101
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Seldin MM, Lusis AJ. Systems-based approaches for investigation of inter-tissue communication. J Lipid Res 2019; 60:450-455. [PMID: 30617149 PMCID: PMC6399495 DOI: 10.1194/jlr.s090316] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2018] [Revised: 12/27/2018] [Indexed: 11/23/2022] Open
Abstract
Secreted proteins serve as crucial mediators of many physiology processes, and beginning with the discovery of insulin, studies have revealed numerous context-specific regulatory networks across various cell types. Here, we review “omics” approaches to deconvolute the complex milieu of proteins that are released from the cell. We emphasize a novel “systems genetics” approach our laboratory has developed to investigate mechanisms of tissue-tissue communication using population-based datasets. Finally, we highlight potential future directions for these studies, discuss several caveats, and propose new ways to investigate modes of endocrine communication.
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Affiliation(s)
- Marcus M Seldin
- Departments of Medicine, University of California, Los Angeles, Los Angeles, CA 90095
| | - Aldons J Lusis
- Departments of Medicine, University of California, Los Angeles, Los Angeles, CA 90095 .,Human Genetics University of California, Los Angeles, Los Angeles, CA 90095.,Microbiology, Immunology, and Molecular Genetics University of California, Los Angeles, Los Angeles, CA 90095
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102
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Carrasco-Valenzuela T, Muñoz-Espinoza C, Riveros A, Pedreschi R, Arús P, Campos-Vargas R, Meneses C. Expression QTL (eQTLs) Analyses Reveal Candidate Genes Associated With Fruit Flesh Softening Rate in Peach [ Prunus persica (L.) Batsch]. FRONTIERS IN PLANT SCIENCE 2019; 10:1581. [PMID: 31850046 PMCID: PMC6901599 DOI: 10.3389/fpls.2019.01581] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Accepted: 11/12/2019] [Indexed: 05/22/2023]
Abstract
Significant differences in softening rate have been reported between melting flesh in peach and nectarine varieties. This trait seems to be controlled by several genes. We aimed to identify candidate genes involved in fruit softening rate by integrating quantitative trait loci (QTL) and expression QTL (eQTL) analyses, comparing siblings with contrasting softening rates. We used a segregating population derived from nectarine cv. 'Venus' selfing, which was phenotyped for softening rate during three seasons. Six siblings with high (HSR) and six with low softening rate (LSR) were sequenced using RNA-Seq. A group of 5,041 differentially expressed genes was identified. Also, we found a QTL with a LOD (logarithm of odds) score of 9.7 on LG4 in all analyzed seasons. Furthermore, we detected 1,062 eQTLs, of which 133 were found co-localizing with the identified QTL. Gene Ontology (GO) analysis showed 'Response to auxin' as one the main over-represented categories. Our findings suggest over-expression of auxin biosynthetic related genes in the HSR group, which implies a higher expression and/or accumulation of auxin, thereby triggering fast softening. Conversely, the LSR phenotype might be explained by an altered auxin-homeostasis associated with low auxin levels. This work will contribute to unraveling the genetic mechanisms responsible for the softening rate in peaches and nectarines and lead to the development of molecular markers.
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Affiliation(s)
- Tomás Carrasco-Valenzuela
- Centro de Biotecnología Vegetal, Facultad de Ciencias de la Vida, Universidad Andres Bello, Santiago, Chile
| | - Claudia Muñoz-Espinoza
- Centro de Biotecnología Vegetal, Facultad de Ciencias de la Vida, Universidad Andres Bello, Santiago, Chile
| | - Aníbal Riveros
- Centro de Biotecnología Vegetal, Facultad de Ciencias de la Vida, Universidad Andres Bello, Santiago, Chile
| | - Romina Pedreschi
- Escuela de Agronomía, Pontificia Universidad Católica de Valparaíso, Quillota, Chile
| | - Pere Arús
- IRTA, Centre de Recerca en Agrigenòmica (CSIC-IRTA-UAB-UB), Barcelona, Spain
| | - Reinaldo Campos-Vargas
- Centro de Biotecnología Vegetal, Facultad de Ciencias de la Vida, Universidad Andres Bello, Santiago, Chile
| | - Claudio Meneses
- Centro de Biotecnología Vegetal, Facultad de Ciencias de la Vida, Universidad Andres Bello, Santiago, Chile
- FONDAP Center for Genome Regulation, Santiago, Chile
- *Correspondence: Claudio Meneses,
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103
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Sheng Q, Samuels DC, Yu H, Ness S, Zhao YY, Guo Y. Cancer-specific expression quantitative loci are affected by expression dysregulation. Brief Bioinform 2018; 21:338-347. [PMID: 30475999 DOI: 10.1093/bib/bby108] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Revised: 10/05/2018] [Accepted: 10/10/2018] [Indexed: 02/05/2023] Open
Abstract
Expression quantitative trait loci (eQTLs) have been touted as the missing piece that can bridge the gap between genetic variants and phenotypes. Over the past decade, we have witnessed a sharp rise of effort in the identification and application of eQTLs. The successful application of eQTLs relies heavily on their reproducibility. The current eQTL databases such as Genotype-Tissue Expression (GTEx) were populated primarily with eQTLs deriving from germline single nucleotide polymorphisms and normal tissue gene expression. The novel scenarios that employ eQTL models for prediction purposes often involve disease phenotypes characterized by altered gene expressions. To evaluate eQTL reproducibility across diverse data sources and the effect of disease-specific gene expression alteration on eQTL identification, we conducted an eQTL study using 5178 samples from The Cancer Genome Atlas (TCGA). We found that the reproducibility of eQTLs between normal and tumor tissues was low in terms of the number of shared eQTLs. However, among the shared eQTLs, the effect directions were generally concordant. This suggests that the source of the gene expression (normal or tumor tissue) has a strong effect on the detectable eQTLs and the effect direction of the eQTLs. Additional analyses demonstrated good directional concordance of eQTLs between GTEx and TCGA. Furthermore, we found that multi-tissue eQTLs may exert opposite effects across multiple tissue types. In summary, our results suggest that eQTL prediction models need to carefully address tissue and disease dependency of eQTLs. Tissue-disease-specific eQTL databases can afford more accurate prediction models for future studies.
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Affiliation(s)
- Quanhu Sheng
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - David C Samuels
- Vanderbilt Genetics Institute, Dept. of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, TN, USA
| | - Hui Yu
- Department of Internal Medicine, University of New Mexico, Albuquerque, NM, USA
| | - Scott Ness
- Department of Internal Medicine, University of New Mexico, Albuquerque, NM, USA
| | - Ying-Yong Zhao
- Key Laboratory of Resource Biology and Biotechnology in Western China, School of Life Sciences, Northwest University, Xi'an, Shaanxi, China
| | - Yan Guo
- Department of Internal Medicine, University of New Mexico, Albuquerque, NM, USA
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104
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Al-Barghouthi BM, Farber CR. Dissecting the Genetics of Osteoporosis using Systems Approaches. Trends Genet 2018; 35:55-67. [PMID: 30470485 DOI: 10.1016/j.tig.2018.10.004] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2018] [Revised: 10/01/2018] [Accepted: 10/22/2018] [Indexed: 02/06/2023]
Abstract
Osteoporosis is a condition characterized by low bone mineral density (BMD) and an increased risk of fracture. Traits contributing to osteoporotic fracture are highly heritable, indicating that a comprehensive understanding of bone requires a thorough understanding of the genetic basis of bone traits. Towards this goal, genome-wide association studies (GWASs) have identified over 500 loci associated with bone traits. However, few of the responsible genes have been identified, and little is known of how these genes work together to influence systems-level bone function. In this review, we describe how systems genetics approaches can be used to fill these knowledge gaps.
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Affiliation(s)
- Basel M Al-Barghouthi
- Center for Public Health Genomics, Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA 22908, USA
| | - Charles R Farber
- Center for Public Health Genomics, Departments of Public Health Sciences and Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA 22908, USA.
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105
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Kara S, Pirela-Morillo GA, Gilliam CT, Wilson GD. Identification of novel susceptibility genes associated with seven autoimmune disorders using whole genome molecular interaction networks. J Autoimmun 2018; 97:48-58. [PMID: 30391024 DOI: 10.1016/j.jaut.2018.10.002] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2018] [Revised: 10/08/2018] [Accepted: 10/11/2018] [Indexed: 12/20/2022]
Abstract
Convergent evidence from multiple and independent genetics studies implicate a small number of genes that predispose individuals to multiple autoimmune disorders (AuD). These intersecting loci reinforced the hypothesis that disorders with overlapping etiology group into a cluster of closely related genes within a whole genome molecular interaction network. We tested the hypothesis that "biological network proximity" within a whole genome molecular interaction network can be used to inform the search for multigene inheritance. Using a set of nine previously published genome wide association studies (GWAS) of AuD genes, we generated AuD-specific molecular interaction networks to identify networks of associated genes. We show that all nine "seed genes" can be connected within a 35-member network via interactions with 26 connecting genes. We show that this network is more connected than expected by chance, and 13 of the connecting genes showed association with multiple AuD upon GWAS reanalysis. Furthermore, we report association of SNPs in five new genes (IL10RA, DGKA, GRB2, STAT5A, and NFATC2) which were not previously considered as AuD candidates, and show significant association in novel disease samples of Crohn's disease and systemic lupus erythematosus. Furthermore, we show that the connecting genes show no association in four non-AuD GWAS. Finally, we test the connecting genes in psoriasis GWAS, and show association to previously identified loci and report new loci. These findings support the hypothesis that molecular interaction networks can be used to inform the search for multigene disease etiology, especially for disorders with overlapping etiology.
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Affiliation(s)
- Sam Kara
- University of Chicago, Departments of Human Genetics, 920 East 58 th St., Chicago, IL 60637, USA; Radiation Oncology Department, Beaumont Health, 3811 W Thirteen Mile Road, Royal Oak, MI, 48073, USA
| | - Gerardo A Pirela-Morillo
- La Universidad del Zulia, Computer Science Department, Laboratories for Computational Models & Languages, and Bioinformatics, Edif. Grano de Oro, Planta Baja, Departamento de Computación, Ave. Universidad con Ave. 22, Maracaibo, 4002, Venezuela
| | - Conrad T Gilliam
- University of Chicago, Departments of Human Genetics, 920 East 58 th St., Chicago, IL 60637, USA
| | - George D Wilson
- Radiation Oncology Department, Beaumont Health, 3811 W Thirteen Mile Road, Royal Oak, MI, 48073, USA.
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106
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Albert E, Duboscq R, Latreille M, Santoni S, Beukers M, Bouchet JP, Bitton F, Gricourt J, Poncet C, Gautier V, Jiménez-Gómez JM, Rigaill G, Causse M. Allele-specific expression and genetic determinants of transcriptomic variations in response to mild water deficit in tomato. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2018; 96:635-650. [PMID: 30079488 DOI: 10.1111/tpj.14057] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Revised: 07/31/2018] [Accepted: 08/02/2018] [Indexed: 06/08/2023]
Abstract
Characterizing the natural diversity of gene expression across environments is an important step in understanding how genotype-by-environment interactions shape phenotypes. Here, we analyzed the impact of water deficit onto gene expression levels in tomato at the genome-wide scale. We sequenced the transcriptome of growing leaves and fruit pericarps at cell expansion stage in a cherry and a large fruited accession and their F1 hybrid grown under two watering regimes. Gene expression levels were steadily affected by the genotype and the watering regime. Whereas phenotypes showed mostly additive inheritance, ~80% of the genes displayed non-additive inheritance. By comparing allele-specific expression (ASE) in the F1 hybrid to the allelic expression in both parental lines, respectively, 3005 genes in leaf and 2857 genes in fruit deviated from 1:1 ratio independently of the watering regime. Among these genes, ~55% were controlled by cis factors, ~25% by trans factors and ~20% by a combination of both types of factors. A total of 328 genes in leaf and 113 in fruit exhibited significant ASE-by-watering regime interaction, among which ~80% presented trans-by-watering regime interaction, suggesting a response to water deficit mediated through a majority of trans-acting loci in tomato. We cross-validated the expression levels of 274 transcripts in fruit and leaves of 124 recombinant inbred lines (RILs) and identified 163 expression quantitative trait loci (eQTLs) mostly confirming the divergences identified by ASE. Combining phenotypic and expression data, we observed a complex network of variation between genes encoding enzymes involved in the sugar metabolism.
