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Yang S, Oksenberg N, Takayama S, Heo SJ, Poliakov A, Ahituv N, Dubchak I, Boffelli D. Functionally conserved enhancers with divergent sequences in distant vertebrates. BMC Genomics 2015; 16:882. [PMID: 26519295 PMCID: PMC4628251 DOI: 10.1186/s12864-015-2070-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2015] [Accepted: 10/13/2015] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND To examine the contributions of sequence and function conservation in the evolution of enhancers, we systematically identified enhancers whose sequences are not conserved among distant groups of vertebrate species, but have homologous function and are likely to be derived from a common ancestral sequence. Our approach combined comparative genomics and epigenomics to identify potential enhancer sequences in the genomes of three groups of distantly related vertebrate species. RESULTS We searched for sequences that were conserved within groups of closely related species but not between groups of more distant species, and were associated with an epigenetic mark of enhancer activity. To facilitate inferring orthology between non-conserved sequences, we limited our search to introns whose orthology could be unambiguously established by mapping the bracketing exons. We show that a subset of these non-conserved but syntenic sequences from the mouse and zebrafish genomes have homologous functions in a zebrafish transgenic enhancer assay. The conserved expression patterns driven by these enhancers are probably associated with short transcription factor-binding motifs present in the divergent sequences. CONCLUSIONS We have identified numerous potential enhancers with divergent sequences but a conserved function. These results indicate that selection on function, rather than sequence, may be a common mode of enhancer evolution; evidence for selection at the sequence level is not a necessary criterion to define a gene regulatory element.
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Affiliation(s)
- Song Yang
- Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
| | - Nir Oksenberg
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, 94158, USA.
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, 94158, USA.
| | - Sachiko Takayama
- Children's Hospital Oakland Research Institute, Oakland, CA, 94609, USA.
| | - Seok-Jin Heo
- Children's Hospital Oakland Research Institute, Oakland, CA, 94609, USA.
| | - Alexander Poliakov
- US Department of Energy Joint Genome Institute, 2800 Mitchell Drive, Walnut Creek, CA, 94598, USA.
| | - Nadav Ahituv
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, 94158, USA.
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, 94158, USA.
| | - Inna Dubchak
- Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
- US Department of Energy Joint Genome Institute, 2800 Mitchell Drive, Walnut Creek, CA, 94598, USA.
| | - Dario Boffelli
- Children's Hospital Oakland Research Institute, Oakland, CA, 94609, USA.
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Dubchak I, Balasubramanian S, Wang S, Meyden C, Sulakhe D, Poliakov A, Börnigen D, Xie B, Taylor A, Ma J, Paciorkowski AR, Mirzaa GM, Dave P, Agam G, Xu J, Al-Gazali L, Mason CE, Ross ME, Maltsev N, Gilliam TC. An integrative computational approach for prioritization of genomic variants. PLoS One 2014; 9:e114903. [PMID: 25506935 PMCID: PMC4266634 DOI: 10.1371/journal.pone.0114903] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2014] [Accepted: 11/15/2014] [Indexed: 12/27/2022] Open
Abstract
An essential step in the discovery of molecular mechanisms contributing to disease phenotypes and efficient experimental planning is the development of weighted hypotheses that estimate the functional effects of sequence variants discovered by high-throughput genomics. With the increasing specialization of the bioinformatics resources, creating analytical workflows that seamlessly integrate data and bioinformatics tools developed by multiple groups becomes inevitable. Here we present a case study of a use of the distributed analytical environment integrating four complementary specialized resources, namely the Lynx platform, VISTA RViewer, the Developmental Brain Disorders Database (DBDB), and the RaptorX server, for the identification of high-confidence candidate genes contributing to pathogenesis of spina bifida. The analysis resulted in prediction and validation of deleterious mutations in the SLC19A placental transporter in mothers of the affected children that causes narrowing of the outlet channel and therefore leads to the reduced folate permeation rate. The described approach also enabled correct identification of several genes, previously shown to contribute to pathogenesis of spina bifida, and suggestion of additional genes for experimental validations. The study demonstrates that the seamless integration of bioinformatics resources enables fast and efficient prioritization and characterization of genomic factors and molecular networks contributing to the phenotypes of interest.
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Affiliation(s)
- Inna Dubchak
- Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America
- Department of Energy Joint Genome Institute, Walnut Creek, California, United States of America
- * E-mail: (ID); (NM)
| | - Sandhya Balasubramanian
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
| | - Sheng Wang
- Toyota Technological Institute at Chicago, Chicago, Illinois, United States of America
| | - Cem Meyden
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, United States of America
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, New York, United States of America
- Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, New York, New York, United States of America
| | - Dinanath Sulakhe
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
- Computation Institute, University of Chicago/Argonne National Laboratory, Chicago, Illinois, United States of America
| | - Alexander Poliakov
- Department of Energy Joint Genome Institute, Walnut Creek, California, United States of America
| | - Daniela Börnigen
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
- Toyota Technological Institute at Chicago, Chicago, Illinois, United States of America
| | - Bingqing Xie
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
- Department of Computer Science, Illinois Institute of Technology, Chicago, Illinois, United States of America
| | - Andrew Taylor
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
| | - Jianzhu Ma
- Toyota Technological Institute at Chicago, Chicago, Illinois, United States of America
| | - Alex R. Paciorkowski
- Departments of Neurology, Pediatrics, and Biomedical Genetics and Center for Neural Development and Disease, University of Rochester Medical Center, Rochester, New York, United States of America
| | - Ghayda M. Mirzaa
- Seattle Children's Research Institute and Department of Pediatrics, University of Washington, Seattle, Washington, United States of America
| | - Paul Dave
- Computation Institute, University of Chicago/Argonne National Laboratory, Chicago, Illinois, United States of America
| | - Gady Agam
- Department of Computer Science, Illinois Institute of Technology, Chicago, Illinois, United States of America
| | - Jinbo Xu
- Toyota Technological Institute at Chicago, Chicago, Illinois, United States of America
| | - Lihadh Al-Gazali
- Department of Pediatrics, Faculty of Medicine and Health Sciences, United Arab Emirates University, Al-Ain, UAE
| | - Christopher E. Mason
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, United States of America
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, New York, United States of America
- Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, New York, New York, United States of America
| | - M. Elizabeth Ross
- Laboratory of Neurogenetics and Development, Weill Cornell Medical College, New York, New York, United States of America
| | - Natalia Maltsev
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
- Computation Institute, University of Chicago/Argonne National Laboratory, Chicago, Illinois, United States of America
- * E-mail: (ID); (NM)
| | - T. Conrad Gilliam
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
- Computation Institute, University of Chicago/Argonne National Laboratory, Chicago, Illinois, United States of America
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