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Abondio P, Bruno F, Passarino G, Montesanto A, Luiselli D. Pangenomics: A new era in the field of neurodegenerative diseases. Ageing Res Rev 2024; 94:102180. [PMID: 38163518 DOI: 10.1016/j.arr.2023.102180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 12/14/2023] [Accepted: 12/28/2023] [Indexed: 01/03/2024]
Abstract
A pangenome is composed of all the genetic variability of a group of individuals, and its application to the study of neurodegenerative diseases may provide valuable insights into the underlying aspects of genetic heterogenetiy for these complex ailments, including gene expression, epigenetics, and translation mechanisms. Furthermore, a reference pangenome allows for the identification of previously undetected structural commonalities and differences among individuals, which may help in the diagnosis of a disease, support the prediction of what will happen over time (prognosis) and aid in developing novel treatments in the perspective of personalized medicine. Therefore, in the present review, the application of the pangenome concept to the study of neurodegenerative diseases will be discussed and analyzed for its potential to enable an improvement in diagnosis and prognosis for these illnesses, leading to the development of tailored treatments for individual patients from the knowledge of the genomic composition of a whole population.
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Affiliation(s)
- Paolo Abondio
- Laboratory of Ancient DNA, Department of Cultural Heritage, University of Bologna, Via degli Ariani 1, 48121 Ravenna, Italy.
| | - Francesco Bruno
- Academy of Cognitive Behavioral Sciences of Calabria (ASCoC), Lamezia Terme, Italy; Regional Neurogenetic Centre (CRN), Department of Primary Care, Azienda Sanitaria Provinciale Di Catanzaro, Viale A. Perugini, 88046 Lamezia Terme, CZ, Italy; Association for Neurogenetic Research (ARN), Lamezia Terme, CZ, Italy
| | - Giuseppe Passarino
- Department of Biology, Ecology and Earth Sciences, University of Calabria, Rende 87036, Italy
| | - Alberto Montesanto
- Department of Biology, Ecology and Earth Sciences, University of Calabria, Rende 87036, Italy
| | - Donata Luiselli
- Laboratory of Ancient DNA, Department of Cultural Heritage, University of Bologna, Via degli Ariani 1, 48121 Ravenna, Italy
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Balachandran S, Prada-Medina CA, Mensah MA, Kakar N, Nagel I, Pozojevic J, Audain E, Hitz MP, Kircher M, Sreenivasan VKA, Spielmann M. STIGMA: Single-cell tissue-specific gene prioritization using machine learning. Am J Hum Genet 2024; 111:338-349. [PMID: 38228144 PMCID: PMC10870135 DOI: 10.1016/j.ajhg.2023.12.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 12/01/2023] [Accepted: 12/07/2023] [Indexed: 01/18/2024] Open
Abstract
Clinical exome and genome sequencing have revolutionized the understanding of human disease genetics. Yet many genes remain functionally uncharacterized, complicating the establishment of causal disease links for genetic variants. While several scoring methods have been devised to prioritize these candidate genes, these methods fall short of capturing the expression heterogeneity across cell subpopulations within tissues. Here, we introduce single-cell tissue-specific gene prioritization using machine learning (STIGMA), an approach that leverages single-cell RNA-seq (scRNA-seq) data to prioritize candidate genes associated with rare congenital diseases. STIGMA prioritizes genes by learning the temporal dynamics of gene expression across cell types during healthy organogenesis. To assess the efficacy of our framework, we applied STIGMA to mouse limb and human fetal heart scRNA-seq datasets. In a cohort of individuals with congenital limb malformation, STIGMA prioritized 469 variants in 345 genes, with UBA2 as a notable example. For congenital heart defects, we detected 34 genes harboring nonsynonymous de novo variants (nsDNVs) in two or more individuals from a set of 7,958 individuals, including the ortholog of Prdm1, which is associated with hypoplastic left ventricle and hypoplastic aortic arch. Overall, our findings demonstrate that STIGMA effectively prioritizes tissue-specific candidate genes by utilizing single-cell transcriptome data. The ability to capture the heterogeneity of gene expression across cell populations makes STIGMA a powerful tool for the discovery of disease-associated genes and facilitates the identification of causal variants underlying human genetic disorders.