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Affiliation(s)
- Elise Albert
- INRA, UR1052, Centre de Recherche PACA, Génétique et Amélioration des Fruits et Légumes, 67 Allée des Chênes, Domaine Saint Maurice, CS60094, Montfavet, 84143, France
| | - Renaud Duboscq
- INRA, UR1052, Centre de Recherche PACA, Génétique et Amélioration des Fruits et Légumes, 67 Allée des Chênes, Domaine Saint Maurice, CS60094, Montfavet, 84143, France
| | - Muriel Latreille
- INRA, UMR1334, Amélioration génétique et Adaptation des Plantes, Montpellier SupAgro-INRA-IRD-UMII, 2 Place Pierre Viala, Montpellier, 34060, France
| | - Sylvain Santoni
- INRA, UMR1334, Amélioration génétique et Adaptation des Plantes, Montpellier SupAgro-INRA-IRD-UMII, 2 Place Pierre Viala, Montpellier, 34060, France
| | - Matthieu Beukers
- INRA, UR1052, Centre de Recherche PACA, Génétique et Amélioration des Fruits et Légumes, 67 Allée des Chênes, Domaine Saint Maurice, CS60094, Montfavet, 84143, France
| | - Jean-Paul Bouchet
- INRA, UR1052, Centre de Recherche PACA, Génétique et Amélioration des Fruits et Légumes, 67 Allée des Chênes, Domaine Saint Maurice, CS60094, Montfavet, 84143, France
| | - Fréderique Bitton
- INRA, UR1052, Centre de Recherche PACA, Génétique et Amélioration des Fruits et Légumes, 67 Allée des Chênes, Domaine Saint Maurice, CS60094, Montfavet, 84143, France
| | - Justine Gricourt
- INRA, UR1052, Centre de Recherche PACA, Génétique et Amélioration des Fruits et Légumes, 67 Allée des Chênes, Domaine Saint Maurice, CS60094, Montfavet, 84143, France
| | - Charles Poncet
- INRA, UMR1095, Génétique Diversité et Ecophysiologie des Céréales, 5 Chemin de Beaulieu, Clermont-Ferrand, 63039, France
| | - Véronique Gautier
- INRA, UMR1095, Génétique Diversité et Ecophysiologie des Céréales, 5 Chemin de Beaulieu, Clermont-Ferrand, 63039, France
| | - José M Jiménez-Gómez
- INRA, UMR1318, Institut Jean-Pierre Bourgin, AgroParisTech-INRA-CNRS, Route de Saint Cyr, Versailles, 78026, France
| | - Guillem Rigaill
- INRA, UMR8071, Laboratoire de Mathématiques et Modélisation d'Evry, Université d'Evry Val d'Essonne, ENSIIE-INRA-CNRS, Évry, 91037, France
| | - Mathilde Causse
- INRA, UR1052, Centre de Recherche PACA, Génétique et Amélioration des Fruits et Légumes, 67 Allée des Chênes, Domaine Saint Maurice, CS60094, Montfavet, 84143, France
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107
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Xiang Y, Ye Y, Zhang Z, Han L. Maximizing the Utility of Cancer Transcriptomic Data. Trends Cancer 2018; 4:823-837. [PMID: 30470304 DOI: 10.1016/j.trecan.2018.09.009] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Revised: 09/23/2018] [Accepted: 09/24/2018] [Indexed: 12/13/2022]
Abstract
Transcriptomic profiling has been applied to large numbers of cancer samples, by large-scale consortia, including The Cancer Genome Atlas, International Cancer Genome Consortium, and Cancer Cell Line Encyclopedia. Advances in mining cancer transcriptomic data enable us to understand the endless complexity of the cancer transcriptome and thereby to discover new biomarkers and therapeutic targets. In this paper, we review computational resources for deep mining of transcriptomic data to identify, quantify, and determine the functional effects and clinical utility of transcriptomic events, including noncoding RNAs, post-transcriptional regulation, exogenous RNAs, and transcribed genetic variants. These approaches can be applied to other complex diseases, thereby greatly leveraging the impact of this work.
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Affiliation(s)
- Yu Xiang
- Department of Biochemistry and Molecular Biology, McGovern Medical School at The University of Texas Health Science Center at Houston, Houston, TX 77030, USA; These authors contributed equally
| | - Youqiong Ye
- Department of Biochemistry and Molecular Biology, McGovern Medical School at The University of Texas Health Science Center at Houston, Houston, TX 77030, USA; These authors contributed equally
| | - Zhao Zhang
- Department of Biochemistry and Molecular Biology, McGovern Medical School at The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Leng Han
- Department of Biochemistry and Molecular Biology, McGovern Medical School at The University of Texas Health Science Center at Houston, Houston, TX 77030, USA; Center for Precision Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
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108
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Qu W, Gurdziel K, Pique-Regi R, Ruden DM. Lead Modulates trans- and cis-Expression Quantitative Trait Loci (eQTLs) in Drosophila melanogaster Heads. Front Genet 2018; 9:395. [PMID: 30294342 PMCID: PMC6158337 DOI: 10.3389/fgene.2018.00395] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Accepted: 08/30/2018] [Indexed: 11/13/2022] Open
Abstract
Lead exposure has long been one of the most important topics in global public health because it is a potent developmental neurotoxin. Here, an eQTL analysis, which is the genome-wide association analysis of genetic variants with gene expression, was performed. In this analysis, the male heads of 79 Drosophila melanogaster inbred lines from Drosophila Synthetic Population Resource (DSPR) were treated with or without developmental exposure, from hatching to adults, to 250 μM lead acetate [Pb(C2H3O2)2]. The goal was to identify genomic intervals that influence the gene-expression response to lead. After detecting 1798 cis-eQTLs and performing an initial trans-eQTL analysis, we focused our analysis on lead-sensitive "trans-eQTL hotspots," defined as genomic regions that are associated with a cluster of genes in a lead-dependent manner. We noticed that the genes associated with one of the 14 detected trans-eQTL hotspots, Chr 2L: 6,250,000 could be roughly divided into two groups based on their differential expression profile patterns and different categories of function. This trans-eQTL hotspot validates one identified in a previous study using different recombinant inbred lines. The expression of all the associated genes in the trans-eQTL hotspot was visualized with hierarchical clustering analysis. Besides the overall expression profile patterns, the heatmap displayed the segregation of differential parental genetic contributions. This suggested that trans-regulatory regions with different genetic contributions from the parental lines have significantly different expression changes after lead exposure. We believe this study confirms our earlier study, and provides important insights to unravel the genetic variation in lead susceptibility in Drosophila model.
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Affiliation(s)
- Wen Qu
- Department of Pharmacology, Wayne State University, Detroit, MI, United States
| | - Katherine Gurdziel
- Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI, United States
| | - Roger Pique-Regi
- Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI, United States.,Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI, United States
| | - Douglas M Ruden
- Department of Pharmacology, Wayne State University, Detroit, MI, United States.,Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI, United States.,Institute of Environmental Health Sciences, Wayne State University, Detroit, MI, United States
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109
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Sharon E, Chen SAA, Khosla NM, Smith JD, Pritchard JK, Fraser HB. Functional Genetic Variants Revealed by Massively Parallel Precise Genome Editing. Cell 2018; 175:544-557.e16. [PMID: 30245013 DOI: 10.1016/j.cell.2018.08.057] [Citation(s) in RCA: 139] [Impact Index Per Article: 23.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2018] [Revised: 06/21/2018] [Accepted: 08/22/2018] [Indexed: 12/26/2022]
Abstract
A major challenge in genetics is to identify genetic variants driving natural phenotypic variation. However, current methods of genetic mapping have limited resolution. To address this challenge, we developed a CRISPR-Cas9-based high-throughput genome editing approach that can introduce thousands of specific genetic variants in a single experiment. This enabled us to study the fitness consequences of 16,006 natural genetic variants in yeast. We identified 572 variants with significant fitness differences in glucose media; these are highly enriched in promoters, particularly in transcription factor binding sites, while only 19.2% affect amino acid sequences. Strikingly, nearby variants nearly always favor the same parent's alleles, suggesting that lineage-specific selection is often driven by multiple clustered variants. In sum, our genome editing approach reveals the genetic architecture of fitness variation at single-base resolution and could be adapted to measure the effects of genome-wide genetic variation in any screen for cell survival or cell-sortable markers.
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Affiliation(s)
- Eilon Sharon
- Department of Biology, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA.
| | - Shi-An A Chen
- Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Neil M Khosla
- Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Justin D Smith
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Jonathan K Pritchard
- Department of Biology, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Hunter B Fraser
- Department of Biology, Stanford University, Stanford, CA 94305, USA.
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110
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Liefferinckx C, Franchimont D. Viewpoint: Toward the Genetic Architecture of Disease Severity in Inflammatory Bowel Diseases. Inflamm Bowel Dis 2018; 24:1428-1439. [PMID: 29788122 DOI: 10.1093/ibd/izy109] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2017] [Indexed: 02/07/2023]
Abstract
Inflammatory bowel disease (IBD) is characterized by uneven disease courses with various clinical outcomes. A few prognostic markers of disease severity may help stratify patients and identify those who will benefit the most from early aggressive treatment. The concept of disease severity remains too broad and vague, mainly because the definition must embrace several disease mechanisms, mainly inflammation and fibrosis, with various rates of disease progression. The magnitude of inflammation is an obvious key driver of disease severity in IBD that ultimately influence disease behavior. Advances in the genetics underlying disease severity are currently emerging, but attempts to overlap the genetics of disease susceptibility and severity have until now been unsatisfactory, suggesting that the genetic architecture of disease severity may be distinct from the genetics of disease susceptibility. In this review, we report on the current knowledge on disease severity and on the main research venues to decipher the genetic architecture of disease severity.
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Affiliation(s)
| | - Denis Franchimont
- Department of Gastroenterology, Erasme Hospital, ULB, Brussels, Belgium
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111
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Schaefke B, Sun W, Li YS, Fang L, Chen W. The evolution of posttranscriptional regulation. WILEY INTERDISCIPLINARY REVIEWS-RNA 2018; 9:e1485. [PMID: 29851258 DOI: 10.1002/wrna.1485] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2018] [Revised: 04/23/2018] [Accepted: 04/26/2018] [Indexed: 12/13/2022]
Abstract
"DNA makes RNA makes protein." After transcription, mRNAs undergo a series of intertwining processes to be finally translated into functional proteins. The "posttranscriptional" regulation (PTR) provides cells an extended option to fine-tune their proteomes. To meet the demands of complex organism development and the appropriate response to environmental stimuli, every step in these processes needs to be finely regulated. Moreover, changes in these regulatory processes are important driving forces underlying the evolution of phenotypic differences across different species. The major PTR mechanisms discussed in this review include the regulation of splicing, polyadenylation, decay, and translation. For alternative splicing and polyadenylation, we mainly discuss their evolutionary dynamics and the genetic changes underlying the regulatory differences in cis-elements versus trans-factors. For mRNA decay and translation, which, together with transcription, determine the cellular RNA or protein abundance, we focus our discussion on how their divergence coordinates with transcriptional changes to shape the evolution of gene expression. Then to highlight the importance of PTR in the evolution of higher complexity, we focus on their roles in two major phenomena during eukaryotic evolution: the evolution of multicellularity and the division of labor between different cell types and tissues; and the emergence of diverse, often highly specialized individual phenotypes, especially those concerning behavior in eusocial insects. This article is categorized under: RNA Evolution and Genomics > RNA and Ribonucleoprotein Evolution Translation > Translation Regulation RNA Processing > Splicing Regulation/Alternative Splicing.
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Affiliation(s)
- Bernhard Schaefke
- Department of Biology, Southern University of Science and Technology, Shenzhen, China
| | - Wei Sun
- Department of Biology, Southern University of Science and Technology, Shenzhen, China.,Department of Pharmaceutical Chemistry and Cardiovascular Research Institute, University of California San Francisco, San Francisco
| | - Yi-Sheng Li
- Department of Biology, Southern University of Science and Technology, Shenzhen, China
| | - Liang Fang
- Department of Biology, Southern University of Science and Technology, Shenzhen, China.,Medi-X Institute, SUSTech Academy for Advanced Interdisciplinary Studies, Southern University of Science and Technology, Shenzhen, China
| | - Wei Chen
- Department of Biology, Southern University of Science and Technology, Shenzhen, China.,Medi-X Institute, SUSTech Academy for Advanced Interdisciplinary Studies, Southern University of Science and Technology, Shenzhen, China
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112
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Im C, Sapkota Y, Moon W, Kawashima M, Nakamura M, Tokunaga K, Yasui Y. Genome-wide haplotype association analysis of primary biliary cholangitis risk in Japanese. Sci Rep 2018; 8:7806. [PMID: 29773854 PMCID: PMC5958065 DOI: 10.1038/s41598-018-26112-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2018] [Accepted: 04/30/2018] [Indexed: 12/16/2022] Open
Abstract
Primary biliary cholangitis (PBC) susceptibility loci have largely been discovered through single SNP association testing. In this study, we report genic haplotype patterns associated with PBC risk genome-wide in two Japanese cohorts. Among the 74 genic PBC risk haplotype candidates we detected with a novel methodological approach in a discovery cohort of 1,937 Japanese, nearly two-thirds were replicated (49 haplotypes, Bonferroni-corrected P < 6.8 × 10-4) in an independent Japanese cohort (N = 949). Along with corroborating known PBC-associated loci (TNFSF15, HLA-DRA), risk haplotypes may potentially model cis-interactions that regulate gene expression. For example, one replicated haplotype association (9q32-9q33.1, OR = 1.7, P = 3.0 × 10-21) consists of intergenic SNPs outside of the human leukocyte antigen (HLA) region that overlap regulatory histone mark peaks in liver and blood cells, and are significantly associated with TNFSF8 expression in whole blood. We also replicated a novel haplotype association involving non-HLA SNPs mapped to UMAD1 (7p21.3; OR = 15.2, P = 3.9 × 10-9) that overlap enhancer peaks in liver and memory Th cells. Our analysis demonstrates the utility of haplotype association analyses in discovering and characterizing PBC susceptibility loci.
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Affiliation(s)
- Cindy Im
- School of Public Health, University of Alberta, Edmonton, Alberta, T6G 1C9, Canada.
| | - Yadav Sapkota
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Wonjong Moon
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Minae Kawashima
- Department of Human Genetics, Graduate School of Medicine, The University of Tokyo, Tokyo, 113-0033, Japan
| | - Minoru Nakamura
- Department of Hepatology, Nagasaki University Graduate School of Biomedical Sciences and Clinical Research Center, National Hospital Organization Nagasaki Medical Center, Omura, Nagasaki, 856-8562, Japan
| | - Katsushi Tokunaga
- Department of Human Genetics, Graduate School of Medicine, The University of Tokyo, Tokyo, 113-0033, Japan
| | - Yutaka Yasui
- School of Public Health, University of Alberta, Edmonton, Alberta, T6G 1C9, Canada. .,Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA.
