International Society for Prenatal Diagnosis 2024 Debate 3—Cytogenetics Is a Dinosaur and Should Be Replaced by Molecular Technologies

ABSTRACT

Cytogenetic technologies such as G‐banding chromosome and FISH analyses have long been the gold standard diagnostic test in prenatal genetic testing. However, unbiased next‐generation sequencing technologies such as fetal exome or genome sequencing (ES/GS) are becoming widely accessible and increasingly utilized, particularly for fetuses with structural anomalies. Emerging studies are now establishing increased diagnostic yields from molecular technologies, but there remains a lack of consensus as to whether ES/GS should replace cytogenetic technologies and targeted genepanel screening as first‐line tests for all prenatal diagnoses. This report is a summary of the debate on this topic presented at the 28th International Conference on Prenatal Diagnosis and Fetal Therapy. Both expert debaters discussed the advantages and disadvantages.

Key Points

• What's already known about the topic?

  • ◦Analyses focusing on large chromosomal changes (e.g. karyotype, chromosomal microarray analysis [CMA]) are the gold standard diagnostic tests in prenatal genetic testing.
  • ◦Unbiased exome and genome sequencing tests are becoming more routinely accessible in the prenatal setting.

• What does this study add?

  • ◦These debaters provide an in‐depth discussion of the continued value of robust and widely accessible cytogenetics by comparison to the more complex data types but higher resolution and increased diagnostic yields of molecular technologies.

1. Introduction (Moderator—A. Breman)

For decades, cytogenetics has played a critical role in prenatal diagnosis, offering a broad range of applications. However, with the rapid adoption of next‐generation sequencing (NGS) methods such as exome and genome sequencing (ES/GS), the natural question the field is asking is whether cytogenetics is becoming obsolete and destined to be replaced by unbiased genome‐wide screening using molecular technologies. Traditionally, G‐banded chromosome analysis (karyotype) has been thought of as the gold standard for prenatal diagnosis, and even today is frequently used to confirm high‐risk findings from cell‐free DNA screening. Fluorescence in situ hybridization (FISH) or quantitative fluorescent PCR often complements a karyotype by facilitating the rapid detection of aneuploidies, while chromosomal microarray analysis (CMA) is commonly employed when ultrasound anomalies are detected. These cytogenetic tools are also invaluable for identifying genetic causes of fetal loss and detecting parental balanced structural rearrangements in cases of recurrent miscarriages.

Let's consider how molecular techniques are currently being applied in prenatal diagnosis. Targeted sequencing for familial variants has long been offered for families with a priori risk, but NGS tests are rapidly becoming available prenatally, and professional societies have published recommendations regarding the use of ES and GS in the prenatal period. The current American College of Obstetricians and Gynecologists (ACOG) guidelines recommend CMA as the first‐tier test in the diagnostic evaluation of fetal structural anomalies [1]. However, ACOG and the Society for Maternal‐Fetal Medicine (SMFM) support ES in specific situations, such as cases where fetuses present with multiple anomalies or recurrent fetal phenotypes that remain undiagnosed after standard genetic testing, including karyotyping or microarray analysis. Likewise, in 2020, the American College of Medical Genetics and Genomics (ACMG) published guidance stating that prenatal ES may be considered for a fetus with structural anomalies but only following a normal CMA or karyotype analysis [2]. In each of these statements, conventional cytogenetic testing is suggested prior to pursuing ES. England took a similar approach in 2020, when the National Health Service (NHS) began offering prenatal ES for the diagnosis of fetal anomalies through its Genomic Medicine Service. Currently, this testing may be performed in parallel with or subsequent to CMA but not as a standalone first‐tier test. Most recently, the International Society for Prenatal Diagnosis (ISPD) released a 2022 position statement on prenatal sequencing [3]. According to their updated guidelines, prenatal sequencing (ES or GS) is recommended in certain scenarios, specifically: (1) a fetus with a major single anomaly or multiple organ system anomalies with a negative CMA or a concurrent CMA, or (2) a family history of a prior fetus or child with major single or multiple anomalies undiagnosed following karyotype or CMA. In summary, the current guidelines already support ES and GS in the prenatal setting, but only in certain high‐risk circumstances. At present, there are limited studies that comprehensively evaluate the evidence supporting the routine use of ES or GS in the absence of a fetal anomaly detected on ultrasound, and CMA (with or without karyotype) remains the gold standard for prenatal diagnosis.

