1
|
Bhattacharyya T, Ghosh A, Verma S, Raghu P, Sowdhamini R. Structural rationale to understand the effect of disease-associated mutations on Myotubularin. Curr Res Struct Biol 2023; 5:100100. [PMID: 37101954 PMCID: PMC10123148 DOI: 10.1016/j.crstbi.2023.100100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 02/16/2023] [Accepted: 02/28/2023] [Indexed: 03/29/2023] Open
Abstract
Myotubularin or MTM1 is a lipid phosphatase that regulates vesicular trafficking in the cell. The MTM1 gene is mutated in a severe form of muscular disease, X-linked myotubular myopathy or XLMTM, affecting 1 in 50,000 newborn males worldwide. There have been several studies on the disease pathology of XLMTM, but the structural effects of missense mutations of MTM1 are underexplored due to the unavailability of a crystal structure. MTM1 consists of three domains-a lipid-binding N-terminal GRAM domain, the phosphatase domain and a coiled-coil domain which aids dimerisation of Myotubularin homologs. While most mutations reported to date map to the phosphatase domain of MTM1, the other two domains on the sequence are also frequently mutated in XLMTM. To understand the overall structural and functional effects of missense mutations on MTM1, we curated several missense mutations and performed in silico and in vitro studies. Apart from significantly impaired binding to substrate, abrogation of phosphatase activity was observed for a few mutants. Possible long-range effects of mutations from non-catalytic domains on phosphatase activity were observed as well. Coiled-coil domain mutants have been characterised here for the first time in XLMTM literature.
Collapse
|
2
|
Shieh JT, Penon-Portmann M, Wong KHY, Levy-Sakin M, Verghese M, Slavotinek A, Gallagher RC, Mendelsohn BA, Tenney J, Beleford D, Perry H, Chow SK, Sharo AG, Brenner SE, Qi Z, Yu J, Klein OD, Martin D, Kwok PY, Boffelli D. Application of full-genome analysis to diagnose rare monogenic disorders. NPJ Genom Med 2021; 6:77. [PMID: 34556655 PMCID: PMC8460793 DOI: 10.1038/s41525-021-00241-5] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Accepted: 10/21/2020] [Indexed: 11/30/2022] Open
Abstract
Current genetic tests for rare diseases provide a diagnosis in only a modest proportion of cases. The Full-Genome Analysis method, FGA, combines long-range assembly and whole-genome sequencing to detect small variants, structural variants with breakpoint resolution, and phasing. We built a variant prioritization pipeline and tested FGA’s utility for diagnosis of rare diseases in a clinical setting. FGA identified structural variants and small variants with an overall diagnostic yield of 40% (20 of 50 cases) and 35% in exome-negative cases (8 of 23 cases), 4 of these were structural variants. FGA detected and mapped structural variants that are missed by short reads, including non-coding duplication, and phased variants across long distances of more than 180 kb. With the prioritization algorithm, longer DNA technologies could replace multiple tests for monogenic disorders and expand the range of variants detected. Our study suggests that genomes produced from technologies like FGA can improve variant detection and provide higher resolution genome maps for future application.
Collapse
Affiliation(s)
- Joseph T Shieh
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA. .,Division of Medical Genetics, Pediatrics, Benioff Children's Hospital, University of California San Francisco, San Francisco, CA, USA.