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113
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A Genomewide Integrative Analysis of GWAS and eQTLs Data Identifies Multiple Genes and Gene Sets Associated with Obesity. BIOMED RESEARCH INTERNATIONAL 2018; 2018:3848560. [PMID: 29854750 PMCID: PMC5964558 DOI: 10.1155/2018/3848560] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 11/10/2017] [Revised: 03/20/2018] [Accepted: 04/03/2018] [Indexed: 12/02/2022]
Abstract
To identify novel susceptibility genes and gene sets for obesity, we conducted a genomewide expression association analysis of obesity via integrating genomewide association study (GWAS) and expression quantitative trait loci (eQTLs) data. GWAS summary data of body mass index (BMI) and waist-to-hip ratio (WHR) was driven from a published study, totally involving 339,224 individuals. The eQTLs dataset (containing 927,753 eQTLs) was obtained from eQTLs meta-analysis of 5,311 subjects. Integrative analysis of GWAS and eQTLs data was conducted by SMR software. The SMR single gene analysis results were further subjected to gene set enrichment analysis (GSEA) for identifying obesity associated gene sets. A total of 13,311 annotated gene sets were analyzed in this study. SMR single gene analysis identified 20 BMI associated genes (TUFM, SPI1, APOB48R, etc.). Also 3 WHR associated genes were detected (CPEB4, WARS2, and L3MBTL3). The significant association between Chr16p11 and BMI was observed by GSEA (FDR adjusted p value = 0.040). The TGCTGCT, MIR-15A, MIR-16, MIR-15B, MIR-195, MIR-424, and MIR-497 (FDR adjusted p value = 0.049) gene set appeared to be linked with WHR. Our results provide novel clues for the genetic mechanism studies of obesity. This study also illustrated the good performance of SMR for susceptibility gene mapping.
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114
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Knight SC, Tjian R, Doudna JA. Genomes in Focus: Development and Applications of CRISPR-Cas9 Imaging Technologies. Angew Chem Int Ed Engl 2018; 57:4329-4337. [PMID: 29080263 PMCID: PMC6014596 DOI: 10.1002/anie.201709201] [Citation(s) in RCA: 59] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2017] [Indexed: 12/14/2022]
Abstract
The discovery of the CRISPR-Cas9 endonuclease has enabled facile genome editing in living cells and organisms. Catalytically inactive Cas9 (dCas9) retains the ability to bind DNA in an RNA-guided fashion, and has additionally been explored as a tool for transcriptional modulation, epigenetic editing, and genome imaging. This Review highlights recent progress and challenges in the development of dCas9 for imaging genomic loci. The emergence and maturation of this technology offers the potential to answer mechanistic questions about chromosome dynamics and three-dimensional genome organization in vivo.
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Affiliation(s)
- Spencer C Knight
- Department of Chemistry, University of California, Berkeley, Berkeley, CA, USA
| | - Robert Tjian
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
- Howard Hughes Medical Institute, USA
- Li Ka Shing Biomedical and Health Sciences Center, University of California, Berkeley, Berkeley, CA, USA
- CIRM Center of Excellence, University of California, Berkeley, Berkeley, CA, USA
| | - Jennifer A Doudna
- Department of Chemistry, University of California, Berkeley, Berkeley, CA, USA
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
- Howard Hughes Medical Institute, USA
- Li Ka Shing Biomedical and Health Sciences Center, University of California, Berkeley, Berkeley, CA, USA
- MBIB Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA
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115
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Espinar L, Schikora Tamarit MÀ, Domingo J, Carey LB. Promoter architecture determines cotranslational regulation of mRNA. Genome Res 2018; 28:509-518. [PMID: 29567675 PMCID: PMC5880241 DOI: 10.1101/gr.230458.117] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2017] [Accepted: 02/27/2018] [Indexed: 01/08/2023]
Abstract
Information that regulates gene expression is encoded throughout each gene but if different regulatory regions can be understood in isolation, or if they interact, is unknown. Here we measure mRNA levels for 10,000 open reading frames (ORFs) transcribed from either an inducible or constitutive promoter. We find that the strength of cotranslational regulation on mRNA levels is determined by promoter architecture. By using a novel computational genetic screen of 6402 RNA-seq experiments, we identify the RNA helicase Dbp2 as the mechanism by which cotranslational regulation is reduced specifically for inducible promoters. Finally, we find that for constitutive genes, but not inducible genes, most of the information encoding regulation of mRNA levels in response to changes in growth rate is encoded in the ORF and not in the promoter. Thus, the ORF sequence is a major regulator of gene expression, and a nonlinear interaction between promoters and ORFs determines mRNA levels.
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Affiliation(s)
- Lorena Espinar
- Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), 08003 Barcelona, Spain
| | | | - Júlia Domingo
- Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain.,EMBL-CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, 08003 Barcelona, Spain
| | - Lucas B Carey
- Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain
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116
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Roberts JD. Noncoding Genetic Variation and Gene Expression: Deciphering the Molecular Drivers of Genome-Wide Association Study Signals in Atrial Fibrillation. CIRCULATION-GENOMIC AND PRECISION MEDICINE 2018; 11:e002109. [PMID: 29545483 DOI: 10.1161/circgen.118.002109] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Affiliation(s)
- Jason D Roberts
- From the Section of Cardiac Electrophysiology, Division of Cardiology, Department of Medicine, Western University, London, ON, Canada.
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117
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Tang Y, Jin B, Zhou L, Lu W. MeQTL analysis of childhood obesity links epigenetics with a risk SNP rs17782313 near MC4R from meta-analysis. Oncotarget 2018; 8:2800-2806. [PMID: 27926527 PMCID: PMC5356842 DOI: 10.18632/oncotarget.13742] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2016] [Accepted: 11/23/2016] [Indexed: 02/06/2023] Open
Abstract
Earlier GWAS has identified that rs17782313 near MC4R was associated with obesity. However, subsequent studies showed conflicting results, especially among childhood. Besides, the mechanisms underlying the association between rs17782313 and childhood obesity remain largely unexplored, and genetic and epigenetic may interact and together affect the development of childhood obesity. We conducted a comprehensive meta-analysis to assess the association between rs17782313 and childhood obesity. MeQTL and eQTL analysis was applied to explore the effect of rs17782313 on DNA methylation and MC4R expression. We found that rs17782313 near MC4R was associated with increased childhood obesity risk and BMI z-score in several inheritable models (P < 0.05). Additionally, the similar trend was observed among subgroups of Asians, Caucasian. Furthermore, meQTL and eQTL analysis indicated that individuals carrying rs17782313 TT genotype were significantly associated with increased methylation level of cg10097150 located in MC4R promoter and decreased expression of MC4R than those with CT/CC genotype (P = 1.7 × 10−4 and P = 1.9 × 10−3 respectively). Our results strongly confirmed that rs17782313 was associated with increased risk of childhood obesity. Furthermore, rs17782313 T allele was correlated with promoter hypermethylation and decreased expression of MC4R, thus involved in the development of childhood obesity.
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Affiliation(s)
- Yuping Tang
- Department of Orthopaedic, Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Bo Jin
- Department of Neurology, Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Lingling Zhou
- Department of Orthopaedic, Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Weifeng Lu
- Surgical Intensive Care Unite, Children's Hospital of Nanjing Medical University, Nanjing, China
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118
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Wang X, Chen Q, Wu Y, Lemmon ZH, Xu G, Huang C, Liang Y, Xu D, Li D, Doebley JF, Tian F. Genome-wide Analysis of Transcriptional Variability in a Large Maize-Teosinte Population. MOLECULAR PLANT 2018; 11:443-459. [PMID: 29275164 DOI: 10.1016/j.molp.2017.12.011] [Citation(s) in RCA: 57] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2017] [Revised: 10/21/2017] [Accepted: 12/11/2017] [Indexed: 05/18/2023]
Abstract
Gene expression regulation plays an important role in controlling plant phenotypes and adaptation. Here, we report a comprehensive assessment of gene expression variation through the transcriptome analyses of a large maize-teosinte experimental population. Genome-wide mapping identified 25 660 expression quantitative trait loci (eQTL) for 17 311 genes, capturing an unprecedented range of expression variation. We found that local eQTL were more frequently mapped to adjacent genes, displaying a mode of expression piggybacking, which consequently created co-regulated gene clusters. Genes within the co-regulated gene clusters tend to have relevant functions and shared chromatin modifications. Distant eQTL formed 125 significant distant eQTL hotspots with their targets significantly enriched in specific functional categories. By integrating different sources of information, we identified putative trans- regulators for a variety of metabolic pathways. We demonstrated that the bHLH transcription factor R1 and hexokinase HEX9 might act as crucial regulators for flavonoid biosynthesis and glycolysis, respectively. Moreover, we showed that domestication or improvement has significantly affected global gene expression, with many genes targeted by selection. Of particular interest, the Bx genes for benzoxazinoid biosynthesis may have undergone coordinated cis-regulatory divergence between maize and teosinte, and a transposon insertion that inactivates Bx12 was under strong selection as maize spread into temperate environments with a distinct herbivore community.
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Affiliation(s)
- Xufeng Wang
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, Laboratory of Crop Heterosis and Utilization, Joint International Research Laboratory of Crop Molecular Breeding, China Agricultural University, Beijing 100193, China
| | - Qiuyue Chen
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, Laboratory of Crop Heterosis and Utilization, Joint International Research Laboratory of Crop Molecular Breeding, China Agricultural University, Beijing 100193, China
| | - Yaoyao Wu
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, Laboratory of Crop Heterosis and Utilization, Joint International Research Laboratory of Crop Molecular Breeding, China Agricultural University, Beijing 100193, China
| | - Zachary H Lemmon
- Department of Genetics, University of Wisconsin, Madison, WI 53706, USA
| | - Guanghui Xu
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, Laboratory of Crop Heterosis and Utilization, Joint International Research Laboratory of Crop Molecular Breeding, China Agricultural University, Beijing 100193, China
| | - Cheng Huang
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, Laboratory of Crop Heterosis and Utilization, Joint International Research Laboratory of Crop Molecular Breeding, China Agricultural University, Beijing 100193, China
| | - Yameng Liang
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, Laboratory of Crop Heterosis and Utilization, Joint International Research Laboratory of Crop Molecular Breeding, China Agricultural University, Beijing 100193, China
| | - Dingyi Xu
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, Laboratory of Crop Heterosis and Utilization, Joint International Research Laboratory of Crop Molecular Breeding, China Agricultural University, Beijing 100193, China
| | - Dan Li
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, Laboratory of Crop Heterosis and Utilization, Joint International Research Laboratory of Crop Molecular Breeding, China Agricultural University, Beijing 100193, China
| | - John F Doebley
- Department of Genetics, University of Wisconsin, Madison, WI 53706, USA
| | - Feng Tian
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, Laboratory of Crop Heterosis and Utilization, Joint International Research Laboratory of Crop Molecular Breeding, China Agricultural University, Beijing 100193, China.
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119
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Dal Santo S, Zenoni S, Sandri M, De Lorenzis G, Magris G, De Paoli E, Di Gaspero G, Del Fabbro C, Morgante M, Brancadoro L, Grossi D, Fasoli M, Zuccolotto P, Tornielli GB, Pezzotti M. Grapevine field experiments reveal the contribution of genotype, the influence of environment and the effect of their interaction (G×E) on the berry transcriptome. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2018; 93:1143-1159. [PMID: 29381239 DOI: 10.1111/tpj.13834] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2017] [Revised: 12/14/2017] [Accepted: 01/04/2018] [Indexed: 05/20/2023]
Abstract
Changes in the performance of genotypes in different environments are defined as genotype × environment (G×E) interactions. In grapevine (Vitis vinifera), complex interactions between different genotypes and climate, soil and farming practices yield unique berry qualities. However, the molecular basis of this phenomenon remains unclear. To dissect the basis of grapevine G×E interactions we characterized berry transcriptome plasticity, the genome methylation landscape and within-genotype allelic diversity in two genotypes cultivated in three different environments over two vintages. We identified, through a novel data-mining pipeline, genes with expression profiles that were: unaffected by genotype or environment, genotype-dependent but unaffected by the environment, environmentally-dependent regardless of genotype, and G×E-related. The G×E-related genes showed different degrees of within-cultivar allelic diversity in the two genotypes and were enriched for stress responses, signal transduction and secondary metabolism categories. Our study unraveled the mutual relationships between genotypic and environmental variables during G×E interaction in a woody perennial species, providing a reference model to explore how cultivated fruit crops respond to diverse environments. Also, the pivotal role of vineyard location in determining the performance of different varieties, by enhancing berry quality traits, was unraveled.
