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Kumar R, K Rajput N, Jolly B, Narwade A, Bhardwaj A. MitoLink: A generic integrated web-based workflow system to evaluate genotype-phenotype correlations in human mitochondrial diseases: Observations from the GenomeAsia Pilot project. Mitochondrion 2021; 61:54-61. [PMID: 34571248 DOI: 10.1016/j.mito.2021.09.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 08/09/2021] [Accepted: 09/22/2021] [Indexed: 11/17/2022]
Abstract
MitoLink is a generic, scalable and modular web-based workflow system developed to study genotype-phenotype correlations in human mitochondrial diseases. MitoLink integrates applications for assessment of genomic variation and currently houses genome-wide datasets from GenomeAsia Pilot project, gnomAD, ClinVar and DisGenNet. In this study, a reference list of nearly 3975 proteins (both nuclear and mitochondrial encoded) with mitochondrial function is reported. This protein set is mapped to disease associated variants in the GenomeAsia Pilot Project and DisGenNet and evaluated for pathogenicity as defined by ClinVar. Observations of shared genetic components in potential comorbidities are discussed from gene-disease network in Asian population, however, the platform is generic and can be applied to any population dataset. MitoLink is a unique customized workflow system that allows for systematic storage, extraction, analysis and visualization of genomic variation to understand genotype-phenotype correlations for mitochondrial diseases. Given the modularity of tool and data integration, MitoLink is a scalable system that can accommodate a diverse set of applications linked via standard data structure within the framework of Galaxy. MitoLink is built on FAIR principles and supports creation of reproducible workflows towards understanding genotype-phenotype correlations across several disease phenotypes globally.
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Affiliation(s)
- Rakesh Kumar
- Bioinformatics Center, CSIR-Institute of Microbial Technology, Sector 39A, Chandigarh 160036, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Neeraj K Rajput
- Bioinformatics Center, CSIR-Institute of Microbial Technology, Sector 39A, Chandigarh 160036, India
| | - Bani Jolly
- Bioinformatics Center, CSIR-Institute of Microbial Technology, Sector 39A, Chandigarh 160036, India
| | - Amol Narwade
- CSIR-Open Source Drug Discovery Consortium, Delhi, India
| | - Anshu Bhardwaj
- Bioinformatics Center, CSIR-Institute of Microbial Technology, Sector 39A, Chandigarh 160036, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
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2
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McCormick EM, Lott MT, Dulik MC, Shen L, Attimonelli M, Vitale O, Karaa A, Bai R, Pineda-Alvarez DE, Singh LN, Stanley CM, Wong S, Bhardwaj A, Merkurjev D, Mao R, Sondheimer N, Zhang S, Procaccio V, Wallace DC, Gai X, Falk MJ. Specifications of the ACMG/AMP standards and guidelines for mitochondrial DNA variant interpretation. Hum Mutat 2020; 41:2028-2057. [PMID: 32906214 DOI: 10.1002/humu.24107] [Citation(s) in RCA: 80] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Revised: 08/20/2020] [Accepted: 08/28/2020] [Indexed: 12/12/2022]
Abstract
Mitochondrial DNA (mtDNA) variant pathogenicity interpretation has special considerations given unique features of the mtDNA genome, including maternal inheritance, variant heteroplasmy, threshold effect, absence of splicing, and contextual effects of haplogroups. Currently, there are insufficient standardized criteria for mtDNA variant assessment, which leads to inconsistencies in clinical variant pathogenicity reporting. An international working group of mtDNA experts was assembled within the Mitochondrial Disease Sequence Data Resource Consortium and obtained Expert Panel status from ClinGen. This group reviewed the 2015 American College of Medical Genetics and Association of Molecular Pathology standards and guidelines that are widely used for clinical interpretation of DNA sequence variants and provided further specifications for additional and specific guidance related to mtDNA variant classification. These Expert Panel consensus specifications allow for consistent consideration of the unique aspects of the mtDNA genome that directly influence variant assessment, including addressing mtDNA genome composition and structure, haplogroups and phylogeny, maternal inheritance, heteroplasmy, and functional analyses unique to mtDNA, as well as specifications for utilization of mtDNA genomic databases and computational algorithms.