In this article, Professors Talkowski and Akkari address the debate over whether or not cytogenetics is a dinosaur that should be replaced by molecular technologies. This was the subject of a lively debate at the 28th International Conference of the International Society for Prenatal Diagnosis and Fetal Therapy in Boston, Massachusetts, in July 2024.

2. The Case in Favor (M. Talkowski)

As a community, when do we evolve toward more advanced technologies that offer superior outcomes for our patients? There are many challenging technical barriers to the adoption of new technologies. The validation, benchmarking, regulatory approval, implementation, and accessibility of the technology are just a few considerations. There are also clear barriers tethered to the acceptance of patients and payers regarding the utility and value of the technology. However, what emerges from discussions such as these is that another critical inflection point is the willingness of providers to transition their infrastructures and legacy processes to re‐envision their delivery of care, and then to train the next generation of clinicians toward paradigm shifting technologies. This is the underlying factor that pervades all facets of this debate. As a healthcare system and a society, what are the timelines that we expect from our providers and payers regarding this evolution? This debate does not hinge on the relative increase in diagnostic yield or the overall value to patients of molecular technologies that unbiasedly profile all sequencing variation in the human genome to those that do not. That comparative value is established; I will show you that systematic studies have clearly demonstrated that ES or GS offer the highest diagnostic yield for patients by comparison to cytogenetic methods or targeted gene panel tests. Short‐read ES and GS technologies have been utilized for over a decade, they are mature, they have been carefully benchmarked, and they will diagnose more patients than cytogenetic methods. These sequencing technologies have also undergone regulatory approval and are being applied and reimbursed in large numbers across many academic healthcare systems and commercial diagnostic providers. For the purposes of this debate, I will take the position that there are sufficient studies to strongly suggest that there is limited added value in continuing to offer patients multiple low‐resolution cytogenetic tests (often followed by a third ES test) as a frontline strategy, rather than a single ES/GS test that has superior diagnostic yield. I have been asked to resolutely take the position that it is time to end the practice of performing genetic tests that target small swaths of the genome with narrowly defined gene panels, or to stop surveying only specific classes of genetic variation using niche assays due to legacy infrastructure or existing billing agreements with payers. Such transitions are always difficult, but I will suggest that there is overwhelming data to support the argument that cytogenetic and targeted gene or variant panel tests fail to detect pathogenic variants that are captured by ES/GS, and therefore simply fail to deliver diagnoses that should be accessible to our patients. In this debate, I will try to compel the community that the time has arrived for all providers to embrace the technology that unbiasedly surveys sequence variation in the human genome to equitably maximize the clinically relevant information that can be delivered to all patients.

We can begin with the seminal paper by Tjio and Levan that established the correct chromosome number in humans in 1956 [4]. Almost 7 decades later, karyotyping is still performed to visualize chromosome count and structure in prenatal diagnostics. While CMA has enabled the discovery of extremely large copy number variants (CNVs) for over two decades [5], a meaningful fraction of the general population can harbor very large CNVs [6]. Our recent analyses have utilized cloud‐based data processing pipelines on very large‐scale GS data in population cohorts such as the genome aggregation database (gnomAD) or the All of Us research program (AoU) to reveal that the average structural variant (SV) in the human genome spans less than 300 bases, yet at least 25% of rare loss‐of‐function variation in each human is derived from these SVs. These analyses show that cytogenetic methods will fail to capture virtually all SVs in most individuals and will miss significant underlying complexity [7, 8, 9]. If I am meant to play the character who killed cytogenetics in this debate, I'll give you one simple premise: our genomes contain over three billion bases represented on two copies of the chromosomes, and every human harbors over four million sequence variants. GS can access most of these sequence variants, whereas cytogenetic methods miss all of them. Moreover, there are over 10,000 SVs per genome accessible to short‐read GS and approximately 25,000 SVs captured by long‐read GS, yet cytogenetic methods are blind to all but the very largest aberrations. For these and myriad other reasons, it is time to embrace technological advances and train our next generation of clinicians in technologies that can rapidly provide the greatest benefit to our patients. This requires a significant shift toward high‐resolution and unbiased genetic testing and away from narrowly targeted applications such as gene panel testing or cytogenetic methods in prenatal diagnostics.