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Affiliation(s)
- Silvia Dal Santo
- Department of Biotechnology, University of Verona, I-37034, Verona, Italy
| | - Sara Zenoni
- Department of Biotechnology, University of Verona, I-37034, Verona, Italy
| | - Marco Sandri
- Department of Biotechnology, University of Verona, I-37034, Verona, Italy
| | - Gabriella De Lorenzis
- Department of Agricultural and Environmental Sciences - Production, Landscape, Agroenergy, University of Milano, I-20133, Milano, Italy
| | | | - Emanuele De Paoli
- Department of Agricultural Food, Environmental and Animal Sciences (DI4A), University of Udine, I-33100, Udine, Italy
| | | | - Cristian Del Fabbro
- Department of Agricultural Food, Environmental and Animal Sciences (DI4A), University of Udine, I-33100, Udine, Italy
| | | | - Lucio Brancadoro
- Department of Agricultural and Environmental Sciences - Production, Landscape, Agroenergy, University of Milano, I-20133, Milano, Italy
| | - Daniele Grossi
- Department of Agricultural and Environmental Sciences - Production, Landscape, Agroenergy, University of Milano, I-20133, Milano, Italy
| | - Marianna Fasoli
- Department of Biotechnology, University of Verona, I-37034, Verona, Italy
| | - Paola Zuccolotto
- Department of Economics and management, University of Brescia, I-25121, Brescia, Italy
| | | | - Mario Pezzotti
- Department of Biotechnology, University of Verona, I-37034, Verona, Italy
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120
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Knight SC, Tjian R, Doudna JA. Genome im Fokus: Entwicklung und Anwendungen von CRISPR-Cas9-Bildgebungstechnologien. Angew Chem Int Ed Engl 2018. [DOI: 10.1002/ange.201709201] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Affiliation(s)
| | - Robert Tjian
- Department of Molecular and Cell Biology; University of California; Berkeley CA USA
- Howard Hughes Medical Institute; USA
- Li Ka Shing Biomedical and Health Sciences Center; University of California; Berkeley CA USA
- CIRM Center of Excellence; University of California, Berkeley; Berkeley CA USA
| | - Jennifer A. Doudna
- Department of Chemistry; University of California; Berkeley CA USA
- Department of Molecular and Cell Biology; University of California; Berkeley CA USA
- Howard Hughes Medical Institute; USA
- Li Ka Shing Biomedical and Health Sciences Center; University of California; Berkeley CA USA
- MBIB Division; Lawrence Berkeley National Laboratory; Berkeley CA USA. Innovative Genomics Institute; University of California, Berkeley; Berkeley CA USA
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121
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Integrative expression quantitative trait locus-based analysis of colorectal cancer identified a functional polymorphism regulating SLC22A5 expression. Eur J Cancer 2018; 93:1-9. [PMID: 29428571 DOI: 10.1016/j.ejca.2018.01.065] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2017] [Revised: 01/03/2018] [Accepted: 01/06/2018] [Indexed: 01/03/2023]
Abstract
Multiple single nucleotide polymorphisms (SNPs) have been found to be highly correlated with colorectal cancer (CRC) risk. However, the variants identified thus far only explain a small part of the cases, suggesting the existence of many uncharacterised genetic determinants. In this study, using the multilevel 'omics' data provided in The Cancer Genome Atlas, we systematically performed expression quantitative trait locus (eQTL) analysis for CRC and identified nine SNPs with significant effects on mRNA expression (correlation |r| > 0.3 and FDR < 0.01). Then we conducted a two-stage case-control study consisting of 1528 cases and 1528 controls to examine the associations between candidate SNPs and CRC risk. We found that rs27437 in SLC22A5 was significantly correlated with CRC risk in both stages and the combined study (additive model, OR = 1.31, 95%CI = 1.17-1.47, P = 1.97 × 10-6). eQTL analysis showed that rs27437 GG and GA genotypes were associated with lower expression of SLC22A5 compared with the AA genotype. Dual-luciferase reporter assays confirmed that the G risk allele could decrease the expression of luciferase. SLC22A5 was significantly decreased in CRC tumour tissues compared with adjacent normal tissues, indicating that SLC22A5 may play important roles in CRC, and rs27437 in SLC22A5 might serve as a novel biomarker for early detection and prevention of CRC.
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122
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González-Quiroz M, Urra H, Limia CM, Hetz C. Homeostatic interplay between FoxO proteins and ER proteostasis in cancer and other diseases. Semin Cancer Biol 2018; 50:42-52. [PMID: 29369790 DOI: 10.1016/j.semcancer.2018.01.011] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2017] [Revised: 01/14/2018] [Accepted: 01/18/2018] [Indexed: 02/08/2023]
Abstract
Cancer cells are exposed to adverse conditions within the tumor microenvironment that challenge cells to adapt and survive. Several of these homeostatic perturbations insults alter the normal function of the endoplasmic reticulum (ER), resulting in the accumulation of misfolded proteins. ER stress triggers a conserved signaling pathway known as the unfolded protein response (UPR) to cope with the stress or trigger apoptosis of damaged cells. The UPR has been described as a major driver in the acquisition of malignant characteristics that ultimately lead to cancer progression. Although, several reports describe the relevance of the UPR in tumor growth, the possible crosstalk with other cancer-related pathways is starting to be elucidated. The Forkhead Box O (FoxO) subfamily of proteins has a major role in cancer progression, where chromosomal translocations and deregulated signaling lead to loss-of-function of FoxO proteins, contributing to tumor progression. Here we discuss the homeostatic connection between the UPR and FoxO proteins and its possible implications to tumor progression and the acquisition of several hallmarks of cancer. In addition, studies linking a crosstalk between the UPR and FoxO proteins in other diseases, including neurodegeneration and metabolic disorders is provided.
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Affiliation(s)
- Matías González-Quiroz
- Biomedical Neuroscience Institute, Faculty of Medicine, University of Chile, Santiago, Chile; Center for Geroscience, Brain Health and Metabolism, Santiago, Chile; Program of Cellular and Molecular Biology, Institute of Biomedical Sciences, University of Chile, Santiago, Chile
| | - Hery Urra
- Biomedical Neuroscience Institute, Faculty of Medicine, University of Chile, Santiago, Chile; Center for Geroscience, Brain Health and Metabolism, Santiago, Chile; Program of Cellular and Molecular Biology, Institute of Biomedical Sciences, University of Chile, Santiago, Chile
| | - Celia María Limia
- Biomedical Neuroscience Institute, Faculty of Medicine, University of Chile, Santiago, Chile; Center for Geroscience, Brain Health and Metabolism, Santiago, Chile; Program of Cellular and Molecular Biology, Institute of Biomedical Sciences, University of Chile, Santiago, Chile
| | - Claudio Hetz
- Biomedical Neuroscience Institute, Faculty of Medicine, University of Chile, Santiago, Chile; Center for Geroscience, Brain Health and Metabolism, Santiago, Chile; Program of Cellular and Molecular Biology, Institute of Biomedical Sciences, University of Chile, Santiago, Chile; The Buck Institute for Research in Aging, Novato CA 94945, USA; Department of Immunology and Infectious Diseases, Harvard School of Public Health, Boston MA 02115, USA.
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123
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A Two-Stage Whole-Genome Gene Expression Association Study of Young-Onset Hypertension in Han Chinese Population of Taiwan. Sci Rep 2018; 8:1800. [PMID: 29379041 PMCID: PMC5789005 DOI: 10.1038/s41598-018-19520-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2017] [Accepted: 01/03/2018] [Indexed: 12/31/2022] Open
Abstract
Hypertension is an important public health problem in the world. Since the intermediate position of the gene expression between genotype and phenotype makes it suitable to link genotype to phenotype, we carried out a two-stage whole-genome gene expression association study to find differentially expressed genes and pathways for hypertension. In the first stage, 126 cases and 149 controls were used to find out the differentially expressed genes. In the second stage, an independent set of samples (127 cases and 150 controls) was used to validate the results. Additionally, we conducted a gene set enrichment analysis (GSEA) to search for differentially affected pathways. A total of nine genes were implicated in the first stage (Bonferroni-corrected p-value < 0.05). Among these genes, ZRANB1, FAM110A, PREP, ANKRD9 and LAMB2 were also differentially expressed in an existing database of hypertensive mouse model (GSE19817). A total of 16 pathways were identified by the GSEA. ZRANB1 and six pathways identified are related to TNF-α. Three pathways are related to interleukin, one to metabolic syndrome, and one to Hedgehog signaling. Identification of these genes and pathways suggest the importance of 1. inflammation, 2. visceral fat metabolism, and 3. adipocytes and osteocytes homeostasis in hypertension mechanisms and complications.
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124
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Mosedale M, Kim Y, Brock WJ, Roth SE, Wiltshire T, Eaddy JS, Keele GR, Corty RW, Xie Y, Valdar W, Watkins PB. Editor's Highlight: Candidate Risk Factors and Mechanisms for Tolvaptan-Induced Liver Injury Are Identified Using a Collaborative Cross Approach. Toxicol Sci 2018; 156:438-454. [PMID: 28115652 DOI: 10.1093/toxsci/kfw269] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
Clinical trials of tolvaptan showed it to be a promising candidate for the treatment of Autosomal Dominant Polycystic Kidney Disease (ADPKD) but also revealed potential for idiosyncratic drug-induced liver injury (DILI) in this patient population. To identify risk factors and mechanisms underlying tolvaptan DILI, 8 mice in each of 45 strains of the genetically diverse Collaborative Cross (CC) mouse population were treated with a single oral dose of either tolvaptan or vehicle. Significant elevations in plasma alanine aminotransferase (ALT) were observed in tolvaptan-treated animals in 3 of the 45 strains. Genetic mapping coupled with transcriptomic analysis in the liver was used to identify several candidate susceptibility genes including epoxide hydrolase 2, interferon regulatory factor 3, and mitochondrial fission factor. Gene pathway analysis revealed that oxidative stress and immune response pathways were activated in response to tolvaptan treatment across all strains, but genes involved in regulation of bile acid homeostasis were most associated with tolvaptan-induced elevations in ALT. Secretory leukocyte peptidase inhibitor (Slpi) mRNA was also induced in the susceptible strains and was associated with increased plasma levels of Slpi protein, suggesting a potential serum marker for DILI susceptibility. In summary, tolvaptan induced signs of oxidative stress, mitochondrial dysfunction, and innate immune response in all strains, but variation in bile acid homeostasis was most associated with susceptibility to the liver response. This CC study has indicated potential mechanisms underlying tolvaptan DILI and biomarkers of susceptibility that may be useful in managing the risk of DILI in ADPKD patients.
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Affiliation(s)
- Merrie Mosedale
- Institute for Drug Safety Sciences, University of North Carolina at Chapel Hill, Research Triangle Park, North Carolina 27709.,Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, Chapel Hill, North Carolina 27599
| | - Yunjung Kim
- Institute for Drug Safety Sciences, University of North Carolina at Chapel Hill, Research Triangle Park, North Carolina 27709.,Department of Genetics, UNC School of Medicine, Chapel Hill, North Carolina 27599
| | - William J Brock
- Otsuka Pharmaceutical Development and Commercialization, Inc., Rockville, Maryland 20850.,Brock Scientific Consulting, Montgomery Village, Maryland 20886
| | - Sharin E Roth
- Otsuka Pharmaceutical Development and Commercialization, Inc., Rockville, Maryland 20850
| | - Tim Wiltshire
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, Chapel Hill, North Carolina 27599.,Department of Genetics, UNC School of Medicine, Chapel Hill, North Carolina 27599
| | - J Scott Eaddy
- Institute for Drug Safety Sciences, University of North Carolina at Chapel Hill, Research Triangle Park, North Carolina 27709.,Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, Chapel Hill, North Carolina 27599
| | - Gregory R Keele
- Department of Genetics, UNC School of Medicine, Chapel Hill, North Carolina 27599
| | - Robert W Corty
- Department of Genetics, UNC School of Medicine, Chapel Hill, North Carolina 27599
| | - Yuying Xie
- Department of Genetics, UNC School of Medicine, Chapel Hill, North Carolina 27599
| | - William Valdar
- Department of Genetics, UNC School of Medicine, Chapel Hill, North Carolina 27599.,Lineberger Comprehensive Cancer Center, Chapel Hill, North Carolina 27599
| | - Paul B Watkins
- Institute for Drug Safety Sciences, University of North Carolina at Chapel Hill, Research Triangle Park, North Carolina 27709.,Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, Chapel Hill, North Carolina 27599
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125
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Maroilley T, Lemonnier G, Lecardonnel J, Esquerré D, Ramayo-Caldas Y, Mercat MJ, Rogel-Gaillard C, Estellé J. Deciphering the genetic regulation of peripheral blood transcriptome in pigs through expression genome-wide association study and allele-specific expression analysis. BMC Genomics 2017; 18:967. [PMID: 29237423 PMCID: PMC5729405 DOI: 10.1186/s12864-017-4354-6] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2017] [Accepted: 11/28/2017] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Efforts to improve sustainability in livestock production systems have focused on two objectives: investigating the genetic control of immune function as it pertains to robustness and disease resistance, and finding predictive markers for use in breeding programs. In this context, the peripheral blood transcriptome represents an important source of biological information about an individual's health and immunological status, and has been proposed for use as an intermediate phenotype to measure immune capacity. The objective of this work was to study the genetic architecture of variation in gene expression in the blood of healthy young pigs using two approaches: an expression genome-wide association study (eGWAS) and allele-specific expression (ASE) analysis. RESULTS The blood transcriptomes of 60-day-old Large White pigs were analyzed by expression microarrays for eGWAS (242 animals) and by RNA-Seq for ASE analysis (38 animals). Using eGWAS, the expression levels of 1901 genes were found to be associated with expression quantitative trait loci (eQTLs). We recovered 2839 local and 1752 distant associations (Single Nucleotide Polymorphism or SNP located less or more than 1 Mb from expression probe, respectively). ASE analyses confirmed the extensive cis-regulation of gene transcription in blood, and revealed allelic imbalance in 2286 SNPs, which affected 763 genes. eQTLs and ASE-genes were widely distributed on all chromosomes. By analyzing mutually overlapping eGWAS results, we were able to describe putative regulatory networks, which were further refined using ASE data. At the functional level, genes with genetically controlled expression that were detected by eGWAS and/or ASE analyses were significantly enriched in biological processes related to RNA processing and immune function. Indeed, numerous distant and local regulatory relationships were detected within the major histocompatibility complex region on chromosome 7, revealing ASE for most class I and II genes. CONCLUSIONS This study represents, to the best of our knowledge, the first genome-wide map of the genetic control of gene expression in porcine peripheral blood. These results represent an interesting resource for the identification of genetic markers and blood biomarkers associated with variations in immunity traits in pigs, as well as any other complex traits for which blood is an appropriate surrogate tissue.
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Affiliation(s)
- T Maroilley
- GABI, INRA, AgroParisTech, Université Paris-Saclay, 78350, Jouy-en-Josas, France.
| | - G Lemonnier
- GABI, INRA, AgroParisTech, Université Paris-Saclay, 78350, Jouy-en-Josas, France
| | - J Lecardonnel
- GABI, INRA, AgroParisTech, Université Paris-Saclay, 78350, Jouy-en-Josas, France
| | - D Esquerré
- GenPhySE, INRA, INPT, ENVT, Université de Toulouse, 31326, Castanet-Tolosan, France
| | - Y Ramayo-Caldas
- GABI, INRA, AgroParisTech, Université Paris-Saclay, 78350, Jouy-en-Josas, France
| | - M J Mercat
- IFIP - Institut du porc/BIOPORC, La Motte au Vicomte, BP 35104, 35651, Le Rheu, France
| | - C Rogel-Gaillard
- GABI, INRA, AgroParisTech, Université Paris-Saclay, 78350, Jouy-en-Josas, France.
| | - J Estellé
- GABI, INRA, AgroParisTech, Université Paris-Saclay, 78350, Jouy-en-Josas, France.