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Affiliation(s)
- Elizabeth M McCormick
- Mitochondrial Medicine Frontier Program, Division of Human Genetics, Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Marie T Lott
- Center for Mitochondrial and Epigenomic Medicine, Division of Human Genetics, Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Matthew C Dulik
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Lishuang Shen
- Center for Personalized Medicine, Department of Pathology and Laboratory Medicine, Children's Hospital Los Angeles, Los Angeles, California, USA
| | - Marcella Attimonelli
- Department of Biosciences, Biotechnology, and Biopharmaceutics, University of Bari "A. Moro", Bari, Italy
| | - Ornella Vitale
- Department of Biosciences, Biotechnology, and Biopharmaceutics, University of Bari "A. Moro", Bari, Italy
| | - Amel Karaa
- Genetics Unit, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | | | | | - Larry N Singh
- Center for Mitochondrial and Epigenomic Medicine, Division of Human Genetics, Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Christine M Stanley
- Variantyx, Inc, Framingham, Massachusetts, USA.,QNA Diagnostics, Cambridge, Massachusetts, USA
| | | | - Anshu Bhardwaj
- CSIR-Institute of Microbial Technology, Chandigarh, India
| | - Daria Merkurjev
- Center for Personalized Medicine, Department of Pathology and Laboratory Medicine, Children's Hospital Los Angeles, Los Angeles, California, USA
| | - Rong Mao
- ARUP Institute for Clinical and Experimental Pathology, ARUP Laboratories, Salt Lake City, Utah, USA.,Department of Pathology, University of Utah, Salt Lake City, Utah, USA
| | - Neal Sondheimer
- Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Shiping Zhang
- Center for Mitochondrial and Epigenomic Medicine, Division of Human Genetics, Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Vincent Procaccio
- Department of Biochemistry and Genetics, MitoVasc Institute, UMR CNRS 6015- INSERM U1083, CHU Angers, Angers, France
| | - Douglas C Wallace
- Center for Mitochondrial and Epigenomic Medicine, Division of Human Genetics, Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Xiaowu Gai
- Center for Personalized Medicine, Department of Pathology and Laboratory Medicine, Children's Hospital Los Angeles, Los Angeles, California, USA.,Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Marni J Falk
- Mitochondrial Medicine Frontier Program, Division of Human Genetics, Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Singh V, Jolly B, Rajput NK, Pramanik S, Bhardwaj A. MtBrowse: An integrative genomics browser for human mitochondrial DNA. Mitochondrion 2019; 48:31-36. [PMID: 30738202 DOI: 10.1016/j.mito.2019.02.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2018] [Revised: 11/10/2018] [Accepted: 02/06/2019] [Indexed: 12/18/2022]
Abstract
The human mitochondrion is a unique semi-autonomous organelle with a genome of its own and also requires nuclear encoded components to carry out its functions. In addition to being the powerhouse of the cell, mitochondria plays a central role in several metabolic pathways. It is therefore challenging to delineate the cause-effect relationship in context of mitochondrial dysfunction. Several studies implicate mutations in mitochondrial DNA (mtDNA) in various complex diseases. The human mitochondrial DNA (mtDNA) encodes a set of 37 genes, 13 protein coding, 22 tRNAs and two ribosomal RNAs, which are essential structural and functional components of the electron transport chain. As mentioned above, variations in these genes have been implicated in a broad spectrum of diseases and are extensively reported in literature and various databases. A large number of databases and prediction methods have been published to elucidate the role of human mitochondrial DNA in various disease phenotypes. However, there is no centralized resource to visualize this genotype-phenotype data. Towards this, we have developed MtBrowse: an integrative genomics browser for human mtDNA. As of now, MtBrowse has four categories - Gene, Disease, Reported variation and Variation prediction. These categories have 105 tracks and house data on mitochondrial reference genes, around 600 variants reported in literature with respect to various disease phenotypes and predictions for potential pathogenic variations in protein-coding genes. MtBrowse also hosts genomic variation data from over 5000 individuals on 22 disease phenotypes. MtBrowse may be accessed at http://ab-openlab.csir.res.in/cgi-bin/gb2/gbrowse.
