1
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Huber PB, Rao A, LaBonne C. BET activity plays an essential role in control of stem cell attributes in Xenopus. Development 2024; 151:dev202990. [PMID: 38884356 PMCID: PMC11266789 DOI: 10.1242/dev.202990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Accepted: 05/31/2024] [Indexed: 06/18/2024]
Abstract
Neural crest cells are a stem cell population unique to vertebrate embryos that retains broad multi-germ layer developmental potential through neurulation. Much remains to be learned about the genetic and epigenetic mechanisms that control the potency of neural crest cells. Here, we examine the role that epigenetic readers of the BET (bromodomain and extra terminal) family play in controlling the potential of pluripotent blastula and neural crest cells. We find that inhibiting BET activity leads to loss of pluripotency at blastula stages and a loss of neural crest at neurula stages. We compare the effects of HDAC (an eraser of acetylation marks) and BET (a reader of acetylation) inhibition and find that they lead to similar cellular outcomes through distinct effects on the transcriptome. Interestingly, loss of BET activity in cells undergoing lineage restriction is coupled to increased expression of genes linked to pluripotency and prolongs the competence of initially pluripotent cells to transit to a neural progenitor state. Together these findings advance our understanding of the epigenetic control of pluripotency and the formation of the vertebrate neural crest.
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Affiliation(s)
- Paul B. Huber
- Department of Molecular Biosciences, Northwestern University, Evanston, IL 60208, USA
- National Institute for Theory and Mathematics in Biology, Northwestern University, Evanston, IL 60208, USA
| | - Anjali Rao
- Department of Molecular Biosciences, Northwestern University, Evanston, IL 60208, USA
| | - Carole LaBonne
- Department of Molecular Biosciences, Northwestern University, Evanston, IL 60208, USA
- National Institute for Theory and Mathematics in Biology, Northwestern University, Evanston, IL 60208, USA
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2
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Yuan M, Goovaerts S, Vanneste M, Matthews H, Hoskens H, Richmond S, Klein OD, Spritz RA, Hallgrimsson B, Walsh S, Shriver MD, Shaffer JR, Weinberg SM, Peeters H, Claes P. Mapping genes for human face shape: exploration of univariate phenotyping strategies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.06.597731. [PMID: 38895298 PMCID: PMC11185724 DOI: 10.1101/2024.06.06.597731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Human facial shape, while strongly heritable, involves both genetic and structural complexity, necessitating precise phenotyping for accurate assessment. Common phenotyping strategies include simplifying 3D facial features into univariate traits such as anthropometric measurements (e.g., inter-landmark distances), unsupervised dimensionality reductions (e.g., principal component analysis (PCA) and auto-encoder (AE) approaches), and assessing resemblance to particular facial gestalts (e.g., syndromic facial archetypes). This study provides a comparative assessment of these strategies in genome-wide association studies (GWASs) of 3D facial shape. Specifically, we investigated inter-landmark distances, PCA and AE-derived latent dimensions, and facial resemblance to random, extreme, and syndromic gestalts within a GWAS of 8,426 individuals of recent European ancestry. Inter-landmark distances exhibit the highest SNP-based heritability as estimated via LD score regression, followed by AE dimensions. Conversely, resemblance scores to extreme and syndromic facial gestalts display the lowest heritability, in line with expectations. Notably, the aggregation of multiple GWASs on facial resemblance to random gestalts reveals the highest number of independent genetic loci. This novel, easy-to-implement phenotyping approach holds significant promise for capturing genetically relevant morphological traits derived from complex biomedical imaging datasets, and its applications extend beyond faces. Nevertheless, these different phenotyping strategies capture different genetic influences on craniofacial shape. Thus, it remains valuable to explore these strategies individually and in combination to gain a more comprehensive understanding of the genetic factors underlying craniofacial shape and related traits. Author Summary Advancements linking variation in the human genome to phenotypes have rapidly evolved in recent decades and have revealed that most human traits are influenced by genetic variants to at least some degree. While many traits, such as stature, are straightforward to acquire and investigate, the multivariate and multipartite nature of facial shape makes quantification more challenging. In this study, we compared the impact of different facial phenotyping approaches on gene mapping outcomes. Our findings suggest that the choice of facial phenotyping method has an impact on apparent trait heritability and the ability to detect genetic association signals. These results offer valuable insights into the importance of phenotyping in genetic investigations, especially when dealing with highly complex morphological traits.
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3
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Wisetchat S, Stevens KA, Frost SR. Facial modeling and measurement based upon homologous topographical features. PLoS One 2024; 19:e0304561. [PMID: 38820264 PMCID: PMC11142440 DOI: 10.1371/journal.pone.0304561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Accepted: 05/13/2024] [Indexed: 06/02/2024] Open
Abstract
Measurement of human faces is fundamental to many applications from recognition to genetic phenotyping. While anthropometric landmarks provide a conventional set of homologous measurement points, digital scans are increasingly used for facial measurement, despite the difficulties in establishing their homology. We introduce an alternative basis for facial measurement, which 1) provides a richer information density than discrete point measurements, 2) derives its homology from shared facial topography (ridges, folds, etc.), and 3) quantifies local morphological variation following the conventions and practices of anatomical description. A parametric model that permits matching a broad range of facial variation by the adjustment of 71 parameters is demonstrated by modeling a sample of 80 adult human faces. The surface of the parametric model can be adjusted to match each photogrammetric surface mesh generally to within 1 mm, demonstrating a novel and efficient means for facial shape encoding. We examine how well this scheme quantifies facial shape and variation with respect to geographic ancestry and sex. We compare this analysis with a more conventional, landmark-based geometric morphometric (GMM) study with 43 landmarks placed on the same set of scans. Our multivariate statistical analysis using the 71 attribute values separates geographic ancestry groups and sexes with a high degree of reliability, and these results are broadly similar to those from GMM, but with some key differences that we discuss. This approach is compared with conventional, non-parametric methods for the quantification of facial shape, including generality, information density, and the separation of size and shape. Potential uses for phenotypic and dysmorphology studies are also discussed.
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Affiliation(s)
- Sawitree Wisetchat
- Department of Anthropology, University of Oregon, Eugene, Oregon, United States of America
| | - Kent A. Stevens
- Department of Computer and Information Science, University of Oregon, Eugene, Oregon, United States of America
| | - Stephen R. Frost
- Department of Anthropology, University of Oregon, Eugene, Oregon, United States of America
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4
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Wilke F, Matthews H, Herrick N, Dopkins N, Claes P, Walsh S. A novel approach to craniofacial analysis using automated 3D landmarking of the skull. Sci Rep 2024; 14:12381. [PMID: 38811771 PMCID: PMC11137148 DOI: 10.1038/s41598-024-63137-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Accepted: 05/24/2024] [Indexed: 05/31/2024] Open
Abstract
Automatic dense 3D surface registration is a powerful technique for comprehensive 3D shape analysis that has found a successful application in human craniofacial morphology research, particularly within the mandibular and cranial vault regions. However, a notable gap exists when exploring the frontal aspect of the human skull, largely due to the intricate and unique nature of its cranial anatomy. To better examine this region, this study introduces a simplified single-surface craniofacial bone mask comprising of 6707 quasi-landmarks, which can aid in the classification and quantification of variation over human facial bone surfaces. Automatic craniofacial bone phenotyping was conducted on a dataset of 31 skull scans obtained through cone-beam computed tomography (CBCT) imaging. The MeshMonk framework facilitated the non-rigid alignment of the constructed craniofacial bone mask with each individual target mesh. To gauge the accuracy and reliability of this automated process, 20 anatomical facial landmarks were manually placed three times by three independent observers on the same set of images. Intra- and inter-observer error assessments were performed using root mean square (RMS) distances, revealing consistently low scores. Subsequently, the corresponding automatic landmarks were computed and juxtaposed with the manually placed landmarks. The average Euclidean distance between these two landmark sets was 1.5 mm, while centroid sizes exhibited noteworthy similarity. Intraclass coefficients (ICC) demonstrated a high level of concordance (> 0.988), with automatic landmarking showing significantly lower errors and variation. These results underscore the utility of this newly developed single-surface craniofacial bone mask, in conjunction with the MeshMonk framework, as a highly accurate and reliable method for automated phenotyping of the facial region of human skulls from CBCT and CT imagery. This craniofacial template bone mask expansion of the MeshMonk toolbox not only enhances our capacity to study craniofacial bone variation but also holds significant potential for shedding light on the genetic, developmental, and evolutionary underpinnings of the overall human craniofacial structure.
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Affiliation(s)
- Franziska Wilke
- Department of Biology, Indiana University Indianapolis, Indianapolis, IN, USA
| | - Harold Matthews
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Murdoch Children's Research Institute, Melbourne, VIC, Australia
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
| | - Noah Herrick
- Department of Biology, Indiana University Indianapolis, Indianapolis, IN, USA
| | - Nichole Dopkins
- Department of Biology, Indiana University Indianapolis, Indianapolis, IN, USA
| | - Peter Claes
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Murdoch Children's Research Institute, Melbourne, VIC, Australia
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
| | - Susan Walsh
- Department of Biology, Indiana University Indianapolis, Indianapolis, IN, USA.
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5
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Naqvi S, Kim S, Tabatabaee S, Pampari A, Kundaje A, Pritchard JK, Wysocka J. Transfer learning reveals sequence determinants of the quantitative response to transcription factor dosage. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.28.596078. [PMID: 38853998 PMCID: PMC11160683 DOI: 10.1101/2024.05.28.596078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Deep learning approaches have made significant advances in predicting cell type-specific chromatin patterns from the identity and arrangement of transcription factor (TF) binding motifs. However, most models have been applied in unperturbed contexts, precluding a predictive understanding of how chromatin state responds to TF perturbation. Here, we used transfer learning to train and interpret deep learning models that use DNA sequence to predict, with accuracy approaching experimental reproducibility, how the concentration of two dosage-sensitive TFs (TWIST1, SOX9) affects regulatory element (RE) chromatin accessibility in facial progenitor cells. High-affinity motifs that allow for heterotypic TF co-binding and are concentrated at the center of REs buffer against quantitative changes in TF dosage and strongly predict unperturbed accessibility. In contrast, motifs with low-affinity or homotypic binding distributed throughout REs lead to sensitive responses with minimal contributions to unperturbed accessibility. Both buffering and sensitizing features show signatures of purifying selection. We validated these predictive sequence features using reporter assays and showed that a biophysical model of TF-nucleosome competition can explain the sensitizing effect of low-affinity motifs. Our approach of combining transfer learning and quantitative measurements of the chromatin response to TF dosage therefore represents a powerful method to reveal additional layers of the cis-regulatory code.
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Affiliation(s)
- Sahin Naqvi
- Departments of Chemical and Systems Biology and Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Genetics, Stanford University, Stanford, California, USA
- Division of Gastroenterology, Hepatology, and Nutrition, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Lead contact
| | - Seungsoo Kim
- Departments of Chemical and Systems Biology and Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA, USA
- These authors contributed equally
| | - Saman Tabatabaee
- Departments of Chemical and Systems Biology and Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
- These authors contributed equally
| | - Anusri Pampari
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Anshul Kundaje
- Department of Genetics, Stanford University, Stanford, California, USA
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Jonathan K Pritchard
- Department of Genetics, Stanford University, Stanford, California, USA
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Joanna Wysocka
- Departments of Chemical and Systems Biology and Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA, USA
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6
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Thomas M, Mackes N, Preuss-Dodhy A, Wieland T, Bundschus M. Assessing Privacy Vulnerabilities in Genetic Data Sets: Scoping Review. JMIR BIOINFORMATICS AND BIOTECHNOLOGY 2024; 5:e54332. [PMID: 38935957 PMCID: PMC11165293 DOI: 10.2196/54332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 03/26/2024] [Accepted: 03/29/2024] [Indexed: 06/29/2024]
Abstract
BACKGROUND Genetic data are widely considered inherently identifiable. However, genetic data sets come in many shapes and sizes, and the feasibility of privacy attacks depends on their specific content. Assessing the reidentification risk of genetic data is complex, yet there is a lack of guidelines or recommendations that support data processors in performing such an evaluation. OBJECTIVE This study aims to gain a comprehensive understanding of the privacy vulnerabilities of genetic data and create a summary that can guide data processors in assessing the privacy risk of genetic data sets. METHODS We conducted a 2-step search, in which we first identified 21 reviews published between 2017 and 2023 on the topic of genomic privacy and then analyzed all references cited in the reviews (n=1645) to identify 42 unique original research studies that demonstrate a privacy attack on genetic data. We then evaluated the type and components of genetic data exploited for these attacks as well as the effort and resources needed for their implementation and their probability of success. RESULTS From our literature review, we derived 9 nonmutually exclusive features of genetic data that are both inherent to any genetic data set and informative about privacy risk: biological modality, experimental assay, data format or level of processing, germline versus somatic variation content, content of single nucleotide polymorphisms, short tandem repeats, aggregated sample measures, structural variants, and rare single nucleotide variants. CONCLUSIONS On the basis of our literature review, the evaluation of these 9 features covers the great majority of privacy-critical aspects of genetic data and thus provides a foundation and guidance for assessing genetic data risk.
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7
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Robinson K, Curtis SW, Leslie EJ. The heterogeneous genetic architectures of orofacial clefts. Trends Genet 2024; 40:410-421. [PMID: 38480105 DOI: 10.1016/j.tig.2024.02.004] [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: 11/20/2023] [Revised: 02/13/2024] [Accepted: 02/13/2024] [Indexed: 05/09/2024]
Abstract
Orofacial clefts (OFCs) are common, affecting 1:1000 live births. OFCs occur across a phenotypic spectrum - including cleft lip (CL), cleft lip and palate (CLP), or cleft palate (CP) - and can be further subdivided based on laterality, severity, or specific structures affected. Herein we review what is known about the genetic architecture underlying each of these subtypes, considering both shared and subtype-specific risks. While there are more known genetic similarities between CL and CLP than CP, recent research supports both shared and subtype-specific genetic risk factors within and between phenotypic classifications of OFCs. Larger sample sizes and deeper phenotyping data will be of increasing importance for the discovery of novel genetic risk factors for OFCs and various subtypes going forward.
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Affiliation(s)
- Kelsey Robinson
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Sarah W Curtis
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Elizabeth J Leslie
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA.
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8
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Miller KA, Cruz Walma DA, Pinkas DM, Tooze RS, Bufton JC, Richardson W, Manning CE, Hunt AE, Cros J, Hartill V, Parker MJ, McGowan SJ, Twigg SRF, Chalk R, Staunton D, Johnson D, Wilkie AOM, Bullock AN. BTB domain mutations perturbing KCTD15 oligomerisation cause a distinctive frontonasal dysplasia syndrome. J Med Genet 2024; 61:490-501. [PMID: 38296633 DOI: 10.1136/jmg-2023-109531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 12/21/2023] [Indexed: 02/02/2024]
Abstract
INTRODUCTION KCTD15 encodes an oligomeric BTB domain protein reported to inhibit neural crest formation through repression of Wnt/beta-catenin signalling, as well as transactivation by TFAP2. Heterozygous missense variants in the closely related paralogue KCTD1 cause scalp-ear-nipple syndrome. METHODS Exome sequencing was performed on a two-generation family affected by a distinctive phenotype comprising a lipomatous frontonasal malformation, anosmia, cutis aplasia of the scalp and/or sparse hair, and congenital heart disease. Identification of a de novo missense substitution within KCTD15 led to targeted sequencing of DNA from a similarly affected sporadic patient, revealing a different missense mutation. Structural and biophysical analyses were performed to assess the effects of both amino acid substitutions on the KCTD15 protein. RESULTS A heterozygous c.310G>C variant encoding p.(Asp104His) within the BTB domain of KCTD15 was identified in an affected father and daughter and segregated with the phenotype. In the sporadically affected patient, a de novo heterozygous c.263G>A variant encoding p.(Gly88Asp) was present in KCTD15. Both substitutions were found to perturb the pentameric assembly of the BTB domain. A crystal structure of the BTB domain variant p.(Gly88Asp) revealed a closed hexameric assembly, whereas biophysical analyses showed that the p.(Asp104His) substitution resulted in a monomeric BTB domain likely to be partially unfolded at physiological temperatures. CONCLUSION BTB domain substitutions in KCTD1 and KCTD15 cause clinically overlapping phenotypes involving craniofacial abnormalities and cutis aplasia. The structural analyses demonstrate that missense substitutions act through a dominant negative mechanism by disrupting the higher order structure of the KCTD15 protein complex.
