1.  Introducation

Chromosomal abnormalities have long been recognized as key contributors to developmental disorders, congenital anomalies, infertility, and certain cancers [1]. The advent of chromosome karyotyping in the 1950s marked a transformative era in medical genetics, enabling direct observation of chromosomal structure and number [2]. As clinical needs for higher diagnostic resolution have grown, so too have the technologies. This review explores the enduring role of conventional karyotyping in medical diagnostics, the rise of advanced genomic tools such as FISH, chromosomal microarray analysis (CMA), and whole genome sequencing (WGS), and discusses their respective advantages, limitations, and future potential.

2.  The foundation: chromosome karyotyping

Karyotyping involves culturing cells (commonly peripheral blood lymphocytes), arresting them in metaphase, staining them using Giemsa to produce banding patterns, and visually inspecting the 23 pairs of human chromosomes. This method is cost-effective and especially powerful for detecting large-scale chromosomal abnormalities (>5 Mb), such as aneuploidies (e.g., trisomy 21), large deletions, duplications, and structural rearrangements like translocations or inversions [2].

In clinical practice, karyotyping remains essential in prenatal screening, recurrent miscarriage investigations, certain infertility cases, and hematologic malignancies like chronic myeloid leukemia (CML). The ability to detect balanced translocations and mosaicism gives it unique value in scenarios where precise chromosomal architecture is critical. Additionally, karyotyping is often the first test performed in cases of ambiguous genitalia or dysmorphic features in newborns, as well as for constitutional chromosomal abnormalities.

However, karyotyping has clear limitations: it is labor-intensive, dependent on dividing cells, and lacks the resolution to detect microdeletions or subtle copy number variations [1]. It also has variable success rates depending on the tissue type and condition of the sample, making it less ideal for certain postnatal applications.

3.  Technological advancements: FISH, CMA, and WGS

To overcome the limitations of karyotyping, a series of more sensitive technologies have emerged:

3.1.  Fluorescence In Situ Hybridization (FISH)

This method uses fluorescent DNA probes to detect specific DNA sequences on chromosomes, enabling identification of known deletions, duplications, or translocations even in non-dividing cells. FISH is especially useful for rapid detection (e.g., aneuploidies in prenatal samples) and confirmation of suspected abnormalities [3]. It plays a critical role in oncology diagnostics, particularly in identifying gene fusions (e.g., BCR-ABL in CML) and HER2 amplification in breast cancer. FISH also supports analysis in interphase cells, making it valuable when metaphase spreads are difficult to obtain.

3.2.  Chromosomal Microarray Analysis (CMA)

CMA allows for genome-wide screening of copy number variations (CNVs) at much higher resolution (50-100 kb), making it a first-tier diagnostic tool for developmental delay, autism spectrum disorders, and congenital anomalies. Unlike karyotyping, CMA does not require dividing cells and can uncover submicroscopic abnormalities invisible to standard cytogenetics [2]. It has replaced karyotyping in many pediatric and prenatal settings due to its superior diagnostic yield, estimated at 15–20% in unexplained developmental disorders. CMA can also detect regions of homozygosity, uniparental disomy, and other clinically relevant genomic imbalances, further expanding its diagnostic utility.

3.3.  Whole Genome Sequencing (WGS)

The most comprehensive approach, WGS captures nearly all types of genomic variation, including point mutations, CNVs, structural variants, and non-coding region changes. Though still costly and requiring sophisticated bioinformatics, WGS is becoming increasingly viable and is being integrated into diagnostic pipelines for rare diseases and oncology [1,4]. WGS has the advantage of detecting balanced structural variants, mobile element insertions, and deep intronic mutations that may be missed by CMA. Moreover, its application is expanding into population-wide screening programs and personalized treatment design.

4.  Comparative analysis and clinical integration

Each diagnostic modality has its niche. Karyotyping is favored for detecting balanced rearrangements and aneuploidies. FISH offers targeted confirmation and rapid results. CMA provides high-resolution, genome-wide detection of CNVs and is often the first-line test for unexplained developmental disorders. WGS, while still evolving in clinical utility, offers unparalleled comprehensiveness and potential for detecting rare or novel pathogenic variants.

Integration of these tools is common. For example, a CMA may reveal a suspected deletion, followed by FISH to confirm mosaicism or inheritance pattern. In oncology, karyotyping may identify a translocation, with WGS used to characterize the fusion breakpoint and associated mutations. Clinical guidelines often recommend a tiered testing strategy: starting with CMA or targeted panels and progressing to WGS when initial results are inconclusive. In some diagnostic workflows, combinations of tests are used simultaneously to enhance diagnostic confidence and guide clinical decision-making.

