Publications by authors named "Julien Bryois"

32 Publications

Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology.

Nat Genet 2021 06 17;53(6):817-829. Epub 2021 May 17.

Department of Neuroscience, Istituto Di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.

Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.
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http://dx.doi.org/10.1038/s41588-021-00857-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8192451PMC
June 2021

Conditional GWAS analysis to identify disorder-specific SNPs for psychiatric disorders.

Mol Psychiatry 2020 May 12. Epub 2020 May 12.

Institute for Molecular Biosciences, University of Queensland, Brisbane, QLD, Australia.

Substantial genetic liability is shared across psychiatric disorders but less is known about risk variants that are specific to a given disorder. We used multi-trait conditional and joint analysis (mtCOJO) to adjust GWAS summary statistics of one disorder for the effects of genetically correlated traits to identify putative disorder-specific SNP associations. We applied mtCOJO to summary statistics for five psychiatric disorders from the Psychiatric Genomics Consortium-schizophrenia (SCZ), bipolar disorder (BIP), major depression (MD), attention-deficit hyperactivity disorder (ADHD) and autism (AUT). Most genome-wide significant variants for these disorders had evidence of pleiotropy (i.e., impact on multiple psychiatric disorders) and hence have reduced mtCOJO conditional effect sizes. However, subsets of genome-wide significant variants had larger conditional effect sizes consistent with disorder-specific effects: 15 of 130 genome-wide significant variants for schizophrenia, 5 of 40 for major depression, 3 of 11 for ADHD and 1 of 2 for autism. We show that decreased expression of VPS29 in the brain may increase risk to SCZ only and increased expression of CSE1L is associated with SCZ and MD, but not with BIP. Likewise, decreased expression of PCDHA7 in the brain is linked to increased risk of MD but decreased risk of SCZ and BIP.
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http://dx.doi.org/10.1038/s41380-020-0705-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7657979PMC
May 2020

Genetic identification of cell types underlying brain complex traits yields insights into the etiology of Parkinson's disease.

Nat Genet 2020 05 27;52(5):482-493. Epub 2020 Apr 27.

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

Genome-wide association studies have discovered hundreds of loci associated with complex brain disorders, but it remains unclear in which cell types these loci are active. Here we integrate genome-wide association study results with single-cell transcriptomic data from the entire mouse nervous system to systematically identify cell types underlying brain complex traits. We show that psychiatric disorders are predominantly associated with projecting excitatory and inhibitory neurons. Neurological diseases were associated with different cell types, which is consistent with other lines of evidence. Notably, Parkinson's disease was genetically associated not only with cholinergic and monoaminergic neurons (which include dopaminergic neurons) but also with enteric neurons and oligodendrocytes. Using post-mortem brain transcriptomic data, we confirmed alterations in these cells, even at the earliest stages of disease progression. Our study provides an important framework for understanding the cellular basis of complex brain maladies, and reveals an unexpected role of oligodendrocytes in Parkinson's disease.
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http://dx.doi.org/10.1038/s41588-020-0610-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7930801PMC
May 2020

Increased burden of ultra-rare structural variants localizing to boundaries of topologically associated domains in schizophrenia.

Nat Commun 2020 04 15;11(1):1842. Epub 2020 Apr 15.

Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA.

Despite considerable progress in schizophrenia genetics, most findings have been for large rare structural variants and common variants in well-imputed regions with few genes implicated from exome sequencing. Whole genome sequencing (WGS) can potentially provide a more complete enumeration of etiological genetic variation apart from the exome and regions of high linkage disequilibrium. We analyze high-coverage WGS data from 1162 Swedish schizophrenia cases and 936 ancestry-matched population controls. Our main objective is to evaluate the contribution to schizophrenia etiology from a variety of genetic variants accessible to WGS but not by previous technologies. Our results suggest that ultra-rare structural variants that affect the boundaries of topologically associated domains (TADs) increase risk for schizophrenia. Alterations in TAD boundaries may lead to dysregulation of gene expression. Future mechanistic studies will be needed to determine the precise functional effects of these variants on biology.
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http://dx.doi.org/10.1038/s41467-020-15707-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7160146PMC
April 2020

Shared genetic risk between eating disorder- and substance-use-related phenotypes: Evidence from genome-wide association studies.

Addict Biol 2021 01 16;26(1):e12880. Epub 2020 Feb 16.

Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, RWTH Aachen University, Aachen, Germany.

Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [r ], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (r = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (r = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (r = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (r = -0.19 to -0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors.
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http://dx.doi.org/10.1111/adb.12880DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7429266PMC
January 2021

The Genetics of the Mood Disorder Spectrum: Genome-wide Association Analyses of More Than 185,000 Cases and 439,000 Controls.

Biol Psychiatry 2020 07 1;88(2):169-184. Epub 2019 Nov 1.

Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, United Kingdom; National Institute for Health Research Maudsley Biomedical Research Centre, King's College London, London, United Kingdom. Electronic address:

Background: Mood disorders (including major depressive disorder and bipolar disorder) affect 10% to 20% of the population. They range from brief, mild episodes to severe, incapacitating conditions that markedly impact lives. Multiple approaches have shown considerable sharing of risk factors across mood disorders despite their diagnostic distinction.