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Affiliation(s)
- Kerry A Miller
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - David A Cruz Walma
- Centre for Medicines Discovery, University of Oxford, Oxford, UK
- Cell Biology Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland, USA
| | - Daniel M Pinkas
- Centre for Medicines Discovery, University of Oxford, Oxford, UK
- Department of Biological Sciences, Universidad Loyola Andalucía, Seville, Spain
| | - Rebecca S Tooze
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Joshua C Bufton
- Centre for Medicines Discovery, University of Oxford, Oxford, UK
| | | | | | - Alice E Hunt
- Centre for Medicines Discovery, University of Oxford, Oxford, UK
| | - Julien Cros
- Centre for Medicines Discovery, University of Oxford, Oxford, UK
| | - Verity Hartill
- Leeds Institute of Medical Research, University of Leeds, Leeds, UK
- Yorkshire Regional Genetics Service, Leeds Teaching Hospitals NHS Trust, Chapel Allerton Hospital, Leeds, UK
| | - Michael J Parker
- Sheffield Clinical Genomics Service, Sheffield Children's Hospital NHS Foundation Trust, Sheffield, UK
| | - Simon J McGowan
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Stephen R F Twigg
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Rod Chalk
- Centre for Medicines Discovery, University of Oxford, Oxford, UK
| | - David Staunton
- Department of Biochemistry, University of Oxford, Oxford, UK
| | - David Johnson
- Craniofacial Unit, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Andrew O M Wilkie
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
- Craniofacial Unit, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Alex N Bullock
- Centre for Medicines Discovery, University of Oxford, Oxford, UK
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9
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Xie M, Kaiser M, Gershtein Y, Schnyder D, Deviatiiarov R, Gazizova G, Shagimardanova E, Zikmund T, Kerckhofs G, Ivashkin E, Batkovskyte D, Newton PT, Andersson O, Fried K, Gusev O, Zeberg H, Kaiser J, Adameyko I, Chagin AS. The level of protein in the maternal murine diet modulates the facial appearance of the offspring via mTORC1 signaling. Nat Commun 2024; 15:2367. [PMID: 38531868 DOI: 10.1038/s41467-024-46030-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 02/09/2024] [Indexed: 03/28/2024] Open
Abstract
The development of craniofacial skeletal structures is fascinatingly complex and elucidation of the underlying mechanisms will not only provide novel scientific insights, but also help develop more effective clinical approaches to the treatment and/or prevention of the numerous congenital craniofacial malformations. To this end, we performed a genome-wide analysis of RNA transcription from non-coding regulatory elements by CAGE-sequencing of the facial mesenchyme of human embryos and cross-checked the active enhancers thus identified against genes, identified by GWAS for the normal range human facial appearance. Among the identified active cis-enhancers, several belonged to the components of the PI3/AKT/mTORC1/autophagy pathway. To assess the functional role of this pathway, we manipulated it both genetically and pharmacologically in mice and zebrafish. These experiments revealed that mTORC1 signaling modulates craniofacial shaping at the stage of skeletal mesenchymal condensations, with subsequent fine-tuning during clonal intercalation. This ability of mTORC1 pathway to modulate facial shaping, along with its evolutionary conservation and ability to sense external stimuli, in particular dietary amino acids, indicate that the mTORC1 pathway may play a role in facial phenotypic plasticity. Indeed, the level of protein in the diet of pregnant female mice influenced the activity of mTORC1 in fetal craniofacial structures and altered the size of skeletogenic clones, thus exerting an impact on the local geometry and craniofacial shaping. Overall, our findings indicate that the mTORC1 signaling pathway is involved in the effect of environmental conditions on the shaping of craniofacial structures.
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Affiliation(s)
- Meng Xie
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
- Department of Biosciences and Nutrition, Karolinska Institute, Flemingsberg, Sweden
- School of Psychological and Cognitive Sciences, PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
| | - Markéta Kaiser
- Central European Institute of Technology, Brno University of Technology, Brno, Czech Republic
| | - Yaakov Gershtein
- Department of Neuroimmunology, Center for Brain Research, Medical University of Vienna, Vienna, Austria
| | - Daniela Schnyder
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
- Centre for Bone and Arthritis Research, Institute of Medicine, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
| | - Ruslan Deviatiiarov
- Regulatory Genomics Research Center, Kazan Federal University, Kazan, Russia
- Endocrinology Research Center, Moscow, Russia
- Life Improvement by Future Technologies (LIFT) Center, Moscow, Russia
- Intractable Disease Research Center, Juntendo University, Tokyo, Japan
| | - Guzel Gazizova
- Regulatory Genomics Research Center, Kazan Federal University, Kazan, Russia
| | - Elena Shagimardanova
- Regulatory Genomics Research Center, Kazan Federal University, Kazan, Russia
- Life Improvement by Future Technologies (LIFT) Center, Moscow, Russia
| | - Tomáš Zikmund
- Central European Institute of Technology, Brno University of Technology, Brno, Czech Republic
| | - Greet Kerckhofs
- Biomechanics Lab, Institute of Mechanics, Materials, and Civil Engineering (iMMC), UCLouvain, Louvain-la-Neuve, Belgium
- Pole of Morphology, Institute of Experimental and Clinical Research (IREC), UCLouvain, Woluwe, Belgium
- Department of Materials Engineering, KU Leuven, Leuven, Belgium
- Prometheus, Division for Skeletal Tissue Engineering, KU Leuven, Leuven, Belgium
| | - Evgeny Ivashkin
- A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Moscow, Russia
- Department of Developmental and Comparative Physiology, N.K. Koltsov Institute of Developmental Biology, Russian Academy of Sciences, Moscow, Russia
| | - Dominyka Batkovskyte
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Phillip T Newton
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
- Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
- Astrid Lindgren Children's hospital, Stockholm, Sweden
| | - Olov Andersson
- Department of Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden
| | - Kaj Fried
- Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Oleg Gusev
- Regulatory Genomics Research Center, Kazan Federal University, Kazan, Russia
- Endocrinology Research Center, Moscow, Russia
- Life Improvement by Future Technologies (LIFT) Center, Moscow, Russia
- Intractable Disease Research Center, Juntendo University, Tokyo, Japan
| | - Hugo Zeberg
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Jozef Kaiser
- Central European Institute of Technology, Brno University of Technology, Brno, Czech Republic
| | - Igor Adameyko
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden.
- Department of Neuroimmunology, Center for Brain Research, Medical University of Vienna, Vienna, Austria.
| | - Andrei S Chagin
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden.
- Centre for Bone and Arthritis Research, Institute of Medicine, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden.
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10
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Qiao H, Tan J, Yan J, Sun C, Yin X, Li Z, Wu J, Guan H, Wen S, Zhang M, Xu S, Jin L. A comprehensive evaluation of the phenotype-first and data-driven approaches in analyzing facial morphological traits. iScience 2024; 27:109325. [PMID: 38487017 PMCID: PMC10937830 DOI: 10.1016/j.isci.2024.109325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 01/17/2024] [Accepted: 02/20/2024] [Indexed: 03/17/2024] Open
Abstract
The phenotype-first approach (PFA) and data-driven approach (DDA) have both greatly facilitated anthropological studies and the mapping of trait-associated genes. However, the pros and cons of the two approaches are poorly understood. Here, we systematically evaluated the two approaches and analyzed 14,838 facial traits in 2,379 Han Chinese individuals. Interestingly, the PFA explained more facial variation than the DDA in the top 100 and 1,000 except in the top 10 phenotypes. Accordingly, the ratio of heterogeneous traits extracted from the PFA was much greater, while more homogenous traits were found using the DDA for different sex, age, and BMI groups. Notably, our results demonstrated that the sex factor accounted for 30% of phenotypic variation in all traits extracted. Furthermore, we linked DDA phenotypes to PFA phenotypes with explicit biological explanations. These findings provide new insights into the analysis of multidimensional phenotypes and expand the understanding of phenotyping approaches.
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Affiliation(s)
- Hui Qiao
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, School of Life Sciences, Fudan University, Shanghai 200438, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 201203, China
| | - Jingze Tan
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, School of Life Sciences, Fudan University, Shanghai 200438, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 201203, China
| | - Jun Yan
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 201203, China
| | - Chang Sun
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 201203, China
| | - Xing Yin
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 201203, China
| | - Zijun Li
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 201203, China
| | - Jiazi Wu
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 201203, China
| | - Haijuan Guan
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 201203, China
| | - Shaoqing Wen
- Institute of Archaeological Science, Fudan University, Shanghai 200433, China
| | - Menghan Zhang
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 201203, China
- Institute of Modern Languages and Linguistics, Fudan University, Shanghai 200433, China
- Research Institute of Intelligent Complex Systems, Fudan University, Shanghai 200433, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, School of Life Sciences, Fudan University, Shanghai 200438, China
- Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, School of Life Sciences, Fudan University, Shanghai 200438, China
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11
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Mohammed J, Arora N, Matthews HS, Hansen K, Bader M, Walsh S, Shaffer JR, Weinberg SM, Swigut T, Claes P, Selleri L, Wysocka J. A common cis-regulatory variant impacts normal-range and disease-associated human facial shape through regulation of PKDCC during chondrogenesis. eLife 2024; 13:e82564. [PMID: 38483448 PMCID: PMC10939500 DOI: 10.7554/elife.82564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 02/18/2024] [Indexed: 03/17/2024] Open
Abstract
Genome-wide association studies (GWAS) identified thousands of genetic variants linked to phenotypic traits and disease risk. However, mechanistic understanding of how GWAS variants influence complex morphological traits and can, in certain cases, simultaneously confer normal-range phenotypic variation and disease predisposition, is still largely lacking. Here, we focus on rs6740960, a single nucleotide polymorphism (SNP) at the 2p21 locus, which in GWAS studies has been associated both with normal-range variation in jaw shape and with an increased risk of non-syndromic orofacial clefting. Using in vitro derived embryonic cell types relevant for human facial morphogenesis, we show that this SNP resides in an enhancer that regulates chondrocytic expression of PKDCC - a gene encoding a tyrosine kinase involved in chondrogenesis and skeletal development. In agreement, we demonstrate that the rs6740960 SNP is sufficient to confer chondrocyte-specific differences in PKDCC expression. By deploying dense landmark morphometric analysis of skull elements in mice, we show that changes in Pkdcc dosage are associated with quantitative changes in the maxilla, mandible, and palatine bone shape that are concordant with the facial phenotypes and disease predisposition seen in humans. We further demonstrate that the frequency of the rs6740960 variant strongly deviated among different human populations, and that the activity of its cognate enhancer diverged in hominids. Our study provides a mechanistic explanation of how a common SNP can mediate normal-range and disease-associated morphological variation, with implications for the evolution of human facial features.
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Affiliation(s)
- Jaaved Mohammed
- Department of Chemical and Systems Biology, Stanford University School of MedicineStanfordUnited States
| | - Neha Arora
- Department of Chemical and Systems Biology, Stanford University School of MedicineStanfordUnited States
| | - Harold S Matthews
- Department of Human Genetics, KU LeuvenLeuvenBelgium
- Medical Imaging Research Center, University Hospitals LeuvenLeuvenBelgium
| | - Karissa Hansen
- Program in Craniofacial Biology, Department of Orofacial Sciences and Department of Anatomy, Institute of Human Genetics, Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San FranciscoSan FranciscoUnited States
| | - Maram Bader
- Department of Chemical and Systems Biology, Stanford University School of MedicineStanfordUnited States
| | - Susan Walsh
- Department of Biology, Indiana University IndianapolisIndianapolisUnited States
| | - John R Shaffer
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of PittsburghPittsburghUnited States
- Department of Human Genetics, University of PittsburghPittsburghUnited States
| | - Seth M Weinberg
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of PittsburghPittsburghUnited States
- Department of Human Genetics, University of PittsburghPittsburghUnited States
- Department of Anthropology, University of PittsburghPittsburghUnited States
| | - Tomek Swigut
- Department of Chemical and Systems Biology, Stanford University School of MedicineStanfordUnited States
| | - Peter Claes
- Department of Human Genetics, KU LeuvenLeuvenBelgium
- Medical Imaging Research Center, University Hospitals LeuvenLeuvenBelgium
- Department of Electrical Engineering, ESAT/PSI, KU LeuvenLeuvenBelgium
- Murdoch Children’s Research InstituteMelbourneAustralia
| | - Licia Selleri
- Program in Craniofacial Biology, Department of Orofacial Sciences and Department of Anatomy, Institute of Human Genetics, Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San FranciscoSan FranciscoUnited States
| | - Joanna Wysocka
- Department of Chemical and Systems Biology, Stanford University School of MedicineStanfordUnited States
- Department of Developmental Biology, Stanford University School of MedicineStanfordUnited States
- Howard Hughes Medical Institute, Stanford University School of MedicineStanfordUnited States
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12
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Rajderkar SS, Paraiso K, Amaral ML, Kosicki M, Cook LE, Darbellay F, Spurrell CH, Osterwalder M, Zhu Y, Wu H, Afzal SY, Blow MJ, Kelman G, Barozzi I, Fukuda-Yuzawa Y, Akiyama JA, Afzal V, Tran S, Plajzer-Frick I, Novak CS, Kato M, Hunter RD, von Maydell K, Wang A, Lin L, Preissl S, Lisgo S, Ren B, Dickel DE, Pennacchio LA, Visel A. Dynamic enhancer landscapes in human craniofacial development. Nat Commun 2024; 15:2030. [PMID: 38448444 PMCID: PMC10917818 DOI: 10.1038/s41467-024-46396-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 02/25/2024] [Indexed: 03/08/2024] Open
Abstract
The genetic basis of human facial variation and craniofacial birth defects remains poorly understood. Distant-acting transcriptional enhancers control the fine-tuned spatiotemporal expression of genes during critical stages of craniofacial development. However, a lack of accurate maps of the genomic locations and cell type-resolved activities of craniofacial enhancers prevents their systematic exploration in human genetics studies. Here, we combine histone modification, chromatin accessibility, and gene expression profiling of human craniofacial development with single-cell analyses of the developing mouse face to define the regulatory landscape of facial development at tissue- and single cell-resolution. We provide temporal activity profiles for 14,000 human developmental craniofacial enhancers. We find that 56% of human craniofacial enhancers share chromatin accessibility in the mouse and we provide cell population- and embryonic stage-resolved predictions of their in vivo activity. Taken together, our data provide an expansive resource for genetic and developmental studies of human craniofacial development.
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Affiliation(s)
- Sudha Sunil Rajderkar
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Kitt Paraiso
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Maria Luisa Amaral
- Bioinformatics and Systems Biology Graduate Program, University of California San Diego, La Jolla, CA, USA
| | - Michael Kosicki
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Laura E Cook
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Fabrice Darbellay
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
- Department of Genetic Medicine and Development, Faculty of Medicine, University of Geneva, 1211, Geneva, Switzerland
| | - Cailyn H Spurrell
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Marco Osterwalder
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
- Department for BioMedical Research (DBMR), University of Bern, 3008, Bern, Switzerland
- Department of Cardiology, Bern University Hospital, Bern, 3010, Switzerland
| | - Yiwen Zhu
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Han Wu
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Sarah Yasmeen Afzal
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
- Lucile Packard Children's Hospital, Stanford University, Stanford, CA, 94304, USA
| | - Matthew J Blow
- U.S. Department of Energy Joint Genome Institute, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Guy Kelman
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
- The Jerusalem Center for Personalized Computational Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Iros Barozzi
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
- Center for Cancer Research, Medical University of Vienna, Borschkegasse 8a 1090, Vienna, Austria
- Department of Surgery and Cancer, Imperial College London, London, UK
| | - Yoko Fukuda-Yuzawa
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
- University Research Management Center, Tohoku University, Sendai, Miyagi, 980-8577, Japan
| | - Jennifer A Akiyama
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Veena Afzal
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Stella Tran
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Ingrid Plajzer-Frick
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Catherine S Novak
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Momoe Kato
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Riana D Hunter
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
- UC San Francisco, Division of Experimental Medicine, 1001 Potrero Ave, San Francisco, CA, 94110, USA
| | - Kianna von Maydell
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Allen Wang
- Center for Epigenomics, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Lin Lin
- Center for Epigenomics, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Sebastian Preissl
- Center for Epigenomics, University of California San Diego School of Medicine, La Jolla, CA, USA
- Institute of Experimental and Clinical Pharmacology and Toxicology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Steven Lisgo
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle, NE1 3BZ, UK
| | - Bing Ren
- Institute of Genome Medicine, Moores Cancer Center, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Diane E Dickel
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
- Octant Inc., Emeryville, CA, 94608, USA
| | - Len A Pennacchio
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
- U.S. Department of Energy Joint Genome Institute, 1 Cyclotron Road, Berkeley, CA, 94720, USA
- Comparative Biochemistry Program, University of California, Berkeley, CA, 94720, USA
| | - Axel Visel
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA.
- U.S. Department of Energy Joint Genome Institute, 1 Cyclotron Road, Berkeley, CA, 94720, USA.
- School of Natural Sciences, University of California, Merced, CA, USA.
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13
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Jordan B. [What "look-alike" individuals tell us]. Med Sci (Paris) 2024; 40:290-292. [PMID: 38520107 DOI: 10.1051/medsci/2024016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/25/2024] Open
Abstract
Rare unrelated individuals show striking resemblance, almost as high as monozygotic twins. Extensive genetic analysis of a set of such individuals shows that every couple shares a given allele at a large set of loci, enriched for "face genes". The similarity is limited to this set of loci, and the rest of the genome is quite diverse in these "look alike" individuals.
