1
|
Kaplow IM, Lawler AJ, Schäffer DE, Srinivasan C, Sestili HH, Wirthlin ME, Phan BN, Prasad K, Brown AR, Zhang X, Foley K, Genereux DP, Karlsson EK, Lindblad-Toh K, Meyer WK, Pfenning AR, Andrews G, Armstrong JC, Bianchi M, Birren BW, Bredemeyer KR, Breit AM, Christmas MJ, Clawson H, Damas J, Di Palma F, Diekhans M, Dong MX, Eizirik E, Fan K, Fanter C, Foley NM, Forsberg-Nilsson K, Garcia CJ, Gatesy J, Gazal S, Genereux DP, Goodman L, Grimshaw J, Halsey MK, Harris AJ, Hickey G, Hiller M, Hindle AG, Hubley RM, Hughes GM, Johnson J, Juan D, Kaplow IM, Karlsson EK, Keough KC, Kirilenko B, Koepfli KP, Korstian JM, Kowalczyk A, Kozyrev SV, Lawler AJ, Lawless C, Lehmann T, Levesque DL, Lewin HA, Li X, Lind A, Lindblad-Toh K, Mackay-Smith A, Marinescu VD, Marques-Bonet T, Mason VC, Meadows JRS, Meyer WK, Moore JE, Moreira LR, Moreno-Santillan DD, Morrill KM, Muntané G, Murphy WJ, Navarro A, Nweeia M, Ortmann S, Osmanski A, Paten B, Paulat NS, Pfenning AR, Phan BN, Pollard KS, Pratt HE, Ray DA, Reilly SK, Rosen JR, Ruf I, Ryan L, Ryder OA, Sabeti PC, Schäffer DE, Serres A, Shapiro B, Smit AFA, Springer M, Srinivasan C, Steiner C, Storer JM, Sullivan KAM, Sullivan PF, Sundström E, Supple MA, Swofford R, Talbot JE, Teeling E, Turner-Maier J, Valenzuela A, Wagner F, Wallerman O, Wang C, Wang J, Weng Z, Wilder AP, Wirthlin ME, Xue JR, Zhang X. Relating enhancer genetic variation across mammals to complex phenotypes using machine learning. Science 2023; 380:eabm7993. [PMID: 37104615 DOI: 10.1126/science.abm7993] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
Protein-coding differences between species often fail to explain phenotypic diversity, suggesting the involvement of genomic elements that regulate gene expression such as enhancers. Identifying associations between enhancers and phenotypes is challenging because enhancer activity can be tissue-dependent and functionally conserved despite low sequence conservation. We developed the Tissue-Aware Conservation Inference Toolkit (TACIT) to associate candidate enhancers with species' phenotypes using predictions from machine learning models trained on specific tissues. Applying TACIT to associate motor cortex and parvalbumin-positive interneuron enhancers with neurological phenotypes revealed dozens of enhancer-phenotype associations, including brain size-associated enhancers that interact with genes implicated in microcephaly or macrocephaly. TACIT provides a foundation for identifying enhancers associated with the evolution of any convergently evolved phenotype in any large group of species with aligned genomes.