Methods: To clarify the shared molecular genetic basis of major depressive disorder and bipolar disorder and to highlight disorder-specific associations, we meta-analyzed data from the latest Psychiatric Genomics Consortium genome-wide association studies of major depression (including data from 23andMe) and bipolar disorder, and an additional major depressive disorder cohort from UK Biobank (total: 185,285 cases, 439,741 controls; nonoverlapping N = 609,424).

Results: Seventy-three loci reached genome-wide significance in the meta-analysis, including 15 that are novel for mood disorders. More loci from the Psychiatric Genomics Consortium analysis of major depression than from that for bipolar disorder reached genome-wide significance. Genetic correlations revealed that type 2 bipolar disorder correlates strongly with recurrent and single-episode major depressive disorder. Systems biology analyses highlight both similarities and differences between the mood disorders, particularly in the mouse brain cell types implicated by the expression patterns of associated genes. The mood disorders also differ in their genetic correlation with educational attainment-the relationship is positive in bipolar disorder but negative in major depressive disorder.

Conclusions: The mood disorders share several genetic associations, and genetic studies of major depressive disorder and bipolar disorder can be combined effectively to enable the discovery of variants not identified by studying either disorder alone. However, we demonstrate several differences between these disorders. Analyzing subtypes of major depressive disorder and bipolar disorder provides evidence for a genetic mood disorders spectrum.
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http://dx.doi.org/10.1016/j.biopsych.2019.10.015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8136147PMC
July 2020

Reproducible Genetic Risk Loci for Anxiety: Results From ∼200,000 Participants in the Million Veteran Program.

Am J Psychiatry 2020 03 7;177(3):223-232. Epub 2020 Jan 7.

Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, Conn., and Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, Conn. (Levey, Gelernter, Polimanti, Zhou, Cheng); VA Clinical Epidemiology Research Center, VA Connecticut Healthcare System, West Haven, Conn. (Aslan, Concato, Radhakrishnan); Department of Medicine, Yale University School of Medicine, New Haven, Conn. (Aslan, Concato); Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston (Quaden); College of Medicine, University of Kentucky, Lexington (Radhakrishnan); Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm (Bryois, Sullivan); Departments of Genetics and Psychiatry, University of North Carolina, Chapel Hill (Sullivan); Psychiatry Service, VA San Diego Healthcare System, San Diego, and Departments of Psychiatry and of Family Medicine and Public Health, University of California San Diego, La Jolla (Stein).

Objective: Anxiety disorders are common and often disabling. The goal of this study was to examine the genetic architecture of anxiety disorders and anxiety symptoms, which are also frequently comorbid with other mental disorders, such as major depressive disorder.

Methods: Using one of the world's largest biobanks including genetic, environmental, and medical information, the Million Veteran Program, the authors performed a genome-wide association study (GWAS) of a continuous trait for anxiety (based on score on the Generalized Anxiety Disorder 2-item scale [GAD-2], N=199,611) as the primary analysis and self-report of physician diagnosis of anxiety disorder (N=224,330) as a secondary analysis.

Results: The authors identified five genome-wide significant signals for European Americans and one for African Americans on GAD-2 score. The strongest were on chromosome 3 (rs4603973) near , a global regulator of gene expression, and on chromosome 6 (rs6557168) near , which encodes an estrogen receptor. The locus identified on chromosome 7 (rs56226325, MAF=0.17) near was previously identified in GWASs of bipolar disorder and schizophrenia. The authors replicated these findings in the summary statistics of two major published GWASs for anxiety, and also found evidence of significant genetic correlation between the GAD-2 score results and previous GWASs for anxiety (r=0.75), depression (r=0.81), and neuroticism (r=0.75).

Conclusions: This is the largest GWAS of anxiety traits to date. The authors identified novel genome-wide significant associations near genes involved with global regulation of gene expression () and the estrogen receptor alpha (). Additionally, the authors identified a locus () that may have implications for genetic vulnerability across several psychiatric disorders. This work provides new insights into genetic risk mechanisms underpinning anxiety and related psychiatric disorders.
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http://dx.doi.org/10.1176/appi.ajp.2019.19030256DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7869502PMC
March 2020

Genome-wide analysis identifies molecular systems and 149 genetic loci associated with income.

Nat Commun 2019 12 16;10(1):5741. Epub 2019 Dec 16.

Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK.

