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Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 92,017 bioRxiv papers from 393,169 authors.

Most downloaded bioRxiv papers, all time

in category genetics

4,664 results found. For more information, click each entry to expand.

81: Efficient lentiviral transduction of different human and mouse cells
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Posted to bioRxiv 25 Jan 2018

Efficient lentiviral transduction of different human and mouse cells
4,205 downloads genetics

Gang Zhang, Taihua Wang

Abstract Background: Lentiviral vectors (LVs) allowing efficient establishment of stable transgene overexpression mammalian and human cell lines are invaluable tools for genetic research. Currently, although LV transductions are broadly adopted, they are often limited due to their low titers for efficient transduction. Results: Here, we described a set of optimized, efficient techniques, which could produce sufficiently high LV titers, and, provide efficient transduction of cells. According to these optimizations, most of the mammalian and human cells, both primary cells and cell lines, could be transduced successfully with high levels of transgene stable expression, including both constitutive and induced expressions. Conclusions: Our data demonstrated the highly usefulness of our optimized methods. Therefore, this study provided an efficient method for most of LV transduction experiments in vitro.

82: CRISPR-Cas9 Gene Editing in Lizards Through Microinjection of Unfertilized Oocytes
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Posted to bioRxiv 31 Mar 2019

CRISPR-Cas9 Gene Editing in Lizards Through Microinjection of Unfertilized Oocytes
4,190 downloads genetics

Ashley M. Rasys, Sungdae Park, Rebecca E. Ball, Aaron J. Alcala, James D. Lauderdale, Douglas B. Menke

CRISPR-cas mediated gene editing has enabled the direct manipulation of gene function in many species. However, the reproductive biology of reptiles presents unique barriers for the use of this technology, and there are currently no reptiles with effective methods for targeted mutagenesis. Here we present a new approach that enables the efficient production of CRISPR-cas induced mutations in Anolis lizards, an important model for studies of reptile evolution and development.

83: Reconstructing Austronesian population history in Island Southeast Asia
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Posted to bioRxiv 27 May 2014

Reconstructing Austronesian population history in Island Southeast Asia
4,171 downloads genetics

Mark Lipson, Po-Ru Loh, Nick Patterson, Priya Moorjani, Ying-Chin Ko, Mark Stoneking, Bonnie Berger, David Reich

Austronesian languages are spread across half the globe, from Easter Island to Madagascar. Evidence from linguistics and archaeology indicates that the "Austronesian expansion," which began 4-5 thousand years ago, likely had roots in Taiwan, but the ancestry of present-day Austronesian-speaking populations remains controversial. Here, focusing primarily on Island Southeast Asia, we analyze genome-wide data from 56 populations using new methods for tracing ancestral gene flow. We show that all sampled Austronesian groups harbor ancestry that is more closely related to aboriginal Taiwanese than to any present-day mainland population. Surprisingly, western Island Southeast Asian populations have also inherited ancestry from a source nested within the variation of present-day populations speaking Austro-Asiatic languages, which have historically been nearly exclusive to the mainland. Thus, either there was once a substantial Austro-Asiatic presence in Island Southeast Asia, or Austronesian speakers migrated to and through the mainland, admixing there before continuing to western Indonesia.

84: Trans effects on gene expression can drive omnigenic inheritance
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Posted to bioRxiv 24 Sep 2018

Trans effects on gene expression can drive omnigenic inheritance
4,167 downloads genetics

Xuanyao Liu, Yang I. Li, Jonathan K Pritchard

Early genome-wide association studies (GWAS) led to the surprising discovery that, for typical complex traits, the most significant genetic variants contribute only a small fraction of the estimated heritability. Instead, it has become clear that a huge number of common variants, each with tiny effects, explain most of the heritability. Previously, we argued that these patterns conflict with standard conceptual models, and that new models are needed. Here we provide a formal model in which genetic contributions to complex traits can be partitioned into direct effects from core genes, and indirect effects from peripheral genes acting as trans-regulators. We argue that the central importance of peripheral genes is a direct consequence of the large contribution of trans-acting variation to gene expression variation. In particular, we propose that if the core genes for a trait are co-regulated - as seems likely - then the effects of peripheral variation can be amplified by these co-regulated networks such that nearly all of the genetic variance is driven by peripheral genes. Thus our model proposes a framework for understanding key features of the architecture of complex traits.

