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Background Complex chromosomal rearrangements (CCRs) are associated with high reproductive risk, infertility, abnormalities in offspring, and recurrent miscarriage in women. It is essential to accurately characterize apparently balanced chromosome rearrangements in unaffected individuals. Methods A CCR young couple who suffered two spontaneous abortions and underwent labor induction due to fetal chromosomal abnormalities was studied using long‐read sequencing(LRS), single‐nucleotide polymorphism (SNP) array, G‐banding karyotype analysis (550‐band resolution), and Sanger sequencing. Results SNP analysis of the amniotic fluid cells during the third pregnancy revealed a 9.9‐Mb duplication at 7q21.11q21.2 and a 24.8‐Mb heterozygous deletion at 13q21.1q31.1. The unaffected female partner was a carrier of a three‐way CCR [46,XX,? ins(7;13)(q21.1;q21.1q22)t(2;13)(p23;q22)]. Subsequent LRS analysis revealed the exact breakpoint locations on the derivative chromosomes and the specific method of chromosome rearrangement, indicating that the CCR carrier was a more complex structural rearrangement comprising five breakpoints. Furthermore, LRS detected an inserted fragment of chromosome 13 in chromosome 7. Conclusions LRS is effective for analyzing the complex structural variations of the human genome and may be used to clarify the specific CCRs for effective genetic counseling and appropriate intervention. This study investigated a de novo case of complex chromosomal rearrangement (CRR) in a young couple visited our hospital for genetic counseling and fertility guidance due to the increased thickness of the fetal nuchal translucency. We successfully identified the female partner as a carrier of a three‐way CCR [46, XX, ? ins(7; 13)(q21.1;q21.1q22)t(2;13)(p23;q22)] using high‐resolution G‐banding karyotype analysis (550‐band resolution). Third‐generation sequencing (TGS) using PromethION platform revealed that the five breakpoints on chromosomes 2, 7, and 13 (2:18044504, 7:82511487, 7:92482297, 13:56958850, and 13:81861586) participated in the CCR.

Recent studies demonstrate that whole-genome sequencing enables detection of cryptic rearrangements in apparently balanced chromosomal rearrangements (also known as balanced chromosomal abnormalities, BCAs) previously identified by conventional cytogenetic methods. We aimed to assess our analytical tool for detecting BCAs in the 1000 Genomes Project without knowing which bands were affected. The 1000 Genomes Project provides an unprecedented integrated map of structural variants in phenotypically normal subjects, but there is no information on potential inclusion of subjects with apparent BCAs akin to those traditionally detected in diagnostic cytogenetics laboratories. We applied our analytical tool to 1,166 genomes from the 1000 Genomes Project with sufficient physical coverage (8.25-fold). With this approach, we detected four reciprocal balanced translocations and four inversions, ranging in size from 57.9kb to 13.3Mb, all of which were confirmed by cytogenetic methods and polymerase chain reaction studies. One of these DNAs has a subtle translocation that is not readily identified by chromosome analysis because of the similarity of the banding patterns and size of exchanged segments, and another results in disruption of all transcripts of an OMIM gene. Our study demonstrates the extension of utilizing low-pass whole-genome sequencing for unbiased detection of BCAs including translocations and inversions previously unknown in the 1000 Genomes Project.