Socioeconomic position (SEP) is a multi-dimensional construct reflecting (and influencing) multiple socio-cultural, physical, and environmental factors. In a sample of 286,301 participants from UK Biobank, we identify 30 (29 previously unreported) independent-loci associated with income. Using a method to meta-analyze data from genetically-correlated traits, we identify an additional 120 income-associated loci. These loci show clear evidence of functionality, with transcriptional differences identified across multiple cortical tissues, and links to GABAergic and serotonergic neurotransmission. By combining our genome wide association study on income with data from eQTL studies and chromatin interactions, 24 genes are prioritized for follow up, 18 of which were previously associated with intelligence. We identify intelligence as one of the likely causal, partly-heritable phenotypes that might bridge the gap between molecular genetic inheritance and phenotypic consequence in terms of income differences. These results indicate that, in modern era Great Britain, genetic effects contribute towards some of the observed socioeconomic inequalities.
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http://dx.doi.org/10.1038/s41467-019-13585-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6915786PMC
December 2019

Comparative genetic architectures of schizophrenia in East Asian and European populations.

Nat Genet 2019 12 18;51(12):1670-1678. Epub 2019 Nov 18.

Psychiatric Genetic Epidemiology and Neurobiology Laboratory (PsychGENe lab), Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA.

Schizophrenia is a debilitating psychiatric disorder with approximately 1% lifetime risk globally. Large-scale schizophrenia genetic studies have reported primarily on European ancestry samples, potentially missing important biological insights. Here, we report the largest study to date of East Asian participants (22,778 schizophrenia cases and 35,362 controls), identifying 21 genome-wide-significant associations in 19 genetic loci. Common genetic variants that confer risk for schizophrenia have highly similar effects between East Asian and European ancestries (genetic correlation = 0.98 ± 0.03), indicating that the genetic basis of schizophrenia and its biology are broadly shared across populations. A fixed-effect meta-analysis including individuals from East Asian and European ancestries identified 208 significant associations in 176 genetic loci (53 novel). Trans-ancestry fine-mapping reduced the sets of candidate causal variants in 44 loci. Polygenic risk scores had reduced performance when transferred across ancestries, highlighting the importance of including sufficient samples of major ancestral groups to ensure their generalizability across populations.
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http://dx.doi.org/10.1038/s41588-019-0512-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6885121PMC
December 2019

Genome-wide association study of post-traumatic stress disorder reexperiencing symptoms in >165,000 US veterans.

Nat Neurosci 2019 09 29;22(9):1394-1401. Epub 2019 Jul 29.

Psychiatry Service, VA San Diego Healthcare System, San Diego, CA, USA.

Post-traumatic stress disorder (PTSD) is a major problem among military veterans and civilians alike, yet its pathophysiology remains poorly understood. We performed a genome-wide association study and bioinformatic analyses, which included 146,660 European Americans and 19,983 African Americans in the US Million Veteran Program, to identify genetic risk factors relevant to intrusive reexperiencing of trauma, which is the most characteristic symptom cluster of PTSD. In European Americans, eight distinct significant regions were identified. Three regions had values of P < 5 × 10: CAMKV; chromosome 17 closest to KANSL1, but within a large high linkage disequilibrium region that also includes CRHR1; and TCF4. Associations were enriched with respect to the transcriptomic profiles of striatal medium spiny neurons. No significant associations were observed in the African American cohort of the sample. Results in European Americans were replicated in the UK Biobank data. These results provide new insights into the biology of PTSD in a well-powered genome-wide association study.
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http://dx.doi.org/10.1038/s41593-019-0447-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6953633PMC
September 2019

Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa.

Nat Genet 2019 08 15;51(8):1207-1214. Epub 2019 Jul 15.

Clinical Genetics Unit, Department of Woman and Child Health, University of Padova, Padova, Italy.

Characterized primarily by a low body-mass index, anorexia nervosa is a complex and serious illness, affecting 0.9-4% of women and 0.3% of men, with twin-based heritability estimates of 50-60%. Mortality rates are higher than those in other psychiatric disorders, and outcomes are unacceptably poor. Here we combine data from the Anorexia Nervosa Genetics Initiative (ANGI) and the Eating Disorders Working Group of the Psychiatric Genomics Consortium (PGC-ED) and conduct a genome-wide association study of 16,992 cases of anorexia nervosa and 55,525 controls, identifying eight significant loci. The genetic architecture of anorexia nervosa mirrors its clinical presentation, showing significant genetic correlations with psychiatric disorders, physical activity, and metabolic (including glycemic), lipid and anthropometric traits, independent of the effects of common variants associated with body-mass index. These results further encourage a reconceptualization of anorexia nervosa as a metabo-psychiatric disorder. Elucidating the metabolic component is a critical direction for future research, and paying attention to both psychiatric and metabolic components may be key to improving outcomes.
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http://dx.doi.org/10.1038/s41588-019-0439-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6779477PMC
August 2019

Single cell analysis of autism patient with bi-allelic NRXN1-alpha deletion reveals skewed fate choice in neural progenitors and impaired neuronal functionality.

Exp Cell Res 2019 10 12;383(1):111469. Epub 2019 Jul 12.

Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden. Electronic address:

We generated human iPS derived neural stem cells and differentiated cells from healthy control individuals and an individual with autism spectrum disorder carrying bi-allelic NRXN1-alpha deletion. We investigated the expression of NRXN1-alpha during neural induction and neural differentiation and observed a pivotal role for NRXN1-alpha during early neural induction and neuronal differentiation. Single cell RNA-seq pinpointed neural stem cells carrying NRXN1-alpha deletion shifting towards radial glia-like cell identity and revealed higher proportion of differentiated astroglia. Furthermore, neuronal cells carrying NRXN1-alpha deletion were identified as immature by single cell RNA-seq analysis, displayed significant depression in calcium signaling activity and presented impaired maturation action potential profile in neurons investigated with electrophysiology. Our observations propose NRXN1-alpha plays an important role for the efficient establishment of neural stem cells, in neuronal differentiation and in maturation of functional excitatory neuronal cells.
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http://dx.doi.org/10.1016/j.yexcr.2019.06.014DOI Listing
October 2019

Obesity remodels activity and transcriptional state of a lateral hypothalamic brake on feeding.

Science 2019 06;364(6447):1271-1274

Department of Psychiatry, University of North Carolina, Chapel Hill, NC 27599, USA.

The current obesity epidemic is a major worldwide health concern. Despite the consensus that the brain regulates energy homeostasis, the neural adaptations governing obesity are unknown. Using a combination of high-throughput single-cell RNA sequencing and longitudinal in vivo two-photon calcium imaging, we surveyed functional alterations of the lateral hypothalamic area (LHA)-a highly conserved brain region that orchestrates feeding-in a mouse model of obesity. The transcriptional profile of LHA glutamatergic neurons was affected by obesity, exhibiting changes indicative of altered neuronal activity. Encoding properties of individual LHA glutamatergic neurons were then tracked throughout obesity, revealing greatly attenuated reward responses. These data demonstrate how diet disrupts the function of an endogenous feeding suppression system to promote overeating and obesity.
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http://dx.doi.org/10.1126/science.aax1184DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7318865PMC
June 2019

Genome-wide analysis of insomnia in 1,331,010 individuals identifies new risk loci and functional pathways.

Nat Genet 2019 03 25;51(3):394-403. Epub 2019 Feb 25.

Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, the Netherlands.

Insomnia is the second most prevalent mental disorder, with no sufficient treatment available. Despite substantial heritability, insight into the associated genes and neurobiological pathways remains limited. Here, we use a large genetic association sample (n = 1,331,010) to detect novel loci and gain insight into the pathways, tissue and cell types involved in insomnia complaints. We identify 202 loci implicating 956 genes through positional, expression quantitative trait loci, and chromatin mapping. The meta-analysis explained 2.6% of the variance. We show gene set enrichments for the axonal part of neurons, cortical and subcortical tissues, and specific cell types, including striatal, hypothalamic, and claustrum neurons. We found considerable genetic correlations with psychiatric traits and sleep duration, and modest correlations with other sleep-related traits. Mendelian randomization identified the causal effects of insomnia on depression, diabetes, and cardiovascular disease, and the protective effects of educational attainment and intracranial volume. Our findings highlight key brain areas and cell types implicated in insomnia, and provide new treatment targets.
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http://dx.doi.org/10.1038/s41588-018-0333-3DOI Listing
March 2019

Genome-wide meta-analysis identifies new loci and functional pathways influencing Alzheimer's disease risk.

Nat Genet 2019 03 7;51(3):404-413. Epub 2019 Jan 7.

MRC Biostatistics Unit, Cambridge Institute of Public Health, University of Cambridge, Cambridge, UK.

Alzheimer's disease (AD) is highly heritable and recent studies have identified over 20 disease-associated genomic loci. Yet these only explain a small proportion of the genetic variance, indicating that undiscovered loci remain. Here, we performed a large genome-wide association study of clinically diagnosed AD and AD-by-proxy (71,880 cases, 383,378 controls). AD-by-proxy, based on parental diagnoses, showed strong genetic correlation with AD (r = 0.81). Meta-analysis identified 29 risk loci, implicating 215 potential causative genes. Associated genes are strongly expressed in immune-related tissues and cell types (spleen, liver, and microglia). Gene-set analyses indicate biological mechanisms involved in lipid-related processes and degradation of amyloid precursor proteins. We show strong genetic correlations with multiple health-related outcomes, and Mendelian randomization results suggest a protective effect of cognitive ability on AD risk. These results are a step forward in identifying the genetic factors that contribute to AD risk and add novel insights into the neurobiology of AD.
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http://dx.doi.org/10.1038/s41588-018-0311-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6836675PMC
March 2019

Examination of the shared genetic basis of anorexia nervosa and obsessive-compulsive disorder.

Mol Psychiatry 2020 09 7;25(9):2036-2046. Epub 2018 Aug 7.

Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

Anorexia nervosa (AN) and obsessive-compulsive disorder (OCD) are often comorbid and likely to share genetic risk factors. Hence, we examine their shared genetic background using a cross-disorder GWAS meta-analysis of 3495 AN cases, 2688 OCD cases, and 18,013 controls. We confirmed a high genetic correlation between AN and OCD (r = 0.49 ± 0.13, p = 9.07 × 10) and a sizable SNP heritability (SNP h = 0.21 ± 0.02) for the cross-disorder phenotype. Although no individual loci reached genome-wide significance, the cross-disorder phenotype showed strong positive genetic correlations with other psychiatric phenotypes (e.g., r = 0.36 with bipolar disorder and 0.34 with neuroticism) and negative genetic correlations with metabolic phenotypes (e.g., r = -0.25 with body mass index and -0.20 with triglycerides). Follow-up analyses revealed that although AN and OCD overlap heavily in their shared risk with other psychiatric phenotypes, the relationship with metabolic and anthropometric traits is markedly stronger for AN than for OCD. We further tested whether shared genetic risk for AN/OCD was associated with particular tissue or cell-type gene expression patterns and found that the basal ganglia and medium spiny neurons were most enriched for AN-OCD risk, consistent with neurobiological findings for both disorders. Our results confirm and extend genetic epidemiological findings of shared risk between AN and OCD and suggest that larger GWASs are warranted.
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http://dx.doi.org/10.1038/s41380-018-0115-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6367065PMC
September 2020

Evaluation of chromatin accessibility in prefrontal cortex of individuals with schizophrenia.

Nat Commun 2018 08 7;9(1):3121. Epub 2018 Aug 7.

Center for Genomic and Computational Biology, Duke University, Durham, NC, 27708, USA.

Schizophrenia genome-wide association studies have identified >150 regions of the genome associated with disease risk, yet there is little evidence that coding mutations contribute to this disorder. To explore the mechanism of non-coding regulatory elements in schizophrenia, we performed ATAC-seq on adult prefrontal cortex brain samples from 135 individuals with schizophrenia and 137 controls, and identified 118,152 ATAC-seq peaks. These accessible chromatin regions in the brain are highly enriched for schizophrenia SNP heritability. Accessible chromatin regions that overlap evolutionarily conserved regions exhibit an even higher heritability enrichment, indicating that sequence conservation can further refine functional risk variants. We identify few differences in chromatin accessibility between cases and controls, in contrast to thousands of age-related differential accessible chromatin regions. Altogether, we characterize chromatin accessibility in the human prefrontal cortex, the effect of schizophrenia and age on chromatin accessibility, and provide evidence that our dataset will allow for fine mapping of risk variants.
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http://dx.doi.org/10.1038/s41467-018-05379-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6081462PMC
August 2018

Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence.

Nat Genet 2018 07 25;50(7):912-919. Epub 2018 Jun 25.

Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.

Intelligence is highly heritable and a major determinant of human health and well-being. Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence, but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.
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http://dx.doi.org/10.1038/s41588-018-0152-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6411041PMC
July 2018

Meta-analysis of genome-wide association studies for neuroticism in 449,484 individuals identifies novel genetic loci and pathways.

Nat Genet 2018 07 25;50(7):920-927. Epub 2018 Jun 25.

Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.

Neuroticism is an important risk factor for psychiatric traits, including depression, anxiety, and schizophrenia. At the time of analysis, previous genome-wide association studies (GWAS) reported 16 genomic loci associated to neuroticism. Here we conducted a large GWAS meta-analysis (n = 449,484) of neuroticism and identified 136 independent genome-wide significant loci (124 new at the time of analysis), which implicate 599 genes. Functional follow-up analyses showed enrichment in several brain regions and involvement of specific cell types, including dopaminergic neuroblasts (P = 3.49 × 10), medium spiny neurons (P = 4.23 × 10), and serotonergic neurons (P = 1.37 × 10). Gene set analyses implicated three specific pathways: neurogenesis (P = 4.43 × 10), behavioral response to cocaine processes (P = 1.84 × 10), and axon part (P = 5.26 × 10). We show that neuroticism's genetic signal partly originates in two genetically distinguishable subclusters ('depressed affect' and 'worry'), suggesting distinct causal mechanisms for subtypes of individuals. Mendelian randomization analysis showed unidirectional and bidirectional effects between neuroticism and multiple psychiatric traits. These results enhance neurobiological understanding of neuroticism and provide specific leads for functional follow-up experiments.
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http://dx.doi.org/10.1038/s41588-018-0151-7DOI Listing
July 2018

Building a schizophrenia genetic network: transcription factor 4 regulates genes involved in neuronal development and schizophrenia risk.

Hum Mol Genet 2018 09;27(18):3246-3256

Department of Pharmacotherapy and Outcomes Science.