85: The druggable genome and support for target identification and validation in drug development
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Posted to bioRxiv 26 Jul 2016

The druggable genome and support for target identification and validation in drug development
4,125 downloads genetics

Chris Finan, Anna Gaulton, Felix A. Kruger, Tom Lumbers, Tina Shah, Jorgen Engmann, Luana Galver, Ryan Kelley, Anneli Karlsson, Rita Santos, John P. Overington, Aroon D. Hingorani, Juan P Casas

Target identification (identifying the correct drug targets for each disease) and target validation (demonstrating the effect of target perturbation on disease biomarkers and disease end-points) are essential steps in drug development. We showed previously that biomarker and disease endpoint associations of single nucleotide polymorphisms (SNPs) in a gene encoding a drug target accurately depict the effect of modifying the same target with a pharmacological agent; others have shown that genomic support for a target is associated with a higher rate of drug development success. To delineate drug development (including repurposing) opportunities arising from this paradigm, we connected complex disease- and biomarker-associated loci from genome wide association studies (GWAS) to an updated set of genes encoding druggable human proteins, to compounds with bioactivity against these targets and, where these were licensed drugs, to clinical indications. We used this set of genes to inform the design of a new genotyping array, to enable druggable genome-wide association studies for drug target selection and validation in human disease.

86: Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types
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Posted to bioRxiv 25 Jan 2017

Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types
4,117 downloads genetics

Hilary K. Finucane, Yakir A. Reshef, Verneri Anttila, Kamil Slowikowsi, Alexander Gusev, Andrea Byrnes, Steven Gazal, Po-Ru Loh, Caleb Lareau, Noam Shoresh, Giulio Genovese, Arpiar Saunders, Evan Macosko, Samuela Pollack, The Brainstorm Consortium, John R.B. Perry, Jason D Buenrostro, Bradley E. Bernstein, Soumya Raychaudhuri, Steven McCarroll, Benjamin Neale, Alkes L. Price

Genetics can provide a systematic approach to discovering the tissues and cell types relevant for a complex disease or trait. Identifying these tissues and cell types is critical for following up on non-coding allelic function, developing ex-vivo models, and identifying therapeutic targets. Here, we analyze gene expression data from several sources, including the GTEx and PsychENCODE consortia, together with genome-wide association study (GWAS) summary statistics for 48 diseases and traits with an average sample size of 169,331, to identify disease-relevant tissues and cell types. We develop and apply an approach that uses stratified LD score regression to test whether disease heritability is enriched in regions surrounding genes with the highest specific expression in a given tissue. We detect tissue-specific enrichments at FDR < 5% for 34 diseases and traits across a broad range of tissues that recapitulate known biology. In our analysis of traits with observed central nervous system enrichment, we detect an enrichment of neurons over other brain cell types for several brain-related traits, enrichment of inhibitory over excitatory neurons for bipolar disorder but excitatory over inhibitory neurons for schizophrenia and body mass index, and enrichments in the cortex for schizophrenia and in the striatum for migraine. In our analysis of traits with observed immunological enrichment, we identify enrichments of T cells for asthma and eczema, B cells for primary biliary cirrhosis, and myeloid cells for Alzheimer's disease, which we validated with independent chromatin data. Our results demonstrate that our polygenic approach is a powerful way to leverage gene expression data for interpreting GWAS signal.