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Affiliation(s)
- Vipin Singh
- University Institute of Biotechnology, Chandigarh University, Mohali, India
| | - Bani Jolly
- Bioinformatics Center, CSIR-Institute of Microbial Technology, Chandigarh, India
| | - Neeraj K Rajput
- Bioinformatics Center, CSIR-Institute of Microbial Technology, Chandigarh, India
| | - Sayan Pramanik
- Department of Biotechnology, Indian Institute of Technology, Kharagpur, India
| | - Anshu Bhardwaj
- Bioinformatics Center, CSIR-Institute of Microbial Technology, Chandigarh, India.
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Niroula A, Vihinen M. PON-mt-tRNA: a multifactorial probability-based method for classification of mitochondrial tRNA variations. Nucleic Acids Res 2016; 44:2020-7. [PMID: 26843426 PMCID: PMC4797295 DOI: 10.1093/nar/gkw046] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2015] [Accepted: 01/14/2016] [Indexed: 12/19/2022] Open
Abstract
Transfer RNAs (tRNAs) are essential for encoding the transcribed genetic information from DNA into proteins. Variations in the human tRNAs are involved in diverse clinical phenotypes. Interestingly, all pathogenic variations in tRNAs are located in mitochondrial tRNAs (mt-tRNAs). Therefore, it is crucial to identify pathogenic variations in mt-tRNAs for disease diagnosis and proper treatment. We collected mt-tRNA variations using a classification based on evidence from several sources and used the data to develop a multifactorial probability-based prediction method, PON-mt-tRNA, for classification of mt-tRNA single nucleotide substitutions. We integrated a machine learning-based predictor and an evidence-based likelihood ratio for pathogenicity using evidence of segregation, biochemistry and histochemistry to predict the posterior probability of pathogenicity of variants. The accuracy and Matthews correlation coefficient (MCC) of PON-mt-tRNA are 1.00 and 0.99, respectively. In the absence of evidence from segregation, biochemistry and histochemistry, PON-mt-tRNA classifies variations based on the machine learning method with an accuracy and MCC of 0.69 and 0.39, respectively. We classified all possible single nucleotide substitutions in all human mt-tRNAs using PON-mt-tRNA. The variations in the loops are more often tolerated compared to the variations in stems. The anticodon loop contains comparatively more predicted pathogenic variations than the other loops. PON-mt-tRNA is available at http://structure.bmc.lu.se/PON-mt-tRNA/.