Why should we evolve on this? Let us reframe the issue. Under many guidelines highlighted by Amy, the first‐tier approach for prenatal diagnostics requires a karyotype to screen for microscopically visible abnormalities, as well as to perform an additional CMA to detect extraordinarily large CNVs. The CMA test cannot detect the balanced chromosomal abnormalities (BCAs) accessible to the karyotype, the karyotype misses most CNVs found by CMA, and neither test captures any of the more than four million sequence variants in each genome. By contrast, GS as a single test will take less time, it will cost less than the combination of multiple cytogenetic tests, and it will undeniably diagnose more cases, as has been empirically demonstrated in thousands of samples across multiple studies. This test is superior in overall diagnostic yield and can improve fetal outcomes and healthcare management. I will further emphasize that we are approaching an era where we can capture virtually all coding variants comparable to ES, as well as the CNVs found by CMA, using a non‐invasive fetal sequencing (NIFS) approach. This would require only a blood test and could obviate the future need for an invasive amniocentesis or chorionic villus sampling (CVS) to perform genetic sequencing [10]. Therefore, while I do not endorse this inflammatory title the organizers have chosen to suggest cytogenetics is a dinosaur and must die, I cannot argue with its validity as the era of high‐resolution prenatal sequencing is inevitable and is likely to become accessible for noninvasive genetic testing.

As a trainee in Jim Gusella's laboratory at Harvard Medical School and Massachusetts General Hospital, one of my first activities in prenatal diagnostics was sequencing a fetal sample that harbored a de novo translocation. At the time, we were developing sequencing methods and driving research trying to dissect the molecular origins and breakpoint organization of balanced chromosomal rearrangements [7, 8, 11]. The fetus in our first study was diagnosed with a de novo translocation by standard‐of‐care karyotype, and unfortunately the risk of an untoward outcome was based solely on the presence of the de novo translocation (6.1% according to Warburton, 1991), irrespective of the specific impact of the breakpoints [12]. We sequenced the case within two weeks and demonstrated that the translocation directly disrupted CHD7, which resulted in a predictive diagnosis of CHARGE syndrome [13]. The diagnosis was confirmed postnatally based on clinical symptoms, and the infant died at 10 days of age due to complications, including neurologic and respiratory depression that prompted intubation after birth. It was 2011 and such routine access to sequence variation was not feasible, but the technology is accessible today.

Implementation of GS is undoubtedly more complex than cytogenetic tests, but its resolution is critical for interpretation. From our extensive analyses across almost a million individuals and over 54 phenotypes from CMA studies, and GS analyses in gnomAD and AoU, we find that large and complex classes of SVs are abundant in the population and observed in each genome [6, 14]. These data continue to suggest that the argument for cytogenetic testing is only meritorious if we are willing to ignore the complexity underlying the variants observed with lower resolution methods, and to accept that we will fail to discover clinically relevant variation when a patient carries a diagnostic sequence variant or a pathogenic CNV that is below the resolution of CMA. Many individuals in developmental disorder and congenital anomaly studies harbor single exon to full gene deletions in known disease loci that collectively confer comparable relative risk to some established genomic disorder deletions [15], yet these CNVs are not considered in cytogenetics. Even some of the most extraordinarily complex genomic rearrangements observed in the population remain cryptic to cytogenetic technologies. In the example shown in Figure 1, we discovered a complex SV that mirrors many of the features of “chromothripsis” observed in cancer cells, including localized chromosome shattering and 49 breakpoints across seven chromosomes. This chromosomal “shattering” event resolved to a relatively balanced state and was inserted into a reassembled 600 kb segment of chromosome 1 [6]. Despite this massively complex genome reorganization, the cytogenetic test shows nothing. As nicely illustrated in this AI generated cartoon by Dr. Monica Salani, there is nothing abnormal observed with these shattered chromosomes under the microscope in a karyotype (Figure 1). In gnomAD, we catalogued 13 classes of recurrent complex SVs, and more recent studies with long‐read GS have revealed a more expansive landscape of complex SVs and repeat expansions [16]. As a field, we should move toward providing the highest resolution and most accurate information possible to patients, and at present that requires routine GS.

FIGURE 1.