87: A novel co-segregating DCTN1 splice site variant in a family with Bipolar Disorder may hold the key to understanding the etiology
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Posted to bioRxiv 22 Jun 2018

A novel co-segregating DCTN1 splice site variant in a family with Bipolar Disorder may hold the key to understanding the etiology
4,086 downloads genetics

André Hallen, Arthur J.L. Cooper

A novel co-segregating splice site variant in the Dynactin-1 ( DCTN1 ) gene was discovered by Next Generation Sequencing (NGS) in a family with a history of bipolar disorder (BD) and major depressive diagnosis (MDD). Psychiatric illness in this family follows an autosomal dominant pattern. DCTN1 codes for the largest dynactin subunit, namely p150Glued, which plays an essential role in retrograde axonal transport and in neuronal autophagy. A GT→TT transversion in the DCTN1 gene, uncovered in the present work, is predicted to disrupt the invariant canonical splice donor site IVS22+1G>T and result in intron retention and a premature termination codon (PTC). Thus, this splice site variant is predicted to trigger RNA nonsense-mediated decay (NMD) and/or result in a C-terminal truncated p150Glued protein (ct-p150Glued), thereby negatively impacting retrograde axonal transport and neuronal autophagy. BD prophylactic medications, and most antipsychotics and antidepressants, are known to enhance neuronal autophagy. This variant is analogous to the dominant-negative GLUED Gl 1 mutation in Drosophila which is responsible for a neurodegenerative phenotype. The newly identified variant may reflect an autosomal dominant cause of psychiatric pathology in this affected family. Factors that affect alternative splicing of the DCTN1 gene, leading to NMD and/or ct-p150Glued, may be of fundamental importance in contributing to our understanding of the etiology of BD as well as MDD. * AD : Alzheimer disease ALS : motor neuron disease aPKC : atypical PKC BDI : bipolar disorder I BDII : bipolar disorder II BDIII : bipolar disorder III or cyclothymic disorder ct-p150Glued : C-terminal truncated p150Glued protein DCTN1 : dynactin-1 gene IP3 : myo -inositol-1,4,5-trisphosphate MDD : major depressive diagnosis NMD : RNA nonsense-mediated decay NGS : next generation sequencing PD : Parkinson disease PKC : protein kinase C PS : Perry syndrome PTC : premature termination codon WES : whole exome sequencing.

88: Re-evaluation of SNP heritability in complex human traits
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Posted to bioRxiv 09 Sep 2016

Re-evaluation of SNP heritability in complex human traits
4,036 downloads genetics

Doug Speed, Na Cai, The UCLEB Consortium, Michael R. Johnson, Sergey Nejentsev, David J Balding

SNP heritability, the proportion of phenotypic variance explained by SNPs, has been reported for many hundreds of traits. Its estimation requires strong prior assumptions about the distribution of heritability across the genome, but the assumptions in current use have not been thoroughly tested. By analyzing imputed data for a large number of human traits, we empirically derive a model that more accurately describes how heritability varies with minor allele frequency, linkage disequilibrium and genotype certainty. Across 19 traits, our improved model leads to estimates of common SNP heritability on average 43% (SD 3) higher than those obtained from the widely-used software GCTA, and 25% (SD 2) higher than those from the recently-proposed extension GCTA-LDMS. Previously, DNaseI hypersensitivity sites were reported to explain 79% of SNP heritability; using our improved heritability model their estimated contribution is only 24%.

89: An interlaboratory study of complex variant detection
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Posted to bioRxiv 23 Nov 2017

An interlaboratory study of complex variant detection
4,009 downloads genetics

Stephen E. Lincoln, Justin M Zook, Shimul Chowdhury, Shazia Mahamdallie, Andrew Fellowes, Eric W Klee, Rebecca Truty, Catherine Huang, Farol L Tomson, Megan H Cleveland, Peter M Vallone, Yan Ding, Sheila Seal, Wasanthi DeSilva, Russell K Garlick, Marc Salit, Nazneen Rahman, Stephen F Kingsmore, Swaroop Aradhya, Robert L. Nussbaum, Matthew J Ferber, Brian H Shirts

Purpose: Next-generation sequencing (NGS) is widely used and cost-effective. Depending on the specific methods, NGS can have limitations detecting certain technically challenging variant types even though they are both prevalent in patients and medically important. These types are underrepresented in validation studies, hindering the uniform assessment of test methodologies by laboratory directors and clinicians. Specimens containing such variants can be difficult to obtain; thus, we evaluated a novel solution to this problem. Methods: A diverse set of technically challenging variants was synthesized and introduced into a known genomic background. This specimen was sequenced by 7 laboratories using 10 different NGS workflows. Results: The specimen was compatible with all 10 workflows and presented biochemical and bioinformatic challenges similar to those of patient specimens. Only 10 of 22 challenging variants were correctly identified by all 10 workflows, and only 3 workflows detected all 22. Many, but not all, of the sensitivity limitations were bioinformatic in nature. Conclusions: Synthetic controls can provide an efficient and informative mechanism to augment studies with technically challenging variants that are difficult to obtain otherwise. Data from such specimens can facilitate inter-laboratory methodologic comparisons and can help establish standards that improve communication between clinicians and laboratories.