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Affiliation(s)
- Abhishek Niroula
- Department of Experimental Medical Science, Lund University, BMC B13, SE-22184 Lund, Sweden
| | - Mauno Vihinen
- Department of Experimental Medical Science, Lund University, BMC B13, SE-22184 Lund, Sweden
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Santorsola M, Calabrese C, Girolimetti G, Diroma MA, Gasparre G, Attimonelli M. A multi-parametric workflow for the prioritization of mitochondrial DNA variants of clinical interest. Hum Genet 2015; 135:121-36. [PMID: 26621530 PMCID: PMC4698288 DOI: 10.1007/s00439-015-1615-9] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2015] [Accepted: 11/12/2015] [Indexed: 02/07/2023]
Abstract
Assigning a pathogenic role to mitochondrial DNA (mtDNA) variants and unveiling the potential involvement of the mitochondrial genome in diseases are challenging tasks in human medicine. Assuming that rare variants are more likely to be damaging, we designed a phylogeny-based prioritization workflow to obtain a reliable pool of candidate variants for further investigations. The prioritization workflow relies on an exhaustive functional annotation through the mtDNA extraction pipeline MToolBox and includes Macro Haplogroup Consensus Sequences to filter out fixed evolutionary variants and report rare or private variants, the nucleotide variability as reported in HmtDB and the disease score based on several predictors of pathogenicity for non-synonymous variants. Cutoffs for both the disease score as well as for the nucleotide variability index were established with the aim to discriminate sequence variants contributing to defective phenotypes. The workflow was validated on mitochondrial sequences from Leber’s Hereditary Optic Neuropathy affected individuals, successfully identifying 23 variants including the majority of the known causative ones. The application of the prioritization workflow to cancer datasets allowed to trim down the number of candidate for subsequent functional analyses, unveiling among these a high percentage of somatic variants. Prioritization criteria were implemented in both standalone (http://sourceforge.net/projects/mtoolbox/) and web version (https://mseqdr.org/mtoolbox.php) of MToolBox.
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Affiliation(s)
- Mariangela Santorsola
- Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Via E.Orabona 4, 70126, Bari, Italy.,Department of Science and Technologies, University of Sannio, Via Port'Arsa 11, 82100, Benevento, Italy
| | - Claudia Calabrese
- Department of Medical and Surgical Sciences, Medical Genetics, University of Bologna Medical School, via Massarenti 9, 40138, Bologna, Italy
| | - Giulia Girolimetti
- Department of Medical and Surgical Sciences, Medical Genetics, University of Bologna Medical School, via Massarenti 9, 40138, Bologna, Italy
| | - Maria Angela Diroma
- Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Via E.Orabona 4, 70126, Bari, Italy
| | - Giuseppe Gasparre
- Department of Medical and Surgical Sciences, Medical Genetics, University of Bologna Medical School, via Massarenti 9, 40138, Bologna, Italy
| | - Marcella Attimonelli
- Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Via E.Orabona 4, 70126, Bari, Italy.
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6
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Kabekkodu SP, Chakrabarty S, Shukla V, Varghese VK, Singh KK, Thangaraj K, Satyamoorthy K. Mitochondrial biology: From molecules to diseases. Mitochondrion 2015. [PMID: 26210788 DOI: 10.1016/j.mito.2015.07.008] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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7
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Singh I, Faruq M, Padma MV, Goyal V, Behari M, Grover A, Mukerji M, Srivastava AK. Investigation of mitochondrial DNA variations among Indian Friedreich's ataxia (FRDA) patients. Mitochondrion 2015; 25:1-5. [PMID: 26321457 DOI: 10.1016/j.mito.2015.08.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2015] [Revised: 08/12/2015] [Accepted: 08/21/2015] [Indexed: 12/30/2022]
Abstract
OBJECTIVE The loss of function mutations (biallelic) in frataxin (FXN) has primarily been implicated in Friedreich's ataxia (FRDA), an autosomal recessive cerebellar ataxia. The protein product of FXN is a nuclear-encoded mitochondrial protein required for the biogenesis of iron- clusters (Fe-S). FRDA is characterized by neurological and non-neurological features which show variable expression in affected individuals. An inverse relationship has been demonstrated between GAA repeat size and age at onset and explains 50% variability of the age at onset. MtDNA variations and haplogroups could be one of the contributory factors to explain the remaining heterogeneity in FRDA, since mitochondrial oxidative stress is thought to be involved in the pathogenesis of FRDA. METHODS In our study, targeted resequencing of the D-loop and coding region of mitochondrial genes (ND1-6 and ATP) was conducted in 30 genetically confirmed FRDA patients and 62 ethnicity-matched unrelated healthy controls to identify the functionally important mtDNA variations and to trace the mitochondrial lineage of Indian FRDA patients. Cumulative mitochondrial SNP scores were computed for the identified variations in the functional region and haplogroups were determined by Haplogrep. RESULTS A significantly higher load of overall mitochondrial variations (with a trend toward the coding region) per individual was noted among FRDA cases rather than controls (p-value<0.03). A non-synonymous variation (p. L237M) in ND2 was over-represented among FRDA cases (p-value 0.04). This variation has a reported association with longevity and myocardial infarction. We also observed over-representation of H haplogroup (Caucasian mitochondrial haplogroup) among FRDA patients. We have not observed the influence of mitochondrial variations and haplogroup upon age at onset of FRDA. CONCLUSIONS Overall, our study identifies the functionally important variations and mitochondrial lineage of Indian FRDA cases and, that underscores the importance of studying the role of mitochondrial genome variations in FRDA.
