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Morris VE, Hashmi SS, Zhu L, Maili L, Urbina C, Blackwell S, Greives MR, Buchanan EP, Mulliken JB, Blanton SH, Zheng WJ, Hecht JT, Letra A. Evidence for craniofacial enhancer variation underlying nonsyndromic cleft lip and palate. Hum Genet 2020; 139:1261-1272. [PMID: 32318854 DOI: 10.1007/s00439-020-02169-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Accepted: 04/13/2020] [Indexed: 12/14/2022]
Abstract
Nonsyndromic cleft lip with or without cleft palate (NSCLP) is a common birth defect for which only ~ 20% of the underlying genetic variation has been identified. Variants in noncoding regions have been increasingly suggested to contribute to the missing heritability. In this study, we investigated whether variation in craniofacial enhancers contributes to NSCLP. Candidate enhancers were identified using VISTA Enhancer Browser and previous publications. Prioritization was based on patterning defects in knockout mice, deletion/duplication of craniofacial genes in animal models and results of whole exome/whole genome sequencing studies. This resulted in 20 craniofacial enhancers to be investigated. Custom amplicon-based sequencing probes were designed and used for sequencing 380 NSCLP probands (from multiplex and simplex families of non-Hispanic white (NHW) and Hispanic ethnicities) using Illumina MiSeq. The frequencies of identified variants were compared to ethnically matched European (CEU) and Los Angeles Mexican (MXL) control genomes and used for association analyses. Variants in mm427/MSX1 and hs1582/SPRY1 showed genome-wide significant association with NSCLP (p ≤ 6.4 × 10-11). In silico analysis showed that these enhancer variants may disrupt important transcription factor binding sites. Haplotypes involving these enhancers and also mm435/ABCA4 were significantly associated with NSCLP, especially in NHW (p ≤ 6.3 × 10-7). Importantly, groupwise burden analysis showed several enhancer combinations significantly over-represented in NSCLP individuals, revealing novel NSCLP pathways and supporting a polygenic inheritance model. Our findings support the role of craniofacial enhancer sequence variation in the etiology of NSCLP.
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Affiliation(s)
- Vershanna E Morris
- Department of Pediatrics, UTHealth McGovern Medical School, Houston, TX, 77030, USA.,Pediatric Research Center, UTHealth McGovern Medical School, Houston, TX, 77030, USA
| | - S Shahrukh Hashmi
- Department of Pediatrics, UTHealth McGovern Medical School, Houston, TX, 77030, USA.,Pediatric Research Center, UTHealth McGovern Medical School, Houston, TX, 77030, USA
| | - Lisha Zhu
- UTHealth School of Biomedical Informatics, Houston, TX, 77054, USA
| | - Lorena Maili
- Department of Pediatrics, UTHealth McGovern Medical School, Houston, TX, 77030, USA.,Pediatric Research Center, UTHealth McGovern Medical School, Houston, TX, 77030, USA
| | - Christian Urbina
- Department of Pediatrics, UTHealth McGovern Medical School, Houston, TX, 77030, USA.,Pediatric Research Center, UTHealth McGovern Medical School, Houston, TX, 77030, USA
| | | | - Matthew R Greives
- Department of Pediatric Surgery, University of Texas Health Science Center McGovern Medical School, Houston, TX, 77030, USA
| | - Edward P Buchanan
- Department of Plastic Surgery, Texas Children's Hospital, Houston, TX, 77030, USA
| | - John B Mulliken
- Department of Plastic Surgery, Boston Children's Hospital, Boston, MA, 02115, USA
| | - Susan H Blanton
- Dr. John T. Macdonald Foundation Department of Human Genetics, John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - W Jim Zheng
- UTHealth School of Biomedical Informatics, Houston, TX, 77054, USA
| | - Jacqueline T Hecht
- Department of Pediatrics, UTHealth McGovern Medical School, Houston, TX, 77030, USA.,Pediatric Research Center, UTHealth McGovern Medical School, Houston, TX, 77030, USA.,Shriners' Hospital for Children, Houston, TX, 77030, USA.,Center for Craniofacial Research, UTHealth School of Dentistry, Houston, TX, 77054, USA
| | - Ariadne Letra
- School of Dentistry, Department of Diagnostic and Biomedical Sciences, University of Texas Health Science Center At Houston, 1941 East Road, BBSB 4210, Houston, TX, 77054, USA. .,Center for Craniofacial Research, UTHealth School of Dentistry, Houston, TX, 77054, USA.