90: Genomic analysis of family data reveals additional genetic effects on intelligence and personality
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Posted to bioRxiv 06 Feb 2017

Genomic analysis of family data reveals additional genetic effects on intelligence and personality
3,988 downloads genetics

W. David Hill, Ruben C. Arslan, Charley Xia, Michelle Luciano, Carmen Amador, Pau Navarro, Caroline Hayward, Reka Nagy, David J. Porteous, Andrew M. McIntosh, I.J. Deary, Chris S. Haley, Lars Penke

Pedigree-based analyses of intelligence have reported that genetic differences account for 50-80% of the phenotypic variation. For personality traits these effects are smaller, with 34-48% of the variance being explained by genetic differences. However, molecular genetic studies using unrelated individuals typically report a heritability estimate of around 30% for intelligence and between 0% and 15% for personality variables. Pedigree-based estimates and molecular genetic estimates may differ because current genotyping platforms are poor at tagging causal variants, variants with low minor allele frequency, copy number variants, and structural variants. Using ~20 000 individuals in the Generation Scotland family cohort genotyped for ~700 000 single nucleotide polymorphisms (SNPs), we exploit the high levels of linkage disequilibrium (LD) found in members of the same family to quantify the total effect of genetic variants that are not tagged in GWASs of unrelated individuals. In our models, genetic variants in low LD with genotyped SNPs explain over half of the genetic variance in intelligence, education, and neuroticism. By capturing these additional genetic effects our models closely approximate the heritability estimates from twin studies for intelligence and education, but not for neuroticism and extraversion. We then replicated our finding using imputed molecular genetic data from unrelated individuals to show that ~50% of differences in intelligence, and ~40% of the differences in education, can be explained by genetic effects when a larger number of rare SNPs are included. From an evolutionary genetic perspective, a substantial contribution of rare genetic variants to individual differences in intelligence and education is consistent with mutation-selection balance.

91: Beyond power: Multivariate discovery, replication, and interpretation of pleiotropic loci using summary association statistics
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Posted to bioRxiv 08 Jul 2015

Beyond power: Multivariate discovery, replication, and interpretation of pleiotropic loci using summary association statistics
3,966 downloads genetics

Zheng Ning, Yakov A. Tsepilov, Sodbo Zh. Sharapov, Alexander K. Grishenko, Xiao Feng, Masoud Shirali, Peter K Joshi, James F Wilson, Yudi Pawitan, Chris S. Haley, Yurii S Aulchenko, Xia Shen