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Affiliation(s)
- Inder Singh
- Department of Neurology, Neuroscience Centre, All India Institute of Medical Sciences, Ansari Nagar, New Delhi 110029, India
| | - Mohammed Faruq
- Genomics and Molecular Medicine, CSIR-Institute of Genomics and Integrative Biology, Mall Road, New Delhi 110007, India.
| | - Madakasira Vasantha Padma
- Department of Neurology, Neuroscience Centre, All India Institute of Medical Sciences, Ansari Nagar, New Delhi 110029, India
| | - Vinay Goyal
- Department of Neurology, Neuroscience Centre, All India Institute of Medical Sciences, Ansari Nagar, New Delhi 110029, India
| | - Madhuri Behari
- Department of Neurology, Neuroscience Centre, All India Institute of Medical Sciences, Ansari Nagar, New Delhi 110029, India
| | - Ashoo Grover
- Indian Council of Medical Research, Ansari Nagar, New Delhi 110029, India
| | - Mitali Mukerji
- Genomics and Molecular Medicine, CSIR-Institute of Genomics and Integrative Biology, Mall Road, New Delhi 110007, India
| | - Achal K Srivastava
- Department of Neurology, Neuroscience Centre, All India Institute of Medical Sciences, Ansari Nagar, New Delhi 110029, India.
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Rajput NK, Singh V, Bhardwaj A. Resources, challenges and way forward in rare mitochondrial diseases research. F1000Res 2015; 4:70. [PMID: 26180633 PMCID: PMC4490798 DOI: 10.12688/f1000research.6208.2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/10/2015] [Indexed: 12/19/2022] Open
Abstract
Over 300 million people are affected by about 7000 rare diseases globally. There are tremendous resource limitations and challenges in driving research and drug development for rare diseases. Hence, innovative approaches are needed to identify potential solutions. This review focuses on the resources developed over the past years for analysis of genome data towards understanding disease biology especially in the context of mitochondrial diseases, given that mitochondria are central to major cellular pathways and their dysfunction leads to a broad spectrum of diseases. Platforms for collaboration of research groups, clinicians and patients and the advantages of community collaborative efforts in addressing rare diseases are also discussed. The review also describes crowdsourcing and crowdfunding efforts in rare diseases research and how the upcoming initiatives for understanding disease biology including analyses of large number of genomes are also applicable to rare diseases.
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Affiliation(s)
- Neeraj Kumar Rajput
- Open Source Drug Discovery (OSDD) Unit, Council of Scientific and Industrial Research, New Delhi, 110001, India
| | - Vipin Singh
- Amity Institute of Biotechnology, Amity University, Noida, Uttar Pradesh, 201301, India
| | - Anshu Bhardwaj
- Open Source Drug Discovery (OSDD) Unit, Council of Scientific and Industrial Research, New Delhi, 110001, India
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Rajput NK, Singh V, Bhardwaj A. Resources, challenges and way forward in rare mitochondrial diseases research. F1000Res 2015; 4:70. [PMID: 26180633 DOI: 10.12688/f1000research.6208.1] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/13/2015] [Indexed: 12/27/2022] Open
Abstract
Over 300 million people are affected by about 7000 rare diseases globally. There are tremendous resource limitations and challenges in driving research and drug development for rare diseases. Hence, innovative approaches are needed to identify potential solutions. This review focuses on the resources developed over the past years for analysis of genome data towards understanding disease biology especially in the context of mitochondrial diseases, given that mitochondria are central to major cellular pathways and their dysfunction leads to a broad spectrum of diseases. Platforms for collaboration of research groups, clinicians and patients and the advantages of community collaborative efforts in addressing rare diseases are also discussed. The review also describes crowdsourcing and crowdfunding efforts in rare diseases research and how the upcoming initiatives for understanding disease biology including analyses of large number of genomes are also applicable to rare diseases.