| | - Monica Penon-Portmann
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA.,Division of Medical Genetics, Pediatrics, Benioff Children's Hospital, University of California San Francisco, San Francisco, CA, USA
| | - Karen H Y Wong
- Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - Michal Levy-Sakin
- Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - Michelle Verghese
- Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - Anne Slavotinek
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA.,Division of Medical Genetics, Pediatrics, Benioff Children's Hospital, University of California San Francisco, San Francisco, CA, USA
| | - Renata C Gallagher
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA.,Division of Medical Genetics, Pediatrics, Benioff Children's Hospital, University of California San Francisco, San Francisco, CA, USA
| | - Bryce A Mendelsohn
- Division of Medical Genetics, Pediatrics, Benioff Children's Hospital, University of California San Francisco, San Francisco, CA, USA
| | - Jessica Tenney
- Division of Medical Genetics, Pediatrics, Benioff Children's Hospital, University of California San Francisco, San Francisco, CA, USA
| | - Daniah Beleford
- Division of Medical Genetics, Pediatrics, Benioff Children's Hospital, University of California San Francisco, San Francisco, CA, USA
| | - Hazel Perry
- Division of Medical Genetics, Pediatrics, Benioff Children's Hospital, University of California San Francisco, San Francisco, CA, USA
| | - Stephen K Chow
- Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - Andrew G Sharo
- Biophysics Graduate Group, University of California Berkeley, Berkeley, CA, USA
| | - Steven E Brenner
- Department of Plant and Microbial Biology, University of California Berkeley, Berkeley, CA, USA
| | - Zhongxia Qi
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Jingwei Yu
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Ophir D Klein
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA.,Division of Medical Genetics, Pediatrics, Benioff Children's Hospital, University of California San Francisco, San Francisco, CA, USA.,Craniofacial Biology and Department of Orofacial Sciences, University of California San Francisco, San Francisco, CA, USA
| | - David Martin
- Children's Hospital Oakland Research Institute, Benioff Children's Hospital Oakland, University of California San Francisco, Oakland, CA, USA
| | - Pui-Yan Kwok
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA.,Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA.,Department of Dermatology, University of California San Francisco, San Francisco, CA, USA
| | - Dario Boffelli
- Children's Hospital Oakland Research Institute, Benioff Children's Hospital Oakland, University of California San Francisco, Oakland, CA, USA
| |
Collapse
|
3
|
Penon M, Zahed H, Berger V, Su I, Shieh JT. Using exome sequencing to decipher family history in a healthy individual: Comparison of pathogenic and population MTM1 variants. Mol Genet Genomic Med 2018; 6:722-727. [PMID: 30047259 PMCID: PMC6160706 DOI: 10.1002/mgg3.405] [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: 11/02/2017] [Revised: 03/11/2018] [Accepted: 03/13/2018] [Indexed: 12/31/2022] Open
Abstract
Background When a family encounters the loss of a child early in life, extensive genetic testing of the affected neonate is sometimes not performed or not possible. However, the increasing availability of genomic sequencing may allow for direct application to families in cases where there is a condition inherited from parental gene(s). When neonatal testing is not possible, it is feasible to perform family testing as long as there is optimal interpretation of the genomic information. Here, we present an example of a healthy adult woman with a history of recurrent male neonatal losses due to severe respiratory distress who presented to Medical Genetics for evaluation. A family history of additional male neonatal loss was present, suggesting a potential inherited genetic etiology. Methods Although there was no DNA available from the neonates, by performing exome sequencing on the healthy adult woman, we found a missense variant in MTM1 as a potential candidate, which was deemed pathogenic based on multiple criteria including past report. Results By performing an analysis of all known MTM1‐disease associated mutations and control population variation, we can also better infer the effects of missense variations on MTM1, as not all variants are truncating. MTM1‐X‐linked myotubular myopathy is a condition that leads to male perinatal respiratory failure and a high risk for early mortality. Conclusions The application of genetic testing in the healthy population here highlights the broader utility of genomic sequencing in evaluating unexplained recurrent neonatal loss, especially when genetic testing is not available on the affected neonates.
Collapse
Affiliation(s)
- Monica Penon
- Department of Pediatrics, Division of Medical Genetics, University of California San Francisco, San Francisco, California
| | - Hengameh Zahed
- Department of Pediatrics, Division of Medical Genetics, University of California San Francisco, San Francisco, California
| | - Victoria Berger
- Department of Pediatrics, Division of Medical Genetics, University of California San Francisco, San Francisco, California.,Department of Obstetrics, Gynecology and Reproductive Science, University of California San Francisco, San Francisco, California
| | - Irene Su
- Department of Pediatrics, Division of Medical Genetics, University of California San Francisco, San Francisco, California
| | - Joseph T Shieh
- Department of Pediatrics, Division of Medical Genetics, University of California San Francisco, San Francisco, California.,Institute for Human Genetics, University of California San Francisco, San Francisco, California
| |
Collapse
|