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Affiliation(s)
- Saranya Balachandran
- Institute of Human Genetics, University Hospital Schleswig-Holstein, University of Lübeck and Kiel University, Lübeck, Germany
| | - Cesar A Prada-Medina
- Human Molecular Genetics Group, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany
| | - Martin A Mensah
- Institut für Medizinische Genetik und Humangenetik, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Augustenburger Platz 1, 13353 Berlin, Germany; BIH Charité Digital Clinician Scientist Program, BIH Biomedical Innovation Academy, Anna-Louisa-Karsch-Strasse 2, 10178 Berlin, Germany; RG Development & Disease, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany
| | - Naseebullah Kakar
- Institute of Human Genetics, University Hospital Schleswig-Holstein, University of Lübeck and Kiel University, Lübeck, Germany; Department of Biotechnology, BUITEMS, Quetta, Pakistan
| | - Inga Nagel
- Institute of Human Genetics, University Hospital Schleswig-Holstein, University of Lübeck and Kiel University, Lübeck, Germany
| | - Jelena Pozojevic
- Institute of Human Genetics, University Hospital Schleswig-Holstein, University of Lübeck and Kiel University, Lübeck, Germany
| | - Enrique Audain
- Institute of Medical Genetics, Carl von Ossietzky University, 26129 Oldenburg, Germany; DZHK e.V. (German Center for Cardiovascular Research), Partner Site Hamburg/Kiel/Lübeck; Department of Congenital Heart Disease and Pediatric Cardiology, University Hospital of Schleswig-Holstein, 24105 Kiel, Germany
| | - Marc-Phillip Hitz
- Institute of Medical Genetics, Carl von Ossietzky University, 26129 Oldenburg, Germany; DZHK e.V. (German Center for Cardiovascular Research), Partner Site Hamburg/Kiel/Lübeck; Department of Congenital Heart Disease and Pediatric Cardiology, University Hospital of Schleswig-Holstein, 24105 Kiel, Germany
| | - Martin Kircher
- Institute of Human Genetics, University Hospital Schleswig-Holstein, University of Lübeck and Kiel University, Lübeck, Germany
| | - Varun K A Sreenivasan
- Institute of Human Genetics, University Hospital Schleswig-Holstein, University of Lübeck and Kiel University, Lübeck, Germany.
| | - Malte Spielmann
- Institute of Human Genetics, University Hospital Schleswig-Holstein, University of Lübeck and Kiel University, Lübeck, Germany; Human Molecular Genetics Group, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany; DZHK e.V. (German Center for Cardiovascular Research), Partner Site Hamburg/Kiel/Lübeck.
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Miao H, Kuruoğlu EE, Xu T. Non-homogeneous Poisson and renewal processes as spatial models for cancer mutation. Comput Biol Chem 2023; 106:107922. [PMID: 37499435 DOI: 10.1016/j.compbiolchem.2023.107922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 07/08/2023] [Accepted: 07/11/2023] [Indexed: 07/29/2023]
Abstract
Advances in sequencing technology assisted biologists in revealing signatures of DNA cancer mutation process and in demonstrating the mutagenesis behind. However, most of these signatures proposed by majority of work focus only on the type and frequency of mutations, without considering spatial information which is non-negligible in exploring mechanisms of mutation occurrence, e.g., Kataegis. Statistical characterization of the distance between consecutive mutations can give us relative spatial information; however, it ignores location information which is as important as distance information. In this work, we assume that DNA cancer mutations are location-dependent and that integrating the two variables, location and inter-distance, is beneficial to study DNA cancer mutation processes more accurately. Particularly, instead of following a specific distribution over the whole DNA sequence, we found out that the distribution of distance between successive mutations alternates between exponential and power-law distributions. Apart from this, the parameters of either of the two distributions vary with DNA locations. The cancers with kataegis phenomenon, a specific mutation pattern caused by abnormal activity of APOBEC protein family, are more likely to be accompanied by higher parameter values of distance distribution, implying higher occurrence rate of mutation. Therefore, we propose non-homogeneous Poisson and Renewal processes to spatially model DNA cancer mutations and to describe mutation patterns quantitatively and more accurately through a statistical perspective.