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126
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Cheng J, Maier KC, Avsec Ž, Rus P, Gagneur J. Cis-regulatory elements explain most of the mRNA stability variation across genes in yeast. RNA (NEW YORK, N.Y.) 2017; 23:1648-1659. [PMID: 28802259 PMCID: PMC5648033 DOI: 10.1261/rna.062224.117] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2017] [Accepted: 07/31/2017] [Indexed: 05/09/2023]
Abstract
The stability of mRNA is one of the major determinants of gene expression. Although a wealth of sequence elements regulating mRNA stability has been described, their quantitative contributions to half-life are unknown. Here, we built a quantitative model for Saccharomyces cerevisiae based on functional mRNA sequence features that explains 59% of the half-life variation between genes and predicts half-life at a median relative error of 30%. The model revealed a new destabilizing 3' UTR motif, ATATTC, which we functionally validated. Codon usage proves to be the major determinant of mRNA stability. Nonetheless, single-nucleotide variations have the largest effect when occurring on 3' UTR motifs or upstream AUGs. Analyzing mRNA half-life data of 34 knockout strains showed that the effect of codon usage not only requires functional decapping and deadenylation, but also the 5'-to-3' exonuclease Xrn1, the nonsense-mediated decay genes, but not no-go decay. Altogether, this study quantitatively delineates the contributions of mRNA sequence features on stability in yeast, reveals their functional dependencies on degradation pathways, and allows accurate prediction of half-life from mRNA sequence.
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Affiliation(s)
- Jun Cheng
- Department of Informatics, Technical University of Munich, 85748 Garching, Germany
- Graduate School of Quantitative Biosciences (QBM), Ludwig-Maximilians-Universität München, 81377 München, Germany
| | - Kerstin C Maier
- Department of Molecular Biology, Max Planck Institute for Biophysical Chemistry, 37077 Göttingen, Germany
| | - Žiga Avsec
- Department of Informatics, Technical University of Munich, 85748 Garching, Germany
- Graduate School of Quantitative Biosciences (QBM), Ludwig-Maximilians-Universität München, 81377 München, Germany
| | - Petra Rus
- Department of Molecular Biology, Max Planck Institute for Biophysical Chemistry, 37077 Göttingen, Germany
| | - Julien Gagneur
- Department of Informatics, Technical University of Munich, 85748 Garching, Germany
- Graduate School of Quantitative Biosciences (QBM), Ludwig-Maximilians-Universität München, 81377 München, Germany
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127
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Qu W, Gurdziel K, Pique-Regi R, Ruden DM. Identification of Splicing Quantitative Trait Loci (sQTL) in Drosophila melanogaster with Developmental Lead (Pb 2+) Exposure. Front Genet 2017; 8:145. [PMID: 29114259 PMCID: PMC5660682 DOI: 10.3389/fgene.2017.00145] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2017] [Accepted: 09/22/2017] [Indexed: 01/09/2023] Open
Abstract
Lead (Pb) poisoning has been a major public health issue globally and the recent Flint water crisis has drawn nation-wide attention to its effects. To better understand how lead plays a role as a neurotoxin, we utilized the Drosophila melanogaster model to study the genetic effects of lead exposure during development and identified lead-responsive genes. In our previous studies, we have successfully identified hundreds of lead-responsive expression QTLs (eQTLs) by using RNA-seq analysis on heads collected from the Drosophila Synthetic Population Resource. Cis-eQTLs, also known as allele-specific expression (ASE) polymorphisms, are generally single-nucleotide polymorphisms in the promoter regions of genes that affect expression of the gene, such as by inhibiting the binding of transcription factors. Trans-eQTLs are genes that regulate mRNA levels for many genes, and are generally thought to be SNPs in trans-acting transcription or translation factors. In this study, we focused our attention on alternative splicing events that are affected by lead exposure. Splicing QTLs (sQTLs), which can be caused by SNPs that alter splicing or alternative splicing (AS), such as by changing the sequence-specific binding affinity of splicing factors to the pre-mRNA. We applied two methods in search for sQTLs by using RNA-seq data from control and lead-exposed w1118Drosophila heads. First, we used the fraction of reads in a gene that falls in each exon as the phenotype. Second, we directly compared the transcript counts among the various splicing isoforms as the phenotype. Among the 1,236 potential Pb-responsive sQTLs (p < 0.0001, FDR < 0.39), mostly cis-sQTLs, one of the most distinct genes is Dscam1 (Down Syndrome Cell Adhesion Molecule), which has over 30,000 potential alternative splicing isoforms. We have also identified a candidate Pb-responsive trans-sQTL hotspot that appears to regulate 129 genes that are enriched in the “cation channel” gene ontology category, suggesting a model in which alternative splicing of these channels might lead to an increase in the elimination of Pb2+ from the neurons encoding these channels. To our knowledge, this is the first paper that uses sQTL analyses to understand the neurotoxicology of an environmental toxin in any organism, and the first reported discovery of a candidate trans-sQTL hotspot.
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Affiliation(s)
- Wen Qu
- Laboratory of Epigenomics, Department of Pharmacology, C.S. Mott Center for Human Growth and Development, Wayne State University, Detroit, MI, United States
| | - Katherine Gurdziel
- Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI, United States
| | - Roger Pique-Regi
- Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI, United States
| | - Douglas M Ruden
- Laboratory of Epigenomics, Department of Pharmacology, C.S. Mott Center for Human Growth and Development, Wayne State University, Detroit, MI, United States.,Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI, United States.,Institute of Environmental Health Sciences, Wayne State University, Detroit, MI, United States
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128
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Delavan B, Roberts R, Huang R, Bao W, Tong W, Liu Z. Computational drug repositioning for rare diseases in the era of precision medicine. Drug Discov Today 2017; 23:382-394. [PMID: 29055182 DOI: 10.1016/j.drudis.2017.10.009] [Citation(s) in RCA: 57] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2017] [Revised: 09/19/2017] [Accepted: 10/11/2017] [Indexed: 12/12/2022]
Abstract
There are tremendous unmet needs in drug development for rare diseases. Computational drug repositioning is a promising approach and has been successfully applied to the development of treatments for diseases. However, how to utilize this knowledge and effectively conduct and implement computational drug repositioning approaches for rare disease therapies is still an open issue. Here, we focus on the means of utilizing accumulated genomic data for accelerating and facilitating drug repositioning for rare diseases. First, we summarize the current genome landscape of rare diseases. Second, we propose several promising bioinformatics approaches and pipelines for computational drug repositioning for rare diseases. Finally, we discuss recent regulatory incentives and other enablers in rare disease drug development and outline the remaining challenges.
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Affiliation(s)
- Brian Delavan
- National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA; University of Arkansas at Little Rock, Little Rock, AR 72204, USA
| | - Ruth Roberts
- ApconiX, BioHub at Alderley Park, Alderley Edge SK10 4TG, UK; University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
| | - Ruili Huang
- National Center for Advancing Translational Sciences, National Institutes of Health Rockville, MD 20850, USA
| | | | - Weida Tong
- National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA.
| | - Zhichao Liu
- National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA.
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129
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Dissecting genetic architecture of startle response in Drosophila melanogaster using multi-omics information. Sci Rep 2017; 7:12367. [PMID: 28959013 PMCID: PMC5620086 DOI: 10.1038/s41598-017-11676-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2016] [Accepted: 08/24/2017] [Indexed: 01/01/2023] Open
Abstract
Startle behavior is important for survival, and abnormal startle responses are related to several neurological diseases. Drosophila melanogaster provides a powerful system to investigate the genetic underpinnings of variation in startle behavior. Since mechanically induced, startle responses and environmental conditions can be readily quantified and precisely controlled. The 156 wild-derived fully sequenced lines of the Drosophila Genetic Reference Panel (DGRP) were used to identify SNPs and transcripts associated with variation in startle behavior. The results validated highly significant effects of 33 quantitative trait SNPs (QTSs) and 81 quantitative trait transcripts (QTTs) directly associated with phenotypic variation of startle response. We also detected QTT variation controlled by 20 QTSs (tQTSs) and 73 transcripts (tQTTs). Association mapping based on genomic and transcriptomic data enabled us to construct a complex genetic network that underlies variation in startle behavior. Based on principles of evolutionary conservation, human orthologous genes could be superimposed on this network. This study provided both genetic and biological insights into the variation of startle response behavior of Drosophila melanogaster, and highlighted the importance of genetic network to understand the genetic architecture of complex traits.
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130
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Sá ACC, Sadee W, Johnson JA. Whole Transcriptome Profiling: An RNA-Seq Primer and Implications for Pharmacogenomics Research. Clin Transl Sci 2017; 11:153-161. [PMID: 28945944 PMCID: PMC5866981 DOI: 10.1111/cts.12511] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2017] [Accepted: 09/03/2017] [Indexed: 12/16/2022] Open
Affiliation(s)
- Ana Caroline C Sá
- Center for Pharmacogenomics & Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, Florida, USA.,Genetics & Genomic Graduate Program, Genetics Institute, University of Florida, Gainesville, Florida, USA
| | - Wolfgang Sadee
- Center for Pharmacogenomics, Department of Cancer Biology and Genetic, College of Medicine, Ohio State University, Columbus, Ohio, USA
| | - Julie A Johnson
- Center for Pharmacogenomics & Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, Florida, USA.,Genetics & Genomic Graduate Program, Genetics Institute, University of Florida, Gainesville, Florida, USA.,Division of Cardiovascular Medicine, Colleges of Pharmacy and Medicine, University of Florida, Gainesville, Florida, USA
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131
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Schwessinger R, Suciu MC, McGowan SJ, Telenius J, Taylor S, Higgs DR, Hughes JR. Sasquatch: predicting the impact of regulatory SNPs on transcription factor binding from cell- and tissue-specific DNase footprints. Genome Res 2017; 27:1730-1742. [PMID: 28904015 PMCID: PMC5630036 DOI: 10.1101/gr.220202.117] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2017] [Accepted: 08/07/2017] [Indexed: 12/22/2022]
Abstract
In the era of genome-wide association studies (GWAS) and personalized medicine, predicting the impact of single nucleotide polymorphisms (SNPs) in regulatory elements is an important goal. Current approaches to determine the potential of regulatory SNPs depend on inadequate knowledge of cell-specific DNA binding motifs. Here, we present Sasquatch, a new computational approach that uses DNase footprint data to estimate and visualize the effects of noncoding variants on transcription factor binding. Sasquatch performs a comprehensive k-mer-based analysis of DNase footprints to determine any k-mer's potential for protein binding in a specific cell type and how this may be changed by sequence variants. Therefore, Sasquatch uses an unbiased approach, independent of known transcription factor binding sites and motifs. Sasquatch only requires a single DNase-seq data set per cell type, from any genotype, and produces consistent predictions from data generated by different experimental procedures and at different sequence depths. Here we demonstrate the effectiveness of Sasquatch using previously validated functional SNPs and benchmark its performance against existing approaches. Sasquatch is available as a versatile webtool incorporating publicly available data, including the human ENCODE collection. Thus, Sasquatch provides a powerful tool and repository for prioritizing likely regulatory SNPs in the noncoding genome.
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Affiliation(s)
- Ron Schwessinger
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Oxford OX3 9DS, United Kingdom
| | - Maria C Suciu
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Oxford OX3 9DS, United Kingdom
| | - Simon J McGowan
- Computational Biology Research Group, MRC Weatherall Institute of Molecular Medicine, Oxford OX3 9DS, United Kingdom
| | - Jelena Telenius
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Oxford OX3 9DS, United Kingdom
| | - Stephen Taylor
- Computational Biology Research Group, MRC Weatherall Institute of Molecular Medicine, Oxford OX3 9DS, United Kingdom
| | - Doug R Higgs
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Oxford OX3 9DS, United Kingdom
| | - Jim R Hughes
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Oxford OX3 9DS, United Kingdom
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132
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Lu Y, Biancotto A, Cheung F, Remmers E, Shah N, McCoy JP, Tsang JS. Systematic Analysis of Cell-to-Cell Expression Variation of T Lymphocytes in a Human Cohort Identifies Aging and Genetic Associations. Immunity 2017; 45:1162-1175. [PMID: 27851916 DOI: 10.1016/j.immuni.2016.10.025] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2016] [Revised: 06/21/2016] [Accepted: 10/04/2016] [Indexed: 12/21/2022]
Abstract
Cell-to-cell expression variation (CEV) is a prevalent feature of even well-defined cell populations, but its functions, particularly at the organismal level, are not well understood. Using single-cell data obtained via high-dimensional flow cytometry of T cells as a model, we introduce an analysis framework for quantifying CEV in primary cell populations and studying its functional associations in human cohorts. Analyses of 840 CEV phenotypes spanning multiple baseline measurements of 14 proteins in 28 T cell subpopulations suggest that the quantitative extent of CEV can exhibit substantial subject-to-subject differences and yet remain stable within healthy individuals over months. We linked CEV to age and disease-associated genetic polymorphisms, thus implicating CEV as a biomarker of aging and disease susceptibility and suggesting that it might play an important role in health and disease. Our dataset, interactive figures, and software for computing CEV with flow cytometry data provide a resource for exploring CEV functions.
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Affiliation(s)
- Yong Lu
- Systems Genomics and Bioinformatics Unit, Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD 20892, USA
| | - Angelique Biancotto
- Trans-NIH Center for Human Immunology, Autoimmunity, and Inflammation, NIH, Bethesda, MD 20892, USA
| | - Foo Cheung
- Trans-NIH Center for Human Immunology, Autoimmunity, and Inflammation, NIH, Bethesda, MD 20892, USA
| | - Elaine Remmers
- National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Naisha Shah
- Systems Genomics and Bioinformatics Unit, Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD 20892, USA
| | - J Philip McCoy
- Trans-NIH Center for Human Immunology, Autoimmunity, and Inflammation, NIH, Bethesda, MD 20892, USA; Hematology Branch, National Heart, Lung and Blood Institute, NIH, Bethesda, MD 20892, USA
| | - John S Tsang
- Systems Genomics and Bioinformatics Unit, Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD 20892, USA; Trans-NIH Center for Human Immunology, Autoimmunity, and Inflammation, NIH, Bethesda, MD 20892, USA.