Limitation of traditional cytogenetic approaches. (Left) This extremely complex structural variant involves 49 breakpoints across seven chromosomes that are disrupted and reassembled in contiguous fragments on chromosome 1 in a relatively balanced state. This image taken from the presented slide was published in Collins et al. [6]. Despite the extensive complexity of this structural rearrangement, this large genomic reorganization was cryptic to karyotyping and CMA. (Right) AI‐generated cartoon to illustrate that karyotyping cannot detect most complex structural variants.

There is now clear evidence to demonstrate the diagnostic value of ES/GS in comparison to cytogenetic methods. In one recent study, we began with autistic individuals and their family members where there was a systematic collection of quartet families with CMA, ES, and GS. The diagnostic yields themselves are irrelevant as they are dependent on genetic architecture of the phenotype being evaluated, but relative incremental yield by technology on the same samples was our motivating question. In a cohort of over 1600 quartet families with matched ES, GS, and CMA from the Simons Foundation Autism Research Initiative (SFARI), a diagnostic yield of 7.8% was observed by GS, while the other technologies each accessed only a portion of these diagnoses (4.4% and 7.4% for CMA and ES, respectively) [17]. Using the same GS pipeline, we then asked this question in 249 trios with fetal structural anomalies in analyses with Ron Wapner, Brynn Levy, Jessica Giordano and colleagues at Columbia University. If you review the diagnostic yield, you can see that GS revealed greater incremental yield than ES, CMA, or karyotype individually or collectively, as well as all of the clinically relevant variants observed by the other methods (Figure 2) [17]. These data suggest that GS is superior to any individual cytogenetic test and captured all of the diagnostic variants that required three other tests. The combination of karyotype, CMA, and ES is thus more time consuming and costly than one GS test, and GS delivers more diagnoses. My position is that with more training in sequencing technologies, clinicians and patients alike will demand the most comprehensive approaches available, and this is clearly ES/GS testing.

FIGURE 2.

Comparison of diagnostic yields across technologies. Expected diagnostic yield of various genetic tests when applied to a cohort of unselected fetuses with structural anomalies. This image taken from the presented slide was published in Lowther et al. [17]. The dashed gray box surrounding the ES bar indicates the diagnostic yield that could be captured if ES‐based CNV methods are applied. Each bar is colored based on the fraction of diagnoses provided by each variant class. CMA, chromosomal microarray; CNV, copy number variant; DEL, deletion; DUP, duplication; ES, exome sequencing; GS, genome sequencing; indel, small insertion and deletion; INV, inversion; SNV, single nucleotide variant; TLOC, translocation.

As a closing note, the analyses I discussed in 2011 and those in the autism cases and fetal anomalies that we initially preprinted with Wapner, Levy and colleagues in 2020 were relatively small and retrospective studies to suggest the capabilities of the technology. A likely defining study for standard‐of‐care GS is currently ongoing in a flagship program known as PrenatalSeq that was funded by NICHD and involved benchmarking prospective GS for fetal anomalies across Baylor College of Medicine, the University of North Carolina, and Columbia University. Although the results are not yet published, they have been presented at this and other meetings and provide indisputable evidence that ES and GS represent tractable alternatives to cytogenetic methods and provide superior diagnostic yields (Wapner, Vora, Giordano, Van den Veyver and colleagues, unpublished). As I highlighted yesterday in my talk, this is likely the launching point for routine sequence variation in prenatal screening. In a prior study, we revealed that a technology we developed at Massachusetts General Hospital can sequence > 23,000 fetal genes as well as large CNVs from cell‐free DNA (cfDNA; Figure 3). This noninvasive fetal sequencing (NIFS) approach was performed using the same Streck tube currently collected for aneuploidy screening with NIPT. In a proof‐of‐principle study with Dr. Kathryn Gray and colleagues, NIFS captured all clinically relevant sequence variants reported from invasive ES/GS data (Figure 3) [10]. In ongoing analyses highlighted at this meeting, we are finding even higher performance of the current NIFS implementation from fresh sample collections and even legacy frozen plasma collected in the PrenatalSEQ study (Brand, Wapner, Giordano, Whelan, Chung, Duyzend, Vora and colleagues, unpublished). These data suggest that another paradigm shift is approaching in fetal genomics where assessment of sequence variation from a single blood test early in pregnancy is likely to eventually represent a front‐line strategy at a fraction of the cost and risk associated with an invasive medical procedure and genetic testing. That is my closing statement for this debate—as an alternative to amniocentesis or CVS and a cytogenetic procedure, I propose a single GS test today, and a future with a simple blood test that will be accessible to all pregnant persons to screen for all aneuploidies, clinically relevant CNVs, and coding sequence variation with superior diagnostic yield to any cytogenetic or narrowly targeted gene panel test. The future is resoundingly going to be driven by sequence‐based diagnostic technologies and tools such as AI to support variant interpretation. The key to facilitating and catalyzing this future is building this expertise in our next generation of clinicians and educating our healthcare systems, patients, and payers on the immeasurable value of early genetic diagnoses in supporting fetal clinical care and maternal health.