The ever-growing genome-wide association studies (GWAS) have revealed widespread pleiotropy. To exploit this, various methods which consider variant association with multiple traits jointly have been developed. However, most effort has been put on improving discovery power: how to replicate and interpret these discovered pleiotropic loci using multivariate methods has yet to be discussed fully. Using only multiple publicly available single-trait GWAS summary statistics, we develop a fast and flexible multi-trait framework that contains modules for (i) multi-trait genetic discovery, (ii) replication of locus pleiotropic profile, and (iii) multi-trait conditional analysis. The procedure is able to handle any level of sample overlap. As an empirical example, we discovered and replicated 23 novel pleiotropic loci for human anthropometry and evaluated their pleiotropic effects on other traits. By applying conditional multivariate analysis on the 23 loci, we discovered and replicated two additional multi-trait associated SNPs. Our results provide empirical evidence that multi-trait analysis allows detection of additional, replicable, highly pleiotropic genetic associations without genotyping additional individuals. The methods are implemented in a free and open source R package MultiABEL. Author summary By analyzing large-scale genomic data, geneticists have revealed widespread pleiotropy, i.e. single genetic variation can affect a wide range of complex traits. Methods have been developed to discover such genetic variants. However, we still lack insights into the relevant genetic architecture - What more can we learn from knowing the effects of these genetic variants? Here, we develop a fast and flexible statistical analysis procedure that includes discovery, replication, and interpretation of pleiotropic effects. The whole analysis pipeline only requires established genetic association study results. We also provide the mathematical theory behind the pleiotropic genetic effects testing. Most importantly, we show how a replication study can be essential to reveal new biology rather than solely increasing sample size in current genomic studies. For instance, we show that, using our proposed replication strategy, we can detect the difference in genetic effects between studies of different geographical origins. We applied the method to the GIANT consortium anthropometric traits to discover new genetic associations, replicated in the UK Biobank, and provided important new insights into growth and obesity. Our pipeline is implemented in an open-source R package MultiABEL, sufficiently efficient that allows researchers to immediately apply on personal computers in minutes.

92: Phenome-wide Heritability Analysis of the UK Biobank
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Posted to bioRxiv 18 Aug 2016

Phenome-wide Heritability Analysis of the UK Biobank
3,955 downloads genetics

Tian Ge, Chia-Yen Chen, Benjamin Neale, Mert R. Sabuncu, Jordan W Smoller

Heritability estimation provides important information about the relative contribution of genetic and environmental factors to phenotypic variation, and provides an upper bound for the utility of genetic risk prediction models. Recent technological and statistical advances have enabled the estimation of additive heritability attributable to common genetic variants (SNP heritability) across a broad phenotypic spectrum. However, assessing the comparative heritability of multiple traits estimated in different cohorts may be misleading due to the population-specific nature of heritability. Here we report the SNP heritability for 551 complex traits derived from the large-scale, population-based UK Biobank, comprising both quantitative phenotypes and disease codes, and examine the moderating effect of three major demographic variables (age, sex and socioeconomic status) on the heritability estimates. Our study represents the first comprehensive phenome-wide heritability analysis in the UK Biobank, and underscores the importance of considering population characteristics in comparing and interpreting heritability.

93: The nature of nurture: effects of parental genotypes
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Posted to bioRxiv 14 Nov 2017

The nature of nurture: effects of parental genotypes
3,938 downloads genetics

Augustine Kong, Gudmar Thorleifsson, Michael L. Frigge, Bjarni J. Vilhjálmsson, Alexander I. Young, Thorgeir E. Thorgeirsson, Stefania Benonisdottir, Asmundur Oddsson, Bjarni V. Halldórsson, Gísli Masson, Daniel F. Gudbjartsson, Agnar Helgason, Gyda Bjornsdottir, Unnur Thorsteinsdottir, Kári Stefánsson

Sequence variants in the parental genomes that are not transmitted to a child/proband are often ignored in genetic studies. Here we show that non-transmitted alleles can impact a child through their effects on the parents and other relatives, a phenomenon we call genetic nurture. Using results from a meta-analysis of educational attainment, the polygenic score computed for the non-transmitted alleles of 21,637 probands with at least one parent genotyped has an estimated effect on the educational attainment of the proband that is 29.9% (P = 1.6×10-14) of that of the transmitted polygenic score. Genetic nurturing effects of this polygenic score extend to other traits. Paternal and maternal polygenic scores have similar effects on educational attainment, but mothers contribute more than fathers to nutrition/heath related traits.

94: Are drug targets with genetic support twice as likely to be approved? Revised estimates of the impact of genetic support for drug mechanisms on the probability of drug approval.
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Posted to bioRxiv 08 Jan 2019

Are drug targets with genetic support twice as likely to be approved? Revised estimates of the impact of genetic support for drug mechanisms on the probability of drug approval.
3,910 downloads genetics