The transcription factor 4 (TCF4) locus is a robust association finding with schizophrenia (SCZ), but little is known about the genes regulated by the encoded transcription factor. Therefore, we conducted chromatin immunoprecipitation sequencing (ChIP-seq) of TCF4 in neural-derived (SH-SY5Y) cells to identify genome-wide TCF4 binding sites, followed by data integration with SCZ association findings. We identified 11 322 TCF4 binding sites overlapping in two ChIP-seq experiments. These sites are significantly enriched for the TCF4 Ebox binding motif (>85% having ≥1 Ebox) and implicate a gene set enriched for genes downregulated in TCF4 small-interfering RNA (siRNA) knockdown experiments, indicating the validity of our findings. The TCF4 gene set was also enriched among (1) gene ontology categories such as axon/neuronal development, (2) genes preferentially expressed in brain, in particular pyramidal neurons of the somatosensory cortex and (3) genes downregulated in postmortem brain tissue from SCZ patients (odds ratio, OR = 2.8, permutation P < 4x10-5). Considering genomic alignments, TCF4 binding sites significantly overlapped those for neural DNA-binding proteins such as FOXP2 and the SCZ-associated EP300. TCF4 binding sites were modestly enriched among SCZ risk loci from the Psychiatric Genomic Consortium (OR = 1.56, P = 0.03). In total, 130 TCF4 binding sites occurred in 39 of the 108 regions published in 2014. Thirteen genes within the 108 loci had both a TCF4 binding site ±10kb and were differentially expressed in siRNA knockdown experiments of TCF4, suggesting direct TCF4 regulation. These findings confirm TCF4 as an important regulator of neural genes and point toward functional interactions with potential relevance for SCZ.
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http://dx.doi.org/10.1093/hmg/ddy222DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6354221PMC
September 2018

Genetic identification of brain cell types underlying schizophrenia.

Nat Genet 2018 06 21;50(6):825-833. Epub 2018 May 21.

Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.

With few exceptions, the marked advances in knowledge about the genetic basis of schizophrenia have not converged on findings that can be confidently used for precise experimental modeling. By applying knowledge of the cellular taxonomy of the brain from single-cell RNA sequencing, we evaluated whether the genomic loci implicated in schizophrenia map onto specific brain cell types. We found that the common-variant genomic results consistently mapped to pyramidal cells, medium spiny neurons (MSNs) and certain interneurons, but far less consistently to embryonic, progenitor or glial cells. These enrichments were due to sets of genes that were specifically expressed in each of these cell types. We also found that many of the diverse gene sets previously associated with schizophrenia (genes involved in synaptic function, those encoding mRNAs that interact with FMRP, antipsychotic targets, etc.) generally implicated the same brain cell types. Our results suggest a parsimonious explanation: the common-variant genetic results for schizophrenia point at a limited set of neurons, and the gene sets point to the same cells. The genetic risk associated with MSNs did not overlap with that of glutamatergic pyramidal cells and interneurons, suggesting that different cell types have biologically distinct roles in schizophrenia.
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http://dx.doi.org/10.1038/s41588-018-0129-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6477180PMC
June 2018

Genetic identification of brain cell types underlying schizophrenia.

Nat Genet 2018 06 21;50(6):825-833. Epub 2018 May 21.

Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.

With few exceptions, the marked advances in knowledge about the genetic basis of schizophrenia have not converged on findings that can be confidently used for precise experimental modeling. By applying knowledge of the cellular taxonomy of the brain from single-cell RNA sequencing, we evaluated whether the genomic loci implicated in schizophrenia map onto specific brain cell types. We found that the common-variant genomic results consistently mapped to pyramidal cells, medium spiny neurons (MSNs) and certain interneurons, but far less consistently to embryonic, progenitor or glial cells. These enrichments were due to sets of genes that were specifically expressed in each of these cell types. We also found that many of the diverse gene sets previously associated with schizophrenia (genes involved in synaptic function, those encoding mRNAs that interact with FMRP, antipsychotic targets, etc.) generally implicated the same brain cell types. Our results suggest a parsimonious explanation: the common-variant genetic results for schizophrenia point at a limited set of neurons, and the gene sets point to the same cells. The genetic risk associated with MSNs did not overlap with that of glutamatergic pyramidal cells and interneurons, suggesting that different cell types have biologically distinct roles in schizophrenia.
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http://dx.doi.org/10.1038/s41588-018-0129-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6477180PMC
June 2018

Biological annotation of genetic loci associated with intelligence in a meta-analysis of 87,740 individuals.

Mol Psychiatry 2019 02 8;24(2):182-197. Epub 2018 Mar 8.

MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK.

Variance in IQ is associated with a wide range of health outcomes, and 1% of the population are affected by intellectual disability. Despite a century of research, the fundamental neural underpinnings of intelligence remain unclear. We integrate results from genome-wide association studies (GWAS) of intelligence with brain tissue and single cell gene expression data to identify tissues and cell types associated with intelligence. GWAS data for IQ (N = 78,308) were meta-analyzed with a study comparing 1247 individuals with mean IQ ~170 to 8185 controls. Genes associated with intelligence implicate pyramidal neurons of the somatosensory cortex and CA1 region of the hippocampus, and midbrain embryonic GABAergic neurons. Tissue-specific analyses find the most significant enrichment for frontal cortex brain expressed genes. These results suggest specific neuronal cell types and genes may be involved in intelligence and provide new hypotheses for neuroscience experiments using model systems.
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http://dx.doi.org/10.1038/s41380-018-0040-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6330082PMC
February 2019

Integrated Bayesian analysis of rare exonic variants to identify risk genes for schizophrenia and neurodevelopmental disorders.

