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Cytogenetics and Cytogenomics in Clinical Diagnostics: Innovations and Applications
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Cytogenetics and Cytogenomics in Clinical Diagnostics: Innovations and Applications

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Cytogenomics".

Deadline for manuscript submissions: 25 August 2025 | Viewed by 1504

Special Issue Editor

Dr. Jinglan Liu

E-Mail Website
Guest Editor
Department of Pathology and Genomic Medicine, Clinical Cytogenomics, Thomas Jefferson University, Philadelphia, PA 19107, USA
Interests: conventional cytogenetics; cytogenomics; epigenetics; epigenomics; laboratory genetics and genomics

Special Issue Information

Dear Colleagues,

Chromosomes serve as both structural and regulatory units of the human genome. Clinical cytogenetics and cytogenomics enable the diagnosis of constitutional and oncological chromosomal abnormalities. While conventional karyotyping provides genome-wide analysis at low resolution, the integration of fluorescence in situ hybridization (FISH), microarray analysis, and optical genome mapping (OGM) since the 1990s has significantly enhanced diagnostic precision and sensitivity.

Despite advances in genomic sequencing technologies that detect nucleotide-level variants, our understanding of chromosomal alterations at microscopic and submicroscopic levels in human disease remains incomplete. Genome function and phenotypic manifestation are regulated across multiple layers of resolution and nuclear organization, with topological genome features coordinating higher-order gene activity. Conventional karyotyping, FISH, and emerging cytogenomic approaches remain essential for comprehensive genomic assessment, allowing for the detection of not only numerical, structural, and sub-chromosomal abnormalities but also the multiple regulatory layers that govern the genome. Looking ahead, the incorporation of artificial intelligence (AI) holds promise for overcoming the limitations of traditional cytogenetic analysis and is expected to play a transformative role across all genomic medicine subspecialties, including cytogenomics.

This Special Issue invites submissions on chromosomal abnormalities and submicroscopic genomic variations in developmental disorders, neuropsychiatric diseases, and neoplastic conditions. We welcome research on mechanistic insights, genotype–phenotype correlations, technological innovations, and clinical applications. Studies on three-dimensional chromosome organization in human diseases and AI-driven advancements in cytogenomics are particularly encouraged. As the field continues to evolve, we seek perspectives on emerging challenges, future directions, and the transformative potential of next-generation cytogenomic technologies.

Dr. Jinglan Liu
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Genes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • karyotyping
  • cytogenomics
  • chromosome territory (CT)
  • nuclear architecture
  • clinical oncology
  • germline
  • development
  • neuropsychiatry
  • artificial intelligence (AI)

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Published Papers (3 papers)