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2
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Couch D, Yu Z, Nam JH, Allen C, Ramos PS, da Silveira WA, Hunt KJ, Hazard ES, Hardiman G, Lawson A, Chung D. GAIL: An interactive webserver for inference and dynamic visualization of gene-gene associations based on gene ontology guided mining of biomedical literature. PLoS One 2019; 14:e0219195. [PMID: 31260503 PMCID: PMC6602258 DOI: 10.1371/journal.pone.0219195] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Accepted: 06/18/2019] [Indexed: 01/08/2023] Open
Abstract
In systems biology, inference of functional associations among genes is compelling because the construction of functional association networks facilitates biomarker discovery. Specifically, such gene associations in human can help identify putative biomarkers that can be used as diagnostic tools in treating patients. Although biomedical literature is considered a valuable data source for this task, currently only a limited number of webservers are available for mining gene-gene associations from the vast amount of biomedical literature using text mining techniques. Moreover, these webservers often have limited coverage of biomedical literature and also lack efficient and user-friendly tools to interpret and visualize mined relationships among genes. To address these limitations, we developed GAIL (Gene-gene Association Inference based on biomedical Literature), an interactive webserver that infers human gene-gene associations from Gene Ontology (GO) guided biomedical literature mining and provides dynamic visualization of the resulting association networks and various gene set enrichment analysis tools. We evaluate the utility and performance of GAIL with applications to gene signatures associated with systemic lupus erythematosus and breast cancer. Results show that GAIL allows effective interrogation and visualization of gene-gene networks and their subnetworks, which facilitates biological understanding of gene-gene associations. GAIL is available at http://chunglab.io/GAIL/.
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Affiliation(s)
- Daniel Couch
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, United States of America
| | - Zhenning Yu
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, United States of America
| | - Jin Hyun Nam
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, United States of America
| | - Carter Allen
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, United States of America
| | - Paula S. Ramos
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, United States of America
- Department of Medicine, Medical University of South Carolina, Charleston, SC, United States of America
| | - Willian A. da Silveira
- Department of Pathology and Laboratory Medicine, Medical University of South Carolina, Charleston, SC, United States of America
- Center for Genomic Medicine, Medical University of South Carolina, Charleston, SC, United States of America
| | - Kelly J. Hunt
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, United States of America
| | - Edward S. Hazard
- Center for Genomic Medicine, Medical University of South Carolina, Charleston, SC, United States of America
| | - Gary Hardiman
- Department of Medicine, Medical University of South Carolina, Charleston, SC, United States of America
- Center for Genomic Medicine, Medical University of South Carolina, Charleston, SC, United States of America
| | - Andrew Lawson
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, United States of America
| | - Dongjun Chung
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, United States of America
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8
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Chen G, Zhao J, Cohen T, Tao C, Sun J, Xu H, Bernstam EV, Lawson A, Zeng J, Johnson AM, Holla V, Bailey AM, Lara-Guerra H, Litzenburger B, Meric-Bernstam F, Jim Zheng W. Using Ontology Fingerprints to disambiguate gene name entities in the biomedical literature. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2015; 2015:bav034. [PMID: 25858285 PMCID: PMC4390608 DOI: 10.1093/database/bav034] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2014] [Accepted: 03/17/2015] [Indexed: 11/14/2022]
Abstract
Ambiguous gene names in the biomedical literature are a barrier to accurate information extraction. To overcome this hurdle, we generated Ontology Fingerprints for selected genes that are relevant for personalized cancer therapy. These Ontology Fingerprints were used to evaluate the association between genes and biomedical literature to disambiguate gene names. We obtained 93.6% precision for the test gene set and 80.4% for the area under a receiver-operating characteristics curve for gene and article association. The core algorithm was implemented using a graphics processing unit-based MapReduce framework to handle big data and to improve performance. We conclude that Ontology Fingerprints can help disambiguate gene names mentioned in text and analyse the association between genes and articles. Database URL: http://www.ontologyfingerprint.org
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Affiliation(s)
- Guocai Chen
- Center for Computational Biomedicine, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA, Department of Public Health Science, Medical University of South Carolina, 135 Cannon Street, Suite 303, Charleston, SC 29425, USA and Department of Investigational Cancer Therapeutics, Institute for Personalized Cancer Therapy, UT-MD Anderson Cancer Center, 1400 Holcombe Blvd., FC8.3044, Houston, TX 77030, USA
| | - Jieyi Zhao
- Center for Computational Biomedicine, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA, Department of Public Health Science, Medical University of South Carolina, 135 Cannon Street, Suite 303, Charleston, SC 29425, USA and Department of Investigational Cancer Therapeutics, Institute for Personalized Cancer Therapy, UT-MD Anderson Cancer Center, 1400 Holcombe Blvd., FC8.3044, Houston, TX 77030, USA
