Estrogen receptor alpha mutations, truncations, heterodimers, and therapies.

Annual breast cancer (BCa) deaths have declined since its apex in 1989 concomitant with widespread adoption of hormone therapies that target estrogen receptor alpha (ERα), the prominent nuclear receptor expressed in ∼80% of BCa. However, up to ∼50% of ER + patients with high-risk disease experience post endocrine therapy relapse and metastasis to distant organs. The vast majority of BCa mortality occurs in this setting, highlighting the inadequacy of current therapies. Genomic abnormalities to ESR1, the gene encoding ERα, emerge under prolonged selective pressure to enable endocrine therapy resistance. These genetic lesions include focal gene amplifications, hotspot missense mutations in the ligand binding domain, truncations, fusions, and complex interactions with other nuclear receptors. Tumor cells utilize aberrant ERα activity to proliferate, spread and evade therapy in BCa as well as other cancers. Cutting edge studies on ERα structural and transcriptional relationships are being harnessed to produce new therapies that have shown benefits in patients with ESR1 hotspot mutations. In this review we discuss the history of ERα, current research unlocking unknown aspects of ERα signaling including the structural basis for receptor antagonism, and future directions of ESR1 investigation. In addition, we discuss the development of endocrine therapies from their inception to present day and survey new avenues of drug development to improve pharmaceutical profiles, targeting, and efficacy.

How structural variants shape avian phenotypes: Lessons from model systems.

Despite receiving significant recent attention, the relevance of structural variation (SV) in driving phenotypic diversity remains understudied, although recent advances in long-read sequencing, bioinformatics and pangenomic approaches have enhanced SV detection. We review the role of SVs in shaping phenotypes in avian model systems, and identify some general patterns in SV type, length and their associated traits. We found that most of the avian SVs so far identified are short indels in chickens, which are frequently associated with changes in body weight and plumage colouration. Overall, we found that relatively short SVs are more frequently detected, likely due to a combination of their prevalence compared to large SVs, and a detection bias, stemming primarily from the widespread use of short-read sequencing and associated analytical methods. SVs most commonly involve non-coding regions, especially introns, and when patterns of inheritance were reported, SVs associated primarily with dominant discrete traits. We summarise several examples of phenotypic convergence across different species, mediated by different SVs in the same or different genes and different types of changes in the same gene that can lead to various phenotypes. Complex rearrangements and supergenes, which can simultaneously affect and link several genes, tend to have pleiotropic phenotypic effects. Additionally, SVs commonly co-occur with single-nucleotide polymorphisms, highlighting the need to consider all types of genetic changes to understand the basis of phenotypic traits. We end by summarising expectations for when long-read technologies become commonly implemented in non-model birds, likely leading to an increase in SV discovery and characterisation. The growing interest in this subject suggests an increase in our understanding of the phenotypic effects of SVs in upcoming years.

Optical Genome Mapping Reveals Genomic Alterations upon Gene Editing in hiPSCs: Implications for Neural Tissue Differentiation and Brain Organoid Research.

Genome editing, notably CRISPR (cluster regularly interspaced short palindromic repeats)/Cas9 (CRISPR-associated protein 9), has revolutionized genetic engineering allowing for precise targeted modifications. This technique's combination with human induced pluripotent stem cells (hiPSCs) is a particularly valuable tool in cerebral organoid (CO) research. In this study, CRISPR/Cas9-generated fluorescently labeled hiPSCs exhibited no significant morphological or growth rate differences compared with unedited controls. However, genomic aberrations during gene editing necessitate efficient genome integrity assessment methods. Optical genome mapping, a high-resolution genome-wide technique, revealed genomic alterations, including chromosomal copy number gain and losses affecting numerous genes. Despite these genomic alterations, hiPSCs retain their pluripotency and capacity to generate COs without major phenotypic changes but one edited cell line showed potential neuroectodermal differentiation impairment. Thus, this study highlights optical genome mapping in assessing genome integrity in CRISPR/Cas9-edited hiPSCs emphasizing the need for comprehensive integration of genomic and morphological analysis to ensure the robustness of hiPSC-based models in cerebral organoid research.

Germline structural variation globally impacts the cancer transcriptome including disease-relevant genes.

Germline variation and somatic alterations contribute to the molecular profile of cancers. We combine RNA with whole genome sequencing across 1,218 cancer patients to determine the extent germline structural variants (SVs) impact expression of nearby genes. For hundreds of genes, recurrent and common germline SV breakpoints within 100 kb associate with increased or decreased expression in tumors spanning various tissues of origin. A significant fraction of germline SV expression associations involves duplication of intergenic enhancers or 3' UTR disruption. Genes altered by both somatic and germline SVs include ATRX and CEBPA. Genes essential in cancer cell lines include BARD1 and IRS2. Genes with both expression and germline SV breakpoint patterns associated with patient survival include GCLM. Our results capture a class of phenotypic variation at work in the disease setting, including genes with cancer roles. Specific germline SVs represent potential cancer risk variants for genetic testing, including those involving genes with targeting implications.