Emily A. King, J Wade Davis, Jacob F Degner

Despite strong vetting for disease activity, only 10% of candidate new molecular entities in early stage clinical trials are eventually approved. Analyzing historical pipeline data, Nelson et al. 2015 (Nat. Genet.) concluded pipeline drug targets with human genetic evidence of disease association are twice as likely to lead to approved drugs. Taking advantage of recent clinical development advances and rapid growth in GWAS datasets, we extend the original work using updated data, test whether genetic evidence predicts future successes and introduce statistical models adjusting for target and indication-level properties. Our work confirms drugs with genetically supported targets were more likely to be successful in Phases II and III. When causal genes are clear (Mendelian traits and GWAS associations linked to coding variants), we find the use of human genetic evidence increases approval from Phase I by greater than two-fold, and, for Mendelian associations, the positive association holds prospectively. Our findings suggest investments into genomics and genetics are likely to be beneficial to companies deploying this strategy.

95: CRISPR-Cas9 Screens In Human Cells And Primary Neurons Identify Modifiers Of C9orf72 Dipeptide Repeat Protein Toxicity
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Posted to bioRxiv 21 Apr 2017

CRISPR-Cas9 Screens In Human Cells And Primary Neurons Identify Modifiers Of C9orf72 Dipeptide Repeat Protein Toxicity
3,878 downloads genetics

Michael S. Haney, Nicholas J. Kramer, David W Morgens, Ana Jovičić, Julien Couthouis, Amy Li, James Ousey, Rosanna Ma, Gregor Bieri, Michael C. Bassik, Aaron D. Gitler

Hexanucleotide repeat expansions in the C9orf72 gene are the most common cause of amyotrophic lateral sclerosis and frontotemporal dementia (c9FTD/ALS). The nucleotide repeat expansions are translated into dipeptide repeat (DPR) proteins, which are aggregation-prone and may contribute to neurodegeneration. Studies in model organisms, including yeast and flies have converged upon nucleocytoplasmic transport as one underlying pathogenic mechanism, but a comprehensive understanding of the molecular and cellular underpinnings of DPR toxicity in human cells is still lacking. We used the bacteria-derived clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 system to perform genome-wide gene knockout screens for suppressors and enhancers of C9orf72 DPR toxicity in human cells. We validated hits by performing secondary CRISPR-Cas9 screens in primary mouse neurons. Our screens revealed genes involved in nucleocytoplasmic transport, reinforcing the previous findings from model systems. We also uncovered new potent modifiers of DPR toxicity whose gene products function in the endoplasmic reticulum (ER), proteasome, RNA processing pathways, and in chromatin modification. Since regulators of ER stress emerged prominently from the screens, we further investigated one such modifier, TMX2, which we identified as a modulator of the ER-stress signature elicited by C9orf72 DPRs in neurons. Together, this work identifies novel suppressors of DPR toxicity that represent potential therapeutic targets and demonstrates the promise of CRISPR-Cas9 screens to define mechanisms of neurodegenerative diseases.

96: Modified penetrance of coding variants by cis-regulatory variation shapes human traits
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Posted to bioRxiv 18 Sep 2017

Modified penetrance of coding variants by cis-regulatory variation shapes human traits
3,877 downloads genetics

Stephane E. Castel, Alejandra Cervera, Pejman Mohammadi, François Aguet, Ferran Reverter, Aaron Wolman, Roderic Guigó, Ivan Iossifov, Ana Vasileva, Tuuli Lappalainen

Coding variants represent many of the strongest associations between genotype and phenotype, however they exhibit inter-individual differences in effect, known as variable penetrance. In this work, we study how cis-regulatory variation modifies the penetrance of coding variants in their target gene. Using functional genomic and genetic data from GTEx, we observed that in the general population, purifying selection has depleted haplotype combinations that lead to higher penetrance of pathogenic coding variants. Conversely, in cancer and autism patients, we observed an enrichment of haplotype combinations that lead to higher penetrance of pathogenic coding variants in disease implicated genes, which provides direct evidence that regulatory haplotype configuration of causal coding variants affects disease risk. Finally, we experimentally demonstrated that a regulatory variant can modify the penetrance of a coding variant by introducing a Mendelian SNP using CRISPR/Cas9 on distinct expression haplotypes and using the transcriptome as a phenotypic readout. Our results demonstrate that joint effects of regulatory and coding variants are an important part of the genetic architecture of human traits, and contribute to modified penetrance of disease-causing variants.