Yanfeng Qin,1 Yan Mei,2 Bailing Liu,2 Sumei Wang1 1Department of Obstetrics, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China; 2Department of Obstetrics, Liuzhou Maternal and Child Health Hospital, Liuzhou, Guangxi Zhuang Autonomous Region, People’s Republic of ChinaCorrespondence: Sumei Wang, Department of Obstetrics, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China, Email 187176076@qq.comBackground: Fetal growth restriction (FGR) is a significant cause of perinatal morbidity and mortality. This study aimed to verify whether high-throughput sequencing technologies (Copy Number Variation Sequencing, CNV-seq; Trio Whole Exome Sequencing, Trio-WES) can overcome the limitations of traditional karyotype analysis and improve the detection rate of genetic etiologies in FGR fetuses, and to analyze associated pregnancy outcomes.Methods: A retrospective analysis was conducted on 235 fetuses who underwent invasive prenatal diagnosis following ultrasound-diagnosed fetal growth restriction (FGR) at Liuzhou Maternal and Child Health Hospital between January 2019 and March 2025. All cases underwent concurrent chromosomal karyotyping and genome-wide copy number variation sequencing (CNV-seq). Among these, 19 cases with normal results from both karyotyping and CNV-seq were further analyzed using trio-whole exome sequencing (Trio-WES). For karyotyping and CNV-seq, genomic DNA was extracted from amniotic fluid or umbilical cord blood samples. For Trio-WES, genomic DNA was obtained from fetal amniotic fluid or umbilical cord blood, along with peripheral blood samples from both parents as controls.Results: Among the 235 FGR specimens, chromosomal abnormalities were detected in 9 cases (3.8%, 9/235) by karyotype analysis of chromosomes, and 26 cases (11.1%,26/235) by CNV-seq technology.Among FGR cases with normal karyotypes, CNV-seq detected an additional 17 abnormalities (7.5%, 17/226). When comparing the two techniques, the abnormal detection rate of CNV-seq technology was higher than that of karyotype analysis, and the difference was statistically significant (P < 0.05). Among the 19 cases negative for both karyotype and CNV-seq, Trio-WES detected 6 abnormalities (31.6%, 6/19), including 3 pathogenic variants, 1 likely pathogenic variant, and 2 variants of uncertain significance (VOUS). A total of 32 cases (13.6%, 32/235) of abnormal variations were detected by the combination of karyotype analysis and high-throughput sequencing. Pregnancy outcomes included: all 9 karyotype-abnormal cases chose termination of pregnancy (TOP); of the 17 CNV-seq-abnormal cases (karyotype-normal), 10 underwent TOP (3 with combined organ malformations) and 7 had live births (6 with normal follow-up to 2 years, 1 with developmental delay and hypertonia at 2-year follow-up); of the 6 Trio-WES-abnormal cases, 5underwent TOP and1 had live births (1 with normal follow-up).Conclusion: Compared with traditional karyotype analysis (3.8% detection rate), high-throughput sequencing technologies (CNV-seq and Trio-WES) significantly improve the detection rate of genetic abnormalities in FGR fetuses to 13.6%. The “karyotype analysis + CNV-seq + Trio-WES” stepwise detection protocol provides critical support for prenatal genetic counseling and clinical decision-making,and contributes to optimizing pregnancy management and outcomes.Keywords: fetal growth restriction, high-throughput sequencing, karyotype analysis of chromosomes, prenatal diagnosis, pregnancy outcome

Objective This study aims to evaluate the association between ultrasound soft markers and fetal chromosomal abnormalities and to compare the diagnostic efficacy of karyotype analysis versus chromosomal microarray analysis (CMA) for prenatal testing strategy optimization. Materials and methods A retrospective review was conducted on 622 cases receiving prenatal diagnosis for abnormal ultrasound soft markers at our center over three years. All cases underwent chromosomal karyotype analysis and CMA testing. The differences between the results of these two tests, as well as the correlation between genetic testing results and abnormal ultrasound soft markers, were analyzed. Additionally, the pregnancy outcomes and postnatal phenotypes of all cases were monitored. Results The overall prevalence of chromosomal abnormalities was 11.41% (71/622). Echogenic intracardiac focus ( P  = 0.012) and multiple soft markers ( P  < 0.001) exhibited a higher correlation with chromosomal abnormalities, with the latter showing a particularly strong association with aneuploidy ( P  < 0.001). Karyotype analysis identified 63 chromosomal abnormalities, while CMA detected 65, with discordant results observed in 18 cases. Among the cases with chromosomal abnormalities, 11 resulted in live births, and follow-up at ages 3–5 revealed no abnormal phenotypes. Conclusion Prenatal genetic diagnosis is strongly recommended for pregnant women presenting with ultrasound soft markers, particularly multiple markers. Concurrent CMA and karyotype analysis are advocated to minimize the risk of missing pathogenic variants.

The fully automatic chromosome analysis system plays an important role in the detection of genetic diseases, which in turn can reduce the diagnosis burden for cytogenetic experts. Chromosome segmentation is a critical step for such a system. However, due to the non-rigid structure of chromosomes, chromosomes may curve in any direction, and two or more chromosomes may touch or overlap to form unpredictable chromosome clusters in metaphase chromosome images, leading to automatic chromosome segmentation as a challenge. In this paper, we propose an automatic progressive segmentation approach to perform the entire metaphase chromosome image segmentation using deep learning with traditional image processing. It follows three stages. In the first stage, thresholding-based and geometric-based methods are employed to divide all chromosomes as single ones and chromosome clusters. To tackle the segmentation for unpredictable chromosome clusters, we first present a new chromosome cluster identification network named CCI-Net to classify all chromosome clusters into different types in the second stage, and then in the third stage, we combine traditional image processing with deep CNNs to accomplish chromosome instance segmentation from different types of clusters. Evaluation results on a clinical dataset of 1148 metaphase chromosome images show that the proposed automatic progressive segmentation method achieves 94.60% chromosome cluster identification accuracy and 99.15% instance segmentation accuracy. The experimental results exhibit that our proposed approach can effectively identify chromosome clusters and successfully perform fully automatic chromosome segmentation. Graphical Abstract