FIGURE 3.

Non‐invasive fetal sequencing (NIFS). A study demonstrating that a simple blood test is capable of unbiased screening of sequence variants across more than 23,000 fetal genes, diagnostic CNVs, and maternal carrier variants in a method referred to as non‐invasive fetal sequencing (NIFS). This method has the potential to capture diagnostic yields comparable to ES but without the need for an invasive procedure [10]. This image is taken from the presented slide and was modified from an image from the Lasker Foundation and Brand et al. [10]. The figure illustrates the process from a blood sample collection and cell free fetal DNA extraction to sequencing and analysis of fetal genes, the representative allele fraction distributions, and genotype predictions to derive clinically relevant fetal sequence variants such as the detection of a COL2A1 variant shown here that is associated with Stickler Syndrome.

3. The Case Against (Y. Akkari)

The most important argument provided in this manuscript is that cytogenetics is not a methodology but rather a science. Throughout history, a science never dies. Therefore, one should focus on the science of chromosome structure and behavior and why its longevity should not be up for debate. In polling the audience as to how many have laboratories like Dr. Talkowski’s that can perform such sequencing analyses, very few raised their hands. This highlights that what is important for this topic is to consider “where do we go next?” A couple of years ago, I was invited to write a commentary for The Pathologist about a topic that is close and dear to me. So, I decided to write about cytogenetics. If we Google the word “cytogenetics”, nowhere does it say that it has a limited lifetime. So why do we keep hearing that cytogenetics is dead? The biggest problem we are currently encountering is that some people equate cytogenetics to the technique of G‐banding or a karyotype, and these kinds of correlations have hurt our field and caused the younger generation to hesitate to pursue a career in cytogenetics. In this discussion, I am really hoping to convince you that the science of cytogenetics is in danger and that we must do something about it.

Methodologies change with time. That is just the evolution of science. It is what makes us get up and go to work with enthusiasm about what we do. Historically, the science of cytogenetics evolved from not knowing the number of chromosomes in human cells to, following a laboratory mistake, the determination of the accurate number of chromosomes in human cells to be 46. This was followed by the ability to generate a karyotype based on size and centromere position that we can appreciate in Figure 4A–C. Subsequently, in the 1970s, Q‐banding was established and was followed by our current banding techniques: G‐banding (Figure 4D) and R‐banding. Then came FISH with its ability to detect targeted copy number and structural rearrangements at a much higher resolution, and then CMA to investigate copy number aberrations genome‐wide. As shown in Figure 4A–H, the methodologies of science evolve. That is just the nature of our work. And that is a good thing. A clinical genetics laboratory plays a critical role beyond simply diagnosing individuals with genetic diseases; it must have a big toolbox supported by a diverse menu of validated tests. This includes testing for a wide range of indications, such as solid and hematologic malignancies, pediatric neurodevelopmental disorders including autism, and adult‐onset genetic conditions. To handle these varied clinical scenarios, the clinical laboratory must have different methodologies tailored to the specific diagnostic context. Therefore, we must seriously think about algorithmic testing, that is, there is an optimal test for the right patient, at the right time, at the right cost. That is what drives the evolution of clinical laboratories in this field. The science of cytogenetics has evolved through time and will continue to do so with emerging technologies.

FIGURE 4.

Changes in testing methodologies. (A) Appearance of metaphase chromosomes prior to the accidental discovery of hypotonic solution as a chromosome spreading agent by Tao‐Chiuh Hsu in 1952. (B) Metaphase chromosomes after treatment of the cells with a hypotonic solution. (C) A karyotype from the pre‐banding era. (D) A karyotype with G‐banded chromosomes showing 46,XY. (E) Sanger sequencing traces. (F) Metaphase FISH image with chromosomes counter‐stained with DAPI. (G) Chromosomal microarray whole‐genome view with the copy number plot in the top half of the image and the SNP data plot in the lower half of the image. (H) Browser screenshot of next‐generation sequencing data.