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Affiliation(s)
- Hengyuan Miao
- Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen, China; Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China.
| | - Ercan Engin Kuruoğlu
- Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen, China; Institute of Data and Information, Tsinghua University, Shenzhen, China; Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China.
| | - Tao Xu
- Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen, China; Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China; Bio-intelligent Manufacturing and Living Matter Bioprinting Center, Research Institute of Tsinghua University in Shenzhen, Tsinghua University, Shenzhen, China; Department of Neurosurgery, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
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Pozojevic J, Spielmann M. Single-Cell Sequencing in Neurodegenerative Disorders. Mol Diagn Ther 2023; 27:553-561. [PMID: 37552451 PMCID: PMC10435411 DOI: 10.1007/s40291-023-00668-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/17/2023] [Indexed: 08/09/2023]
Abstract
Neurodegenerative disorders are typically characterized by late onset progressive damage to specific (sub)populations of cells of the nervous system that are essential for mobility, coordination, strength, sensation, and cognition. Addressing this selective cellular vulnerability has become feasible with the emergence of single-cell-omics technologies, which now represent the state-of-the-art approach to profile heterogeneity of complex tissues including human post-mortem brain at unprecedented resolution. In this review, we briefly recapitulate the experimental workflow of single-cell RNA sequencing and summarize the recent knowledge acquired with it in the most common neurodegenerative diseases: Parkinson's, Alzheimer's, Huntington's disease, and multiple sclerosis. We also discuss the possibility of applying single-cell approaches in the diagnostics and therapy of neurodegenerative disorders, as well as the limitations. While we are currently at the point of deeply exploring the transcriptomic changes in the affected cells, further technological developments hold a promise of manipulating the affected pathways once we understand them better.
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Affiliation(s)
- Jelena Pozojevic
- Institute of Human Genetics, Universitätsklinikum Schleswig-Holstein, University of Lübeck and University of Kiel, 23562, Lübeck, Germany
| | - Malte Spielmann
- Institute of Human Genetics, Universitätsklinikum Schleswig-Holstein, University of Lübeck and University of Kiel, 23562, Lübeck, Germany.
- Human Molecular Genomics Group, Max Planck Institute for Molecular Genetics, 14195, Berlin, Germany.
- German Centre for Cardiovascular Research (DZHK), Partner Site Hamburg/Lübeck/Kiel, 23562, Lübeck, Germany.
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Abondio P, Cilli E, Luiselli D. Human Pangenomics: Promises and Challenges of a Distributed Genomic Reference. Life (Basel) 2023; 13:1360. [PMID: 37374141 DOI: 10.3390/life13061360] [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: 05/15/2023] [Revised: 06/02/2023] [Accepted: 06/08/2023] [Indexed: 06/29/2023] Open
Abstract
A pangenome is a collection of the common and unique genomes that are present in a given species. It combines the genetic information of all the genomes sampled, resulting in a large and diverse range of genetic material. Pangenomic analysis offers several advantages compared to traditional genomic research. For example, a pangenome is not bound by the physical constraints of a single genome, so it can capture more genetic variability. Thanks to the introduction of the concept of pangenome, it is possible to use exceedingly detailed sequence data to study the evolutionary history of two different species, or how populations within a species differ genetically. In the wake of the Human Pangenome Project, this review aims at discussing the advantages of the pangenome around human genetic variation, which are then framed around how pangenomic data can inform population genetics, phylogenetics, and public health policy by providing insights into the genetic basis of diseases or determining personalized treatments, targeting the specific genetic profile of an individual. Moreover, technical limitations, ethical concerns, and legal considerations are discussed.