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Affiliation(s)
- Bertrand Jordan
- Biologiste, généticien et immunologiste, Président d'Aprogène (Association pour la promotion de la Génomique), 13007 Marseille, France
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14
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Barash M, McNevin D, Fedorenko V, Giverts P. Machine learning applications in forensic DNA profiling: A critical review. Forensic Sci Int Genet 2024; 69:102994. [PMID: 38086200 DOI: 10.1016/j.fsigen.2023.102994] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2023] [Revised: 11/06/2023] [Accepted: 11/26/2023] [Indexed: 01/29/2024]
Abstract
Machine learning (ML) is a range of powerful computational algorithms capable of generating predictive models via intelligent autonomous analysis of relatively large and often unstructured data. ML has become an integral part of our daily lives with a plethora of applications, including web, business, automotive industry, clinical diagnostics, scientific research, and more recently, forensic science. In the field of forensic DNA, the manual analysis of complex data can be challenging, time-consuming, and error-prone. The integration of novel ML-based methods may aid in streamlining this process while maintaining the high accuracy and reproducibility required for forensic tools. Due to the relative novelty of such applications, the forensic community is largely unaware of ML capabilities and limitations. Furthermore, computer science and ML professionals are often unfamiliar with the forensic science field and its specific requirements. This manuscript offers a brief introduction to the capabilities of machine learning methods and their applications in the context of forensic DNA analysis and offers a critical review of the current literature in this rapidly developing field.
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Affiliation(s)
- Mark Barash
- Department of Justice Studies, San José State University, San Jose, CA, United States; Centre for Forensic Science, School of Mathematical and Physical Sciences, Faculty of Science, University of Technology Sydney, Broadway, Ultimo, NSW 2007, Australia.
| | - Dennis McNevin
- Centre for Forensic Science, School of Mathematical and Physical Sciences, Faculty of Science, University of Technology Sydney, Broadway, Ultimo, NSW 2007, Australia
| | - Vladimir Fedorenko
- The Educational and Scientific Laboratory of Forensic Materials Engineering of the Saratov State University, Russia
| | - Pavel Giverts
- Division of Identification and Forensic Science, Israel Police HQ, Haim Bar-Lev Road, Jerusalem, Israel
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15
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Wilke F, Matthews H, Herrick N, Dopkins N, Claes P, Walsh S. Automated 3D Landmarking of the Skull: A Novel Approach for Craniofacial Analysis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.09.579642. [PMID: 38405968 PMCID: PMC10888852 DOI: 10.1101/2024.02.09.579642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Automatic dense 3D surface registration is a powerful technique for comprehensive 3D shape analysis that has found a successful application in human craniofacial morphology research, particularly within the mandibular and cranial vault regions. However, a notable gap exists when exploring the frontal aspect of the human skull, largely due to the intricate and unique nature of its cranial anatomy. To better examine this region, this study introduces a simplified single-surface craniofacial bone mask comprising 9,999 quasi-landmarks, which can aid in the classification and quantification of variation over human facial bone surfaces. Automatic craniofacial bone phenotyping was conducted on a dataset of 31 skull scans obtained through cone-beam computed tomography (CBCT) imaging. The MeshMonk framework facilitated the non-rigid alignment of the constructed craniofacial bone mask with each individual target mesh. To gauge the accuracy and reliability of this automated process, 20 anatomical facial landmarks were manually placed three times by three independent observers on the same set of images. Intra- and inter-observer error assessments were performed using root mean square (RMS) distances, revealing consistently low scores. Subsequently, the corresponding automatic landmarks were computed and juxtaposed with the manually placed landmarks. The average Euclidean distance between these two landmark sets was 1.5mm, while centroid sizes exhibited noteworthy similarity. Intraclass coefficients (ICC) demonstrated a high level of concordance (>0.988), and automatic landmarking showing significantly lower errors and variation. These results underscore the utility of this newly developed single-surface craniofacial bone mask, in conjunction with the MeshMonk framework, as a highly accurate and reliable method for automated phenotyping of the facial region of human skulls from CBCT and CT imagery. This craniofacial template bone mask expansion of the MeshMonk toolbox not only enhances our capacity to study craniofacial bone variation but also holds significant potential for shedding light on the genetic, developmental, and evolutionary underpinnings of the overall human craniofacial structure.
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Affiliation(s)
- Franziska Wilke
- Department of Biology, Indiana University Indianapolis, Indianapolis, USA
| | - Harold Matthews
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
| | - Noah Herrick
- Department of Biology, Indiana University Indianapolis, Indianapolis, USA
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of Pittsburgh, Pittsburgh, PA, USA
| | - Nichole Dopkins
- Department of Biology, Indiana University Indianapolis, Indianapolis, USA
| | - Peter Claes
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
| | - Susan Walsh
- Department of Biology, Indiana University Indianapolis, Indianapolis, USA
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16
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Kim S, Morgunova E, Naqvi S, Goovaerts S, Bader M, Koska M, Popov A, Luong C, Pogson A, Swigut T, Claes P, Taipale J, Wysocka J. DNA-guided transcription factor cooperativity shapes face and limb mesenchyme. Cell 2024; 187:692-711.e26. [PMID: 38262408 PMCID: PMC10872279 DOI: 10.1016/j.cell.2023.12.032] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 10/23/2023] [Accepted: 12/27/2023] [Indexed: 01/25/2024]
Abstract
Transcription factors (TFs) can define distinct cellular identities despite nearly identical DNA-binding specificities. One mechanism for achieving regulatory specificity is DNA-guided TF cooperativity. Although in vitro studies suggest that it may be common, examples of such cooperativity remain scarce in cellular contexts. Here, we demonstrate how "Coordinator," a long DNA motif composed of common motifs bound by many basic helix-loop-helix (bHLH) and homeodomain (HD) TFs, uniquely defines the regulatory regions of embryonic face and limb mesenchyme. Coordinator guides cooperative and selective binding between the bHLH family mesenchymal regulator TWIST1 and a collective of HD factors associated with regional identities in the face and limb. TWIST1 is required for HD binding and open chromatin at Coordinator sites, whereas HD factors stabilize TWIST1 occupancy at Coordinator and titrate it away from HD-independent sites. This cooperativity results in the shared regulation of genes involved in cell-type and positional identities and ultimately shapes facial morphology and evolution.
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Affiliation(s)
- Seungsoo Kim
- Department of Chemical and Systems Biology, Stanford University, Stanford, CA 94305, USA; Department of Developmental Biology, Stanford University, Stanford, CA 94305, USA; Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford, CA 94305, USA
| | - Ekaterina Morgunova
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Solna, Sweden
| | - Sahin Naqvi
- Department of Chemical and Systems Biology, Stanford University, Stanford, CA 94305, USA; Department of Developmental Biology, Stanford University, Stanford, CA 94305, USA; Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Seppe Goovaerts
- Medical Imaging Research Center, UZ Leuven, Leuven, Belgium; Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Maram Bader
- Department of Chemical and Systems Biology, Stanford University, Stanford, CA 94305, USA; Department of Developmental Biology, Stanford University, Stanford, CA 94305, USA; Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA 94305, USA
| | - Mervenaz Koska
- Department of Developmental Biology, Stanford University, Stanford, CA 94305, USA
| | | | - Christy Luong
- Department of Chemical and Systems Biology, Stanford University, Stanford, CA 94305, USA
| | - Angela Pogson
- Department of Developmental Biology, Stanford University, Stanford, CA 94305, USA
| | - Tomek Swigut
- Department of Chemical and Systems Biology, Stanford University, Stanford, CA 94305, USA; Department of Developmental Biology, Stanford University, Stanford, CA 94305, USA; Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford, CA 94305, USA
| | - Peter Claes
- Medical Imaging Research Center, UZ Leuven, Leuven, Belgium; Department of Human Genetics, KU Leuven, Leuven, Belgium; Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
| | - Jussi Taipale
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Solna, Sweden; Department of Biochemistry, University of Cambridge, Cambridge, UK; Applied Tumor Genomics Program, University of Helsinki, Helsinki, Finland
| | - Joanna Wysocka
- Department of Chemical and Systems Biology, Stanford University, Stanford, CA 94305, USA; Department of Developmental Biology, Stanford University, Stanford, CA 94305, USA; Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford, CA 94305, USA.
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17
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Aponte JD, Bannister JJ, Hoskens H, Matthews H, Katsura K, Da Silva C, Cruz T, Pilz JHM, Spritz RA, Forkert ND, Claes P, Bernier FP, Klein OD, Katz DC, Hallgrímsson B. An interactive atlas of three-dimensional syndromic facial morphology. Am J Hum Genet 2024; 111:39-47. [PMID: 38181734 PMCID: PMC10806736 DOI: 10.1016/j.ajhg.2023.11.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 11/26/2023] [Accepted: 11/29/2023] [Indexed: 01/07/2024] Open
Abstract
Craniofacial phenotyping is critical for both syndrome delineation and diagnosis because craniofacial abnormalities occur in 30% of characterized genetic syndromes. Clinical reports, textbooks, and available software tools typically provide two-dimensional, static images and illustrations of the characteristic phenotypes of genetic syndromes. In this work, we provide an interactive web application that provides three-dimensional, dynamic visualizations for the characteristic craniofacial effects of 95 syndromes. Users can visualize syndrome facial appearance estimates quantified from data and easily compare craniofacial phenotypes of different syndromes. Our application also provides a map of morphological similarity between a target syndrome and other syndromes. Finally, users can upload 3D facial scans of individuals and compare them to our syndrome atlas estimates. In summary, we provide an interactive reference for the craniofacial phenotypes of syndromes that allows for precise, individual-specific comparisons of dysmorphology.
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Affiliation(s)
- J David Aponte
- Department of Cell Biology & Anatomy, Alberta Children's Hospital Research Institute and McCaig Bone and Joint Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; DeepSurface AI Inc., Calgary, AB, Canada
| | | | - Hanne Hoskens
- Department of Cell Biology & Anatomy, Alberta Children's Hospital Research Institute and McCaig Bone and Joint Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | | | - Kaitlin Katsura
- Department of Orofacial Sciences and Program in Craniofacial Biology, University of California, San Francisco, San Francisco, CA, USA
| | - Cassidy Da Silva
- Department of Cell Biology & Anatomy, Alberta Children's Hospital Research Institute and McCaig Bone and Joint Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Tim Cruz
- DeepSurface AI Inc., Calgary, AB, Canada
| | | | - Richard A Spritz
- Department of Pediatrics and the Human Medical Genetics and Genomics Program, University of Colorado School of Medicine, Aurora, CO, USA
| | - Nils D Forkert
- Department of Radiology and Alberta Children's Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Peter Claes
- Department of Human Genetics, KU Leuven, Leuven, Belgium; Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
| | - Francois P Bernier
- Department of Medical Genetics and the Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
| | - Ophir D Klein
- Department of Orofacial Sciences and Program in Craniofacial Biology, University of California, San Francisco, San Francisco, CA, USA; Department of Pediatrics, Cedars-Sinai Guerin Children's, Los Angeles, CA, USA
| | - David C Katz
- Department of Cell Biology & Anatomy, Alberta Children's Hospital Research Institute and McCaig Bone and Joint Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; DeepSurface AI Inc., Calgary, AB, Canada
| | - Benedikt Hallgrímsson
- Department of Cell Biology & Anatomy, Alberta Children's Hospital Research Institute and McCaig Bone and Joint Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
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18
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Wilderman A, D'haene E, Baetens M, Yankee TN, Winchester EW, Glidden N, Roets E, Van Dorpe J, Janssens S, Miller DE, Galey M, Brown KM, Stottmann RW, Vergult S, Weaver KN, Brugmann SA, Cox TC, Cotney J. A distant global control region is essential for normal expression of anterior HOXA genes during mouse and human craniofacial development. Nat Commun 2024; 15:136. [PMID: 38167838 PMCID: PMC10762089 DOI: 10.1038/s41467-023-44506-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 12/14/2023] [Indexed: 01/05/2024] Open
Abstract
Craniofacial abnormalities account for approximately one third of birth defects. The regulatory programs that build the face require precisely controlled spatiotemporal gene expression, achieved through tissue-specific enhancers. Clusters of coactivated enhancers and their target genes, known as superenhancers, are important in determining cell identity but have been largely unexplored in development. In this study we identified superenhancer regions unique to human embryonic craniofacial tissue. To demonstrate the importance of such regions in craniofacial development and disease, we focused on an ~600 kb noncoding region located between NPVF and NFE2L3. We identified long range interactions with this region in both human and mouse embryonic craniofacial tissue with the anterior portion of the HOXA gene cluster. Mice lacking this superenhancer exhibit perinatal lethality, and present with highly penetrant skull defects and orofacial clefts phenocopying Hoxa2-/- mice. Moreover, we identified two cases of de novo copy number changes of the superenhancer in humans both with severe craniofacial abnormalities. This evidence suggests we have identified a critical noncoding locus control region that specifically regulates anterior HOXA genes and copy number changes are pathogenic in human patients.
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Affiliation(s)
| | - Eva D'haene
- Center for Medical Genetics, Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Machteld Baetens
- Center for Medical Genetics, Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | | | - Emma Wentworth Winchester
- Graduate Program UConn Health, Farmington, CT, USA
- University of Connecticut School of Dental Medicine, Farmington, CT, USA
| | - Nicole Glidden
- Department of Genetics and Genome Sciences, University of Connecticut School of Medicine, Farmington, CT, USA
| | - Ellen Roets
- Department of Obstetrics, Women's Clinic, Ghent University Hospital, Ghent, Belgium
| | - Jo Van Dorpe
- Department of Pathology, Ghent University, Ghent University Hospital, Ghent, Belgium
| | - Sandra Janssens
- Center for Medical Genetics, Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Danny E Miller
- Department of Pediatrics, Division of Genetic Medicine, University of Washington, Washington, WA, USA
- Seattle Children's Hospital, Seattle, WA, 98195, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, 98195, USA
- Brotman Baty Institute of Precision Medicine, University of Washington, Seattle, WA, 98195, USA
| | - Miranda Galey
- Department of Pediatrics, Division of Genetic Medicine, University of Washington, Washington, WA, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, 98195, USA
| | - Kari M Brown
- Division of Developmental Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Rolf W Stottmann
- Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
- The Abigail Wexner Research Institute, Nationwide Children's Hospital, Columbus, OH, USA
- Department of Pediatrics, The Ohio State University School of Medicine, Columbus, OH, USA
| | - Sarah Vergult
- Center for Medical Genetics, Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - K Nicole Weaver
- Division of Developmental Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Samantha A Brugmann
- Division of Developmental Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Timothy C Cox
- Department of Oral & Craniofacial Sciences, University of Missouri Kansas City, Kansas City, MO, USA
- Department of Pediatrics, University of Missouri Kansas City, Kansas City, MO, USA
| | - Justin Cotney
- Department of Genetics and Genome Sciences, University of Connecticut School of Medicine, Farmington, CT, USA.
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA.
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19
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Vanneste M, Hoskens H, Goovaerts S, Matthews H, Aponte JD, Cole J, Shriver M, Marazita ML, Weinberg SM, Walsh S, Richmond S, Klein OD, Spritz RA, Peeters H, Hallgrímsson B, Claes P. Syndrome-informed phenotyping identifies a polygenic background for achondroplasia-like facial variation in the general population. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.07.570544. [PMID: 38106188 PMCID: PMC10723447 DOI: 10.1101/2023.12.07.570544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Human craniofacial shape is highly variable yet highly heritable with genetic variants interacting through multiple layers of development. Here, we hypothesize that Mendelian phenotypes represent the extremes of a phenotypic spectrum and, using achondroplasia as an example, we introduce a syndrome-informed phenotyping approach to identify genomic loci associated with achondroplasia-like facial variation in the normal population. We compared three-dimensional facial scans from 43 individuals with achondroplasia and 8246 controls to calculate achondroplasia-like facial scores. Multivariate GWAS of the control scores revealed a polygenic basis for normal facial variation along an achondroplasia-specific shape axis, identifying genes primarily involved in skeletal development. Jointly modeling these genes in two independent control samples showed craniofacial effects approximating the characteristic achondroplasia phenotype. These findings suggest that both complex and Mendelian genetic variation act on the same developmentally determined axes of facial variation, providing new insights into the genetic intersection of complex traits and Mendelian disorders.