Interestingly, both in the science of cytogenetics, which is the study of chromosome behavior and structure, and in molecular genetics, which is the science of DNA at its nucleotide level, there are a lot of parallel evolutions. As with the evolution of cytogenetics, a very parallel phenomenon happened to molecular genetics. From Maxim‐Gilbert sequencing to Sanger sequencing with polyacrylamide gel loading followed by automated gel electrophoresis, to computer‐assisted visualization of the sequencing data, to massively parallel sequencing and the development of bioinformatics pipelines, and most recently to long‐read sequencing, the molecular diagnostics community has adapted to change. Cytogenetics also continues to evolve; we are working on AI‐generated karyotype processes, methylation arrays for disease classification, and most recently optical genome mapping (OGM), which is also a methodology in cytogenetics.

We must challenge the rumor that cytogenetics “is a dinosaur” or “is dead”. In reality, it is we cytogeneticists who are spreading the rumor—I've never heard a molecular geneticist say cytogenetics is dead, nor did Dr. Talkowski in his advocacy for evolving technologies. This is why it is our responsibility, as cytogenetically trained individuals, to stop propagating this rumor because it is giving us a bad reputation. We must instead convince our colleagues that cytogenetics allows us to study chromosome structure and behavior, and that its understanding is crucial for the training of LGG (laboratory genetics and genomics—ABMGG) fellows in the clinical laboratories. Here, please allow me to emphasize “clinical laboratories”—because there is a big difference between discovery/research labs and clinical labs. In discovery/research, folks are at the forefront of technologies, using the latest methodology and informing us on what we need to prepare for in the clinical laboratories. Are we completely there yet? No. I even asked Dr. Talkowski if the telomere‐to‐telomere (T2T) assembly mapping is ready for clinical testing. His answer was “not yet”. Is it coming? Absolutely. We are surely looking forward to providing more information to our patients. That said, it doesn’t mean that teaching a fellow how to look at a G‐banded analysis of chromosomes is not valuable. The value of looking at a single cell genome and understanding chromosome‐level rearrangements is extremely important for the education of clinical laboratory geneticists. If we do not educate about the science, structure and behavior of chromosomes, we cannot generate good molecular geneticists. When one sees, in long‐read or short‐read next generation sequencing data, a duplication at the end of one chromosome and a deletion at the end of another chromosome, it is crucial to immediately think about the possibility of a recombinant chromosome from a balanced parental translocation. We use visuals to teach them; a karyogram is the best visual to teach these concepts.

In addition, it is imperative to think about global resources and health care equity. While it is true that in the United States, there are lots of labs able to perform genome sequencing, globally many countries cannot. Personally, I am from Lebanon, and in that region of the world, we can barely give Gleevec (imatinib mesylate) when a patient is diagnosed with chronic myeloid leukemia. Genome sequencing is not even on their radar. Moreover, if I think about Africa or remote areas in Asia or South America, I think about the importance of offering methodologies that are affordable to ensure global healthcare equity. Why does it matter? Why can’t we just bring everybody to the forefront of science? Because we have gaps in education and differences in resources. Moreover, while genome sequencing may not be cost prohibitive anymore, what remains pricey is the analysis, which is crucial for the derivation and interpretation of sequencing data. So, if you think about democratizing genome sequencing, we must look at the challenges in analysis. In my institution, we offer rapid genome sequencing for the neonatal intensive care unit, and I can tell you that we're not yet calling structural variants. We are in a clinical lab where a patient is waiting for our results. And so if a child comes with all the indications of trisomy 18, you'd better believe I will run a karyotype first.

Another point to consider is that different diseases are driven by different genetic aberrations. We have structural aberrations, repeat disorders, gene amplification, single nucleotide variants, indels, and uniparental disomy. And I think the onus is on us geneticists to understand what is the disease with which we are dealing; this is especially valid in the setting of a clinical diagnosis as opposed to the setting of discovery. So, there is a little bit of a paradigm shift. There is a lot of emphasis placed on molecular techniques, and a lot of resources. From the beginning of human genome sequencing, we have understood that there is a huge value in understanding the sequence of humans—and other organisms, for that matter—and that these are the methodologies and tools we need to build upon. The same evolution is happening in cytogenetics. We haven’t stopped evolving either. We went from G‐banding to FISH to CMA. Now, I would argue that optical genome mapping is really a great tool to use for the detection of structural abnormalities as well as a copy number variation at a high resolution. It doesn’t give you sequence variation, which is acknowledged, but it certainly does enable the detection of many of these aberrations that cause disease.