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133
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Lukowski SW, Lloyd-Jones LR, Holloway A, Kirsten H, Hemani G, Yang J, Small K, Zhao J, Metspalu A, Dermitzakis ET, Gibson G, Spector TD, Thiery J, Scholz M, Montgomery GW, Esko T, Visscher PM, Powell JE. Genetic correlations reveal the shared genetic architecture of transcription in human peripheral blood. Nat Commun 2017; 8:483. [PMID: 28883458 PMCID: PMC5589780 DOI: 10.1038/s41467-017-00473-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2016] [Accepted: 06/30/2017] [Indexed: 01/29/2023] Open
Abstract
Transcript co-expression is regulated by a combination of shared genetic and environmental factors. Here, we estimate the proportion of co-expression that is due to shared genetic variance. To do so, we estimated the genetic correlations between each pairwise combination of 2469 transcripts that are highly heritable and expressed in whole blood in 1748 unrelated individuals of European ancestry. We identify 556 pairs with a significant genetic correlation of which 77% are located on different chromosomes, and report 934 expression quantitative trait loci, identified in an independent cohort, with significant effects on both transcripts in a genetically correlated pair. We show significant enrichment for transcription factor control and physical proximity through chromatin interactions as possible mechanisms of shared genetic control. Finally, we construct networks of interconnected transcripts and identify their underlying biological functions. Using genetic correlations to investigate transcriptional co-regulation provides valuable insight into the nature of the underlying genetic architecture of gene regulation. Covariance of gene expression pairs is due to a combination of shared genetic and environmental factors. Here the authors estimate the genetic correlation between highly heritable pairs and identify transcription factor control and chromatin interactions as possible mechanisms of correlation.
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Affiliation(s)
- Samuel W Lukowski
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, 4072, Australia
| | - Luke R Lloyd-Jones
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, 4072, Australia.,Centre for Neurogenetics and Statistical Genomics, Queensland Brain Institute, University of Queensland, Brisbane, QLD, 4072, Australia
| | - Alexander Holloway
- Centre for Neurogenetics and Statistical Genomics, Queensland Brain Institute, University of Queensland, Brisbane, QLD, 4072, Australia
| | - Holger Kirsten
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, 04107, Germany.,LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, 04103, Germany
| | - Gibran Hemani
- MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, BS8 2BN, UK.,School of Social and Community Medicine, University of Bristol, Bristol, BS8 2BN, UK
| | - Jian Yang
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, 4072, Australia.,Centre for Neurogenetics and Statistical Genomics, Queensland Brain Institute, University of Queensland, Brisbane, QLD, 4072, Australia
| | - Kerrin Small
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK
| | - Jing Zhao
- School of Biology and Center for Integrative Genomics, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu, 51010, Estonia
| | - Emmanouil T Dermitzakis
- Department of Genetic Medicine and Development, University of Geneva, Geneva, CH-1211, Switzerland
| | - Greg Gibson
- School of Biology and Center for Integrative Genomics, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Timothy D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK
| | - Joachim Thiery
- LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, 04103, Germany.,Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University of Leipzig, Leipzig, 04103, Germany
| | - Markus Scholz
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, 04107, Germany.,LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, 04103, Germany
| | - Grant W Montgomery
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, 4072, Australia.,QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane, QLD, 4006, Australia
| | - Tonu Esko
- Estonian Genome Center, University of Tartu, Tartu, 51010, Estonia
| | - Peter M Visscher
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, 4072, Australia.,Centre for Neurogenetics and Statistical Genomics, Queensland Brain Institute, University of Queensland, Brisbane, QLD, 4072, Australia
| | - Joseph E Powell
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, 4072, Australia. .,Centre for Neurogenetics and Statistical Genomics, Queensland Brain Institute, University of Queensland, Brisbane, QLD, 4072, Australia.
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134
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Epigenomics of Major Depressive Disorders and Schizophrenia: Early Life Decides. Int J Mol Sci 2017; 18:ijms18081711. [PMID: 28777307 PMCID: PMC5578101 DOI: 10.3390/ijms18081711] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2017] [Revised: 07/31/2017] [Accepted: 08/02/2017] [Indexed: 12/13/2022] Open
Abstract
Brain development is guided by the interactions between the genetic blueprint and the environment. Epigenetic mechanisms, especially DNA methylation, can mediate these interactions and may also trigger long-lasting adaptations in developmental programs that increase the risk of major depressive disorders (MDD) and schizophrenia (SCZ). Early life adversity is a major risk factor for MDD/SCZ and can trigger persistent genome-wide changes in DNA methylation at genes important to early, but also to mature, brain function, including neural proliferation, differentiation, and synaptic plasticity, among others. Moreover, genetic variations controlling dynamic DNA methylation in early life are thought to influence later epigenomic changes in SCZ. This finding corroborates the high genetic load and a neurodevelopmental origin of SCZ and shows that epigenetic responses to the environment are, at least in part, genetically controlled. Interestingly, genetic variants influencing DNA methylation are also enriched in risk variants from genome-wide association studies (GWAS) on SCZ supporting a role in neurodevelopment. Overall, epigenomic responses to early life adversity appear to be controlled to different degrees by genetics in MDD/SCZ, even though the potential reversibility of epigenomic processes may offer new hope for timely therapeutic interventions in MDD/SCZ.
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135
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Kel I, Chang Z, Galluccio N, Romeo M, Beretta S, Diomede L, Mezzelani A, Milanesi L, Dieterich C, Merelli I. SPIRE, a modular pipeline for eQTL analysis of RNA-Seq data, reveals a regulatory hotspot controlling miRNA expression in C. elegans. MOLECULAR BIOSYSTEMS 2017; 12:3447-3458. [PMID: 27722582 DOI: 10.1039/c6mb00453a] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
The interpretation of genome-wide association study is difficult, as it is hard to understand how polymorphisms can affect gene regulation, in particular for trans-regulatory elements located far from their controlling gene. Using RNA or protein expression data as phenotypes, it is possible to correlate their variations with specific genotypes. This technique is usually referred to as expression Quantitative Trait Loci (eQTLs) analysis and only few packages exist for the integration of genotype patterns and expression profiles. In particular, tools are needed for the analysis of next-generation sequencing (NGS) data on a genome-wide scale, which is essential to identify eQTLs able to control a large number of genes (hotspots). Here we present SPIRE (Software for Polymorphism Identification Regulating Expression), a generic, modular and functionally highly flexible pipeline for eQTL processing. SPIRE integrates different univariate and multivariate approaches for eQTL analysis, paying particular attention to the scalability of the procedure in order to support cis- as well as trans-mapping, thus allowing the identification of hotspots in NGS data. In particular, we demonstrated how SPIRE can handle big association study datasets, reproducing published results and improving the identification of trans-eQTLs. Furthermore, we employed the pipeline to analyse novel data concerning the genotypes of two different C. elegans strains (N2 and Hawaii) and related miRNA expression data, obtained using RNA-Seq. A miRNA regulatory hotspot was identified in chromosome 1, overlapping the transcription factor grh-1, known to be involved in the early phases of embryonic development of C. elegans. In a follow-up qPCR experiment we were able to verify most of the predicted eQTLs, as well as to show, for a novel miRNA, a significant difference in the sequences of the two analysed strains of C. elegans. SPIRE is publicly available as open source software at , together with some example data, a readme file, supplementary material and a short tutorial.
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Affiliation(s)
- Ivan Kel
- Instituto di Tecnologie Biomediche - Consiglio Nazionale delle Ricerche, via F.lli Cervi 93, 20090, Segrate, Milano, Italy.
| | - Zisong Chang
- Max Delbrück Center for Molecular Medicine, Berlin Institute for Medical Systems Biology, Robert-Rössle-Straße 10, 13125, Berlin, Germany.
| | - Nadia Galluccio
- Instituto di Tecnologie Biomediche - Consiglio Nazionale delle Ricerche, via F.lli Cervi 93, 20090, Segrate, Milano, Italy.
| | - Margherita Romeo
- Dipartimento di Biochimica e Farmacologia Molecolare, IRCCS - Istituto di Ricerche Farmacologiche "Mario Negri", Via Giuseppe La Masa 19, Milan, Italy.
| | - Stefano Beretta
- Dipartimento di Informatica Sistemistica e Comunicazione, Università degli studi di Milano-Biccoca, Viale Sarca 336, 20125 Milano, Italy.
| | - Luisa Diomede
- Dipartimento di Biochimica e Farmacologia Molecolare, IRCCS - Istituto di Ricerche Farmacologiche "Mario Negri", Via Giuseppe La Masa 19, Milan, Italy.
| | - Alessandra Mezzelani
- Instituto di Tecnologie Biomediche - Consiglio Nazionale delle Ricerche, via F.lli Cervi 93, 20090, Segrate, Milano, Italy.
| | - Luciano Milanesi
- Instituto di Tecnologie Biomediche - Consiglio Nazionale delle Ricerche, via F.lli Cervi 93, 20090, Segrate, Milano, Italy.
| | - Christoph Dieterich
- Section of Bioinformatics and Systems Cardiology, Klaus Tschira Institute for Integrative Computational Cardiology and Department of Internal Medicine III, University of Heidelberg, Grabengasse 1, 69117 Heidelberg, Germany.
| | - Ivan Merelli
- Instituto di Tecnologie Biomediche - Consiglio Nazionale delle Ricerche, via F.lli Cervi 93, 20090, Segrate, Milano, Italy.
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136
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A sex-linked supergene controls sperm morphology and swimming speed in a songbird. Nat Ecol Evol 2017; 1:1168-1176. [DOI: 10.1038/s41559-017-0235-2] [Citation(s) in RCA: 56] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2016] [Accepted: 06/06/2017] [Indexed: 01/08/2023]
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137
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Umemura T, Joshita S, Hamano H, Yoshizawa K, Kawa S, Tanaka E, Ota M. Association of autoimmune hepatitis with Src homology 2 adaptor protein 3 gene polymorphisms in Japanese patients. J Hum Genet 2017; 62:963-967. [DOI: 10.1038/jhg.2017.74] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2017] [Revised: 06/14/2017] [Accepted: 06/14/2017] [Indexed: 12/24/2022]
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138
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Calvete JJ, Petras D, Calderón-Celis F, Lomonte B, Encinar JR, Sanz-Medel A. Protein-species quantitative venomics: looking through a crystal ball. J Venom Anim Toxins Incl Trop Dis 2017; 23:27. [PMID: 28465678 PMCID: PMC5408492 DOI: 10.1186/s40409-017-0116-9] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2017] [Accepted: 04/19/2017] [Indexed: 12/16/2022] Open
Abstract
In this paper we discuss recent significant developments in the field of venom research, specifically the emergence of top-down proteomic applications that allow achieving compositional resolution at the level of the protein species present in the venom, and the absolute quantification of the venom proteins (the term “protein species” is used here to refer to all the different molecular forms in which a protein can be found. Please consult the special issue of Jornal of Proteomics “Towards deciphering proteomes via the proteoform, protein speciation, moonlighting and protein code concepts” published in 2016, vol. 134, pages 1-202). Challenges remain to be solved in order to achieve a compact and automated platform with which to routinely carry out comprehensive quantitative analysis of all toxins present in a venom. This short essay reflects the authors’ view of the immediate future in this direction for the proteomic analysis of venoms, particularly of snakes.
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Affiliation(s)
- Juan J Calvete
- Structural and Functional Venomics Laboratory, Instituto de Biomedicina de Valencia, C.S.I.C, Jaime Roig 11, 46010 Valencia, Spain
| | - Daniel Petras
- Skaggs School of Pharmacy & Pharmaceutical Sciences, University of California-San Diego, La Jolla, CA USA
| | | | - Bruno Lomonte
- Instituto Clodomiro Picado, Facultad de Microbiología, Universidad de Costa Rica, San José, Costa Rica
| | - Jorge Ruiz Encinar
- Department of Physical and Analytical Chemistry, University of Oviedo, Oviedo, Spain
| | - Alfredo Sanz-Medel
- Department of Physical and Analytical Chemistry, University of Oviedo, Oviedo, Spain
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139
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Ampattu BJ, Hagmann L, Liang C, Dittrich M, Schlüter A, Blom J, Krol E, Goesmann A, Becker A, Dandekar T, Müller T, Schoen C. Transcriptomic buffering of cryptic genetic variation contributes to meningococcal virulence. BMC Genomics 2017; 18:282. [PMID: 28388876 PMCID: PMC5383966 DOI: 10.1186/s12864-017-3616-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2016] [Accepted: 03/10/2017] [Indexed: 01/06/2023] Open
Abstract
Background Commensal bacteria like Neisseria meningitidis sometimes cause serious disease. However, genomic comparison of hyperinvasive and apathogenic lineages did not reveal unambiguous hints towards indispensable virulence factors. Here, in a systems biological approach we compared gene expression of the invasive strain MC58 and the carriage strain α522 under different ex vivo conditions mimicking commensal and virulence compartments to assess the strain-specific impact of gene regulation on meningococcal virulence. Results Despite indistinguishable ex vivo phenotypes, both strains differed in the expression of over 500 genes under infection mimicking conditions. These differences comprised in particular metabolic and information processing genes as well as genes known to be involved in host-damage such as the nitrite reductase and numerous LOS biosynthesis genes. A model based analysis of the transcriptomic differences in human blood suggested ensuing metabolic flux differences in energy, glutamine and cysteine metabolic pathways along with differences in the activation of the stringent response in both strains. In support of the computational findings, experimental analyses revealed differences in cysteine and glutamine auxotrophy in both strains as well as a strain and condition dependent essentiality of the (p)ppGpp synthetase gene relA and of a short non-coding AT-rich repeat element in its promoter region. Conclusions Our data suggest that meningococcal virulence is linked to transcriptional buffering of cryptic genetic variation in metabolic genes including global stress responses. They further highlight the role of regulatory elements for bacterial virulence and the limitations of model strain approaches when studying such genetically diverse species as N. meningitidis. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-3616-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Biju Joseph Ampattu
- Institute for Hygiene and Microbiology, Joseph-Schneider-Straße 2, University of Würzburg, 97080, Würzburg, Germany
| | - Laura Hagmann
- Institute for Hygiene and Microbiology, Joseph-Schneider-Straße 2, University of Würzburg, 97080, Würzburg, Germany
| | - Chunguang Liang
- Department of Bioinformatics, Biocenter, University of Würzburg, Am Hubland, 97074, Würzburg, Germany
| | - Marcus Dittrich
- Department of Bioinformatics, Biocenter, University of Würzburg, Am Hubland, 97074, Würzburg, Germany.,Department of Human Genetics, Biocenter, University of Würzburg, Am Hubland, 97074, Würzburg, Germany
| | - Andreas Schlüter
- Center for Biotechnology (CeBiTec), Bielefeld University, Universitätsstr. 27, 33615, Bielefeld, Germany
| | - Jochen Blom
- Institute for Bioinformatics and Systems Biology, Justus Liebig University Gießen, Heinrich-Buff-Ring 58, 35392, Gießen, Germany
| | - Elizaveta Krol
- LOEWE-Center for Synthetic Microbiology, Hans-Meerwein-Straße, 35032, Marburg, Germany
| | - Alexander Goesmann
- Institute for Bioinformatics and Systems Biology, Justus Liebig University Gießen, Heinrich-Buff-Ring 58, 35392, Gießen, Germany
| | - Anke Becker
- LOEWE-Center for Synthetic Microbiology, Hans-Meerwein-Straße, 35032, Marburg, Germany
| | - Thomas Dandekar
- Department of Bioinformatics, Biocenter, University of Würzburg, Am Hubland, 97074, Würzburg, Germany
| | - Tobias Müller
- Department of Bioinformatics, Biocenter, University of Würzburg, Am Hubland, 97074, Würzburg, Germany
| | - Christoph Schoen
- Institute for Hygiene and Microbiology, Joseph-Schneider-Straße 2, University of Würzburg, 97080, Würzburg, Germany.