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Affiliation(s)
| | - Hanne Hoskens
- Department of Cell Biology & Anatomy, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Children’s Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- McCaig Bone and Joint Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Seppe Goovaerts
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
| | - Harold Matthews
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
| | - Jose D Aponte
- Department of Cell Biology & Anatomy, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Children’s Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- McCaig Bone and Joint Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Joanne Cole
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, USA
| | - Mark Shriver
- Department of Anthropology, Pennsylvania State University, State College, PA, USA
| | - Mary L. Marazita
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Seth M. Weinberg
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Susan Walsh
- Department of Biology, Indiana University Purdue University Indianapolis, Indianapolis, IN, USA
| | - Stephen Richmond
- Applied Clinical Research and Public Health, School of Dentistry, Cardiff University, Cardiff, UK
| | - Ophir D Klein
- Department of Orofacial Sciences and Program in Craniofacial Biology, University of California, San Francisco, CA, 94143, USA
- Department of Pediatrics, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Richard A Spritz
- Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO, USA
| | - Hilde Peeters
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Benedikt Hallgrímsson
- Department of Cell Biology & Anatomy, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Children’s Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- McCaig Bone and Joint Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Peter Claes
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
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20
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Li Z, Melograna F, Hoskens H, Duroux D, Marazita ML, Walsh S, Weinberg SM, Shriver MD, Müller-Myhsok B, Claes P, Van Steen K. netMUG: a novel network-guided multi-view clustering workflow for dissecting genetic and facial heterogeneity. Front Genet 2023; 14:1286800. [PMID: 38125750 PMCID: PMC10731261 DOI: 10.3389/fgene.2023.1286800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 11/14/2023] [Indexed: 12/23/2023] Open
Abstract
Introduction: Multi-view data offer advantages over single-view data for characterizing individuals, which is crucial in precision medicine toward personalized prevention, diagnosis, or treatment follow-up. Methods: Here, we develop a network-guided multi-view clustering framework named netMUG to identify actionable subgroups of individuals. This pipeline first adopts sparse multiple canonical correlation analysis to select multi-view features possibly informed by extraneous data, which are then used to construct individual-specific networks (ISNs). Finally, the individual subtypes are automatically derived by hierarchical clustering on these network representations. Results: We applied netMUG to a dataset containing genomic data and facial images to obtain BMI-informed multi-view strata and showed how it could be used for a refined obesity characterization. Benchmark analysis of netMUG on synthetic data with known strata of individuals indicated its superior performance compared with both baseline and benchmark methods for multi-view clustering. The clustering derived from netMUG achieved an adjusted Rand index of 1 with respect to the synthesized true labels. In addition, the real-data analysis revealed subgroups strongly linked to BMI and genetic and facial determinants of these subgroups. Discussion: netMUG provides a powerful strategy, exploiting individual-specific networks to identify meaningful and actionable strata. Moreover, the implementation is easy to generalize to accommodate heterogeneous data sources or highlight data structures.
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Affiliation(s)
- Zuqi Li
- BIO3 - Laboratory for Systems Medicine, Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
| | - Federico Melograna
- BIO3 - Laboratory for Systems Medicine, Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Hanne Hoskens
- BIO3 - Laboratory for Systems Medicine, Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
| | - Diane Duroux
- BIO3 - Laboratory for Systems Genetics, GIGA-R Medical Genomics, University of Liège, Liège, Belgium
| | - Mary L. Marazita
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, United States
| | - Susan Walsh
- Department of Biology, Indiana University Indianapolis, Indianapolis, IN, United States
| | - Seth M. Weinberg
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, United States
| | - Mark D. Shriver
- Department of Anthropology, Pennsylvania State University, State College, PA, United States
| | | | - Peter Claes
- BIO3 - Laboratory for Systems Medicine, Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Electrical Engineering, KU Leuven, Leuven, Belgium
- Murdoch Children’s Research Institute, Melbourne, VIC, Australia
| | - Kristel Van Steen
- BIO3 - Laboratory for Systems Medicine, Department of Human Genetics, KU Leuven, Leuven, Belgium
- BIO3 - Laboratory for Systems Genetics, GIGA-R Medical Genomics, University of Liège, Liège, Belgium
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21
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Kapila S, Vora SR, Rengasamy Venugopalan S, Elnagar MH, Akyalcin S. Connecting the dots towards precision orthodontics. Orthod Craniofac Res 2023; 26 Suppl 1:8-19. [PMID: 37968678 DOI: 10.1111/ocr.12725] [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] [Accepted: 10/20/2023] [Indexed: 11/17/2023]
Abstract
Precision orthodontics entails the use of personalized clinical, biological, social and environmental knowledge of each patient for deep individualized clinical phenotyping and diagnosis combined with the delivery of care using advanced customized devices, technologies and biologics. From its historical origins as a mechanotherapy and materials driven profession, the most recent advances in orthodontics in the past three decades have been propelled by technological innovations including volumetric and surface 3D imaging and printing, advances in software that facilitate the derivation of diagnostic details, enhanced personalization of treatment plans and fabrication of custom appliances. Still, the use of these diagnostic and therapeutic technologies is largely phenotype driven, focusing mainly on facial/skeletal morphology and tooth positions. Future advances in orthodontics will involve comprehensive understanding of an individual's biology through omics, a field of biology that involves large-scale rapid analyses of DNA, mRNA, proteins and other biological regulators from a cell, tissue or organism. Such understanding will define individual biological attributes that will impact diagnosis, treatment decisions, risk assessment and prognostics of therapy. Equally important are the advances in artificial intelligence (AI) and machine learning, and its applications in orthodontics. AI is already being used to perform validation of approaches for diagnostic purposes such as landmark identification, cephalometric tracings, diagnosis of pathologies and facial phenotyping from radiographs and/or photographs. Other areas for future discoveries and utilization of AI will include clinical decision support, precision orthodontics, payer decisions and risk prediction. The synergies between deep 3D phenotyping and advances in materials, omics and AI will propel the technological and omics era towards achieving the goal of delivering optimized and predictable precision orthodontics.
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Affiliation(s)
- Sunil Kapila
- Strategic Initiatives and Operations, UCLA School of Dentistry, Los Angeles, California, USA
| | - Siddharth R Vora
- Oral Health Sciences, University of British Columbia, Vancouver, British Columbia, USA
| | | | - Mohammed H Elnagar
- Department of Orthodontics, College of Dentistry, University of Illinois Chicago, Chicago, Illinois, USA
| | - Sercan Akyalcin
- Department of Developmental Biology, Harvard School of Dental Medicine, Boston, Massachusetts, USA
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22
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Goovaerts S, Hoskens H, Eller RJ, Herrick N, Musolf AM, Justice CM, Yuan M, Naqvi S, Lee MK, Vandermeulen D, Szabo-Rogers HL, Romitti PA, Boyadjiev SA, Marazita ML, Shaffer JR, Shriver MD, Wysocka J, Walsh S, Weinberg SM, Claes P. Joint multi-ancestry and admixed GWAS reveals the complex genetics behind human cranial vault shape. Nat Commun 2023; 14:7436. [PMID: 37973980 PMCID: PMC10654897 DOI: 10.1038/s41467-023-43237-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 11/01/2023] [Indexed: 11/19/2023] Open
Abstract
The cranial vault in humans is highly variable, clinically relevant, and heritable, yet its genetic architecture remains poorly understood. Here, we conduct a joint multi-ancestry and admixed multivariate genome-wide association study on 3D cranial vault shape extracted from magnetic resonance images of 6772 children from the ABCD study cohort yielding 30 genome-wide significant loci. Follow-up analyses indicate that these loci overlap with genomic risk loci for sagittal craniosynostosis, show elevated activity cranial neural crest cells, are enriched for processes related to skeletal development, and are shared with the face and brain. We present supporting evidence of regional localization for several of the identified genes based on expression patterns in the cranial vault bones of E15.5 mice. Overall, our study provides a comprehensive overview of the genetics underlying normal-range cranial vault shape and its relevance for understanding modern human craniofacial diversity and the etiology of congenital malformations.
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Affiliation(s)
- Seppe Goovaerts
- Department of Human Genetics, KU Leuven, Leuven, Belgium.
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium.
| | - Hanne Hoskens
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
| | - Ryan J Eller
- Department of Biology, Indiana University Indianapolis, Indianapolis, IN, USA
| | - Noah Herrick
- Department of Biology, Indiana University Indianapolis, Indianapolis, IN, USA
| | - Anthony M Musolf
- Statistical Genetics Section, Computational and Statistical Genomics Branch, NHGRI, NIH, MD, Baltimore, USA
| | - Cristina M Justice
- Genometrics Section, Computational and Statistical Genomics Branch, Division of Intramural Research, NHGRI, NIH, Baltimore, MD, USA
- Neurobehavioral Clinical Research Section, Social and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Meng Yuan
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
| | - Sahin Naqvi
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA
- Departments of Genetics and Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - Myoung Keun Lee
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Dirk Vandermeulen
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
| | - Heather L Szabo-Rogers
- Department of Anatomy, Physiology and Pharmacology, University of Saskatchewan, Saskatchewan, Canada
| | - Paul A Romitti
- Department of Epidemiology, College of Public Health, The University of Iowa, Iowa City, IA, USA
| | - Simeon A Boyadjiev
- Department of Pediatrics, University of California Davis, Sacramento, CA, USA
| | - Mary L Marazita
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - John R Shaffer
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mark D Shriver
- Department of Anthropology, Pennsylvania State University, State College, PA, USA
| | - Joanna Wysocka
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Susan Walsh
- Department of Biology, Indiana University Indianapolis, Indianapolis, IN, USA
| | - Seth M Weinberg
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Anthropology, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Peter Claes
- Department of Human Genetics, KU Leuven, Leuven, Belgium.
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium.
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium.
- Murdoch Children's Research Institute, Melbourne, VIC, Australia.
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23
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Autio AH, Paavola J, Tervonen J, Lång M, Huuskonen TJ, Huttunen J, Kärkkäinen V, von Und Zu Fraunberg M, Lindgren AE, Koivisto T, Kurola J, Jääskeläinen JE, Kämäräinen OP. Should individual timeline and serial CT/MRI panels of all patients be presented in acute brain insult cohorts? A pilot study of 45 patients with decompressive craniectomy after aneurysmal subarachnoid hemorrhage. Acta Neurochir (Wien) 2023; 165:3299-3323. [PMID: 36715752 PMCID: PMC10624760 DOI: 10.1007/s00701-022-05473-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 12/20/2022] [Indexed: 01/31/2023]
Abstract
PURPOSE Our review of acute brain insult articles indicated that the patients' individual (i) timeline panels with the defined time points since the emergency call and (ii) serial brain CT/MRI slice panels through the neurointensive care until death or final brain tissue outcome at 12 months or later are not presented. METHODS We retrospectively constructed such panels for the 45 aneurysmal subarachnoid hemorrhage (aSAH) patients with a secondary decompressive craniectomy (DC) after the acute admission to neurointensive care at Kuopio University Hospital (KUH) from a defined population from 2005 to 2018. The patients were indicated by numbers (1.-45.) in the pseudonymized panels, tables, results, and discussion. The timelines contained up to ten defined time points on a logarithmic time axis until death ([Formula: see text]; 56%) or 3 years ([Formula: see text]; 44%). The brain CT/MRI panels contained a representative slice from the following time points: SAH diagnosis, after aneurysm closure, after DC, at about 12 months (20 survivors). RESULTS The timelines indicated re-bleeds and allowed to compare the times elapsed between any two time points, in terms of workflow swiftness. The serial CT/MRI slices illustrated the presence and course of intracerebral hemorrhage (ICH), perihematomal edema, intraventricular hemorrhage (IVH), hydrocephalus, delayed brain injury, and, in the 20 (44%) survivors, the brain tissue outcome. CONCLUSIONS The pseudonymized timeline panels and serial brain imaging panels, indicating the patients by numbers, allowed the presentation and comparison of individual clinical courses. An obvious application would be the quality control in acute or elective medicine for timely and equal access to clinical care.
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Affiliation(s)
- Anniina H Autio
- Neurosurgery, NeuroCenter, Kuopio University Hospital, PL 100, 70029, Kuopio, Finland.
- Institute of Clinical Medicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland.
| | - Juho Paavola
- Neurosurgery, NeuroCenter, Kuopio University Hospital, PL 100, 70029, Kuopio, Finland
- Institute of Clinical Medicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Joona Tervonen
- Neurosurgery, NeuroCenter, Kuopio University Hospital, PL 100, 70029, Kuopio, Finland
- Institute of Clinical Medicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Maarit Lång
- Institute of Clinical Medicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- Neurointensive Care Unit, Kuopio University Hospital, Kuopio, Finland
| | - Terhi J Huuskonen
- Neurosurgery, NeuroCenter, Kuopio University Hospital, PL 100, 70029, Kuopio, Finland
- Institute of Clinical Medicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Jukka Huttunen
- Neurosurgery, NeuroCenter, Kuopio University Hospital, PL 100, 70029, Kuopio, Finland
- Institute of Clinical Medicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Virve Kärkkäinen
- Neurosurgery, NeuroCenter, Kuopio University Hospital, PL 100, 70029, Kuopio, Finland
| | - Mikael von Und Zu Fraunberg
- Neurosurgery, NeuroCenter, Kuopio University Hospital, PL 100, 70029, Kuopio, Finland
- Institute of Clinical Medicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- Department of Neurosurgery, Oulu University Hospital, Oulu, Finland
- Research Unit of Clinical Medicine, University of Oulu, Oulu, Finland
| | - Antti E Lindgren
- Neurosurgery, NeuroCenter, Kuopio University Hospital, PL 100, 70029, Kuopio, Finland
- Institute of Clinical Medicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- Clinical Radiology, Kuopio University Hospital, Kuopio, Finland
| | - Timo Koivisto
- Neurosurgery, NeuroCenter, Kuopio University Hospital, PL 100, 70029, Kuopio, Finland
- Institute of Clinical Medicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Jouni Kurola
- Institute of Clinical Medicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- Center for Prehospital Emergency Care, Kuopio University Hospital, Kuopio, Finland
| | - Juha E Jääskeläinen
- Neurosurgery, NeuroCenter, Kuopio University Hospital, PL 100, 70029, Kuopio, Finland
- Institute of Clinical Medicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Olli-Pekka Kämäräinen
- Neurosurgery, NeuroCenter, Kuopio University Hospital, PL 100, 70029, Kuopio, Finland
- Institute of Clinical Medicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
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24
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Cho HW, Ban HJ, Jin HS, Cha S, Eom YB. A genome-wide association scan reveals novel loci for facial traits of Koreans. Genomics 2023; 115:110710. [PMID: 37734486 DOI: 10.1016/j.ygeno.2023.110710] [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: 07/05/2023] [Revised: 09/07/2023] [Accepted: 09/18/2023] [Indexed: 09/23/2023]
Abstract
DNA-based prediction of externally visible characteristics (EVC) with SNPs is one of the research areas of interest in the forensic field. Based on a previous study performing GWAS on facial traits in a Korean population, herein, we present results stemming from GWA analysis with KoreanChip and novel genetic loci satisfying genome-wide significant level. We discovered a total of 20 signals and 12 loci were found to have novel associations with facial traits, including six loci located in intergenic regions and six loci located at UBE2O, HECTD2, CCDC108, TPK1, FCN2, and FRMPD1. Additionally, we performed a polygenic score analysis for 33 distance-related traits in facial phenotyping and determined genetic relationships between facial traits and SNPs using the GCTA program. The results of the current study offer an understanding of how facial morphology is influenced by complex genetic structures and provide insights into forensic investigation and population genetics.
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Affiliation(s)
- Hye-Won Cho
- Department of Medical Sciences, Graduate School, Soonchunhyang University, Asan, Chungnam 31538, Republic of Korea
| | - Hyo-Jeong Ban
- Korea Medicine (KM) Data Division, Korea Institute of Oriental Medicine, Daejeon 34054, Republic of Korea
| | - Hyun-Seok Jin
- Department of Biomedical Laboratory Science, College of Life and Health Sciences, Hoseo University, Asan, Chungnam 31499, Republic of Korea
| | - Seongwon Cha
- Korea Medicine (KM) Data Division, Korea Institute of Oriental Medicine, Daejeon 34054, Republic of Korea.
| | - Yong-Bin Eom
- Department of Medical Sciences, Graduate School, Soonchunhyang University, Asan, Chungnam 31538, Republic of Korea; Department of Biomedical Laboratory Science, College of Medical Sciences, Soonchunhyang University, Asan, Chungnam 31538, Republic of Korea.
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25
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He Y, Guo Y, Zheng W, Yue T, Zhang H, Wang B, Feng Z, Ouzhuluobu, Cui C, Liu K, Zhou B, Zeng X, Li L, Wang T, Wang Y, Zhang C, Xu S, Qi X, Su B. Polygenic adaptation leads to a higher reproductive fitness of native Tibetans at high altitude. Curr Biol 2023; 33:4037-4051.e5. [PMID: 37643619 DOI: 10.1016/j.cub.2023.08.021] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Revised: 06/01/2023] [Accepted: 08/04/2023] [Indexed: 08/31/2023]
Abstract
The adaptation of Tibetans to high-altitude environments has been studied extensively. However, the direct assessment of evolutionary adaptation, i.e., the reproductive fitness of Tibetans and its genetic basis, remains elusive. Here, we conduct systematic phenotyping and genome-wide association analysis of 2,252 mother-newborn pairs of indigenous Tibetans, covering 12 reproductive traits and 76 maternal physiological traits. Compared with the lowland immigrants living at high altitudes, indigenous Tibetans show better reproductive outcomes, reflected by their lower abortion rate, higher birth weight, and better fetal development. The results of genome-wide association analyses indicate a polygenic adaptation of reproduction in Tibetans, attributed to the genomic backgrounds of both the mothers and the newborns. Furthermore, the EPAS1-edited mice display higher reproductive fitness under chronic hypoxia, mirroring the situation in Tibetans. Collectively, these results shed new light on the phenotypic pattern and the genetic mechanism of human reproductive fitness in extreme environments.