Let's discuss some examples as to why cytogenetic methodologies are still valuable. Do I believe that everybody forever is going to do G‐banding? The answer is “no”. It is a methodology that will evolve and has evolved. Now we have AI to generate a karyotype. We also have structural callers from whole genome sequencing to understand the structure of the genome. That said, there are certain chromosome aberrations that we still need to clarify and may benefit from G‐banding: Robertsonian translocations, for instance. They will likely be resolved by T2T assemblies, but it’s not clinical yet. Another example is marker chromosomes, which involve a gain of genetic material that may not be recognized as a distinct marker without cytogenetic analysis. You cannot really see that it is an independent marker chromosome unless you look at the chromosomes, which also helps in understanding the underlying mechanism. Therefore, my plea to the reader is that it is our responsibility to educate the masses, to educate on cytogenetics, the science, the understanding of chromosome behavior and structure, to really re‐emphasize training in cytogenetics and to think about cost and resources.

This brings me back to the fact that, as a community, we must challenge the rumor that cytogenetics is dead. This rumor is preventing our young generation of high school and college graduates from wanting to understand the science of chromosomes. There is really a concern regarding the lack of emphasis on cytogenetic training. Thirty or 40 years ago, we had more than a dozen cytogenetic training centers in the US. Currently, we are down to two—one in Michigan and one in Texas. It is just not enough. As much as we want people to understand next‐generation sequencing, we also need them to understand the structure and behavior of chromosomes. Of note, I had the chance to share a pizza with Dr. Ron Wapner once at a meeting, and Ron asked me, “would you encourage your kids to go into cytogenetics?” I'm a mother, and I very genuinely said yes. I totally meant it because the science of cytogenetics will make them understand chromosomes. Understanding chromosomes will make them understand behavior. Understanding everything about this science will make them able to fully understand the data that labs like Dr. Talkowski’s are able to generate at large‐scale.

So, there is a technologist at Oregon Health and Science University, Richard Sherman, who I worked with, who drew a cartoon that many cytogeneticists may be familiar with. The cartoon showed, in 1997, a renowned scientist standing up on a podium and declaring “cytogenetics is dead”. Then, we see the same scientist in 2007 saying the same thing, and then again in 2017 saying the same thing. I don’t know of any lab whose cytogenetics workload has decreased yet, but in the final frame of the cartoon, the renowned scientist is dead, and that's it.

4. Summary

In this debate, the supporting argument from the molecular genetics advocate demonstrated that the diagnostic value of sequencing represents a more comprehensive and higher‐resolution genetic screen for prenatal diagnostics, and that the future will be driven by unbiased genome‐wide invasive and non‐invasive sequencing technologies. The rebuttal argument from the cytogenetics advocate articulated that the science and discipline of chromosomal behavior is vital to retain in our field, and that the clinical management must have access to a toolbox of diagnostic modalities to best serve patients. It also emphasized that the existing infrastructure and expertise dictate the current testing landscape. In the concluding comments, both debaters agree that the science of understanding chromosomes is essential to the field of clinical genetics and that education and training remain central to our overarching mission as a field to support patients and improve healthcare outcomes.

Conflicts of Interest

Dr. Talkowski's laboratory and consortia projects have received scientific support (reagents, data, and/or resources) from the following companies: Pacific Biosciences, Oxford Nanopore Technologies, Bionano, Illumina, Microsoft, Levo Therapeutics (Acadia), Ionis Pharmaceuticals, and he is a co‐founder of First Genomic Insights. Dr. Talkowski is an inventor on patent PCT/US2023/031556 filed by Massachusetts General Hospital.

Akkari, Yassmine M. N. , Talkowski Michael E., and Breman Amy M.. 2025. “International Society for Prenatal Diagnosis 2024 Debate 3—Cytogenetics Is a Dinosaur and Should Be Replaced by Molecular Technologies.” Prenatal Diagnosis: 1334–1342. 10.1002/pd.6847.

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.