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140
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Yao C, Joehanes R, Johnson AD, Huan T, Liu C, Freedman JE, Munson PJ, Hill DE, Vidal M, Levy D. Dynamic Role of trans Regulation of Gene Expression in Relation to Complex Traits. Am J Hum Genet 2017; 100:571-580. [PMID: 28285768 DOI: 10.1016/j.ajhg.2017.02.003] [Citation(s) in RCA: 66] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2016] [Accepted: 02/01/2017] [Indexed: 11/29/2022] Open
Abstract
Identifying causal genetic variants and understanding their mechanisms of effect on traits remains a challenge in genome-wide association studies (GWASs). In particular, how genetic variants (i.e., trans-eQTLs) affect expression of remote genes (i.e., trans-eGenes) remains unknown. We hypothesized that some trans-eQTLs regulate expression of distant genes by altering the expression of nearby genes (cis-eGenes). Using published GWAS datasets with 39,165 single-nucleotide polymorphisms (SNPs) associated with 1,960 traits, we explored whole blood gene expression associations of trait-associated SNPs in 5,257 individuals from the Framingham Heart Study. We identified 2,350 trans-eQTLs (at p < 10-7); more than 80% of them were found to have cis-associated eGenes. Mediation testing suggested that for 35% of trans-eQTL-trans-eGene pairs in different chromosomes and 90% pairs in the same chromosome, the disease-associated SNP may alter expression of the trans-eGene via cis-eGene expression. In addition, we identified 13 trans-eQTL hotspots, affecting from ten to hundreds of genes, suggesting the existence of master genetic regulators. Using causal inference testing, we searched causal variants across eight cardiometabolic traits (BMI, systolic and diastolic blood pressure, LDL cholesterol, HDL cholesterol, total cholesterol, triglycerides, and fasting blood glucose) and identified several cis-eGenes (ALDH2 for systolic and diastolic blood pressure, MCM6 and DARS for total cholesterol, and TRIB1 for triglycerides) that were causal mediators for the corresponding traits, as well as examples of trans-mediators (TAGAP for LDL cholesterol). The finding of extensive evidence of genome-wide mediation effects suggests a critical role of cryptic gene regulation underlying many disease traits.
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Affiliation(s)
- Chen Yao
- The Framingham Heart Study, 73 Mt. Wayte Avenue, Framingham, MA 01702, USA; The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, NIH, Bethesda, MD 20892, USA
| | - Roby Joehanes
- The Framingham Heart Study, 73 Mt. Wayte Avenue, Framingham, MA 01702, USA; The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, NIH, Bethesda, MD 20892, USA; Hebrew Senior Life, 1200 Centre Street Room #609, Boston, MA 02131, USA
| | - Andrew D Johnson
- The Framingham Heart Study, 73 Mt. Wayte Avenue, Framingham, MA 01702, USA; The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, NIH, Bethesda, MD 20892, USA
| | - Tianxiao Huan
- The Framingham Heart Study, 73 Mt. Wayte Avenue, Framingham, MA 01702, USA; The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, NIH, Bethesda, MD 20892, USA
| | - Chunyu Liu
- The Framingham Heart Study, 73 Mt. Wayte Avenue, Framingham, MA 01702, USA; The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, NIH, Bethesda, MD 20892, USA
| | - Jane E Freedman
- Department of Medicine, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Peter J Munson
- Mathematical and Statistical Computing Laboratory, Center for Information Technology, NIH, Bethesda, MD 20817, USA
| | - David E Hill
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Marc Vidal
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Daniel Levy
- The Framingham Heart Study, 73 Mt. Wayte Avenue, Framingham, MA 01702, USA; The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, NIH, Bethesda, MD 20892, USA.
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141
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Brynedal B, Choi J, Raj T, Bjornson R, Stranger BE, Neale BM, Voight BF, Cotsapas C. Large-Scale trans-eQTLs Affect Hundreds of Transcripts and Mediate Patterns of Transcriptional Co-regulation. Am J Hum Genet 2017; 100:581-591. [PMID: 28285767 DOI: 10.1016/j.ajhg.2017.02.004] [Citation(s) in RCA: 66] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2016] [Accepted: 02/09/2017] [Indexed: 12/15/2022] Open
Abstract
Efforts to decipher the causal relationships between differences in gene regulation and corresponding differences in phenotype have been stymied by several basic technical challenges. Although detecting local, cis-eQTLs is now routine, trans-eQTLs, which are distant from the genes of origin, are far more difficult to find because millions of SNPs must currently be compared to thousands of transcripts. Here, we demonstrate an alternative approach: we looked for SNPs associated with the expression of many genes simultaneously and found that hundreds of trans-eQTLs each affect hundreds of transcripts in lymphoblastoid cell lines across three African populations. These trans-eQTLs target the same genes across the three populations and show the same direction of effect. We discovered that target transcripts of a high-confidence set of trans-eQTLs encode proteins that interact more frequently than expected by chance, are bound by the same transcription factors, and are enriched for pathway annotations indicative of roles in basic cell homeostasis. We thus demonstrate that our approach can uncover trans-acting transcriptional control circuits that affect co-regulated groups of genes: a key to understanding how cellular pathways and processes are orchestrated.
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Affiliation(s)
- Boel Brynedal
- Department of Neurology, Yale University School of Medicine, New Haven, CT 06520, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
| | - JinMyung Choi
- Department of Neurology, Yale University School of Medicine, New Haven, CT 06520, USA
| | - Towfique Raj
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Division of Genetics, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Neurology, Brigham and Women's Hospital, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA
| | - Robert Bjornson
- Department of Computer Science, Yale University, New Haven, CT 06510, USA
| | - Barbara E Stranger
- Institute for Genomics and Systems Biology The University of Chicago, Chicago, IL 60637, USA
| | - Benjamin M Neale
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Harvard Medical School, Boston, MA 02115, USA; Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Benjamin F Voight
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Institute of Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Chris Cotsapas
- Department of Neurology, Yale University School of Medicine, New Haven, CT 06520, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Department of Genetics, Yale University School of Medicine, New Haven, CT 06520, USA.
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142
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Sabik OL, Farber CR. Using GWAS to identify novel therapeutic targets for osteoporosis. Transl Res 2017; 181:15-26. [PMID: 27837649 PMCID: PMC5357198 DOI: 10.1016/j.trsl.2016.10.009] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2016] [Revised: 10/17/2016] [Accepted: 10/20/2016] [Indexed: 12/14/2022]
Abstract
Osteoporosis is a common, increasingly prevalent, global health burden characterized by low bone mineral density (BMD) and increased risk of fracture. Despite its significant impact on human health, there is currently a lack of highly effective treatments free of side effects for osteoporosis. Therefore, a major goal in the field is to identify new drug targets. Genetic discovery has been shown to be effective in the unbiased identification of novel drug targets and genome-wide association studies (GWASs) have begun to provide insight into genetic basis of osteoporosis. Over the last decade, GWASs have led to the identification of ∼100 loci associated with BMD and other bone traits related to risk of fracture. However, there have been limited efforts to identify the causal genes underlying the GWAS loci or the mechanisms by which GWAS loci alter bone physiology. In this review, we summarize the current state of the field and discuss strategies for causal gene discovery and the evidence that the novel genes underlying GWAS loci are likely to be a new source of drug targets.
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Affiliation(s)
- Olivia L Sabik
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, Va; Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, Va
| | - Charles R Farber
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, Va; Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, Va; Department of Public Health Science, School of Medicine, University of Virginia, Charlottesville, Va.
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143
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Nijveen H, Ligterink W, Keurentjes JJB, Loudet O, Long J, Sterken MG, Prins P, Hilhorst HW, de Ridder D, Kammenga JE, Snoek BL. AraQTL - workbench and archive for systems genetics in Arabidopsis thaliana. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2017; 89:1225-1235. [PMID: 27995664 DOI: 10.1111/tpj.13457] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2016] [Revised: 11/24/2016] [Accepted: 12/06/2016] [Indexed: 06/06/2023]
Abstract
Genetical genomics studies uncover genome-wide genetic interactions between genes and their transcriptional regulators. High-throughput measurement of gene expression in recombinant inbred line populations has enabled investigation of the genetic architecture of variation in gene expression. This has the potential to enrich our understanding of the molecular mechanisms affected by and underlying natural variation. Moreover, it contributes to the systems biology of natural variation, as a substantial number of experiments have resulted in a valuable amount of interconnectable phenotypic, molecular and genotypic data. A number of genetical genomics studies have been published for Arabidopsis thaliana, uncovering many expression quantitative trait loci (eQTLs). However, these complex data are not easily accessible to the plant research community, leaving most of the valuable genetic interactions unexplored as cross-analysis of these studies is a major effort. We address this problem with AraQTL (http://www.bioinformatics.nl/Ara QTL/), an easily accessible workbench and database for comparative analysis and meta-analysis of all published Arabidopsis eQTL datasets. AraQTL provides a workbench for comparing, re-using and extending upon the results of these experiments. For example, one can easily screen a physical region for specific local eQTLs that could harbour candidate genes for phenotypic QTLs, or detect gene-by-environment interactions by comparing eQTLs under different conditions.
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Affiliation(s)
- Harm Nijveen
- Bioinformatics Group, Wageningen University, Droevendaalsesteeg 1, Wageningen, NL-6708 PB, The Netherlands
- Wageningen Seed Lab, Laboratory of Plant Physiology, Wageningen University, Droevendaalsesteeg 1, Wageningen, NL-6708 PB, The Netherlands
| | - Wilco Ligterink
- Wageningen Seed Lab, Laboratory of Plant Physiology, Wageningen University, Droevendaalsesteeg 1, Wageningen, NL-6708 PB, The Netherlands
| | - Joost J B Keurentjes
- Laboratory of Genetics, Wageningen University, Droevendaalsesteeg 1, Wageningen, NL-6708 PB, The Netherlands
| | - Olivier Loudet
- Institut Jean-Pierre Bourgin, INRA, AgroParisTech, CNRS, Université Paris-Saclay, Versailles, 78000, France
| | - Jiao Long
- Bioinformatics Group, Wageningen University, Droevendaalsesteeg 1, Wageningen, NL-6708 PB, The Netherlands
- Laboratory of Nematology, Wageningen University, Droevendaalsesteeg 1, Wageningen, NL-6708 PB, The Netherlands
| | - Mark G Sterken
- Laboratory of Nematology, Wageningen University, Droevendaalsesteeg 1, Wageningen, NL-6708 PB, The Netherlands
| | - Pjotr Prins
- Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, TN, 38163, USA
| | - Henk W Hilhorst
- Wageningen Seed Lab, Laboratory of Plant Physiology, Wageningen University, Droevendaalsesteeg 1, Wageningen, NL-6708 PB, The Netherlands
| | - Dick de Ridder
- Bioinformatics Group, Wageningen University, Droevendaalsesteeg 1, Wageningen, NL-6708 PB, The Netherlands
| | - Jan E Kammenga
- Laboratory of Nematology, Wageningen University, Droevendaalsesteeg 1, Wageningen, NL-6708 PB, The Netherlands
| | - Basten L Snoek
- Laboratory of Nematology, Wageningen University, Droevendaalsesteeg 1, Wageningen, NL-6708 PB, The Netherlands
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144
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Zhou J, Li X, Chen Y, Dai CC. De novo Transcriptome Assembly of Phomopsis liquidambari Provides Insights into Genes Associated with Different Lifestyles in Rice ( Oryza sativa L.). FRONTIERS IN PLANT SCIENCE 2017; 8:121. [PMID: 28220138 PMCID: PMC5292412 DOI: 10.3389/fpls.2017.00121] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2016] [Accepted: 01/20/2017] [Indexed: 05/25/2023]
Abstract
The mechanisms that trigger the switch from endophytic fungi to saprophytic fungi are largely unexplored. Broad host range Phomopsis liquidambari is established in endophytic and saprophytic systems with rice (Oryza sativa L.). Endophytic P. liquidambari promotes rice growth, increasing rice yield and improving the efficiency of nitrogen fertilizer. This species's saprophytic counterpart can decompose rice litterfall, promoting litter organic matter cycling and the release of nutrients and improving the soil microbial environment. Fluorescence microscopy, confocal laser scanning microscopy and quantitative PCR investigated the colonization dynamics and biomass of P. liquidambari in rice in vivo. P. liquidambari formed infection structures similar to phytopathogens with infected vascular tissues that systematically spread to acrial parts. However, different from pathogenic infection, P. liquidambari colonization exhibits space restriction and quantity restriction. Direct comparison of a fungal transcriptome under three different habitats provided a better understanding of lifestyle conversion during plant-fungi interactions. The isolated total RNA of Ck (pure culture), EP (endophytic culture) and FP (saprophytic culture) was subjected to Illumina transcriptome sequencing. To the best of our knowledge, this study is the first to investigate Phomopsis sp. using RNA-seq technology to obtain whole transcriptome information. A total of 27,401,258 raw reads were generated and 22,700 unigenes were annotated. Functional annotation indicated that carbohydrate metabolism and biosynthesis of secondary metabolites played important roles. There were 2522 differentially expressed genes (DEGs) between the saprophytic and endophytic lifestyles. Quantitative PCR analysis validated the DEGs of RNA-seq. Analysis of DEGs between saprophytic and endophytic lifestyles revealed that most genes from amino acids metabolism, carbohydrate metabolism, fatty acid biosynthesis, secondary metabolism and terpenoid and steroid biosynthesis were up-regulated in EP. Secondary metabolites of these pathways may affect fungal growth and development and contribute to signaling communication with the host. Most pathways of xenobiotic biodegradation and metabolism were upregulated in FP. Cytochrome P450s play diverse vital roles in endophytism and saprophytism, as their highly specialized functions are evolutionarily adapted to various ecological niches. These results help to characterize the relationship between fungi and plants, the diversity of fungi for ecological adaptations and the application prospects for fungi in sustainable agriculture.