Background: The joint College of American Pathologists/American College of Medical Genetics and Genomics Cytogenetics Committee works to ensure the competency and proficiency of clinical cytogenetic testing laboratories through proficiency testing (PT) programs for various clinical tests offered by such laboratories, including the evaluation of cytogenetic abnormalities in solid tumors. Methods: Review and analyze 25 years (1999–2023) of solid tumor chromosome analysis PT results, utilizing G-banded karyograms. A retrospective review of results from 1999 to 2023 was performed, identifying the challenges addressing solid tumors. The chromosomal abnormalities and overall performance were evaluated. Results: A total of 21 solid tumor challenges were administered during the period 1999–2018. No solid tumor challenges were administered during the period 2019–2023. Challenges consisted of metaphase images and accompanying clinical history for the evaluation of numerical and/or structural abnormalities. All 21 cases reached 80% grading consensus for abnormality recognition. However, five cases (24%) failed to reach consensus for nomenclature reporting by participating laboratories. These cases illustrate errors in reporting chromosomal abnormalities, including whole-arm translocations and those involving sex chromosomes. In addition, they highlight the challenges with differentiation of terminal and interstitial deletions, difficulties in identifying correct breakpoints, and omission of brackets in neoplastic cases. Conclusions: This comprehensive 25-year review demonstrates the exceptional proficiency of cytogenetic laboratories in accurately identifying chromosome abnormalities in solid tumors, while also highlighting the challenges of reporting specific types of chromosomal abnormalities.

Chromosomal microarray analysis enables the detection of microdeletions/duplications and has become the standard in clinical diagnostic testing for individuals with congenital anomalies and developmental disabilities. In the era of genomic arrays, the value of traditional chromosome analysis needs to be reassessed. We studied 3,710 unrelated patients by chromosomal microarray analysis and chromosome analysis simultaneously and compared the results. We found that chromosomal microarray analysis detected the chromosomal imbalances that were identified by chromosome analysis with the exception of six cases (0.16%) that had mosaic abnormalities. Of note, one case showed mosaicism for two abnormal cell lines, resulting in a balanced net effect and a normal chromosomal microarray analysis. Further structural abnormalities such as unbalanced translocations, rings, and complex rearrangements were subsequently clarified by chromosome analysis in 18% of the cases with abnormal chromosomal microarray analysis results. Apparently balanced rearrangements were detected by chromosome analysis in 30 cases (0.8%). Our data demonstrate that although chromosomal microarray analysis should be the first-tier test for clinical diagnosis of chromosome abnormalities, chromosome analysis remains valuable in the detection of mosaicism and delineation of chromosomal structural rearrangements. Genet Med 2013:15(6):450–457

Satellited non-acrocentric autosomal chromosomes (ps–qs-chromosomes) are the result of an interchange between sub- or telomeric regions of autosomes and the p arm of acrocentrics. The sequence homology at the rearrangement breakpoints appears to be, among others, the most frequent mechanism generating these variant chromosomes. The unbalanced carriers of this type of translocation may or may not display phenotypic abnormalities. With the aim to understand the causative mechanism, we revised all the ps–qs-chromosomes identified in five medical genetics laboratories, which used the same procedures for karyotype analysis, reporting 24 unrelated cases involving eight chromosomes. In conclusion, we observed three different scenarios: true translocation, benign variant and complex rearrangement. The detection of translocation partners is essential to evaluate possible euchromatic unbalances and to infer their effect on phenotype. Moreover, we emphasize the importance to perform both, molecular and conventional cytogenetics methods, to better understand the behavior of our genome.

Artificial intelligence (AI) has entered the medical subspecialty of cytogenetics with the recent introduction of AI-guided karyotyping into the clinical laboratory. Karyotyping is an essential component of the cytogenetic analysis process; however, it is both labor-intensive and time-consuming. The introduction of AI algorithms into karyotyping software streamlines this process to provide accurate and abundant auto-karyotyped images for laboratory professionals to review and, also, alters the paradigm for chromosome analysis. Herein, we provide an overview of the AI-guided karyotyping products currently available for clinical use, discuss their utilization in the cytogenetics laboratory, and highlight changes AI-guided karyotyping has brought for early users. Finally, we reflect on our own laboratory observations and experience to discuss issues and practices that may need to adapt to best utilize this promising new technology.

Chromosomal inversion polymorphisms have special importance in the Anopheles gambiae complex of malaria vector mosquitoes, due to their role in local adaptation and range expansion. The study of inversions in natural populations is reliant on polytene chromosome analysis by expert cytogeneticists, a process that is limited by the rarity of trained specialists, low throughput, and restrictive sampling requirements. To overcome this barrier, we ascertained tag single nucleotide polymorphisms (SNPs) that are highly correlated with inversion status (inverted or standard orientation). We compared the performance of the tag SNPs using two alternative high throughput molecular genotyping approaches vs. traditional cytogenetic karyotyping of the same 960 individual An. gambiae and An. coluzzii mosquitoes sampled from Burkina Faso, West Africa. We show that both molecular approaches yield comparable results, and that either one performs as well or better than cytogenetics in terms of genotyping accuracy. Given the ability of molecular genotyping approaches to be conducted at scale and at relatively low cost without restriction on mosquito sex or developmental stage, molecular genotyping via tag SNPs has the potential to revitalize research into the role of chromosomal inversions in the behavior and ongoing adaptation of An. gambiae and An. coluzzii to environmental heterogeneities.