On- and off-target effects of paired CRISPR-Cas nickase in primary human cells.

Undesired on- and off-target effects of CRISPR-Cas nucleases remain a challenge in genome editing. While the use of Cas9 nickases has been shown to minimize off-target mutagenesis, their use in therapeutic genome editing has been hampered by a lack of efficacy. To overcome this limitation, we and others have developed double-nickase-based strategies to generate staggered DNA double-strand breaks to mediate gene disruption or gene correction with high efficiency. However, the impact of paired single-strand nicks on genome integrity has remained largely unexplored. Here, we developed a novel CAST-seq pipeline, dual CAST, to characterize chromosomal aberrations induced by paired CRISPR-Cas9 nickases at three different loci in primary keratinocytes derived from patients with epidermolysis bullosa. While targeting COL7A1, COL17A1, or LAMA3 with Cas9 nucleases caused previously undescribed chromosomal rearrangements, no chromosomal translocations were detected following paired-nickase editing. While the double-nicking strategy induced large deletions/inversions within a 10 kb region surrounding the target sites at all three loci, similar to the nucleases, the chromosomal on-target aberrations were qualitatively different and included a high proportion of insertions. Taken together, our data indicate that double-nickase approaches combine efficient editing with greatly reduced off-target effects but still leave substantial chromosomal aberrations at on-target sites.

Long read sequencing on its way to the routine diagnostics of genetic diseases.

The clinical application of technological progress in the identification of DNA alterations has always led to improvements of diagnostic yields in genetic medicine. At chromosome side, from cytogenetic techniques evaluating number and gross structural defects to genomic microarrays detecting cryptic copy number variants, and at molecular level, from Sanger method studying the nucleotide sequence of single genes to the high-throughput next-generation sequencing (NGS) technologies, resolution and sensitivity progressively increased expanding considerably the range of detectable DNA anomalies and alongside of Mendelian disorders with known genetic causes. However, particular genomic regions (i.e., repetitive and GC-rich sequences) are inefficiently analyzed by standard genetic tests, still relying on laborious, time-consuming and low-sensitive approaches (i.e., southern-blot for repeat expansion or long-PCR for genes with highly homologous pseudogenes), accounting for at least part of the patients with undiagnosed genetic disorders. Third generation sequencing, generating long reads with improved mappability, is more suitable for the detection of structural alterations and defects in hardly accessible genomic regions. Although recently implemented and not yet clinically available, long read sequencing (LRS) technologies have already shown their potential in genetic medicine research that might greatly impact on diagnostic yield and reporting times, through their translation to clinical settings. The main investigated LRS application concerns the identification of structural variants and repeat expansions, probably because techniques for their detection have not evolved as rapidly as those dedicated to single nucleotide variants (SNV) identification: gold standard analyses are karyotyping and microarrays for balanced and unbalanced chromosome rearrangements, respectively, and southern blot and repeat-primed PCR for the amplification and sizing of expanded alleles, impaired by limited resolution and sensitivity that have not been significantly improved by the advent of NGS. Nevertheless, more recently, with the increased accuracy provided by the latest product releases, LRS has been tested also for SNV detection, especially in genes with highly homologous pseudogenes and for haplotype reconstruction to assess the parental origin of alleles with de novo pathogenic variants. We provide a review of relevant recent scientific papers exploring LRS potential in the diagnosis of genetic diseases and its potential future applications in routine genetic testing.

Whole-Genome Sequencing Analysis of Male Breast Cancer Unveils Novel Structural Events and Potential Therapeutic Targets.

The molecular characterization of male breast cancer (MaBC) has received limited attention in research, mostly because of its low incidence rate, accounting for only 0.5% to 1% of all reported cases of breast cancer each year. Managing MaBC presents significant challenges, with most treatment protocols being adapted from those developed for female breast cancer. Utilizing whole-genome sequencing (WGS) and state-of-the-art analyses, the genomic features of 10 MaBC cases (n = 10) were delineated and correlated with clinical and histopathologic characteristics. Using fluorescence in situ hybridization, an additional cohort of 18 patients was interrogated to supplement WGS findings. The genomic landscape of MaBC uncovered significant genetic alterations that could influence diagnosis and treatment. We found common somatic mutations in key driver genes, such as FAT1, GATA3, SMARCA4, and ARID2. Our study also mapped out structural variants that impact cancer-associated genes, such as ARID1A, ESR1, GATA3, NTRK1, and NF1. Using a WGS-based classifier, homologous recombination deficiency (HRD) was identified in 2 cases, both presenting with deleterious variants in BRCA2. Noteworthy was the observation of FGFR1 amplification in 21% of cases. Altogether, we identified at least 1 potential therapeutic target in 8 of the 10 cases, including high tumor mutational burden, FGFR1 amplification, and HRD. Our study is the first WGS characterization of MaBC, which uncovered potentially relevant variants, including structural events in cancer genes, HRD signatures, and germline pathogenic mutations. Our results demonstrate unique genetic markers and potential treatment targets in MaBC, thereby underlining the necessity of tailoring treatment strategies for this understudied patient population. These WGS-based findings add to the growing knowledge of MaBC genomics and highlight the need to expand research on this type of cancer.