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145
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Ishikawa A, Kusakabe M, Yoshida K, Ravinet M, Makino T, Toyoda A, Fujiyama A, Kitano J. Different contributions of local- and distant-regulatory changes to transcriptome divergence between stickleback ecotypes. Evolution 2017; 71:565-581. [PMID: 28075479 DOI: 10.1111/evo.13175] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2016] [Accepted: 12/21/2016] [Indexed: 12/12/2022]
Abstract
Differential gene expression can play an important role in phenotypic evolution and divergent adaptation. Although differential gene expression can be caused by both local- and distant-regulatory changes, we know little about their relative contribution to transcriptome evolution in natural populations. Here, we conducted expression quantitative trait loci (eQTL) analysis to investigate the genetic architecture underlying transcriptome divergence between marine and stream ecotypes of threespine sticklebacks (Gasterosteus aculeatus). We identified both local and distant eQTLs, some of which constitute hotspots, regions with a disproportionate number of significant eQTLs relative to the genomic background. The majority of local eQTLs including those in the hotspots caused expression changes consistent with the direction of transcriptomic divergence between ecotypes. Genome scan analysis showed that many local eQTLs overlapped with genomic regions of high differentiation. In contrast, nearly half of the distant eQTLs including those in the hotspots caused opposite expression changes, and few overlapped with regions of high differentiation, indicating that distant eQTLs may act as a constraint of transcriptome evolution. Finally, a comparison between two salinity conditions revealed that nearly half of eQTL hotspots were environment specific, suggesting that analysis of genetic architecture in multiple conditions is essential for predicting response to selection.
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Affiliation(s)
- Asano Ishikawa
- Division of Ecological Genetics, National Institute of Genetics, Shizuoka, Japan
| | - Makoto Kusakabe
- Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba, Japan.,Department of Biological Science, Faculty of Science, Shizuoka University, Shizuoka, Japan
| | - Kohta Yoshida
- Division of Ecological Genetics, National Institute of Genetics, Shizuoka, Japan
| | - Mark Ravinet
- Division of Ecological Genetics, National Institute of Genetics, Shizuoka, Japan.,Centre for Ecological and Evolutionary Synthesis, University of Oslo, Oslo, Norway
| | - Takashi Makino
- Division of Ecology and Evolutionary Biology, Graduate School of Life Sciences, Tohoku University, Miyagi, Japan
| | - Atsushi Toyoda
- Comparative Genomics Laboratory, National Institute of Genetics, Shizuoka, Japan
| | - Asao Fujiyama
- Comparative Genomics Laboratory, National Institute of Genetics, Shizuoka, Japan
| | - Jun Kitano
- Division of Ecological Genetics, National Institute of Genetics, Shizuoka, Japan
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146
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Tan H. The association between gene SNPs and cancer predisposition: Correlation or causality? EBioMedicine 2017; 16:8-9. [PMID: 28163041 PMCID: PMC5474513 DOI: 10.1016/j.ebiom.2017.01.047] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2017] [Accepted: 01/31/2017] [Indexed: 01/08/2023] Open
Affiliation(s)
- Hua Tan
- Center for Bioinformatics & Systems Biology, Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA.
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147
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Abstract
BACKGROUND Alternative splicing plays important roles in many regulatory processes and diseases in human. Many genetic variants contribute to phenotypic differences in gene expression and splicing that determine variations in human traits. Detecting genetic variants that affect splicing phenotypes is essential for understanding the functional impact of genetic variations on alternative splicing. For many situations, the key phenotype is the relative splicing ratios of alternative isoforms rather than the expression values of individual isoforms. Splicing quantitative trait loci (sQTL) analysis methods have been proposed for detecting associations of genetic variants with the vectors of isoform splicing ratios of genes. We call this task as composite sQTL analysis. Existing methods are computationally intensive and cannot scale up for whole genome analysis. RESULTS We developed an ultra-fast method named ulfasQTL for this task based on a previous method sQTLseekeR. It transforms tests of splicing ratios of multiple genes to a matrix form for efficient computation, and therefore can be applied for sQTL analysis at whole-genome scales at the speed thousands times faster than the existing method. We tested ulfasQTL on the data from the GEUVADIS project and compared it with an existing method. CONCLUSIONS ulfasQTL is a very efficient tool for composite splicing QTL analysis and can be applied on whole-genome analysis with acceptable time.
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Affiliation(s)
- Qian Yang
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST, Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Yue Hu
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST, Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Jun Li
- Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN, 46556, USA
| | - Xuegong Zhang
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST, Department of Automation, Tsinghua University, Beijing, 100084, China. .,School of Life Sciences, Tsinghua University, Beijing, 100084, China. .,Center for Synthetic and Systems Biology, Tsinghua University, Beijing, 100084, China.
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148
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The Future is The Past: Methylation QTLs in Schizophrenia. Genes (Basel) 2016; 7:genes7120104. [PMID: 27886132 PMCID: PMC5192480 DOI: 10.3390/genes7120104] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2016] [Revised: 11/13/2016] [Accepted: 11/16/2016] [Indexed: 12/12/2022] Open
Abstract
Genome-wide association studies (GWAS) have remarkably advanced insight into the genetic basis of schizophrenia (SCZ). Still, most of the functional variance in disease risk remains unexplained. Hence, there is a growing need to map genetic variability-to-genes-to-functions for understanding the pathophysiology of SCZ and the development of better treatments. Genetic variation can regulate various cellular functions including DNA methylation, an epigenetic mark with important roles in transcription and the mediation of environmental influences. Methylation quantitative trait loci (meQTLs) are derived by mapping levels of DNA methylation in genetically different, genotyped individuals and define loci at which DNA methylation is influenced by genetic variation. Recent evidence points to an abundance of meQTLs in brain tissues whose functional contributions to development and mental diseases are still poorly understood. Interestingly, fetal meQTLs reside in regulatory domains affecting methylome reconfiguration during early brain development and are enriched in loci identified by GWAS for SCZ. Moreover, fetal meQTLs are preserved in the adult brain and could trace early epigenomic deregulation during vulnerable periods. Overall, these findings highlight the role of fetal meQTLs in the genetic risk for and in the possible neurodevelopmental origin of SCZ.
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149
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Chen J, Tian W. Explaining the disease phenotype of intergenic SNP through predicted long range regulation. Nucleic Acids Res 2016; 44:8641-8654. [PMID: 27280978 PMCID: PMC5062962 DOI: 10.1093/nar/gkw519] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2016] [Revised: 05/05/2016] [Accepted: 05/29/2016] [Indexed: 12/27/2022] Open
Abstract
Thousands of disease-associated SNPs (daSNPs) are located in intergenic regions (IGR), making it difficult to understand their association with disease phenotypes. Recent analysis found that non-coding daSNPs were frequently located in or approximate to regulatory elements, inspiring us to try to explain the disease phenotypes of IGR daSNPs through nearby regulatory sequences. Hence, after locating the nearest distal regulatory element (DRE) to a given IGR daSNP, we applied a computational method named INTREPID to predict the target genes regulated by the DRE, and then investigated their functional relevance to the IGR daSNP's disease phenotypes. 36.8% of all IGR daSNP-disease phenotype associations investigated were possibly explainable through the predicted target genes, which were enriched with, were functionally relevant to, or consisted of the corresponding disease genes. This proportion could be further increased to 60.5% if the LD SNPs of daSNPs were also considered. Furthermore, the predicted SNP-target gene pairs were enriched with known eQTL/mQTL SNP-gene relationships. Overall, it's likely that IGR daSNPs may contribute to disease phenotypes by interfering with the regulatory function of their nearby DREs and causing abnormal expression of disease genes.
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Affiliation(s)
- Jingqi Chen
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200436, P.R. China Department of Biostatistics and Computational Biology, School of Life Sciences, Fudan University, Shanghai 200436, P.R. China
| | - Weidong Tian
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200436, P.R. China Department of Biostatistics and Computational Biology, School of Life Sciences, Fudan University, Shanghai 200436, P.R. China
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150
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Brand B, Scheinhardt MO, Friedrich J, Zimmer D, Reinsch N, Ponsuksili S, Schwerin M, Ziegler A. Adrenal cortex expression quantitative trait loci in a German Holstein × Charolais cross. BMC Genet 2016; 17:135. [PMID: 27716033 PMCID: PMC5053117 DOI: 10.1186/s12863-016-0442-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2016] [Accepted: 09/28/2016] [Indexed: 12/30/2022] Open
Abstract
Background The importance of the adrenal gland in regard to lactation and reproduction in cattle has been recognized early. Caused by interest in animal welfare and the impact of stress on economically important traits in farm animals the adrenal gland and its function within the stress response is of increasing interest. However, the molecular mechanisms and pathways involved in stress-related effects on economically important traits in farm animals are not fully understood. Gene expression is an important mechanism underlying complex traits, and genetic variants affecting the transcript abundance are thought to influence the manifestation of an expressed phenotype. We therefore investigated the genetic background of adrenocortical gene expression by applying an adaptive linear rank test to identify genome-wide expression quantitative trait loci (eQTL) for adrenal cortex transcripts in cattle. Results A total of 10,986 adrenal cortex transcripts and 37,204 single nucleotide polymorphisms (SNPs) were analysed in 145 F2 cows of a Charolais × German Holstein cross. We identified 505 SNPs that were associated with the abundance of 129 transcripts, comprising 482 cis effects and 17 trans effects. These SNPs were located on all chromosomes but X, 16, 24 and 28. Associated genes are mainly involved in molecular and cellular functions comprising free radical scavenging, cellular compromise, cell morphology and lipid metabolism, including genes such as CYP27A1 and LHCGR that have been shown to affect economically important traits in cattle. Conclusions In this study we showed that adrenocortical eQTL affect the expression of genes known to contribute to the phenotypic manifestation in cattle. Furthermore, some of the identified genes and related molecular pathways were previously shown to contribute to the phenotypic variation of behaviour, temperament and growth at the onset of puberty in the same population investigated here. We conclude that eQTL analysis appears to be a useful approach providing insight into the molecular and genetic background of complex traits in cattle and will help to understand molecular networks involved. Electronic supplementary material The online version of this article (doi:10.1186/s12863-016-0442-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Bodo Brand
- Institute for Genome Biology, Leibniz Institute for Farm Animal Biology, Wilhelm-Stahl-Allee, Dummerstorf, Germany.,Current affiliation: Institute for Farm Animal Research and Technology, University of Rostock, Justus-von-Liebig-Weg, 18059, Rostock, Germany
| | - Markus O Scheinhardt
- Institute of Medical Biometry and Statistics, University of Lübeck, Ratzeburger Allee, Lübeck, Germany
| | - Juliane Friedrich
- Institute for Farm Animal Research and Technology, University of Rostock, Justus-von-Liebig-Weg, Rostock, Germany
| | - Daisy Zimmer
- Institute for Farm Animal Research and Technology, University of Rostock, Justus-von-Liebig-Weg, Rostock, Germany
| | - Norbert Reinsch
- Institute for Genetics and Biometry, Leibniz Institute for Farm Animal Biology, Wilhelm-Stahl-Allee, Dummerstorf, Germany
| | - Siriluck Ponsuksili
- Institute for Genome Biology, Leibniz Institute for Farm Animal Biology, Wilhelm-Stahl-Allee, Dummerstorf, Germany
| | - Manfred Schwerin
- Institute for Genome Biology, Leibniz Institute for Farm Animal Biology, Wilhelm-Stahl-Allee, Dummerstorf, Germany.,Institute for Farm Animal Research and Technology, University of Rostock, Justus-von-Liebig-Weg, Rostock, Germany
| | - Andreas Ziegler
- Institute of Medical Biometry and Statistics, University of Lübeck, Ratzeburger Allee, Lübeck, Germany. .,Center for Clinical Trials, University of Lübeck, Ratzeburger Allee, Lübeck, Germany. .,School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Pietermaritzburg, South Africa.
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