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Affiliation(s)
- Paolo Abondio
- Laboratory of Ancient DNA, Department of Cultural Heritage, University of Bologna, Via degli Ariani 1, 48121 Ravenna, Italy
| | - Elisabetta Cilli
- Laboratory of Ancient DNA, Department of Cultural Heritage, University of Bologna, Via degli Ariani 1, 48121 Ravenna, Italy
| | - Donata Luiselli
- Laboratory of Ancient DNA, Department of Cultural Heritage, University of Bologna, Via degli Ariani 1, 48121 Ravenna, Italy
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Sreenivasan VKA, Dore R, Resch J, Maier J, Dietrich C, Henck J, Balachandran S, Mittag J, Spielmann M. Single-cell RNA-based phenotyping reveals a pivotal role of thyroid hormone receptor alpha for hypothalamic development. Development 2023; 150:286776. [PMID: 36715020 PMCID: PMC10110490 DOI: 10.1242/dev.201228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 12/23/2022] [Indexed: 01/31/2023]
Abstract
Thyroid hormone and its receptor TRα1 play an important role in brain development. Several animal models have been used to investigate this function, including mice heterozygous for the TRα1R384C mutation, which confers receptor-mediated hypothyroidism. These mice display abnormalities in several autonomic functions, which was partially attributed to a developmental defect in hypothalamic parvalbumin neurons. However, whether other cell types in the hypothalamus are similarly affected remains unknown. Here, we used single-nucleus RNA sequencing to obtain an unbiased view on the importance of TRα1 for hypothalamic development and cellular diversity. Our data show that defective TRα1 signaling has surprisingly little effect on the development of hypothalamic neuronal populations, but it heavily affects hypothalamic oligodendrocytes. Using selective reactivation of the mutant TRα1 during specific developmental periods, we find that early postnatal thyroid hormone action seems to be crucial for proper hypothalamic oligodendrocyte maturation. Taken together, our findings underline the well-known importance of postnatal thyroid health for brain development and provide an unbiased roadmap for the identification of cellular targets of TRα1 action in mouse hypothalamic development.
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Affiliation(s)
- Varun K A Sreenivasan
- Institute of Human Genetics, Universitätsklinikum Schleswig-Holstein, University of Lübeck and University of Kiel, Lübeck 23562, Germany
| | - Riccardo Dore
- Institute for Endocrinology and Diabetes, University of Lübeck and Universitätsklinikum Schleswig-Holstein Campus Lübeck, Center of Brain Behavior and Metabolism (CBBM), Ratzeburger Allee 160, 23562 Lübeck, Germany
| | - Julia Resch
- Institute for Endocrinology and Diabetes, University of Lübeck and Universitätsklinikum Schleswig-Holstein Campus Lübeck, Center of Brain Behavior and Metabolism (CBBM), Ratzeburger Allee 160, 23562 Lübeck, Germany
| | - Julia Maier
- Institute for Endocrinology and Diabetes, University of Lübeck and Universitätsklinikum Schleswig-Holstein Campus Lübeck, Center of Brain Behavior and Metabolism (CBBM), Ratzeburger Allee 160, 23562 Lübeck, Germany
| | - Carola Dietrich
- Human Molecular Genomics Group, Max Planck Institute for Molecular Genetics, Berlin 14195, Germany
| | - Jana Henck
- Institute of Human Genetics, Universitätsklinikum Schleswig-Holstein, University of Lübeck and University of Kiel, Lübeck 23562, Germany
- Human Molecular Genomics Group, Max Planck Institute for Molecular Genetics, Berlin 14195, Germany
| | - Saranya Balachandran
- Institute of Human Genetics, Universitätsklinikum Schleswig-Holstein, University of Lübeck and University of Kiel, Lübeck 23562, Germany
- German Centre for Cardiovascular Research (DZHK), partner site Hamburg/Lübeck/Kiel, Lübeck 23562, Germany
| | - Jens Mittag
- Institute for Endocrinology and Diabetes, University of Lübeck and Universitätsklinikum Schleswig-Holstein Campus Lübeck, Center of Brain Behavior and Metabolism (CBBM), Ratzeburger Allee 160, 23562 Lübeck, Germany
| | - Malte Spielmann
- Institute of Human Genetics, Universitätsklinikum Schleswig-Holstein, University of Lübeck and University of Kiel, Lübeck 23562, Germany
- Human Molecular Genomics Group, Max Planck Institute for Molecular Genetics, Berlin 14195, Germany