Collapse
Affiliation(s)
- Irene M Kaplow
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Alyssa J Lawler
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Daniel E Schäffer
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Chaitanya Srinivasan
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Heather H Sestili
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Morgan E Wirthlin
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - BaDoi N Phan
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
- Medical Scientist Training Program, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Kavya Prasad
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Ashley R Brown
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Xiaomeng Zhang
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Kathleen Foley
- Department of Biological Sciences, Lehigh University, Bethlehem, PA, USA
| | - Diane P Genereux
- Broad Institute, Cambridge, MA, USA
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Elinor K Karlsson
- Broad Institute, Cambridge, MA, USA
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Kerstin Lindblad-Toh
- Broad Institute, Cambridge, MA, USA
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Wynn K Meyer
- Department of Biological Sciences, Lehigh University, Bethlehem, PA, USA
| | - Andreas R Pfenning
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
3
|
Raghunathan R, Polinski NK, Klein JA, Hogan JD, Shao C, Khatri K, Leon D, McComb ME, Manfredsson FP, Sortwell CE, Zaia J. Glycomic and Proteomic Changes in Aging Brain Nigrostriatal Pathway. Mol Cell Proteomics 2018; 17:1778-1787. [PMID: 29915149 DOI: 10.1074/mcp.ra118.000680] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2018] [Revised: 06/12/2018] [Indexed: 12/19/2022] Open
Abstract
Parkinson's disease (PD) is a neurological disorder characterized by the progressive loss of functional dopaminergic neurons in the nigrostriatal pathway in the brain. Although current treatments provide only symptomatic relief, gene therapy has the potential to slow or halt the degeneration of nigrostriatal dopamine neurons in PD patients. Adeno-associated viruses (AAV) are vectors of choice in gene therapy because of their well-characterized safety and efficacy profiles; however, although gene therapy has been successful in preclinical models of the disease, clinical trials in humans have failed to demonstrate efficacy. Significantly, all primary AAV receptors of the virus are glycans. We thus hypothesize that age related changes in glycan receptors of heparan sulfate (HS) proteoglycans (receptor for rAAV2), and/or N-glycans with terminal galactose (receptor for rAAV9) results in poor adeno-associated virus binding in either the striatum or substantia nigra, or both, affecting transduction and gene delivery. To test our hypothesis we analyzed the striatum and substantia nigra for changes in HS, N-glycans and proteomic signatures in young versus aged rat brain striatum and substantia nigra. We observed different brain region-specific HS disaccharide profiles in aged compared with young adult rats for brain region-specific profiles in striatum versus substantia nigra. We observed brain region- and age-specific N-glycan compositional profiles with respect to the terminal galactose units that serve as receptors for AAV9. We also observed brain region-specific changes in protein expression in the aging nigrostriatal pathway. These studies provide insight into age- and brain region-specific changes in glycan receptors and proteome that will inform design of improved viral vectors for Parkinson Disease (PD) gene therapy.
Collapse
Affiliation(s)
- Rekha Raghunathan
- From the ‡Department of Molecular and Translational Medicine, Center for Biomedical Mass Spectrometry, Boston University Medical Campus, Boston, Massachusetts
| | - Nicole K Polinski
- ‖Department of Translational Science and Molecular Medicine, Michigan State University
| | - Joshua A Klein
- ¶Bioinformatics Program, Boston University, Boston, Massachusetts
| | - John D Hogan
- ¶Bioinformatics Program, Boston University, Boston, Massachusetts
| | - Chun Shao
- §Department of Biochemistry, Center for Biomedical Mass Spectrometry, Boston University Medical Campus, Boston, Massachusetts
| | - Kshitij Khatri
- §Department of Biochemistry, Center for Biomedical Mass Spectrometry, Boston University Medical Campus, Boston, Massachusetts
| | - Deborah Leon
- §Department of Biochemistry, Center for Biomedical Mass Spectrometry, Boston University Medical Campus, Boston, Massachusetts
| | - Mark E McComb
- §Department of Biochemistry, Center for Biomedical Mass Spectrometry, Boston University Medical Campus, Boston, Massachusetts
| | - Fredric P Manfredsson
- ‖Department of Translational Science and Molecular Medicine, Michigan State University
| | - Caryl E Sortwell
- ‖Department of Translational Science and Molecular Medicine, Michigan State University
| | - Joseph Zaia