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Research

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9 pages, 645 KiB  
Article
Results of Chromosomal Microarray Need to Always Be Checked by (Molecular) Cytogenetics—Even If They Seem to Be Simple Deletions
by Thomas Liehr, Sylke Singer, Ulrike Mau-Holzmann, Stefanie Kankel, Niklas Padutsch, Luisa Person, Eva Daumiller and Uwe Kornak
Genes 2025, 16(6), 714; https://doi.org/10.3390/genes16060714 - 17 Jun 2025
Viewed by 755
Abstract
Background/Objectives: Chromosome microarrays (CMAs) tend to be used as the first line test or as a test that does not require confirmation or verification by a second test. However, to understand the implications of a duplication or deletion for a family seeking genetic [...] Read more.
Background/Objectives: Chromosome microarrays (CMAs) tend to be used as the first line test or as a test that does not require confirmation or verification by a second test. However, to understand the implications of a duplication or deletion for a family seeking genetic counseling, it is crucial to know the nature of the underlying chromosomal rearrangement. Here, we present seven cases with apparent isolated copy number loss, five of which showed unexpected complexity. Methods: Seven cases were investigated by CMA due to intellectual disability and/or dysmorphic features. Isolated deletions ranging in size from ~0.6 to ~21 Mb were found and referred for further characterization of the underlying chromosomal rearrangement. To elucidate the cases, fluorescence in situ hybridization was performed using locus-specific, whole and partial chromosome painting and/or multicolor banding. Results: Among the seven selected cases, there were five with unexpected complexity. Isolated deletions were actually evidence of chromoanasynthesis, ring chromosome formation, unbalanced translocation, or unbalanced insertion. Conclusions: These results clearly underscore that it seems reasonable to examine every case with a copy number variant—even if it appears to be “only” a simple partial deletion—using banding and/or molecular cytogenetic testing in order to make a qualified assessment of the situation and, on this basis, ensure sound genetic counseling. Full article
(This article belongs to the Special Issue Cytogenetics and Cytogenomics in Clinical Diagnostics: Innovations and Applications)
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12 pages, 1158 KiB  
Article
ChromoCheck: Predicting Postnatal Chromosomal Trisomy Cases Using a Support Vector Machine Learning Model
by Nabras Al-Mahrami, Nuha Al Jabri, Amal A. W. Sallam, Najwa Al Jahdhami and Fahad Zadjali
Genes 2025, 16(6), 695; https://doi.org/10.3390/genes16060695 - 8 Jun 2025
Viewed by 475
Abstract
Introduction: Chromosomal study via karyotype is one of the historical gold-standard procedures used to provide a clearer view of chromosomal trisomy abnormalities. It has been used to correlate several phenotypic manifestations that require immediate medical intervention. However, the laboratory procedure persisted with various [...] Read more.
Introduction: Chromosomal study via karyotype is one of the historical gold-standard procedures used to provide a clearer view of chromosomal trisomy abnormalities. It has been used to correlate several phenotypic manifestations that require immediate medical intervention. However, the laboratory procedure persisted with various drawbacks. The recent machine learning model shed light on prediction capabilities in the medical field. In this study, we aimed to use a support vector machine model for predicting postnatal chromosomal trisomy cases. Methods: A dataset of 946 neonatal records from the Royal Hospital, Muscat, Oman, covering the period from 2013 to 2023, has been used in this model. The model is based on features such as thyroxine hormone levels and thyroid-stimulating hormone levels. With different R packages, we used a support vector machine model with leave-one-out cross-validation and ten iterations to test three kernel functions: linear, radial, and polynomial. Results: Among the obtained kernel performances, the linear kernel has optimal classification performance. The training accuracy was 81%, and the testing accuracy was 82%. Sensitivity ranged from 97 to 98%, and specificity ranged from 79 to 80%. The area under the curve in relation to the training dataset came to 0.89, and it came to 0.90 for the test dataset. We deployed the trained models in a website tool called ChromoCheck. Conclusions: Our study is an example of how machine learning can be instrumental in augmenting conventional methods of cytogenetics diagnosis and decision-making in a clinical setup. Full article
(This article belongs to the Special Issue Cytogenetics and Cytogenomics in Clinical Diagnostics: Innovations and Applications)
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Review

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30 pages, 2258 KiB  
Review
Cytogenetics and Cytogenomics in Clinical Diagnostics: Genome Architecture, Structural Variants, and Translational Applications
by Concetta Federico, Desiree Brancato, Francesca Bruno, Elvira Coniglio, Valentina Sturiale and Salvatore Saccone
Genes 2025, 16(7), 780; https://doi.org/10.3390/genes16070780 (registering DOI) - 30 Jun 2025
Abstract
The spatial organization of the genome within the nucleus is a fundamental regulator of gene expression, genome stability, and cell identity. This review addresses the central question of how nuclear genome architecture contributes to disease mechanisms and diagnostics, and how technological advances enable [...] Read more.
The spatial organization of the genome within the nucleus is a fundamental regulator of gene expression, genome stability, and cell identity. This review addresses the central question of how nuclear genome architecture contributes to disease mechanisms and diagnostics, and how technological advances enable its clinical exploration. We first outline the principles of nuclear genome architecture, including chromosome territories, replication timing, and 3D domains, and their role in gene regulation and disease. We then explore the mechanisms and consequences of chromosomal rearrangements, and how replication dynamics intersect with epigenetic regulation and genome stability. Diagnostic tools are presented in chronological progression, from conventional cytogenetics to high-resolution genomic and single-cell techniques. A dedicated section focuses on cancer cytogenomics and its clinical implications. We further highlight emerging technologies for 3D genome and epigenome profiling and their integration into diagnostic workflows. Finally, we discuss current challenges, such as standardization and cost, and the transformative potential of multi-omics and artificial intelligence for future precision diagnostics. Overall, we provide a comprehensive overview of how cytogenetics and cytogenomics contribute to the understanding and clinical diagnosis of genetic and neoplastic diseases. Full article
(This article belongs to the Special Issue Cytogenetics and Cytogenomics in Clinical Diagnostics: Innovations and Applications)
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