Genome Med 2017 Dec 20;9(1):114. Epub 2017 Dec 20.

Division of Psychiatric Genomics, Department of Genetics and Genomic Sciences, Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, 10029, NY, USA.

Background: Integrating rare variation from trio family and case-control studies has successfully implicated specific genes contributing to risk of neurodevelopmental disorders (NDDs) including autism spectrum disorders (ASD), intellectual disability (ID), developmental disorders (DDs), and epilepsy (EPI). For schizophrenia (SCZ), however, while sets of genes have been implicated through the study of rare variation, only two risk genes have been identified.

Methods: We used hierarchical Bayesian modeling of rare-variant genetic architecture to estimate mean effect sizes and risk-gene proportions, analyzing the largest available collection of whole exome sequence data for SCZ (1,077 trios, 6,699 cases, and 13,028 controls), and data for four NDDs (ASD, ID, DD, and EPI; total 10,792 trios, and 4,058 cases and controls).

Results: For SCZ, we estimate there are 1,551 risk genes. There are more risk genes and they have weaker effects than for NDDs. We provide power analyses to predict the number of risk-gene discoveries as more data become available. We confirm and augment prior risk gene and gene set enrichment results for SCZ and NDDs. In particular, we detected 98 new DD risk genes at FDR < 0.05. Correlations of risk-gene posterior probabilities are high across four NDDs (ρ>0.55), but low between SCZ and the NDDs (ρ<0.3). An in-depth analysis of 288 NDD genes shows there is highly significant protein-protein interaction (PPI) network connectivity, and functionally distinct PPI subnetworks based on pathway enrichment, single-cell RNA-seq cell types, and multi-region developmental brain RNA-seq.

Conclusions: We have extended a pipeline used in ASD studies and applied it to infer rare genetic parameters for SCZ and four NDDs ( https://github.com/hoangtn/extTADA ). We find many new DD risk genes, supported by gene set enrichment and PPI network connectivity analyses. We find greater similarity among NDDs than between NDDs and SCZ. NDD gene subnetworks are implicated in postnatally expressed presynaptic and postsynaptic genes, and for transcriptional and post-transcriptional gene regulation in prenatal neural progenitor and stem cells.
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http://dx.doi.org/10.1186/s13073-017-0497-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5738153PMC
December 2017

Time-dependent genetic effects on gene expression implicate aging processes.

Genome Res 2017 04 16;27(4):545-552. Epub 2017 Mar 16.

Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva 4, Switzerland.

Gene expression is dependent on genetic and environmental factors. In the last decade, a large body of research has significantly improved our understanding of the genetic architecture of gene expression. However, it remains unclear whether genetic effects on gene expression remain stable over time. Here, we show, using longitudinal whole-blood gene expression data from a twin cohort, that the genetic architecture of a subset of genes is unstable over time. In addition, we identified 2213 genes differentially expressed across time points that we linked with aging within and across studies. Interestingly, we discovered that most differentially expressed genes were affected by a subset of 77 putative causal genes. Finally, we observed that putative causal genes and down-regulated genes were affected by a loss of genetic control between time points. Taken together, our data suggest that instability in the genetic architecture of a subset of genes could lead to widespread effects on the transcriptome with an aging signature.
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http://dx.doi.org/10.1101/gr.207688.116DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5378173PMC
April 2017

Tissue-specific effects of genetic and epigenetic variation on gene regulation and splicing.

PLoS Genet 2015 Jan 29;11(1):e1004958. Epub 2015 Jan 29.

Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland; Institute of Genetics and Genomics in Geneva (iGE3), Geneva, Switzerland; Swiss Institute of Bioinformatics (SIB), Geneva, Switzerland; Center of Excellence in Genomic Medicine Research, KingAbdulaziz University, Jeddah, Saudi Arabia.

Understanding how genetic variation affects distinct cellular phenotypes, such as gene expression levels, alternative splicing and DNA methylation levels, is essential for better understanding of complex diseases and traits. Furthermore, how inter-individual variation of DNA methylation is associated to gene expression is just starting to be studied. In this study, we use the GenCord cohort of 204 newborn Europeans' lymphoblastoid cell lines, T-cells and fibroblasts derived from umbilical cords. The samples were previously genotyped for 2.5 million SNPs, mRNA-sequenced, and assayed for methylation levels in 482,421 CpG sites. We observe that methylation sites associated to expression levels are enriched in enhancers, gene bodies and CpG island shores. We show that while the correlation between DNA methylation and gene expression can be positive or negative, it is very consistent across cell-types. However, this epigenetic association to gene expression appears more tissue-specific than the genetic effects on gene expression or DNA methylation (observed in both sharing estimations based on P-values and effect size correlations between cell-types). This predominance of genetic effects can also be reflected by the observation that allele specific expression differences between individuals dominate over tissue-specific effects. Additionally, we discover genetic effects on alternative splicing and interestingly, a large amount of DNA methylation correlating to alternative splicing, both in a tissue-specific manner. The locations of the SNPs and methylation sites involved in these associations highlight the participation of promoter proximal and distant regulatory regions on alternative splicing. Overall, our results provide high-resolution analyses showing how genome sequence variation has a broad effect on cellular phenotypes across cell-types, whereas epigenetic factors provide a secondary layer of variation that is more tissue-specific. Furthermore, the details of how this tissue-specificity may vary across inter-relations of molecular traits, and where these are occurring, can yield further insights into gene regulation and cellular biology as a whole.
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http://dx.doi.org/10.1371/journal.pgen.1004958DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4310612PMC
January 2015

Cis and trans effects of human genomic variants on gene expression.