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Affiliation(s)
- Neeraj Kumar Rajput
- Open Source Drug Discovery (OSDD) Unit, Council of Scientific and Industrial Research, New Delhi, 110001, India
| | - Vipin Singh
- Amity Institute of Biotechnology, Amity University, Noida, Uttar Pradesh, 201301, India
| | - Anshu Bhardwaj
- Open Source Drug Discovery (OSDD) Unit, Council of Scientific and Industrial Research, New Delhi, 110001, India
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10
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Desler C, Rasmussen LJ. Mitochondria in biology and medicine — 2012. Mitochondrion 2014; 16:2-6. [DOI: 10.1016/j.mito.2013.05.010] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2013] [Accepted: 05/21/2013] [Indexed: 12/11/2022]
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Mikami E, Fuku N, Kong QP, Takahashi H, Ohiwa N, Murakami H, Miyachi M, Higuchi M, Tanaka M, Pitsiladis YP, Kawahara T. Comprehensive analysis of common and rare mitochondrial DNA variants in elite Japanese athletes: a case–control study. J Hum Genet 2013; 58:780-7. [DOI: 10.1038/jhg.2013.102] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2013] [Revised: 09/02/2013] [Accepted: 09/05/2013] [Indexed: 12/26/2022]
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Wang WF, Li X, Guo MZ, Chen JD, Yang YS, Peng LH, Wang YH, Zhang CY, Li HH. Mitochondrial ATP 6 and 8 polymorphisms in irritable bowel syndrome with diarrhea. World J Gastroenterol 2013; 19:3847-3853. [PMID: 23840124 PMCID: PMC3699044 DOI: 10.3748/wjg.v19.i24.3847] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2013] [Revised: 03/30/2013] [Accepted: 04/10/2013] [Indexed: 02/06/2023] Open
Abstract
AIM: To investigate mitochondrial ATP 6 and 8 polymorphisms in the colon and ileum of patients with irritable bowel syndrome with diarrhea (IBS-D).
METHODS: Twenty-eight patients fulfilling the Rome III criteria for IBS-D and 28 healthy subjects were investigated. All study participants underwent screening colonoscopy and mucosal biopsies were obtained from the colon and/or terminal ileum. Genomic DNA was extracted from specimens based on standard protocols. Mitochondrial ATP (MT-ATP) 6 and 8 genes in specimens were polymerase chain reaction amplified and sequenced. Sequencing data were analyzed via Variant Reporter™ Software and compared with the reference sequence from Genbank (accession No. NC_012920) to indicate possible polymorphisms. The protocol was registered at www.clinicaltrials.gov as NCT01028898.
RESULTS: Twenty-five polymorphic sites of MT-ATP 6 and 8 genes were detected and 12 of them were missense mutations. A median of two polymorphic sites in MT-ATP genes was found in colon specimens of controls while a median of three polymorphic sites was noted in patients with IBS-D (Mann-Whitney test, P = 0.012). The variants of the colon and ileum specimens from the same subjects were identical in all but one case. Symptom duration in IBS was not found to be a significant factor associated with the mtDNA polymorphism (Spearman correlation, P = 0.592). The mitochondrial DNA change at 8860 was present in all cases of both groups. The frequency of the 8701 polymorphism was found to be the second most frequent; however, no statistical difference was noted between the groups (χ2 test, P = 0.584).