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Affiliation(s)
- Yaoxi He
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China.
| | - Yongbo Guo
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Wangshan Zheng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Tian Yue
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Hui Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650000, China
| | - Bin Wang
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa 850000, China
| | - Zhanying Feng
- CEMS, NCMIS, MDIS, Academy of Mathematics & Systems Science, Chinese Academy of Sciences, Beijing 100080, China
| | - Ouzhuluobu
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa 850000, China; High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa 850000, China
| | - Chaoying Cui
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa 850000, China; High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa 850000, China
| | - Kai Liu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Bin Zhou
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Xuerui Zeng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Liya Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Tianyun Wang
- Department of Medical Genetics, Center for Medical Genetics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing 100191, China
| | - Yong Wang
- CEMS, NCMIS, MDIS, Academy of Mathematics & Systems Science, Chinese Academy of Sciences, Beijing 100080, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
| | - Chao Zhang
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China; Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai 201203, China
| | - Xuebin Qi
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa 850000, China; State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650000, China.
| | - Bing Su
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China.
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26
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Tseng KC, Crump JG. Craniofacial developmental biology in the single-cell era. Development 2023; 150:dev202077. [PMID: 37812056 PMCID: PMC10617621 DOI: 10.1242/dev.202077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
The evolution of a unique craniofacial complex in vertebrates made possible new ways of breathing, eating, communicating and sensing the environment. The head and face develop through interactions of all three germ layers, the endoderm, ectoderm and mesoderm, as well as the so-called fourth germ layer, the cranial neural crest. Over a century of experimental embryology and genetics have revealed an incredible diversity of cell types derived from each germ layer, signaling pathways and genes that coordinate craniofacial development, and how changes to these underlie human disease and vertebrate evolution. Yet for many diseases and congenital anomalies, we have an incomplete picture of the causative genomic changes, in particular how alterations to the non-coding genome might affect craniofacial gene expression. Emerging genomics and single-cell technologies provide an opportunity to obtain a more holistic view of the genes and gene regulatory elements orchestrating craniofacial development across vertebrates. These single-cell studies generate novel hypotheses that can be experimentally validated in vivo. In this Review, we highlight recent advances in single-cell studies of diverse craniofacial structures, as well as potential pitfalls and the need for extensive in vivo validation. We discuss how these studies inform the developmental sources and regulation of head structures, bringing new insights into the etiology of structural birth anomalies that affect the vertebrate head.
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Affiliation(s)
- Kuo-Chang Tseng
- Department of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine of University of Southern California, Los Angeles, CA 90033, USA
| | - J. Gage Crump
- Department of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine of University of Southern California, Los Angeles, CA 90033, USA
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27
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Pollen AA, Kilik U, Lowe CB, Camp JG. Human-specific genetics: new tools to explore the molecular and cellular basis of human evolution. Nat Rev Genet 2023; 24:687-711. [PMID: 36737647 PMCID: PMC9897628 DOI: 10.1038/s41576-022-00568-4] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/08/2022] [Indexed: 02/05/2023]
Abstract
Our ancestors acquired morphological, cognitive and metabolic modifications that enabled humans to colonize diverse habitats, develop extraordinary technologies and reshape the biosphere. Understanding the genetic, developmental and molecular bases for these changes will provide insights into how we became human. Connecting human-specific genetic changes to species differences has been challenging owing to an abundance of low-effect size genetic changes, limited descriptions of phenotypic differences across development at the level of cell types and lack of experimental models. Emerging approaches for single-cell sequencing, genetic manipulation and stem cell culture now support descriptive and functional studies in defined cell types with a human or ape genetic background. In this Review, we describe how the sequencing of genomes from modern and archaic hominins, great apes and other primates is revealing human-specific genetic changes and how new molecular and cellular approaches - including cell atlases and organoids - are enabling exploration of the candidate causal factors that underlie human-specific traits.
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Affiliation(s)
- Alex A Pollen
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA.
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.
| | - Umut Kilik
- Institute of Human Biology (IHB), Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Craig B Lowe
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC, USA.
| | - J Gray Camp
- Institute of Human Biology (IHB), Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland.
- University of Basel, Basel, Switzerland.
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28
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Selleri L, Rijli FM. Shaping faces: genetic and epigenetic control of craniofacial morphogenesis. Nat Rev Genet 2023; 24:610-626. [PMID: 37095271 DOI: 10.1038/s41576-023-00594-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/14/2023] [Indexed: 04/26/2023]
Abstract
Major differences in facial morphology distinguish vertebrate species. Variation of facial traits underlies the uniqueness of human individuals, and abnormal craniofacial morphogenesis during development leads to birth defects that significantly affect quality of life. Studies during the past 40 years have advanced our understanding of the molecular mechanisms that establish facial form during development, highlighting the crucial roles in this process of a multipotent cell type known as the cranial neural crest cell. In this Review, we discuss recent advances in multi-omics and single-cell technologies that enable genes, transcriptional regulatory networks and epigenetic landscapes to be closely linked to the establishment of facial patterning and its variation, with an emphasis on normal and abnormal craniofacial morphogenesis. Advancing our knowledge of these processes will support important developments in tissue engineering, as well as the repair and reconstruction of the abnormal craniofacial complex.
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Affiliation(s)
- Licia Selleri
- Program in Craniofacial Biology, Department of Orofacial Sciences, School of Dentistry, University of California, San Francisco, CA, USA.
- Department of Anatomy, School of Medicine, University of California, San Francisco, CA, USA.
| | - Filippo M Rijli
- Laboratory of Developmental Neuroepigenetics, Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.
- University of Basel, Basel, Switzerland.
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29
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Dingemans AJM, Hinne M, Truijen KMG, Goltstein L, van Reeuwijk J, de Leeuw N, Schuurs-Hoeijmakers J, Pfundt R, Diets IJ, den Hoed J, de Boer E, Coenen-van der Spek J, Jansen S, van Bon BW, Jonis N, Ockeloen CW, Vulto-van Silfhout AT, Kleefstra T, Koolen DA, Campeau PM, Palmer EE, Van Esch H, Lyon GJ, Alkuraya FS, Rauch A, Marom R, Baralle D, van der Sluijs PJ, Santen GWE, Kooy RF, van Gerven MAJ, Vissers LELM, de Vries BBA. PhenoScore quantifies phenotypic variation for rare genetic diseases by combining facial analysis with other clinical features using a machine-learning framework. Nat Genet 2023; 55:1598-1607. [PMID: 37550531 DOI: 10.1038/s41588-023-01469-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 07/05/2023] [Indexed: 08/09/2023]
Abstract
Several molecular and phenotypic algorithms exist that establish genotype-phenotype correlations, including facial recognition tools. However, no unified framework that investigates both facial data and other phenotypic data directly from individuals exists. We developed PhenoScore: an open-source, artificial intelligence-based phenomics framework, combining facial recognition technology with Human Phenotype Ontology data analysis to quantify phenotypic similarity. Here we show PhenoScore's ability to recognize distinct phenotypic entities by establishing recognizable phenotypes for 37 of 40 investigated syndromes against clinical features observed in individuals with other neurodevelopmental disorders and show it is an improvement on existing approaches. PhenoScore provides predictions for individuals with variants of unknown significance and enables sophisticated genotype-phenotype studies by testing hypotheses on possible phenotypic (sub)groups. PhenoScore confirmed previously known phenotypic subgroups caused by variants in the same gene for SATB1, SETBP1 and DEAF1 and provides objective clinical evidence for two distinct ADNP-related phenotypes, already established functionally.
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Affiliation(s)
- Alexander J M Dingemans
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Artificial Intelligence, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Max Hinne
- Department of Artificial Intelligence, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Kim M G Truijen
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Lia Goltstein
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Jeroen van Reeuwijk
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Nicole de Leeuw
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Janneke Schuurs-Hoeijmakers
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Rolph Pfundt
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Illja J Diets
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Joery den Hoed
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
| | - Elke de Boer
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Jet Coenen-van der Spek
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Sandra Jansen
- Department of Human Genetics, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Bregje W van Bon
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Noraly Jonis
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Charlotte W Ockeloen
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Anneke T Vulto-van Silfhout
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Tjitske Kleefstra
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - David A Koolen
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Philippe M Campeau
- Department of Pediatrics, University of Montreal, Montreal, Quebec, Canada
| | - Elizabeth E Palmer
- Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia
- Sydney Children's Hospitals Network, Sydney, New South Wales, Australia
| | - Hilde Van Esch
- Center for Human Genetics, University Hospitals Leuven, University of Leuven, Leuven, Belgium
| | - Gholson J Lyon
- Department of Human Genetics and George A. Jervis Clinic, Institute for Basic Research in Developmental Disabilities (IBR), Staten Island, NY, USA
- Biology PhD Program, The Graduate Center, The City University of New York, New York City, NY, USA
| | - Fowzan S Alkuraya
- Department of Translational Genomics, Center for Genomic Medicine, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Anita Rauch
- Institute of Medical Genetics, University of Zürich, Zürich, Switzerland
| | - Ronit Marom
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Diana Baralle
- Faculty of Medicine, University of Southampton, Southampton, UK
| | | | - Gijs W E Santen
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - R Frank Kooy
- Department of Medical Genetics, University of Antwerp, Antwerp, Belgium
| | - Marcel A J van Gerven
- Department of Artificial Intelligence, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Lisenka E L M Vissers
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands.
| | - Bert B A de Vries
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands.
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30
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Yuan M, Goovaerts S, Hoskens H, Richmond S, Walsh S, Shriver MD, Shaffer JR, Marazita ML, Weinberg SM, Peeters H, Claes P. Data-driven trait heritability-based extraction of human facial phenotypes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.13.553129. [PMID: 37645810 PMCID: PMC10462092 DOI: 10.1101/2023.08.13.553129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
A genome-wide association study (GWAS) of a complex, multi-dimensional morphological trait, such as the human face, typically relies on predefined and simplified phenotypic measurements, such as inter-landmark distances and angles. These measures are predominantly designed by human experts based on perceived biological or clinical knowledge. To avoid use handcrafted phenotypes (i.e., a priori expert-identified phenotypes), alternative automatically extracted phenotypic descriptors, such as features derived from dimension reduction techniques (e.g., principal component analysis), are employed. While the features generated by such computational algorithms capture the geometric variations of the biological shape, they are not necessarily genetically relevant. Therefore, genetically informed data-driven phenotyping is desirable. Here, we propose an approach where phenotyping is done through a data-driven optimization of trait heritability, defined as the degree of variation in a phenotypic trait in a population that is due to genetic variation. The resulting phenotyping process consists of two steps: 1) constructing a feature space that models shape variations using dimension reduction techniques, and 2) searching for directions in the feature space exhibiting high trait heritability using a genetic search algorithm (i.e., heuristic inspired by natural selection). We show that the phenotypes resulting from the proposed trait heritability-optimized training differ from those of principal components in the following aspects: 1) higher trait heritability, 2) higher SNP heritability, and 3) identification of the same number of independent genetic loci with a smaller number of effective traits. Our results demonstrate that data-driven trait heritability-based optimization enables the automatic extraction of genetically relevant phenotypes, as shown by their increased power in genome-wide association scans.
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31
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Li Y, Xiong Z, Zhang M, Hysi PG, Qian Y, Adhikari K, Weng J, Wu S, Du S, Gonzalez-Jose R, Schuler-Faccini L, Bortolini MC, Acuna-Alonzo V, Canizales-Quinteros S, Gallo C, Poletti G, Bedoya G, Rothhammer F, Wang J, Tan J, Yuan Z, Jin L, Uitterlinden AG, Ghanbari M, Ikram MA, Nijsten T, Zhu X, Lei Z, Jia P, Ruiz-Linares A, Spector TD, Wang S, Kayser M, Liu F. Combined genome-wide association study of 136 quantitative ear morphology traits in multiple populations reveal 8 novel loci. PLoS Genet 2023; 19:e1010786. [PMID: 37459304 PMCID: PMC10351707 DOI: 10.1371/journal.pgen.1010786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 05/16/2023] [Indexed: 07/20/2023] Open
Abstract
Human ear morphology, a complex anatomical structure represented by a multidimensional set of correlated and heritable phenotypes, has a poorly understood genetic architecture. In this study, we quantitatively assessed 136 ear morphology traits using deep learning analysis of digital face images in 14,921 individuals from five different cohorts in Europe, Asia, and Latin America. Through GWAS meta-analysis and C-GWASs, a recently introduced method to effectively combine GWASs of many traits, we identified 16 genetic loci involved in various ear phenotypes, eight of which have not been previously associated with human ear features. Our findings suggest that ear morphology shares genetic determinants with other surface ectoderm-derived traits such as facial variation, mono eyebrow, and male pattern baldness. Our results enhance the genetic understanding of human ear morphology and shed light on the shared genetic contributors of different surface ectoderm-derived phenotypes. Additionally, gene editing experiments in mice have demonstrated that knocking out the newly ear-associated gene (Intu) and a previously ear-associated gene (Tbx15) causes deviating mouse ear morphology.
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Affiliation(s)
- Yi Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, China
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, China
| | - Ziyi Xiong
- Department of Genetic Identification, Erasmus MC, University Medical Center, the Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center, the Netherlands
| | - Manfei Zhang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, China
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, China
| | - Pirro G. Hysi
- Department of Twin Research and Genetic Epidemiology, King’s College London, United Kingdom
| | - Yu Qian
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, China
- Beijing No.8 High School, Beijing, China
| | - Kaustubh Adhikari
- Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, United Kingdom
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, United Kingdom
| | - Jun Weng
- Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China
| | - Sijie Wu
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, China
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, China
| | - Siyuan Du
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, China
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
- University of Chinese Academy of Sciences, China
| | - Rolando Gonzalez-Jose
- Instituto Patagonico de Ciencias Sociales y Humanas, Centro Nacional Patagonico, CONICET, Argentina
| | | | | | - Victor Acuna-Alonzo
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico
| | - Samuel Canizales-Quinteros
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Quimica, UNAM-Instituto Nacional de Medicina Genomica, Mexico
| | - Carla Gallo
- Laboratorios de Investigacion y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Peru
| | - Giovanni Poletti
- Laboratorios de Investigacion y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Peru
| | - Gabriel Bedoya
- GENMOL (Genetica Molecular), Universidad de Antioquia, Medellin, Colombia
| | | | - Jiucun Wang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, China
| | - Jingze Tan
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, China
| | - Ziyu Yuan
- Fudan-Taizhou Institute of Health Sciences, China
| | - Li Jin
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, China
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, China
- Fudan-Taizhou Institute of Health Sciences, China
| | - André G. Uitterlinden
- Department of Epidemiology, Erasmus MC, University Medical Center, the Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center, the Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC, University Medical Center, the Netherlands
| | - M. Arfan Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center, the Netherlands
| | - Tamar Nijsten
- Department of Dermatology, Erasmus MC, University Medical Center, the Netherlands
| | - Xiangyu Zhu
- Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, China
| | - Zhen Lei
- Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, China
| | - Peilin Jia
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, China
| | - Andres Ruiz-Linares
- Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, United Kingdom
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, China
- Aix-Marseille Universite, CNRS, EFS, ADES, France
| | - Timothy D. Spector
- Department of Twin Research and Genetic Epidemiology, King’s College London, United Kingdom
| | - Sijia Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, China
| | - Manfred Kayser
- Department of Genetic Identification, Erasmus MC, University Medical Center, the Netherlands
| | - Fan Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, China
- Department of Genetic Identification, Erasmus MC, University Medical Center, the Netherlands
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32
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Rajderkar SS, Paraiso K, Amaral ML, Kosicki M, Cook LE, Darbellay F, Spurrell CH, Osterwalder M, Zhu Y, Wu H, Afzal SY, Blow MJ, Kelman G, Barozzi I, Fukuda-Yuzawa Y, Akiyama JA, Afzal V, Tran S, Plajzer-Frick I, Novak CS, Kato M, Hunter RD, von Maydell K, Wang A, Lin L, Preissl S, Lisgo S, Ren B, Dickel DE, Pennacchio LA, Visel A. Cell Type- and Tissue-specific Enhancers in Craniofacial Development. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.26.546603. [PMID: 37425964 PMCID: PMC10327103 DOI: 10.1101/2023.06.26.546603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
The genetic basis of craniofacial birth defects and general variation in human facial shape remains poorly understood. Distant-acting transcriptional enhancers are a major category of non-coding genome function and have been shown to control the fine-tuned spatiotemporal expression of genes during critical stages of craniofacial development1-3. However, a lack of accurate maps of the genomic location and cell type-specific in vivo activities of all craniofacial enhancers prevents their systematic exploration in human genetics studies. Here, we combined histone modification and chromatin accessibility profiling from different stages of human craniofacial development with single-cell analyses of the developing mouse face to create a comprehensive catalogue of the regulatory landscape of facial development at tissue- and single cell-resolution. In total, we identified approximately 14,000 enhancers across seven developmental stages from weeks 4 through 8 of human embryonic face development. We used transgenic mouse reporter assays to determine the in vivo activity patterns of human face enhancers predicted from these data. Across 16 in vivo validated human enhancers, we observed a rich diversity of craniofacial subregions in which these enhancers are active in vivo. To annotate the cell type specificities of human-mouse conserved enhancers, we performed single-cell RNA-seq and single-nucleus ATAC-seq of mouse craniofacial tissues from embryonic days e11.5 to e15.5. By integrating these data across species, we find that the majority (56%) of human craniofacial enhancers are functionally conserved in mice, providing cell type- and embryonic stage-resolved predictions of their in vivo activity profiles. Using retrospective analysis of known craniofacial enhancers in combination with single cell-resolved transgenic reporter assays, we demonstrate the utility of these data for predicting the in vivo cell type specificity of enhancers. Taken together, our data provide an expansive resource for genetic and developmental studies of human craniofacial development.