97: Genomic risk prediction of coronary artery disease in nearly 500,000 adults: implications for early screening and primary prevention
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Posted to bioRxiv 19 Jan 2018

Genomic risk prediction of coronary artery disease in nearly 500,000 adults: implications for early screening and primary prevention
3,876 downloads genetics

Michael Inouye, Gad Abraham, Christopher P Nelson, Angela M. Wood, Michael J Sweeting, Frank Dudbridge, Florence Y Lai, Stephen Kaptoge, Marta Brozynska, Tingting Wang, Shu Ye, Thomas R. Webb, Martin K Rutter, Ioanna Tzoulaki, Riyaz S Patel, Ruth J.F. Loos, Bernard Keavney, Harry Hemingway, John Thompson, Hugh Watkins, Panos Deloukas, Emanuele Di Angelantonio, Adam S. Butterworth, John Danesh, Nilesh J. Samani, for The UK Biobank CardioMetabolic Consortium CHD Working Group

Background: Coronary artery disease (CAD) has substantial heritability and a polygenic architecture; however, genomic risk scores have not yet leveraged the totality of genetic information available nor been externally tested at population-scale to show potential utility in primary prevention. Methods: Using a meta-analytic approach to combine large-scale genome-wide and targeted genetic association data, we developed a new genomic risk score for CAD (metaGRS), consisting of 1.7 million genetic variants. We externally tested metaGRS, individually and in combination with available conventional risk factors, in 22,242 CAD cases and 460,387 non-cases from UK Biobank. Findings: In UK Biobank, a standard deviation increase in metaGRS had a hazard ratio (HR) of 1.71 (95% CI 1.68-1.73) for CAD, greater than any other externally tested genetic risk score. Individuals in the top 20% of the metaGRS distribution had a HR of 4.17 (95% CI 3.97-4.38) compared with those in the bottom 20%. The metaGRS had higher C-index (C=0.623, 95% CI 0.615-0.631) for incident CAD than any of four conventional factors (smoking, diabetes, hypertension, and body mass index), and addition of the metaGRS to a model of conventional risk factors increased C-index by 3.7%. In individuals on lipid-lowering or anti-hypertensive medications at recruitment, metaGRS hazard for incident CAD was significantly but only partially attenuated with HR of 2.83 (95% CI 2.61-3.07) between the top and bottom 20% of the metaGRS distribution. Interpretation: Recent genetic association studies have yielded enough information to meaningfully stratify individuals using the metaGRS for CAD risk in both early and later life, thus enabling targeted primary intervention in combination with conventional risk factors. The metaGRS effect was partially attenuated by lipid and blood pressure-lowering medication, however other prevention strategies will be required to fully benefit from earlier genomic risk stratification.

98: Neurodevelopmental disease genes implicated by de novo mutation and CNV morbidity
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Posted to bioRxiv 28 Oct 2017

Neurodevelopmental disease genes implicated by de novo mutation and CNV morbidity
3,794 downloads genetics

Bradley P. Coe, Holly A.F. Stessman, Arvis Sulovari, Madeleine Geisheker, Fereydoun Hormozdiari, E. E. Eichler

We combined de novo mutation (DNM) data from 10,927 cases of developmental delay and autism to identify 301 candidate neurodevelopmental disease genes showing an excess of missense and/or likely gene-disruptive (LGD) mutations. 164 genes were predicted by two different DNM models, including 116 genes with an excess of LGD mutations. Among the 301 genes, 76% show DNM in both autism and intellectual disability/developmental delay cohorts where they occur in 10.3% and 28.4% of the cases, respectively. Intersecting these results with copy number variation (CNV) morbidity data identifies a significant enrichment for the intersection of our gene set and genomic disorder regions (36/301, LR+ 2.53, p=0.0005). This analysis confirms many recurrent LGD genes and CNV deletion syndromes (e.g., KANSL1, PAFAH1B1, RA1, etc.), consistent with a model of haploinsufficiency. We also identify genes with an excess of missense DNMs overlapping deletion syndromes (e.g., KIF1A and the 2q37 deletion) as well as duplication syndromes, such as recurrent MAPK3 missense mutations within the chromosome 16p11.2 duplication, recurrent CHD4 missense DNMs in the 12p13 duplication region, and recurrent WDFY4 missense DNMs in the 10q11.23 duplication region. Finally, we also identify pathogenic CNVs overlapping more than one recurrently mutated gene (e.g., Sotos and Kleefstra syndromes) raising the possibility that multiple gene-dosage imbalances may contribute to phenotypic complexity of these disorders. Network analyses of genes showing an excess of DNMs confirm previous well-known enrichments but also highlight new functional networks, including cell-specific enrichments in the D1+ and D2+ spiny neurons of the striatum for both recurrently mutated genes and genes where missense mutations cluster.