- From the ‡Department of Molecular and Translational Medicine, Center for Biomedical Mass Spectrometry, Boston University Medical Campus, Boston, Massachusetts; .,§Department of Biochemistry, Center for Biomedical Mass Spectrometry, Boston University Medical Campus, Boston, Massachusetts.,¶Bioinformatics Program, Boston University, Boston, Massachusetts
| |
Collapse
|
4
|
Farhan SMK, Wang J, Robinson JF, Prasad AN, Rupar CA, Siu VM, Hegele RA. Old gene, new phenotype: mutations in heparan sulfate synthesis enzyme, EXT2 leads to seizure and developmental disorder, no exostoses. J Med Genet 2015; 52:666-75. [PMID: 26246518 DOI: 10.1136/jmedgenet-2015-103279] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2015] [Accepted: 07/06/2015] [Indexed: 01/24/2023]
Abstract
BACKGROUND Heparan sulfate proteoglycans are vital components of the extracellular matrix and are essential for cellular homeostasis. Many genes are involved in modulating heparan sulfate synthesis, and when these genes are mutated, they can give rise to early-onset developmental disorders affecting multiple body systems. Herein, we describe a consanguineous family of four sibs with a novel disorder, which we designate as seizures-scoliosis-macrocephaly syndrome, characterised by seizures, intellectual disability, hypotonia, scoliosis, macrocephaly, hypertelorism and renal dysfunction. METHODS Our application of autozygosity mapping and whole-exome sequencing allowed us to identify mutations in the patients. To confirm the autosomal-recessive mode of inheritance, all available family members were genotyped. We also studied the effect of these mutations on protein expression and function in patient cells and using an in vitro system. RESULTS We identified two homozygous mutations p.Met87Arg and p.Arg95 Cys in exostosin 2, EXT2, a ubiquitously expressed gene that encodes a glycosyltransferase required for heparan sulfate synthesis. In patient cells, we observed diminished EXT2 expression and function. We also performed an in vitro assay to determine which mutation has a larger effect on protein expression and observed reduced EXT2 expression in constructs expressing either one of the mutations but a greater reduction when both residues were mutated. CONCLUSIONS In short, we have unravelled the genetic basis of a new recessive disorder, seizures-scoliosis-macrocephaly syndrome. Our results have implicated a well-characterised gene in a new developmental disorder and have further illustrated the spectrum of phenotypes that can arise due to errors in glycosylation.
Collapse
Affiliation(s)
- Sali M K Farhan
- Robarts Research Institute, London, Ontario, Canada Department of Biochemistry, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Jian Wang
- Robarts Research Institute, London, Ontario, Canada
| | | | - Asuri N Prasad
- Division of Clinical Neurological Sciences, Department of Pediatrics, London Health Sciences Centre, London, Ontario, Canada Children's Health Research Institute, London, Ontario, Canada
| | - C Anthony Rupar
- Department of Biochemistry, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada Children's Health Research Institute, London, Ontario, Canada Medical Genetics Program, Department of Pediatrics, London Health Sciences Centre, London, Ontario, Canada
| | - Victoria M Siu
- Department of Biochemistry, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada Children's Health Research Institute, London, Ontario, Canada Medical Genetics Program, Department of Pediatrics, London Health Sciences Centre, London, Ontario, Canada
| | | | - Robert A Hegele
- Robarts Research Institute, London, Ontario, Canada Department of Biochemistry, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| |
Collapse
|
5
|
Fedoseeva LA, Shevelev OB, Kolosova NG, Dymshits GM. MS2 phage ribonucleoproteins as exogenous internal control for RT-qPCR data normalization in gene expression study of developing rat brain. BIOCHEMISTRY (MOSCOW) 2015; 79:706-16. [PMID: 25108333 DOI: 10.1134/s0006297914070128] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
The most popular strategy for normalization of RT-qPCR data involves presenting them in comparison with expression of "housekeeping" genes. However, the required stable expression of the control genes is not always achievable. As an alternative, we used ribonucleoprotein phage particles as an exogenous internal control and demonstrated that this type of normalization provides a simple and reliable method for quantification in RT-qPCR experiments. Using phage-based normalization, we analyzed mRNA levels of three popular housekeeping genes coding β-actin, glyceraldehyde-3-phosphate dehydrogenase, and ribosomal protein L30 and showed high variability in their expression patterns during rat brain development, indicating that they should not be used as controls in gene expression studies of the developing brain either individually or in combination. Using phage-based controls, we showed interstrain differences and age-related changes in the expression of genes involved in proteoglycan biosynthesis and degradation in developing brain of senescence-accelerated OXYS rats and control Wistar rats.
Collapse
Affiliation(s)
- L A Fedoseeva
- Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, 630090, Russia.
| | | | | | | |
Collapse
|