CONCLUSION: Patients with IBS-D have a higher incidence of MT-ATP 6 and 8 polymorphisms than healthy subjects, implying that the mtDNA polymorphism may play a role in IBS-D.
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MitoLSDB: a comprehensive resource to study genotype to phenotype correlations in human mitochondrial DNA variations. PLoS One 2013; 8:e60066. [PMID: 23585830 PMCID: PMC3621970 DOI: 10.1371/journal.pone.0060066] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2012] [Accepted: 02/20/2013] [Indexed: 01/16/2023] Open
Abstract
Human mitochondrial DNA (mtDNA) encodes a set of 37 genes which are essential structural and functional components of the electron transport chain. Variations in these genes have been implicated in a broad spectrum of diseases and are extensively reported in literature and various databases. In this study, we describe MitoLSDB, an integrated platform to catalogue disease association studies on mtDNA (http://mitolsdb.igib.res.in). The main goal of MitoLSDB is to provide a central platform for direct submissions of novel variants that can be curated by the Mitochondrial Research Community. MitoLSDB provides access to standardized and annotated data from literature and databases encompassing information from 5231 individuals, 675 populations and 27 phenotypes. This platform is developed using the Leiden Open (source) Variation Database (LOVD) software. MitoLSDB houses information on all 37 genes in each population amounting to 132397 variants, 5147 unique variants. For each variant its genomic location as per the Revised Cambridge Reference Sequence, codon and amino acid change for variations in protein-coding regions, frequency, disease/phenotype, population, reference and remarks are also listed. MitoLSDB curators have also reported errors documented in literature which includes 94 phantom mutations, 10 NUMTs, six documentation errors and one artefactual recombination. MitoLSDB is the largest repository of mtDNA variants systematically standardized and presented using the LOVD platform. We believe that this is a good starting resource to curate mtDNA variants and will facilitate direct submissions enhancing data coverage, annotation in context of pathogenesis and quality control by ensuring non-redundancy in reporting novel disease associated variants.
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Dudley JT, Kim Y, Liu L, Markov GJ, Gerold K, Chen R, Butte AJ, Kumar S. Human genomic disease variants: a neutral evolutionary explanation. Genome Res 2012; 22:1383-94. [PMID: 22665443 PMCID: PMC3409252 DOI: 10.1101/gr.133702.111] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Many perspectives on the role of evolution in human health include nonempirical assumptions concerning the adaptive evolutionary origins of human diseases. Evolutionary analyses of the increasing wealth of clinical and population genomic data have begun to challenge these presumptions. In order to systematically evaluate such claims, the time has come to build a common framework for an empirical and intellectual unification of evolution and modern medicine. We review the emerging evidence and provide a supporting conceptual framework that establishes the classical neutral theory of molecular evolution (NTME) as the basis for evaluating disease- associated genomic variations in health and medicine. For over a decade, the NTME has already explained the origins and distribution of variants implicated in diseases and has illuminated the power of evolutionary thinking in genomic medicine. We suggest that a majority of disease variants in modern populations will have neutral evolutionary origins (previously neutral), with a relatively smaller fraction exhibiting adaptive evolutionary origins (previously adaptive). This pattern is expected to hold true for common as well as rare disease variants. Ultimately, a neutral evolutionary perspective will provide medicine with an informative and actionable framework that enables objective clinical assessment beyond convenient tendencies to invoke past adaptive events in human history as a root cause of human disease.