99: Environmental factors dominate over host genetics in shaping human gut microbiota composition
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Posted to bioRxiv 16 Jun 2017

Environmental factors dominate over host genetics in shaping human gut microbiota composition
3,778 downloads genetics

Daphna Rothschild, Omer Weissbrod, Elad Barkan, Tal Korem, David Zeevi, Paul I Costea, Anastasia Godneva, Iris Kalka, Noam Bar, Niv Zmora, Meirav Pevsner-Fischer, David Israeli, Noa Kosower, Gal Malka, Bat Chen Wolf, Tali Avnit-Sagi, Maya Lotan-Pompan, Adina Weinberger, Zamir Halpern, Shai Carmi, Eran Elinav, Eran Segal

Human gut microbiome composition is shaped by multiple host intrinsic and extrinsic factors, but the relative contribution of host genetic compared to environmental factors remains elusive. Here, we genotyped a cohort of 696 healthy individuals from several distinct ancestral origins and a relatively common environment, and demonstrate that there is no statistically significant association between microbiome composition and ethnicity, single nucleotide polymorphisms (SNPs), or overall genetic similarity, and that only 5 of 211 (2.4%) previously reported microbiome-SNP associations replicate in our cohort. In contrast, we find similarities in the microbiome composition of genetically unrelated individuals who share a household. We define the term biome-explainability as the variance of a host phenotype explained by the microbiome after accounting for the contribution of human genetics. Consistent with our finding that microbiome and host genetics are largely independent, we find significant biome-explainability levels of 16-33% for body mass index (BMI), fasting glucose, high-density lipoprotein (HDL) cholesterol, waist circumference, waist-hip ratio (WHR), and lactose consumption. We further show that several human phenotypes can be predicted substantially more accurately when adding microbiome data to host genetics data, and that the contribution of both data sources to prediction accuracy is largely additive. Overall, our results suggest that human microbiome composition is dominated by environmental factors rather than by host genetics.

100: Robust genome editing with short single-stranded and long, partially single-stranded DNA donors in C. elegans
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Posted to bioRxiv 20 Jun 2018

Robust genome editing with short single-stranded and long, partially single-stranded DNA donors in C. elegans
3,691 downloads genetics

Gregoriy A. Dokshin, Krishna S. Ghanta, Katherine M Piscopo, Craig C Mello

CRISPR-based genome editing using ribonucleoprotein (RNP) complexes and synthetic single stranded oligodeoxynucleotide (ssODN) donors can be highly effective. However, reproducibility can vary, and precise, targeted integration of longer constructs – such as green fluorescent protein (GFP) tags remains challenging in many systems. Here we describe a streamlined and optimized editing protocol for the nematode C. elegans. We demonstrate its efficacy, flexibility, and cost-effectiveness by affinity-tagging all twelve of the Worm-specific Argonaute (WAGO) proteins in C. elegans using ssODN donors. In addition, we describe a novel PCR-based partially single-stranded "hybrid" donor design that yields high efficiency editing with large (kilobase-scale) constructs. We use these hybrid donors to introduce fluorescent protein tags into multiple loci achieving editing efficiencies that approach those previously obtained only with much shorter ssODN donors. The principals and strategies described here are likely to translate to other systems and should allow researchers to reproducibly and efficiently obtain both long and short precision genome edits.

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