Additionally, diagnostic interpretation increasingly depends on multidisciplinary teams, including clinical geneticists, molecular pathologists, genetic counselors, and bioinformaticians. Laboratories must consider variant classification guidelines (such as ACMG criteria) and integrate clinical phenotype, inheritance patterns, and family history when interpreting genomic findings. The increasing complexity of genetic data necessitates robust communication between lab professionals and clinicians to ensure actionable and ethically sound interpretation.

5.  Insights from clinical practice

A clinical interview with a diagnostic cytogenetics laboratory revealed that nearly all steps in the karyotyping workflow—cell culturing, metaphase harvesting, chromosome spreading, and imaging—are now largely automated. The only remaining technically challenging manual step is placing the coverslip on the slide before final imaging. In addition, specialized software systems now assist in chromosome recognition and karyogram organization, greatly streamlining the process.

Despite the rise of CMA and WGS, practicing clinicians maintain that karyotyping remains irreplaceable in many diagnostic workflows. It is not only cost-effective but also especially well-suited for detecting balanced translocations and large chromosomal rearrangements that may be missed or ambiguously interpreted by other methods. Furthermore, the ability to review metaphase images provides an intuitive and visual confirmation of genomic architecture, which many clinicians find essential in complex cases. These practical advantages, along with its long-established reliability, suggest that karyotyping will continue to play a central role in clinical genetics, particularly in settings where rapid and affordable initial assessments are needed.

6.  Discussion

As sequencing costs decrease, WGS may become the default diagnostic method, providing both breadth and depth. Pilot programs for population-wide genomic screening are already underway in several countries, aiming to detect actionable genetic risks in healthy individuals. Simultaneously, machine learning and AI-based karyotype interpretation tools are emerging, aiming to automate and standardize traditional cytogenetics workflows [5]. These advances have the potential to streamline analysis and reduce diagnostic turnaround times, particularly in high-volume clinical settings.

However, widespread use of genomic tools raises ethical concerns: incidental findings, uncertain variants of unknown significance (VUS), disparities in access to testing, and data privacy must all be carefully managed. The psychological burden of receiving ambiguous or non-actionable results is particularly relevant in prenatal and predictive testing contexts. For instance, a healthy individual may learn they carry a pathogenic BRCA1 mutation, triggering anxiety and challenging life decisions about surgery or childbearing. Ethical frameworks must also account for consent in pediatric testing, the storage and reanalysis of genomic data, and equity in global health systems.

Moreover, the increasing interest in using cfDNA (cell-free DNA) for non-invasive testing opens new avenues for early cancer detection, organ transplant monitoring, and prenatal diagnostics beyond aneuploidy. Technologies like liquid biopsy may allow for continuous genomic monitoring of patients, shifting the focus from reactive to proactive medicine.

AI technologies also hold promise for scaling genomic diagnostics. Algorithms trained on large datasets can aid variant prioritization, phenotype-genotype correlation, and even suggest possible diagnoses. Yet, AI tools must be developed with caution: their outputs are only as reliable as the data they are trained on. Importantly, clinicians must remain central in interpreting these tools, ensuring that patient context, emotion, and nuance are not lost to algorithms.

7.  Conclusion

Chromosomal diagnostics have evolved significantly since the advent of karyotyping, with advanced technologies like FISH, CMA, and WGS offering unprecedented resolution and diagnostic yield. While conventional karyotyping remains indispensable for detecting large-scale abnormalities and balanced rearrangements, newer genomic tools excel in identifying submicroscopic variants, enhancing precision in diagnosing developmental disorders, cancers, and rare diseases. The integration of these methods—guided by clinical context and a tiered testing approach—optimizes diagnostic accuracy and patient care. Looking ahead, the declining cost of WGS and the integration of AI-driven analysis promise to revolutionize cytogenetics, enabling comprehensive, rapid, and automated genomic assessments. However, these advancements also bring ethical challenges, including variant interpretation, data privacy, and equitable access. In is necessary to ensure responsible implementation. As the field progresses, multidisciplinary collaboration and ongoing technological refinement will be key to unlocking the full potential of genomic medicine while resolving its complexities. Ultimately, the synergy of traditional and new methods will continue to shape the future of genetic diagnostics, improving outcomes for patients worldwide.