlight the ability of the mouse to inform human genetics.

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Genome-wide genetic data on ~500,000 UK Biobank participants

10.1101/166298 ◽

2017 ◽

Cited By ~ 303

Author(s):

Clare Bycroft ◽

Colin Freeman ◽

Desislava Petkova ◽

Gavin Band ◽

Lloyd T. Elliott ◽

...

Keyword(s):

Quality Control ◽

Allelic Variation ◽

Association Studies ◽

Genetic Data ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genotype Data ◽

Uk Biobank ◽

Genome Wide ◽

Wide Range

AbstractThe UK Biobank project is a large prospective cohort study of ~500,000 individuals from across the United Kingdom, aged between 40-69 at recruitment. A rich variety of phenotypic and health-related information is available on each participant, making the resource unprecedented in its size and scope. Here we describe the genome-wide genotype data (~805,000 markers) collected on all individuals in the cohort and its quality control procedures. Genotype data on this scale offers novel opportunities for assessing quality issues, although the wide range of ancestries of the individuals in the cohort also creates particular challenges. We also conducted a set of analyses that reveal properties of the genetic data – such as population structure and relatedness – that can be important for downstream analyses. In addition, we phased and imputed genotypes into the dataset, using computationally efficient methods combined with the Haplotype Reference Consortium (HRC) and UK10K haplotype resource. This increases the number of testable variants by over 100-fold to ~96 million variants. We also imputed classical allelic variation at 11 human leukocyte antigen (HLA) genes, and as a quality control check of this imputation, we replicate signals of known associations between HLA alleles and many common diseases. We describe tools that allow efficient genome-wide association studies (GWAS) of multiple traits and fast phenome-wide association studies (PheWAS), which work together with a new compressed file format that has been used to distribute the dataset. As a further check of the genotyped and imputed datasets, we performed a test-case genome-wide association scan on a well-studied human trait, standing height.

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An integrated platform to systematically identify causal variants and genes for polygenic human traits

10.1101/813618 ◽

2019 ◽

Cited By ~ 3

Author(s):

Damien J. Downes ◽

Ron Schwessinger ◽

Stephanie J. Hill ◽

Lea Nussbaum ◽

Caroline Scott ◽

...

Keyword(s):

Genetic Variants ◽

Association Studies ◽

Significant Proportion ◽

Genome Wide Association Studies ◽

Effector Genes ◽

Genome Wide ◽

Common Genetic Variants ◽

Integrated Platform ◽

Causal Variants

ABSTRACTGenome-wide association studies (GWAS) have identified over 150,000 links between common genetic variants and human traits or complex diseases. Over 80% of these associations map to polymorphisms in non-coding DNA. Therefore, the challenge is to identify disease-causing variants, the genes they affect, and the cells in which these effects occur. We have developed a platform using ATAC-seq, DNaseI footprints, NG Capture-C and machine learning to address this challenge. Applying this approach to red blood cell traits identifies a significant proportion of known causative variants and their effector genes, which we show can be validated by direct in vivo modelling.

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Identification of putative effector genes across the GWAS Catalog using molecular quantitative trait loci from 68 tissues and cell types

10.1101/808444 ◽

2019 ◽

Cited By ~ 2

Author(s):

Cong Guo ◽

Karsten B. Sieber ◽

Jorge Esparza-Gordillo ◽

Mark R. Hurle ◽

Kijoung Song ◽

...

Keyword(s):

Quantitative Trait Loci ◽

Quantitative Trait ◽

Complex Traits ◽

Association Studies ◽

Genome Wide Association Studies ◽

Genetic Associations ◽

Effector Genes ◽

Genome Wide ◽

Trait Loci ◽

Gwas Catalog

AbstractIdentifying the effector genes from genome-wide association studies (GWAS) is a crucial step towards understanding the biological mechanisms underlying complex traits and diseases. Colocalization of expression and protein quantitative trait loci (eQTL and pQTL, hereafter collectively called “xQTL”) can be effective for mapping associations to genes in many loci. However, existing colocalization methods require full single-variant summary statistics which are often not readily available for many published GWAS or xQTL studies. Here, we present PICCOLO, a method that uses minimum SNP p-values within a locus to determine if pairs of genetic associations are colocalized. This method greatly expands the number of GWAS and xQTL datasets that can be tested for colocalization. We applied PICCOLO to 10,759 genome-wide significant associations across the NHGRI-EBI GWAS Catalog with xQTLs from 28 studies. We identified at least one colocalized gene-xQTL in at least one tissue for 30% of associations, and we pursued multiple lines of evidence to demonstrate that these mappings are biologically meaningful. PICCOLO genes are significantly enriched for biologically relevant tissues, and 4.3-fold enriched for targets of approved drugs.

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