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Affiliation(s)
- Joel T Dudley
- Program in Biomedical Informatics, Stanford University School of Medicine, Stanford, California 94305, USA
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Voets AM, van den Bosch BJC, Stassen AP, Hendrickx AT, Hellebrekers DM, Van Laer L, Van Eyken E, Van Camp G, Pyle A, Baudouin SV, Chinnery PF, Smeets HJM. Large scale mtDNA sequencing reveals sequence and functional conservation as major determinants of homoplasmic mtDNA variant distribution. Mitochondrion 2011; 11:964-72. [PMID: 21946566 DOI: 10.1016/j.mito.2011.09.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2010] [Revised: 04/19/2011] [Accepted: 09/09/2011] [Indexed: 02/07/2023]
Abstract
The mitochondrial DNA (mtDNA) is highly variable, containing large numbers of pathogenic mutations and neutral polymorphisms. The spectrum of homoplasmic mtDNA variation was characterized in 730 subjects and compared with known pathogenic sites. The frequency and distribution of variants in protein coding genes were inversely correlated with conservation at the amino acid level. Analysis of tRNA secondary structures indicated a preference of variants for the loops and some acceptor stem positions. This comprehensive overview of mtDNA variants distinguishes between regions and positions which are likely not critical, mainly conserved regions with pathogenic mutations and essential regions containing no mutations at all.
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Affiliation(s)
- A M Voets
- Department of Genetics and Cell Biology, Maastricht University, Maastricht, The Netherlands
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Kumar S, Dudley JT, Filipski A, Liu L. Phylomedicine: an evolutionary telescope to explore and diagnose the universe of disease mutations. Trends Genet 2011; 27:377-86. [PMID: 21764165 PMCID: PMC3272884 DOI: 10.1016/j.tig.2011.06.004] [Citation(s) in RCA: 66] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2011] [Revised: 06/10/2011] [Accepted: 06/13/2011] [Indexed: 12/30/2022]
Abstract
Modern technologies have made the sequencing of personal genomes routine. They have revealed thousands of nonsynonymous (amino acid altering) single nucleotide variants (nSNVs) of protein-coding DNA per genome. What do these variants foretell about an individual's predisposition to diseases? The experimental technologies required to carry out such evaluations at a genomic scale are not yet available. Fortunately, the process of natural selection has lent us an almost infinite set of tests in nature. During long-term evolution, new mutations and existing variations have been evaluated for their biological consequences in countless species, and outcomes are readily revealed by multispecies genome comparisons. We review studies that have investigated evolutionary characteristics and in silico functional diagnoses of nSNVs found in thousands of disease-associated genes. We conclude that the patterns of long-term evolutionary conservation and permissible sequence divergence are essential and instructive modalities for functional assessment of human genetic variations.
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Affiliation(s)
- Sudhir Kumar
- School of Life Sciences, Arizona State University, Tempe, AZ 85287-4501, USA.
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17
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Fan L, Yao YG. MitoTool: a web server for the analysis and retrieval of human mitochondrial DNA sequence variations. Mitochondrion 2010; 11:351-6. [PMID: 20933105 DOI: 10.1016/j.mito.2010.09.013] [Citation(s) in RCA: 104] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2010] [Accepted: 09/28/2010] [Indexed: 10/19/2022]
Abstract
MitoTool, a web-based bioinformatics platform, is designed for deciphering human mitochondrial DNA (mtDNA) data in batch mode. The platform has advantages in (i) parsing diverse types of mtDNA data; (ii) automatically classifying haplogroup according to mtDNA sequences or variants; (iii) discovering possibly missing variants of the samples with claimed haplogroups status; (iv) estimating the evolutionary conservation index, protein coding effect and potential pathogenicity of certain substitutions; (v) performing statistical analysis for haplogroup distribution frequency between case and control groups. Furthermore, it offers an integrated database for retrieving five types of mitochondrion-related information. The MitoTool is freely accessed at http://www.mitotool.org.
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Affiliation(s)
- Long Fan
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Kunming, Yunnan, China.
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Baker CJO, Rebholz-Schuhmann D. Between proteins and phenotypes: annotation and interpretation of mutations. BMC Bioinformatics 2009; 10 Suppl 8:I1. [PMID: 19758463 PMCID: PMC2745581 DOI: 10.1186/1471-2105-10-s8-i1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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