- German Centre for Cardiovascular Research (DZHK), partner site Hamburg/Lübeck/Kiel, Lübeck 23562, Germany
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Embracing lipidomics at single-cell resolution: Promises and pitfalls. Trends Analyt Chem 2023. [DOI: 10.1016/j.trac.2023.116973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
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Sreenivasan VK, Henck J, Spielmann M. Single-cell sequencing: promises and challenges for human genetics. MED GENET-BERLIN 2022. [DOI: 10.1515/medgen-2022-2156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Abstract
Over the last decade, single-cell sequencing has transformed many fields. It has enabled the unbiased molecular phenotyping of even whole organisms with unprecedented cellular resolution. In the field of human genetics, where the phenotypic consequences of genetic and epigenetic alterations are of central concern, this transformative technology promises to functionally annotate every region in the human genome and all possible variants within them at a massive scale. In this review aimed at the clinicians in human genetics, we describe the current status of the field of single-cell sequencing and its role for human genetics, including how the technology works as well as how it is being applied to characterize and monitor diseases, to develop human cell atlases, and to annotate the genome.
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Affiliation(s)
- Varun K. A. Sreenivasan
- Institute of Human Genetics, University Hospital Schleswig-Holstein , University of Lübeck and Kiel University , 23562 Lübeck, 24105 Kiel , Germany
| | - Jana Henck
- Institute of Human Genetics, University Hospital Schleswig-Holstein , University of Lübeck and Kiel University , 23562 Lübeck, 24105 Kiel , Germany
- Human Molecular Genomics Group , Max Planck Institute for Molecular Genetics , Berlin , Germany
| | - Malte Spielmann
- Institute of Human Genetics, University Hospital Schleswig-Holstein , University of Lübeck and Kiel University , 23562 Lübeck, 24105 Kiel , Germany
- Human Molecular Genomics Group , Max Planck Institute for Molecular Genetics , Berlin , Germany
- DZHK e. V. (German Center for Cardiovascular Research) , Partner Site Hamburg/Kiel/Lübeck , Lübeck , Germany
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Comparative single-cell analysis of the adult heart and coronary vasculature. Mamm Genome 2022:10.1007/s00335-022-09968-7. [DOI: 10.1007/s00335-022-09968-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 11/07/2022] [Indexed: 11/21/2022]
Abstract
AbstractThe structure and function of the circulatory system, including the heart, have undergone substantial changes with the vertebrate evolution. Although the basic function of the heart is to pump blood through the body, its size, shape, speed, regeneration capacity, etc. vary considerably across species. Here, we address the differences among vertebrate hearts using a single-cell transcriptomics approach. Published datasets of macaque (Macaca fascicularis), mouse, and zebrafish hearts were integrated and compared to the human heart as a reference. While the three mammalian hearts integrated well, the zebrafish heart showed very little overlap with the other species. Our analysis revealed a mouse-specific cell subpopulation of ventricular cardiomyocytes (CM), represented by strikingly different expression patterns of specific genes related to high-energy metabolism. Interestingly, the observed differences between mouse and human CM coincided with actual biological differences between the two species. Smooth muscle and endothelial cells (EC) exhibited species-specific differences in clustering and gene expression, respectively, which we attribute to the tissues selected for sequencing, given different focuses of the original studies. Finally, we compared human and zebrafish heart-specific fibroblasts (FB) and identified a distinctively high expression of genes associated with heart regeneration following injury in zebrafish. Together, our results show that integration of numerous datasets of different species and different sequencing technologies is feasible and that this approach can identify species-specific differences and similarities in the heart.
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