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Affiliation(s)
- Sudha Sunil Rajderkar
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
| | - Kitt Paraiso
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
| | - Maria Luisa Amaral
- Bioinformatics and Systems Biology Graduate Program, University of California San Diego, La Jolla, CA, USA
| | - Michael Kosicki
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
| | - Laura E. Cook
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
| | - Fabrice Darbellay
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
- Department of Genetic Medicine and Development, Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland
| | - Cailyn H. Spurrell
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
| | - Marco Osterwalder
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
- Department for BioMedical Research, University of Bern, 3008 Bern, Switzerland
| | - Yiwen Zhu
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
| | - Han Wu
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
| | - Sarah Yasmeen Afzal
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
- Lucile Packard Children’s Hospital, Stanford University, Stanford, CA 94304
| | - Matthew J. Blow
- U.S. Department of Energy Joint Genome Institute, 1 Cyclotron Road, Berkeley, CA 94720, USA
| | - Guy Kelman
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
- The Jerusalem Center for Personalized Computational Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Iros Barozzi
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
- Center for Cancer Research, Medical University of Vienna, Borschkegasse 8a 1090, Vienna, Austria
- Department of Surgery and Cancer, Imperial College London, London, UK
| | - Yoko Fukuda-Yuzawa
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
- University Research Management Center, Tohoku University, Sendai, Miyagi, 980-8577, Japan
| | - Jennifer A. Akiyama
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
| | - Veena Afzal
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
| | - Stella Tran
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
| | - Ingrid Plajzer-Frick
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
| | - Catherine S. Novak
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
| | - Momoe Kato
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
| | - Riana D. Hunter
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
- UC San Francisco, Division of Experimental Medicine, 1001 Potrero Ave, San Francisco, CA 94110
| | - Kianna von Maydell
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
| | - Allen Wang
- Center for Epigenomics, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Lin Lin
- Center for Epigenomics, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Sebastian Preissl
- Center for Epigenomics, University of California San Diego School of Medicine, La Jolla, CA, USA
- Institute of Experimental and Clinical Pharmacology and Toxicology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Steven Lisgo
- Human Developmental Biology Resource, Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, NE1 3BZ, UK
- Newcastle University Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle, NE1 3BZ, UK
| | - Bing Ren
- Institute of Genome Medicine, Moores Cancer Center, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Diane E. Dickel
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
- Octant Inc., Emeryville, CA 94608, USA
| | - Len A. Pennacchio
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
- U.S. Department of Energy Joint Genome Institute, 1 Cyclotron Road, Berkeley, CA 94720, USA
- Comparative Biochemistry Program, University of California, Berkeley, CA 94720, USA
| | - Axel Visel
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
- U.S. Department of Energy Joint Genome Institute, 1 Cyclotron Road, Berkeley, CA 94720, USA
- School of Natural Sciences, University of California, Merced, Merced, California, USA
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van Meijeren-van Lunteren AW, Liu X, Veenman FCH, Grgic O, Dhamo B, van der Tas JT, Prijatelj V, Roshchupkin GV, Rivadeneira F, Wolvius EB, Kragt L. Oral and craniofacial research in the Generation R study: an executive summary. Clin Oral Investig 2023:10.1007/s00784-023-05076-1. [PMID: 37301790 DOI: 10.1007/s00784-023-05076-1] [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: 03/09/2022] [Accepted: 05/04/2023] [Indexed: 06/12/2023]
Abstract
OBJECTIVES Oral conditions are of high prevalence and chronic character within the general population. Identifying the risk factors and determinants of oral disease is important, not only to reduce the burden of oral diseases, but also to improve (equal access to) oral health care systems, and to develop effective oral health promotion programs. Longitudinal population-based (birth-)cohort studies are very suitable to study risk factors on common oral diseases and have the potential to emphasize the importance of a healthy start for oral health. In this paper, we provide an overview of the comprehensive oral and craniofacial dataset that has been collected in the Generation R study: a population-based prospective birth cohort in the Netherlands that was designed to identify causes of health from fetal life until adulthood. METHODS Within the multidisciplinary context of the Generation R study, oral and craniofacial data has been collected from the age of 3 years onwards, and continued at the age of six, nine, and thirteen. Data collection is continuing in 17-year-old participants. RESEARCH OUTCOMES In total, the cohort population comprised 9749 children at birth, and 7405 eligible participants at the age of seventeen. Based on questionnaires, the dataset contains information on oral hygiene, dental visits, oral habits, oral health-related quality of life, orthodontic treatment, and obstructive sleep apnea. Based on direct measurements, the dataset contains information on dental caries, developmental defects of enamel, objective orthodontic treatment need, dental development, craniofacial characteristics, mandibular cortical thickness, and 3D facial measurements. CONCLUSIONS Several research lines have been set up using the oral and craniofacial data linked with the extensive data collection that exists within the Generation R study. CLINICAL RELEVANCE Being embedded in a multidisciplinary and longitudinal birth cohort study allows researchers to study several determinants of oral and craniofacial health, and to provide answers and insight into unknown etiologies and oral health problems in the general population.
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Affiliation(s)
- Agatha W van Meijeren-van Lunteren
- Department of Oral & Maxillofacial Surgery, Special Dental Care and Orthodontics, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
- The Generation R Study Group, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
| | - Xianjing Liu
- Department of Oral & Maxillofacial Surgery, Special Dental Care and Orthodontics, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
- The Generation R Study Group, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
| | - Francien C H Veenman
- Department of Oral & Maxillofacial Surgery, Special Dental Care and Orthodontics, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
- The Generation R Study Group, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
| | - Olja Grgic
- Department of Oral & Maxillofacial Surgery, Special Dental Care and Orthodontics, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
- The Generation R Study Group, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
| | - Brunilda Dhamo
- Department of Oral & Maxillofacial Surgery, Special Dental Care and Orthodontics, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
- The Generation R Study Group, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
| | - Justin T van der Tas
- Department of Oral & Maxillofacial Surgery, Special Dental Care and Orthodontics, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
- The Generation R Study Group, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
| | - Vid Prijatelj
- Department of Oral & Maxillofacial Surgery, Special Dental Care and Orthodontics, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
- The Generation R Study Group, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
| | - Gennady V Roshchupkin
- The Generation R Study Group, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
| | - Fernando Rivadeneira
- Department of Oral & Maxillofacial Surgery, Special Dental Care and Orthodontics, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
- The Generation R Study Group, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
| | - Eppo B Wolvius
- Department of Oral & Maxillofacial Surgery, Special Dental Care and Orthodontics, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
- The Generation R Study Group, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
| | - Lea Kragt
- Department of Oral & Maxillofacial Surgery, Special Dental Care and Orthodontics, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, the Netherlands.
- The Generation R Study Group, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, the Netherlands.
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Kim S, Morgunova E, Naqvi S, Bader M, Koska M, Popov A, Luong C, Pogson A, Claes P, Taipale J, Wysocka J. DNA-guided transcription factor cooperativity shapes face and limb mesenchyme. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.29.541540. [PMID: 37398193 PMCID: PMC10312427 DOI: 10.1101/2023.05.29.541540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Transcription factors (TFs) can define distinct cellular identities despite nearly identical DNA-binding specificities. One mechanism for achieving regulatory specificity is DNA-guided TF cooperativity. Although in vitro studies suggest it may be common, examples of such cooperativity remain scarce in cellular contexts. Here, we demonstrate how 'Coordinator', a long DNA motif comprised of common motifs bound by many basic helix-loop-helix (bHLH) and homeodomain (HD) TFs, uniquely defines regulatory regions of embryonic face and limb mesenchyme. Coordinator guides cooperative and selective binding between the bHLH family mesenchymal regulator TWIST1 and a collective of HD factors associated with regional identities in the face and limb. TWIST1 is required for HD binding and open chromatin at Coordinator sites, while HD factors stabilize TWIST1 occupancy at Coordinator and titrate it away from HD-independent sites. This cooperativity results in shared regulation of genes involved in cell-type and positional identities, and ultimately shapes facial morphology and evolution.
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Affiliation(s)
- Seungsoo Kim
- Department of Chemical and Systems Biology, Stanford University, Stanford, CA 94305
- Department of Developmental Biology, Stanford University, Stanford, CA 94305
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA 94305
- Howard Hughes Medical Institute, Stanford, CA 94305
| | - Ekaterina Morgunova
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Solna, Sweden
| | - Sahin Naqvi
- Department of Chemical and Systems Biology, Stanford University, Stanford, CA 94305
- Department of Developmental Biology, Stanford University, Stanford, CA 94305
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA 94305
- Department of Genetics, Stanford University, Stanford, CA 94305
| | - Maram Bader
- Department of Chemical and Systems Biology, Stanford University, Stanford, CA 94305
- Department of Developmental Biology, Stanford University, Stanford, CA 94305
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA 94305
| | - Mervenaz Koska
- Department of Developmental Biology, Stanford University, Stanford, CA 94305
| | | | - Christy Luong
- Department of Chemical and Systems Biology, Stanford University, Stanford, CA 94305
| | - Angela Pogson
- Department of Developmental Biology, Stanford University, Stanford, CA 94305
| | - Peter Claes
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, UZ Leuven, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Jussi Taipale
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Solna, Sweden
- Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom
- Applied Tumor Genomics Program, University of Helsinki, Helsinki, Finland
| | - Joanna Wysocka
- Department of Chemical and Systems Biology, Stanford University, Stanford, CA 94305
- Department of Developmental Biology, Stanford University, Stanford, CA 94305
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA 94305
- Howard Hughes Medical Institute, Stanford, CA 94305
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35
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Li Q, Chen J, Faux P, Delgado ME, Bonfante B, Fuentes-Guajardo M, Mendoza-Revilla J, Chacón-Duque JC, Hurtado M, Villegas V, Granja V, Jaramillo C, Arias W, Barquera R, Everardo-Martínez P, Sánchez-Quinto M, Gómez-Valdés J, Villamil-Ramírez H, Silva de Cerqueira CC, Hünemeier T, Ramallo V, Wu S, Du S, Giardina A, Paria SS, Khokan MR, Gonzalez-José R, Schüler-Faccini L, Bortolini MC, Acuña-Alonzo V, Canizales-Quinteros S, Gallo C, Poletti G, Rojas W, Rothhammer F, Navarro N, Wang S, Adhikari K, Ruiz-Linares A. Automatic landmarking identifies new loci associated with face morphology and implicates Neanderthal introgression in human nasal shape. Commun Biol 2023; 6:481. [PMID: 37156940 PMCID: PMC10167347 DOI: 10.1038/s42003-023-04838-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 04/12/2023] [Indexed: 05/10/2023] Open
Abstract
We report a genome-wide association study of facial features in >6000 Latin Americans based on automatic landmarking of 2D portraits and testing for association with inter-landmark distances. We detected significant associations (P-value <5 × 10-8) at 42 genome regions, nine of which have been previously reported. In follow-up analyses, 26 of the 33 novel regions replicate in East Asians, Europeans, or Africans, and one mouse homologous region influences craniofacial morphology in mice. The novel region in 1q32.3 shows introgression from Neanderthals and we find that the introgressed tract increases nasal height (consistent with the differentiation between Neanderthals and modern humans). Novel regions include candidate genes and genome regulatory elements previously implicated in craniofacial development, and show preferential transcription in cranial neural crest cells. The automated approach used here should simplify the collection of large study samples from across the world, facilitating a cosmopolitan characterization of the genetics of facial features.
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Affiliation(s)
- Qing Li
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, 200438, China
| | - Jieyi Chen
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, 200438, China
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Pierre Faux
- Aix-Marseille Université, CNRS, EFS, ADES, Marseille, 13005, France
| | - Miguel Eduardo Delgado
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, 200438, China
- División Antropología, Facultad de Ciencias Naturales y Museo, Universidad Nacional de La Plata, La Plata, República Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas, CONICET, Buenos Aires, República Argentina
| | - Betty Bonfante
- Aix-Marseille Université, CNRS, EFS, ADES, Marseille, 13005, France
| | - Macarena Fuentes-Guajardo
- Departamento de Tecnología Médica, Facultad de Ciencias de la Salud, Universidad de Tarapacá, Arica, 1000000, Chile
| | - Javier Mendoza-Revilla
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, 31, Perú
- Unit of Human Evolutionary Genetics, Institut Pasteur, Paris, 75015, France
| | - J Camilo Chacón-Duque
- Division of Vertebrates and Anthropology, Department of Earth Sciences, Natural History Museum, London, SW7 5BD, UK
| | - Malena Hurtado
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, 31, Perú
| | - Valeria Villegas
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, 31, Perú
| | - Vanessa Granja
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, 31, Perú
| | - Claudia Jaramillo
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín, 5001000, Colombia
| | - William Arias
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín, 5001000, Colombia
| | - Rodrigo Barquera
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, 14050, Mexico, 6600, Mexico
- Department of Archaeogenetics, Max Planck Institute for the Science of Human History (MPI-SHH), Jena, 07745, Germany
| | - Paola Everardo-Martínez
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, 14050, Mexico, 6600, Mexico
| | - Mirsha Sánchez-Quinto
- Forensic Science, Faculty of Medicine, UNAM (Universidad Nacional Autónoma de México), Mexico City, 06320, Mexico
| | - Jorge Gómez-Valdés
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, 14050, Mexico, 6600, Mexico
| | - Hugo Villamil-Ramírez
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, Mexico City, 4510, Mexico
| | | | - Tábita Hünemeier
- Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, São Paulo, SP, 05508-090, Brazil
| | - Virginia Ramallo
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, 90040-060, Brazil
- Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, Puerto Madryn, U9129ACD, Argentina
| | - Sijie Wu
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, 200438, China
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Siyuan Du
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Andrea Giardina
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, MK7 6AA, United Kingdom
| | - Soumya Subhra Paria
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, MK7 6AA, United Kingdom
| | - Mahfuzur Rahman Khokan
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, MK7 6AA, United Kingdom
| | - Rolando Gonzalez-José
- Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, Puerto Madryn, U9129ACD, Argentina
| | - Lavinia Schüler-Faccini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, 90040-060, Brazil
| | - Maria-Cátira Bortolini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, 90040-060, Brazil
| | - Victor Acuña-Alonzo
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, 14050, Mexico, 6600, Mexico
| | - Samuel Canizales-Quinteros
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, Mexico City, 4510, Mexico
| | - Carla Gallo
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, 31, Perú
| | - Giovanni Poletti
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, 31, Perú
| | - Winston Rojas
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín, 5001000, Colombia
| | - Francisco Rothhammer
- Instituto de Alta Investigación, Universidad de Tarapacá, Arica, Arica, 1000000, Chile
| | - Nicolas Navarro
- Biogéosciences, UMR 6282 CNRS, Université de Bourgogne, Dijon, 21000, France
- EPHE, PSL University, Paris, 75014, France
| | - Sijia Wang
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, 200438, China
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Kaustubh Adhikari
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, MK7 6AA, United Kingdom.
- Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London, WC1E 6BT, UK.
| | - Andrés Ruiz-Linares
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, 200438, China.
- Aix-Marseille Université, CNRS, EFS, ADES, Marseille, 13005, France.
- Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London, WC1E 6BT, UK.
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Li Z, Melograna F, Hoskens H, Duroux D, Marazita ML, Walsh S, Weinberg SM, Shriver MD, Müller-Myhsok B, Claes P, Van Steen K. netMUG: a novel network-guided multi-view clustering workflow for dissecting genetic and facial heterogeneity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.04.539350. [PMID: 37205363 PMCID: PMC10187283 DOI: 10.1101/2023.05.04.539350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Multi-view data offer advantages over single-view data for characterizing individuals, which is crucial in precision medicine toward personalized prevention, diagnosis, or treatment follow-up. Here, we develop a network-guided multi-view clustering framework named netMUG to identify actionable subgroups of individuals. This pipeline first adopts sparse multiple canonical correlation analysis to select multi-view features possibly informed by extraneous data, which are then used to construct individual-specific networks (ISNs). Finally, the individual subtypes are automatically derived by hierarchical clustering on these network representations. We applied netMUG to a dataset containing genomic data and facial images to obtain BMI-informed multi-view strata and showed how it could be used for a refined obesity characterization. Benchmark analysis of netMUG on synthetic data with known strata of individuals indicated its superior performance compared with both baseline and benchmark methods for multi-view clustering. In addition, the real-data analysis revealed subgroups strongly linked to BMI and genetic and facial determinants of these classes. NetMUG provides a powerful strategy, exploiting individual-specific networks to identify meaningful and actionable strata. Moreover, the implementation is easy to generalize to accommodate heterogeneous data sources or highlight data structures.