PLoS Genet 2014 Jul 10;10(7):e1004461. Epub 2014 Jul 10.

Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland; Institute of Genetics and Genomics in Geneva (iGE3), Geneva, Switzerland; Swiss Institute of Bioinformatics (SIB), Geneva, Switzerland; Center of Excellence for Genomic Medicine Research, King Abdulaziz University, Jeddah, Saudi Arabia.

Gene expression is a heritable cellular phenotype that defines the function of a cell and can lead to diseases in case of misregulation. In order to detect genetic variations affecting gene expression, we performed association analysis of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) with gene expression measured in 869 lymphoblastoid cell lines of the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort in cis and in trans. We discovered that 3,534 genes (false discovery rate (FDR) = 5%) are affected by an expression quantitative trait locus (eQTL) in cis and 48 genes are affected in trans. We observed that CNVs are more likely to be eQTLs than SNPs. In addition, we found that variants associated to complex traits and diseases are enriched for trans-eQTLs and that trans-eQTLs are enriched for cis-eQTLs. As a variant affecting both a gene in cis and in trans suggests that the cis gene is functionally linked to the trans gene expression, we looked specifically for trans effects of cis-eQTLs. We discovered that 26 cis-eQTLs are associated to 92 genes in trans with the cis-eQTLs of the transcriptions factors BATF3 and HMX2 affecting the most genes. We then explored if the variation of the level of expression of the cis genes were causally affecting the level of expression of the trans genes and discovered several causal relationships between variation in the level of expression of the cis gene and variation of the level of expression of the trans gene. This analysis shows that a large sample size allows the discovery of secondary effects of human variations on gene expression that can be used to construct short directed gene regulatory networks.
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http://dx.doi.org/10.1371/journal.pgen.1004461DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4091791PMC
July 2014

Whole exome sequencing of a dominant retinitis pigmentosa family identifies a novel deletion in PRPF31.

Invest Ophthalmol Vis Sci 2014 Apr 7;55(4):2121-9. Epub 2014 Apr 7.

Virtual Eye Care MD, Mérida, Yucatán, México.

Purpose: Mutations at some retinitis pigmentosa (RP) loci are associated with variable penetrance and expressivity, exacerbating diagnostic challenges. The purpose of this study was to dissect the genetic underpinnings of nonsyndromic RP with variable age of onset in a large Mexican family.

Methods: We ascertained members of a large, multigenerational pedigree using a complete ophthalmic examination. We performed whole exome sequencing on two affected first cousins, an obligate carrier, and a married-in spouse. Confirmatory sequencing of candidate variants was performed in the entire pedigree, as well as genotyping and mRNA studies to investigate expression changes in the causal locus.

Results: We identified a 14-base pair (bp) deletion in PRPF31, a gene implicated previously in autosomal dominant (ad) RP. The mutation segregated with the phenotype of all 10 affected females, but also was present in six asymptomatics (two females and four males). Studies in patient cells showed that the penetrance/expressivity of the PRPF31 deletion allele was concordant with the expression levels of wild-type message. However, neither the known PRPF31 modulators nor cis-eQTLs within 1 Mb of the locus could account for the variable expression of message or the clinical phenotype.

Conclusions: We have identified a novel 14-bp deletion in PRPF31 as the genetic driver of adRP in a large Mexican family that exhibits nonpenetrance and variable expressivity, known properties of this locus. However, our studies intimate the presence of additional loci that can modify PRPF31 expression.
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http://dx.doi.org/10.1167/iovs.13-13827DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3979517PMC
April 2014

Coordinated effects of sequence variation on DNA binding, chromatin structure, and transcription.

Science 2013 Nov 17;342(6159):744-7. Epub 2013 Oct 17.

Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland.

DNA sequence variation has been associated with quantitative changes in molecular phenotypes such as gene expression, but its impact on chromatin states is poorly characterized. To understand the interplay between chromatin and genetic control of gene regulation, we quantified allelic variability in transcription factor binding, histone modifications, and gene expression within humans. We found abundant allelic specificity in chromatin and extensive local, short-range, and long-range allelic coordination among the studied molecular phenotypes. We observed genetic influence on most of these phenotypes, with histone modifications exhibiting strong context-dependent behavior. Our results implicate transcription factors as primary mediators of sequence-specific regulation of gene expression programs, with histone modifications frequently reflecting the primary regulatory event.
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http://dx.doi.org/10.1126/science.1242463DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5502466PMC
November 2013