| | - Trevor Cohen
- Center for Computational Biomedicine, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA, Department of Public Health Science, Medical University of South Carolina, 135 Cannon Street, Suite 303, Charleston, SC 29425, USA and Department of Investigational Cancer Therapeutics, Institute for Personalized Cancer Therapy, UT-MD Anderson Cancer Center, 1400 Holcombe Blvd., FC8.3044, Houston, TX 77030, USA
| | - Cui Tao
- Center for Computational Biomedicine, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA, Department of Public Health Science, Medical University of South Carolina, 135 Cannon Street, Suite 303, Charleston, SC 29425, USA and Department of Investigational Cancer Therapeutics, Institute for Personalized Cancer Therapy, UT-MD Anderson Cancer Center, 1400 Holcombe Blvd., FC8.3044, Houston, TX 77030, USA
| | - Jingchun Sun
- Center for Computational Biomedicine, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA, Department of Public Health Science, Medical University of South Carolina, 135 Cannon Street, Suite 303, Charleston, SC 29425, USA and Department of Investigational Cancer Therapeutics, Institute for Personalized Cancer Therapy, UT-MD Anderson Cancer Center, 1400 Holcombe Blvd., FC8.3044, Houston, TX 77030, USA
| | - Hua Xu
- Center for Computational Biomedicine, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA, Department of Public Health Science, Medical University of South Carolina, 135 Cannon Street, Suite 303, Charleston, SC 29425, USA and Department of Investigational Cancer Therapeutics, Institute for Personalized Cancer Therapy, UT-MD Anderson Cancer Center, 1400 Holcombe Blvd., FC8.3044, Houston, TX 77030, USA
| | - Elmer V Bernstam
- Center for Computational Biomedicine, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA, Department of Public Health Science, Medical University of South Carolina, 135 Cannon Street, Suite 303, Charleston, SC 29425, USA and Department of Investigational Cancer Therapeutics, Institute for Personalized Cancer Therapy, UT-MD Anderson Cancer Center, 1400 Holcombe Blvd., FC8.3044, Houston, TX 77030, USA
| | - Andrew Lawson
- Center for Computational Biomedicine, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA, Department of Public Health Science, Medical University of South Carolina, 135 Cannon Street, Suite 303, Charleston, SC 29425, USA and Department of Investigational Cancer Therapeutics, Institute for Personalized Cancer Therapy, UT-MD Anderson Cancer Center, 1400 Holcombe Blvd., FC8.3044, Houston, TX 77030, USA
| | - Jia Zeng
- Center for Computational Biomedicine, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA, Department of Public Health Science, Medical University of South Carolina, 135 Cannon Street, Suite 303, Charleston, SC 29425, USA and Department of Investigational Cancer Therapeutics, Institute for Personalized Cancer Therapy, UT-MD Anderson Cancer Center, 1400 Holcombe Blvd., FC8.3044, Houston, TX 77030, USA
| | - Amber M Johnson
- Center for Computational Biomedicine, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA, Department of Public Health Science, Medical University of South Carolina, 135 Cannon Street, Suite 303, Charleston, SC 29425, USA and Department of Investigational Cancer Therapeutics, Institute for Personalized Cancer Therapy, UT-MD Anderson Cancer Center, 1400 Holcombe Blvd., FC8.3044, Houston, TX 77030, USA
| | - Vijaykumar Holla
- Center for Computational Biomedicine, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA, Department of Public Health Science, Medical University of South Carolina, 135 Cannon Street, Suite 303, Charleston, SC 29425, USA and Department of Investigational Cancer Therapeutics, Institute for Personalized Cancer Therapy, UT-MD Anderson Cancer Center, 1400 Holcombe Blvd., FC8.3044, Houston, TX 77030, USA
| | - Ann M Bailey
- Center for Computational Biomedicine, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA, Department of Public Health Science, Medical University of South Carolina, 135 Cannon Street, Suite 303, Charleston, SC 29425, USA and Department of Investigational Cancer Therapeutics, Institute for Personalized Cancer Therapy, UT-MD Anderson Cancer Center, 1400 Holcombe Blvd., FC8.3044, Houston, TX 77030, USA
| | - Humberto Lara-Guerra
- Center for Computational Biomedicine, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA, Department of Public Health Science, Medical University of South Carolina, 135 Cannon Street, Suite 303, Charleston, SC 29425, USA and Department of Investigational Cancer Therapeutics, Institute for Personalized Cancer Therapy, UT-MD Anderson Cancer Center, 1400 Holcombe Blvd., FC8.3044, Houston, TX 77030, USA
| | - Beate Litzenburger
- Center for Computational Biomedicine, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA, Department of Public Health Science, Medical University of South Carolina, 135 Cannon Street, Suite 303, Charleston, SC 29425, USA and Department of Investigational Cancer Therapeutics, Institute for Personalized Cancer Therapy, UT-MD Anderson Cancer Center, 1400 Holcombe Blvd., FC8.3044, Houston, TX 77030, USA
| | - Funda Meric-Bernstam
- Center for Computational Biomedicine, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA, Department of Public Health Science, Medical University of South Carolina, 135 Cannon Street, Suite 303, Charleston, SC 29425, USA and Department of Investigational Cancer Therapeutics, Institute for Personalized Cancer Therapy, UT-MD Anderson Cancer Center, 1400 Holcombe Blvd., FC8.3044, Houston, TX 77030, USA
| | - W Jim Zheng
- Center for Computational Biomedicine, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA, Department of Public Health Science, Medical University of South Carolina, 135 Cannon Street, Suite 303, Charleston, SC 29425, USA and Department of Investigational Cancer Therapeutics, Institute for Personalized Cancer Therapy, UT-MD Anderson Cancer Center, 1400 Holcombe Blvd., FC8.3044, Houston, TX 77030, USA
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