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Affiliation(s)
- Zuqi Li
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
| | | | - Hanne Hoskens
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
| | - Diane Duroux
- GIGA-R Medical Genomics, University of Liège, Liège, Belgium
| | - Mary L. Marazita
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of Pittsburgh, Pittsburgh, PA 15219, USA
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Susan Walsh
- Department of Biology, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202, USA
| | - Seth M. Weinberg
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of Pittsburgh, Pittsburgh, PA 15219, USA
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Mark D. Shriver
- Department of Anthropology, Pennsylvania State University, State College, PA 16801, USA
| | | | - Peter Claes
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
- Murdoch Children’s Research Institute, Melbourne, Victoria, Australia
| | - Kristel Van Steen
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- GIGA-R Medical Genomics, University of Liège, Liège, Belgium
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37
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Naqvi S, Kim S, Hoskens H, Matthews HS, Spritz RA, Klein OD, Hallgrímsson B, Swigut T, Claes P, Pritchard JK, Wysocka J. Precise modulation of transcription factor levels identifies features underlying dosage sensitivity. Nat Genet 2023; 55:841-851. [PMID: 37024583 PMCID: PMC10181932 DOI: 10.1038/s41588-023-01366-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Accepted: 03/07/2023] [Indexed: 04/08/2023]
Abstract
Transcriptional regulation exhibits extensive robustness, but human genetics indicates sensitivity to transcription factor (TF) dosage. Reconciling such observations requires quantitative studies of TF dosage effects at trait-relevant ranges, largely lacking so far. TFs play central roles in both normal-range and disease-associated variation in craniofacial morphology; we therefore developed an approach to precisely modulate TF levels in human facial progenitor cells and applied it to SOX9, a TF associated with craniofacial variation and disease (Pierre Robin sequence (PRS)). Most SOX9-dependent regulatory elements (REs) are buffered against small decreases in SOX9 dosage, but REs directly and primarily regulated by SOX9 show heightened sensitivity to SOX9 dosage; these RE responses partially predict gene expression responses. Sensitive REs and genes preferentially affect functional chondrogenesis and PRS-like craniofacial shape variation. We propose that such REs and genes underlie the sensitivity of specific phenotypes to TF dosage, while buffering of other genes leads to robust, nonlinear dosage-to-phenotype relationships.
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Affiliation(s)
- Sahin Naqvi
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA
- Departments of Genetics and Biology, Stanford University, Stanford, CA, USA
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - Seungsoo Kim
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Hanne Hoskens
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Cell Biology & Anatomy, Alberta Children's Hospital Research Institute and McCaig Bone and Joint Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Harold S Matthews
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
| | - Richard A Spritz
- Human Medical Genetics and Genomics Program and Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO, USA
| | - Ophir D Klein
- Departments of Orofacial Sciences and Pediatrics, Program in Craniofacial Biology, and Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Department of Pediatrics, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Benedikt Hallgrímsson
- Department of Cell Biology & Anatomy, Alberta Children's Hospital Research Institute and McCaig Bone and Joint Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Tomek Swigut
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - Peter Claes
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
- Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | | | - Joanna Wysocka
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA.
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA, USA.
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Kayser M, Branicki W, Parson W, Phillips C. Recent advances in Forensic DNA Phenotyping of appearance, ancestry and age. Forensic Sci Int Genet 2023; 65:102870. [PMID: 37084623 DOI: 10.1016/j.fsigen.2023.102870] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 04/04/2023] [Indexed: 04/09/2023]
Abstract
Forensic DNA Phenotyping (FDP) comprises the prediction of a person's externally visible characteristics regarding appearance, biogeographic ancestry and age from DNA of crime scene samples, to provide investigative leads to help find unknown perpetrators that cannot be identified with forensic STR-profiling. In recent years, FDP has advanced considerably in all of its three components, which we summarize in this review article. Appearance prediction from DNA has broadened beyond eye, hair and skin color to additionally comprise other traits such as eyebrow color, freckles, hair structure, hair loss in men, and tall stature. Biogeographic ancestry inference from DNA has progressed from continental ancestry to sub-continental ancestry detection and the resolving of co-ancestry patterns in genetically admixed individuals. Age estimation from DNA has widened beyond blood to more somatic tissues such as saliva and bones as well as new markers and tools for semen. Technological progress has allowed forensically suitable DNA technology with largely increased multiplex capacity for the simultaneous analysis of hundreds of DNA predictors with targeted massively parallel sequencing (MPS). Forensically validated MPS-based FDP tools for predicting from crime scene DNA i) several appearance traits, ii) multi-regional ancestry, iii) several appearance traits together with multi-regional ancestry, and iv) age from different tissue types, are already available. Despite recent advances that will likely increase the impact of FDP in criminal casework in the near future, moving reliable appearance, ancestry and age prediction from crime scene DNA to the level of detail and accuracy police investigators may desire, requires further intensified scientific research together with technical developments and forensic validations as well as the necessary funding.
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Affiliation(s)
- Manfred Kayser
- Department of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.
| | - Wojciech Branicki
- Institute of Zoology and Biomedical Research, Jagiellonian University, Kraków, Poland,; Institute of Forensic Research, Kraków, Poland
| | - Walther Parson
- Institute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria; Forensic Science Program, The Pennsylvania State University, PA, USA
| | - Christopher Phillips
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Spain
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Matthews HS, Mahdi S, Penington AJ, Marazita ML, Shaffer JR, Walsh S, Shriver MD, Claes P, Weinberg SM. Using data-driven phenotyping to investigate the impact of sex on 3D human facial surface morphology. J Anat 2023. [PMID: 36943032 DOI: 10.1111/joa.13866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 02/28/2023] [Accepted: 03/06/2023] [Indexed: 03/23/2023] Open
Abstract
The effects of sex on human facial morphology have been widely documented. Because sexual dimorphism is relevant to a variety of scientific and applied disciplines, it is imperative to have a complete and accurate account of how and where male and female faces differ. We apply a comprehensive facial phenotyping strategy to a large set of existing 3D facial surface images. We investigate facial sexual dimorphism in terms of size, shape, and shape variance. We also assess the ability to correctly assign sex based on shape, both for the whole face and for subregions. We applied a predefined data-driven segmentation to partition the 3D facial surfaces of 2446 adults into 63 hierarchically linked regions, ranging from global (whole face) to highly localized subparts. Each facial region was then analyzed with spatially dense geometric morphometrics. To describe the major modes of shape variation, principal components analysis was applied to the Procrustes aligned 3D points comprising each of the 63 facial regions. Both nonparametric and permutation-based statistics were then used to quantify the facial size and shape differences and visualizations were generated. Males were significantly larger than females for all 63 facial regions. Statistically significant sex differences in shape were also seen in all regions and the effects tended to be more pronounced for the upper lip and forehead, with more subtle changes emerging as the facial regions became more granular. Males also showed greater levels of shape variance, with the largest effect observed for the central forehead. Classification accuracy was highest for the full face (97%), while most facial regions showed an accuracy of 75% or greater. In summary, sex differences in both size and shape were present across every part of the face. By breaking the face into subparts, some shape differences emerged that were not apparent when analyzing the face as a whole. The increase in facial shape variance suggests possible evolutionary origins and may offer insights for understanding congenital facial malformations. Our classification results indicate that a high degree of accuracy is possible with only parts of the face, which may have implications for biometrics applications.
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Affiliation(s)
- Harold S Matthews
- Department of Human Genetics, KU Leuven, 3000, Leuven, Belgium
- Medical Imaging Research Center, UZ Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Soha Mahdi
- Medical Imaging Research Center, UZ Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Anthony J Penington
- Facial Sciences Research Group, Murdoch Children's Research Institute, Parkville, 3052, Australia
- Department of Plastic and Maxillofacial Surgery, Royal Children's Hospital, Melbourne, 3052, Australia
- Department of Pediatrics, University of Melbourne, Melbourne, 3052, Australia
| | - Mary L Marazita
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, 15219, USA
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA
| | - John R Shaffer
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, 15219, USA
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA
| | - Susan Walsh
- Department of Biology, Indiana University Purdue University Indianapolis, Indianapolis, Indiana, 46202, USA
| | - Mark D Shriver
- Department of Anthropology, Pennsylvania State University, State College, Pennsylvania, 16802, USA
| | - Peter Claes
- Department of Human Genetics, KU Leuven, 3000, Leuven, Belgium
- Medical Imaging Research Center, UZ Leuven, Herestraat 49, 3000, Leuven, Belgium
- Facial Sciences Research Group, Murdoch Children's Research Institute, Parkville, 3052, Australia
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, 3000, Leuven, Belgium
| | - Seth M Weinberg
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, 15219, USA
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA
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Collier AE, Piekos SN, Liu A, Pattison JM, Felix F, Bailetti AA, Sedov E, Gaddam S, Zhen H, Oro AE. GRHL2 and AP2a coordinate early surface ectoderm lineage commitment during development. iScience 2023; 26:106125. [PMID: 36843855 PMCID: PMC9950457 DOI: 10.1016/j.isci.2023.106125] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Revised: 05/09/2022] [Accepted: 01/30/2023] [Indexed: 02/05/2023] Open
Abstract
Ectodermal dysplasias including skin abnormalities and cleft lip/palate result from improper surface ectoderm (SE) patterning. However, the connection between SE gene regulatory networks and disease remains poorly understood. Here, we dissect human SE differentiation with multiomics and establish GRHL2 as a key mediator of early SE commitment, which acts by skewing cell fate away from the neural lineage. GRHL2 and master SE regulator AP2a balance early cell fate output, with GRHL2 facilitating AP2a binding to SE loci. In turn, AP2a restricts GRHL2 DNA binding away from de novo chromatin contacts. Integration of these regulatory sites with ectodermal dysplasia-associated genomic variants annotated within the Biomedical Data Commons identifies 55 loci previously implicated in craniofacial disorders. These include ABCA4/ARHGAP29 and NOG regulatory regions where disease-linked variants directly affect GRHL2/AP2a binding and gene transcription. These studies elucidate the logic underlying SE commitment and deepen our understanding of human oligogenic disease pathogenesis.
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Affiliation(s)
- Ann E. Collier
- Program in Epithelial Biology, Stanford University, Stanford, CA USA
| | - Samantha N. Piekos
- Stem Cell Biology and Regenerative Medicine Graduate Program, Stanford University, Stanford, CA USA
| | - Angela Liu
- Program in Epithelial Biology, Stanford University, Stanford, CA USA
- Stem Cell Biology and Regenerative Medicine Graduate Program, Stanford University, Stanford, CA USA
| | | | - Franco Felix
- Program in Epithelial Biology, Stanford University, Stanford, CA USA
- Stem Cell Biology and Regenerative Medicine Graduate Program, Stanford University, Stanford, CA USA
| | | | - Egor Sedov
- Program in Epithelial Biology, Stanford University, Stanford, CA USA
| | - Sadhana Gaddam
- Program in Epithelial Biology, Stanford University, Stanford, CA USA
| | - Hanson Zhen
- Program in Epithelial Biology, Stanford University, Stanford, CA USA
| | - Anthony E. Oro
- Program in Epithelial Biology, Stanford University, Stanford, CA USA
- Stem Cell Biology and Regenerative Medicine Graduate Program, Stanford University, Stanford, CA USA
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Wilke F, Herrick N, Matthews H, Hoskens H, Singh S, Shaffer JR, Weinberg SM, Shriver MD, Claes P, Walsh S. Exploring regional aspects of 3D facial variation within European individuals. Sci Rep 2023; 13:3708. [PMID: 36879022 PMCID: PMC9988837 DOI: 10.1038/s41598-023-30855-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 03/02/2023] [Indexed: 03/08/2023] Open
Abstract
Facial ancestry can be described as variation that exists in facial features that are shared amongst members of a population due to environmental and genetic effects. Even within Europe, faces vary among subregions and may lead to confounding in genetic association studies if unaccounted for. Genetic studies use genetic principal components (PCs) to describe facial ancestry to circumvent this issue. Yet the phenotypic effect of these genetic PCs on the face has yet to be described, and phenotype-based alternatives compared. In anthropological studies, consensus faces are utilized as they depict a phenotypic, not genetic, ancestry effect. In this study, we explored the effects of regional differences on facial ancestry in 744 Europeans using genetic and anthropological approaches. Both showed similar ancestry effects between subgroups, localized mainly to the forehead, nose, and chin. Consensus faces explained the variation seen in only the first three genetic PCs, differing more in magnitude than shape change. Here we show only minor differences between the two methods and discuss a combined approach as a possible alternative for facial scan correction that is less cohort dependent, more replicable, non-linear, and can be made open access for use across research groups, enhancing future studies in this field.
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Affiliation(s)
- Franziska Wilke
- Department of Biology, Indiana University-Purdue University Indianapolis, 723 W Michigan St, Indianapolis, IN, 46202, USA
| | - Noah Herrick
- Department of Biology, Indiana University-Purdue University Indianapolis, 723 W Michigan St, Indianapolis, IN, 46202, USA
| | - Harold Matthews
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Murdoch Children's Research Institute, Melbourne, VIC, Australia
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
| | - Hanne Hoskens
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
| | - Sylvia Singh
- Department of Biology, Indiana University-Purdue University Indianapolis, 723 W Michigan St, Indianapolis, IN, 46202, USA
| | - John R Shaffer
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Seth M Weinberg
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Anthropology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mark D Shriver
- Department of Anthropology, The Pennsylvania State University, University Park, PA, USA
| | - Peter Claes
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Murdoch Children's Research Institute, Melbourne, VIC, Australia
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
| | - Susan Walsh
- Department of Biology, Indiana University-Purdue University Indianapolis, 723 W Michigan St, Indianapolis, IN, 46202, USA.
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Cheng H, Zhang Z, Wen J, Lenstra JA, Heller R, Cai Y, Guo Y, Li M, Li R, Li W, He S, Wang J, Shao J, Song Y, Zhang L, Billah M, Wang X, Liu M, Jiang Y. Long divergent haplotypes introgressed from wild sheep are associated with distinct morphological and adaptive characteristics in domestic sheep. PLoS Genet 2023; 19:e1010615. [PMID: 36821549 PMCID: PMC9949681 DOI: 10.1371/journal.pgen.1010615] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 01/13/2023] [Indexed: 02/24/2023] Open
Abstract
The worldwide sheep population comprises more than 1000 breeds. Together, these exhibit a considerable morphological diversity, which has not been extensively investigated at the molecular level. Here, we analyze whole-genome sequencing individuals of 1,098 domestic sheep from 154 breeds, and 69 wild sheep from seven Ovis species. On average, we detected 6.8%, 1.0% and 0.2% introgressed sequence in domestic sheep originating from Iranian mouflon, urial and argali, respectively, with rare introgressions from other wild species. Interestingly, several introgressed haplotypes contributed to the morphological differentiations across sheep breeds, such as a RXFP2 haplotype from Iranian mouflon conferring the spiral horn trait, a MSRB3 haplotype from argali strongly associated with ear morphology, and a VPS13B haplotype probably originating from urial and mouflon possibly associated with facial traits. Our results reveal that introgression events from wild Ovis species contributed to the high rate of morphological differentiation in sheep breeds, but also to individual variation within breeds. We propose that long divergent haplotypes are a ubiquitous source of phenotypic variation that allows adaptation to a variable environment, and that these remain intact in the receiving population probably due to reduced recombination.
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Affiliation(s)
- Hong Cheng
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Zhuangbiao Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Jiayue Wen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Johannes A. Lenstra
- Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Rasmus Heller
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Yudong Cai
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Yingwei Guo
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Ming Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Ran Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Wenrong Li
- Key Laboratory of Ruminant Genetics, Breeding & Reproduction, Ministry of Agriculture, China
- Key Laboratory of Animal Biotechnology of Xinjiang, Institute of Biotechnology, Xinjiang Academy of Animal Science, Urumqi, Xinjiang, China
| | - Sangang He
- Key Laboratory of Ruminant Genetics, Breeding & Reproduction, Ministry of Agriculture, China
- Key Laboratory of Animal Biotechnology of Xinjiang, Institute of Biotechnology, Xinjiang Academy of Animal Science, Urumqi, Xinjiang, China
| | - Jintao Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Junjie Shao
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Yuxuan Song
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Lei Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Masum Billah
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Xihong Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Mingjun Liu
- Key Laboratory of Ruminant Genetics, Breeding & Reproduction, Ministry of Agriculture, China
- Key Laboratory of Animal Biotechnology of Xinjiang, Institute of Biotechnology, Xinjiang Academy of Animal Science, Urumqi, Xinjiang, China
- * E-mail: (ML); (YJ)
| | - Yu Jiang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
- * E-mail: (ML); (YJ)
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43
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Advancement in Human Face Prediction Using DNA. Genes (Basel) 2023; 14:genes14010136. [PMID: 36672878 PMCID: PMC9858985 DOI: 10.3390/genes14010136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 12/15/2022] [Accepted: 12/21/2022] [Indexed: 01/05/2023] Open
Abstract
The rapid improvements in identifying the genetic factors contributing to facial morphology have enabled the early identification of craniofacial syndromes. Similarly, this technology can be vital in forensic cases involving human identification from biological traces or human remains, especially when reference samples are not available in the deoxyribose nucleic acid (DNA) database. This review summarizes the currently used methods for predicting human phenotypes such as age, ancestry, pigmentation, and facial features based on genetic variations. To identify the facial features affected by DNA, various two-dimensional (2D)- and three-dimensional (3D)-scanning techniques and analysis tools are reviewed. A comparison between the scanning technologies is also presented in this review. Face-landmarking techniques and face-phenotyping algorithms are discussed in chronological order. Then, the latest approaches in genetic to 3D face shape analysis are emphasized. A systematic review of the current markers that passed the threshold of a genome-wide association (GWAS) of single nucleotide polymorphism (SNP)-face traits from the GWAS Catalog is also provided using the preferred reporting items for systematic reviews and meta-analyses (PRISMA), approach. Finally, the current challenges in forensic DNA phenotyping are analyzed and discussed.
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44
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Xiong Z, Gao X, Chen Y, Feng Z, Pan S, Lu H, Uitterlinden AG, Nijsten T, Ikram A, Rivadeneira F, Ghanbari M, Wang Y, Kayser M, Liu F. Combining genome-wide association studies highlight novel loci involved in human facial variation. Nat Commun 2022; 13:7832. [PMID: 36539420 PMCID: PMC9767941 DOI: 10.1038/s41467-022-35328-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 11/28/2022] [Indexed: 12/24/2022] Open
Abstract
Standard genome-wide association studies (GWASs) rely on analyzing a single trait at a time. However, many human phenotypes are complex and composed by multiple correlated traits. Here we introduce C-GWAS, a method for combining GWAS summary statistics of multiple potentially correlated traits. Extensive computer simulations demonstrated increased statistical power of C-GWAS compared to the minimal p-values of multiple single-trait GWASs (MinGWAS) and the current state-of-the-art method for combining single-trait GWASs (MTAG). Applying C-GWAS to a meta-analysis dataset of 78 single trait facial GWASs from 10,115 Europeans identified 56 study-wide suggestively significant loci with multi-trait effects on facial morphology of which 17 are novel loci. Using data from additional 13,622 European and Asian samples, 46 (82%) loci, including 9 (53%) novel loci, were replicated at nominal significance with consistent allele effects. Functional analyses further strengthen the reliability of our C-GWAS findings. Our study introduces the C-GWAS method and makes it available as computationally efficient open-source R package for widespread future use. Our work also provides insights into the genetic architecture of human facial appearance.
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Affiliation(s)
- Ziyi Xiong
- grid.5645.2000000040459992XDepartment of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Xingjian Gao
- grid.9227.e0000000119573309CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China ,grid.440259.e0000 0001 0115 7868National Clinical Research Center of Kidney Diseases, Jinling Hospital, Nanjing, Jiangsu China
| | - Yan Chen
- grid.5645.2000000040459992XDepartment of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.9227.e0000000119573309CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Zhanying Feng
- grid.9227.e0000000119573309CEMS, NCMIS, HCMS, MDIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China
| | - Siyu Pan
- grid.9227.e0000000119573309CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Haojie Lu
- grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.5645.2000000040459992XDepartment of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Andre G. Uitterlinden
- grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.5645.2000000040459992XDepartment of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Tamar Nijsten
- grid.5645.2000000040459992XDepartment of Dermatology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Arfan Ikram
- grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Fernando Rivadeneira
- grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.5645.2000000040459992XDepartment of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.5645.2000000040459992XDepartment of Oral and Maxillofacial Surgery, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Mohsen Ghanbari
- grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Yong Wang
- grid.9227.e0000000119573309CEMS, NCMIS, HCMS, MDIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China
| | - Manfred Kayser
- grid.5645.2000000040459992XDepartment of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Fan Liu
- grid.5645.2000000040459992XDepartment of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.9227.e0000000119573309CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
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Bastide S, Chomsky E, Saudemont B, Loe-Mie Y, Schmutz S, Novault S, Marlow H, Tanay A, Spitz F. TATTOO-seq delineates spatial and cell type-specific regulatory programs in the developing limb. SCIENCE ADVANCES 2022; 8:eadd0695. [PMID: 36516250 PMCID: PMC9750149 DOI: 10.1126/sciadv.add0695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 11/14/2022] [Indexed: 06/17/2023]
Abstract
The coordinated differentiation of progenitor cells into specialized cell types and their spatial organization into distinct domains is central to embryogenesis. Here, we developed and applied an unbiased spatially resolved single-cell transcriptomics method to identify the genetic programs underlying the emergence of specialized cell types during mouse limb development and their spatial integration. We identify multiple transcription factors whose expression patterns are predominantly associated with cell type specification or spatial position, suggesting two parallel yet highly interconnected regulatory systems. We demonstrate that the embryonic limb undergoes a complex multiscale reorganization upon perturbation of one of its spatial organizing centers, including the loss of specific cell populations, alterations of preexisting cell states' molecular identities, and changes in their relative spatial distribution. Our study shows how multidimensional single-cell, spatially resolved molecular atlases can allow the deconvolution of spatial identity and cell fate and reveal the interconnected genetic networks that regulate organogenesis and its reorganization upon genetic alterations.
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Affiliation(s)
- Sébastien Bastide
- (Epi)genomics of Animal Development, Department of Developmental and Stem Cell Biology, Institut Pasteur, Paris, France
- École Doctorale “Complexité du Vivant”, Sorbonne Université, 75005 Paris, France
- Department of Human Genetics, The University of Chicago, Chicago, IL, USA
| | - Elad Chomsky
- Department of Computer Science and Applied Mathematics, Weizmann Institute, Rehovot, Israel
- Department of Biological Regulation, Weizmann Institute, Rehovot, Israel
| | - Baptiste Saudemont
- (Epi)genomics of Animal Development, Department of Developmental and Stem Cell Biology, Institut Pasteur, Paris, France
| | - Yann Loe-Mie
- (Epi)genomics of Animal Development, Department of Developmental and Stem Cell Biology, Institut Pasteur, Paris, France
- Hub de Bioinformatique et Biostatistique, Département Biologie Computationnelle, Institut Pasteur, Paris, France
| | - Sandrine Schmutz
- Cytometry and Biomarkers, Center for Technological Resources and Research, Institut Pasteur, Paris, France
| | - Sophie Novault
- Cytometry and Biomarkers, Center for Technological Resources and Research, Institut Pasteur, Paris, France
| | - Heather Marlow
- (Epi)genomics of Animal Development, Department of Developmental and Stem Cell Biology, Institut Pasteur, Paris, France
- Department of Organismal Biology and Anatomy, The University of Chicago, Chicago, IL, USA
| | - Amos Tanay
- Department of Computer Science and Applied Mathematics, Weizmann Institute, Rehovot, Israel
| | - François Spitz
- (Epi)genomics of Animal Development, Department of Developmental and Stem Cell Biology, Institut Pasteur, Paris, France
- Department of Human Genetics, The University of Chicago, Chicago, IL, USA
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Chen Q, Dai J, Bian Q. Integration of 3D genome topology and local chromatin features uncovers enhancers underlying craniofacial-specific cartilage defects. SCIENCE ADVANCES 2022; 8:eabo3648. [PMID: 36417512 PMCID: PMC9683718 DOI: 10.1126/sciadv.abo3648] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Aberrations in tissue-specific enhancers underlie many developmental defects. Disrupting a noncoding region distal from the human SOX9 gene causes the Pierre Robin sequence (PRS) characterized by the undersized lower jaw. Such a craniofacial-specific defect has been previously linked to enhancers transiently active in cranial neural crest cells (CNCCs). We demonstrate that the PRS region also strongly regulates Sox9 in CNCC-derived Meckel's cartilage (MC), but not in limb cartilages, even after decommissioning of CNCC enhancers. Such an MC-specific regulatory effect correlates with the MC-specific chromatin contacts between the PRS region and Sox9, highlighting the importance of lineage-dependent chromatin topology in instructing enhancer usage. By integrating the enhancer signatures and chromatin topology, we uncovered >10,000 enhancers that function differentially between MC and limb cartilages and demonstrated their association with human diseases. Our findings provide critical insights for understanding the choreography of gene regulation during development and interpreting the genetic basis of craniofacial pathologies.
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Affiliation(s)
- Qiming Chen
- Department of Oral and Cranio-maxillofacial Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, College of Stomatology, Shanghai Jiao Tong University, National Center for Stomatology, National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology, Shanghai, 200011, China
| | - Jiewen Dai
- Department of Oral and Cranio-maxillofacial Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, College of Stomatology, Shanghai Jiao Tong University, National Center for Stomatology, National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology, Shanghai, 200011, China
- Shanghai University of Medicine and Health Sciences, Shanghai, 201318, China
- Corresponding author. (J.D.); (Q.B.)
| | - Qian Bian
- Department of Oral and Cranio-maxillofacial Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, College of Stomatology, Shanghai Jiao Tong University, National Center for Stomatology, National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology, Shanghai, 200011, China
- Shanghai Institute of Precision Medicine, Shanghai, 200125, China
- Shanghai Key Laboratory of Reproductive Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Corresponding author. (J.D.); (Q.B.)
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Tanikawa C, Kurata M, Tanizaki N, Takeuchi M, Zere E, Fukuo K, Takada K. Influence of the nutritional status on facial morphology in young Japanese women. Sci Rep 2022; 12:18557. [PMID: 36329131 PMCID: PMC9633753 DOI: 10.1038/s41598-022-21919-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Accepted: 10/05/2022] [Indexed: 11/06/2022] Open
Abstract
Evidence regarding the possible influence of nutritional status on the facial morphology has thus far been insufficient. We examined whether or not the physical body compositions and dietary behaviors were correlated with any morphological characteristics of the face. One hundred and fifteen young Japanese women participated. Variables representing the dietary behaviors were extracted from self-reported survey data, and corresponding three-dimensional (3D) facial images and body compositions were examined. Multivariate analyses identified significant relationships between the nutritional status and facial topography (p < 0.05). The clustering method revealed the existence of three dietary condition patterns ("balanced diet", "high-calorie-diet" with obesity tendency, and "imbalanced low-calorie-diet" with sarcopenic obesity tendency). Among these three patterns, a round face (increased facial width; analysis of variance [ANOVA], p < 0.05) was observed in the high-calorie-diet pattern, while the imbalanced low-calorie-diet pattern showed a more masculine face (increased face height, decreased eye height, increased non-allometric sexual shape differences; ANOVA, p < 0.05), thus suggesting the possibility of sex-hormonal influences. In summary, the body composition and dietary behaviors were found to influence the facial morphology, and potential biological influences were discussed.
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Affiliation(s)
- Chihiro Tanikawa
- grid.136593.b0000 0004 0373 3971Department of Orthodontics and Dentofacial Orthopedics, Osaka University Dental Hospital, Suita, Osaka Japan
| | - Miki Kurata
- grid.260338.c0000 0004 0372 6210Department of Food Sciences and Nutrition, School of Human Environmental Sciences, Mukogawa Women’s University, Nishinomiya, Hyogo Japan
| | - Noriko Tanizaki
- grid.260338.c0000 0004 0372 6210Department of Food Sciences and Nutrition, School of Human Environmental Sciences, Mukogawa Women’s University, Nishinomiya, Hyogo Japan
| | - Mika Takeuchi
- grid.260338.c0000 0004 0372 6210Department of Food Sciences and Nutrition, School of Human Environmental Sciences, Mukogawa Women’s University, Nishinomiya, Hyogo Japan
| | - Edlira Zere
- grid.136593.b0000 0004 0373 3971Department of Orthodontics and Dentofacial Orthopedics, Osaka University Dental Hospital, Suita, Osaka Japan
| | - Keisuke Fukuo
- grid.260338.c0000 0004 0372 6210Department of Food Sciences and Nutrition, School of Human Environmental Sciences, Mukogawa Women’s University, Nishinomiya, Hyogo Japan
| | - Kenji Takada
- grid.136593.b0000 0004 0373 3971Center for Advanced Medical Engineering and Informatics, Osaka University, Suita, Osaka Japan
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48
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New Genetic Variants Underlying East Asian Facial Morphology. Am J Med Genet A 2022; 188:3149-3150. [PMID: 36209349 DOI: 10.1002/ajmg.a.62328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
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Liu XM, Mao Y, Wang S, Zhou J, Qian SB. METTL3 modulates chromatin and transcription dynamics during cell fate transition. Cell Mol Life Sci 2022; 79:559. [PMID: 36266520 DOI: 10.1007/s00018-022-04590-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 10/05/2022] [Accepted: 10/06/2022] [Indexed: 11/26/2022]
Abstract
Transcriptional programming plays a key role in determining the cell state. Timely reconfiguration of chromatin structure and attenuation of pluripotent genes are required for efficient embryonic stem cell (ESC) differentiation. Here, we identify METTL3, a core N6-methyladenosine (m6A) catalyzing enzyme, as a crucial modulator of dynamic transcription and chromatin accessibility upon ESC-derived cardiac differentiation. Genome-wide analysis of chromatin-associated RNAs revealed that depletion of METTL3 failed to dramatically attenuate the transcription of pluripotent genes, as well as activate nascent cardiomyocyte-specific transcripts upon differentiation. Consistently, ATAC-seq analysis showed that loss of METTL3 markedly attenuated the dynamic alteration of chromatin accessibility at both promoters and gene bodies, resulting in reduced sensitivity of ESC chromatin structure to cardiac differentiation signal. Furthermore, we found that METTL3 negatively regulated the histone modifications H3K4me3 and H3K36me3, which are involved in METTL3-modulated dynamic chromatin architecture during cell state transition. Unexpectedly, using chromatin-associated m6A sequencing, we found that nuclear m6A underwent a dramatic increase upon differentiation, which correlates with the decrease of chromatin accessibility. Collectively, our findings reveal that METTL3 and nuclear m6A epitranscriptome couple with chromatin state to ensure transcriptional regulation of cell fate transition.
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Affiliation(s)
- Xiao-Min Liu
- School of Life Science and Technology, China Pharmaceutical University, Nanjing, 210009, Jiangsu, China.
| | - Yuanhui Mao
- Division of Nutritional Sciences, Cornell University, Ithaca, NY, 14853, USA
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, China
| | - Shen Wang
- School of Life Science and Technology, China Pharmaceutical University, Nanjing, 210009, Jiangsu, China
| | - Jun Zhou
- School of Life Science and Technology, China Pharmaceutical University, Nanjing, 210009, Jiangsu, China
| | - Shu-Bing Qian
- Division of Nutritional Sciences, Cornell University, Ithaca, NY, 14853, USA.
- Field of Genetics, Genomics, and Development, Cornell University, Ithaca, NY, 14853, USA.
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Caton NR, Dixson BJW. Beyond facial width-to-height ratios: bizygomatic width is highly sexually dimorphic when adjusting for allometry. Biol Lett 2022; 18:20220211. [PMCID: PMC9554718 DOI: 10.1098/rsbl.2022.0211] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
A large and ever-growing literature implicates male facial width-to-height ratio (bizygomatic width divided by facial height) as a secondary sexual trait linked to numerous physical and psychological perceptions. However, this research is based entirely on the premise that bizygomatic width is sexually dimorphic, which recent research has called into question. Unfortunately, statisticians for the last 125 years have noted that morphological ratio measurements may engender spurious correlations and biased effect-size estimates. In the current study, we find that bizygomatic width is highly sexually dimorphic (equivalent d = 1.39), even after adjusting for 92 allometric measurements, including multiple facial height and other craniofacial measurements (equivalent d = 1.07) in a sample of 6068 men and women. By contrast, facial width-to-height ratio (fWHR) measurements demonstrated a statistical pattern consistent with the age-old argument that morphological ratio measurements may engender spurious correlations and biased effect-size estimates. Thus, when avoiding facial ratio measurements and adjusting for allometry in craniofacial measures, we found strong support for a key premise in the human evolutionary and behavioural sciences that bizygomatic width exhibits male-biased sexual dimorphism.
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Affiliation(s)
- Neil R. Caton
- School of Psychology, The University of Queensland, Saint Lucia, Queensland, Australia
| | - Barnaby J. W. Dixson
- School of Psychology, The University of Queensland, Saint Lucia, Queensland, Australia,School of Psychology, The University of the Sunshine Coast, Sunshine Coast, Queensland, Australia,Evolution & Ecology Research Centre, School of Biological, Earth & Environmental Sciences, University of New South Wales, Sydney, New South Wales, Australia
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