Diallel panel reveals a significant impact of low-frequency genetic variants on gene expression variation in yeast.

Unraveling the genetic sources of gene expression variation is essential to better understand the origins of phenotypic diversity in natural populations. Genome-wide association studies identified thousands of variants involved in gene expression variation, however, variants detected only explain part of the heritability. In fact, variants such as low-frequency and structural variants (SVs) are poorly captured in association studies. To assess the impact of these variants on gene expression variation, we explored a half-diallel panel composed of 323 hybrids originated from pairwise crosses of 26 natural Saccharomyces cerevisiae isolates. Using short- and long-read sequencing strategies, we established an exhaustive catalog of single nucleotide polymorphisms (SNPs) and SVs for this panel. Combining this dataset with the transcriptomes of all hybrids, we comprehensively mapped SNPs and SVs associated with gene expression variation. While SVs impact gene expression variation, SNPs exhibit a higher effect size with an overrepresentation of low-frequency variants compared to common ones. These results reinforce the importance of dissecting the heritability of complex traits with a comprehensive catalog of genetic variants at the population level.

Structural genomic variation in the inbred Scandinavian wolf population contributes to the realized genetic load but is positively affected by immigration.

When populations decrease in size and may become isolated, genomic erosion by loss of diversity from genetic drift and accumulation of deleterious mutations is likely an inevitable consequence. In such cases, immigration (genetic rescue) is necessary to restore levels of genetic diversity and counteract inbreeding depression. Recent work in conservation genomics has studied these processes focusing on the genetic diversity of single nucleotide polymorphisms. In contrast, our knowledge about structural genomic variation (insertions, deletions, duplications and inversions) in endangered species is limited. We analysed whole-genome, short-read sequences from 212 wolves from the inbred Scandinavian population and from neighbouring populations in Finland and Russia, and detected >35,000 structural variants (SVs) after stringent quality and genotype frequency filtering; >26,000 high-confidence variants remained after manual curation. The majority of variants were shorter than 1 kb, with a distinct peak in the length distribution of deletions at 190 bp, corresponding to insertion events of SINE/tRNA-Lys elements. The site frequency spectrum of SVs in protein-coding regions was significantly shifted towards rare alleles compared to putatively neutral variants, consistent with purifying selection. The realized genetic load of SVs in protein-coding regions increased with inbreeding levels in the Scandinavian population, but immigration provided a genetic rescue effect by lowering the load and reintroducing ancestral alleles at loci fixed for derived SVs. Our study shows that structural variation comprises a common type of in part deleterious mutations in endangered species and that establishing gene flow is necessary to mitigate the negative consequences of loss of diversity.

Genomic vulnerability of a freshwater salmonid under climate change.

Understanding the adaptive potential of populations and species is pivotal for minimizing the loss of biodiversity in this era of rapid climate change. Adaptive potential has been estimated in various ways, including based on levels of standing genetic variation, presence of potentially beneficial alleles, and/or the severity of environmental change. Kokanee salmon, the non-migratory ecotype of sockeye salmon (Oncorhynchus nerka), is culturally and economically important and has already been impacted by the effects of climate change. To assess its climate vulnerability moving forward, we integrated analyses of standing genetic variation, genotype-environment associations, and climate modeling based on sequence and structural genomic variation from 224 whole genomes sampled from 22 lakes in British Columbia and Yukon (Canada). We found that variables for extreme temperatures, particularly warmer temperatures, had the most pervasive signature of selection in the genome and were the strongest predictors of levels of standing variation and of putatively adaptive genomic variation, both sequence and structural. Genomic offset estimates, a measure of climate vulnerability, were significantly correlated with higher increases in extreme warm temperatures, further highlighting the risk of summer heat waves that are predicted to increase in frequency in the future. Levels of standing genetic variation, an important metric for population viability and resilience, were not correlated with genomic offset. Nonetheless, our combined approach highlights the importance of integrating different sources of information and genomic data to formulate more comprehensive and accurate predictions on the vulnerability of populations and species to future climate change.

T/myeloid mixed phenotype acute leukaemia harbouring TLX3::BCL11B with TLX3 activation.

T/myeloid mixed phenotype acute leukaemia (MPAL) is a rare aggressive acute leukaemia with poorly understood pathogenesis. Herein, we report two cases of T/myeloid MPAL harbouring BCL11B-associated structural variants that activate TLX3 (TLX3::BCL11B-TLX3-activation) by genome sequencing and transcriptomic analyses. Both patients were young males with extramedullary involvement. Cooperative gene alterations characteristic of T/myeloid MPAL and T-lymphoblastic leukaemia (T-ALL) were detected. Both patients achieved initial remission following lineage-matched ALL-based therapy with one patient requiring a lineage-switched myeloid-based therapy. Our study is the first to demonstrate the clinicopathological and genomic features of TLX3::BCL11B-TLX3-activated T/myeloid MPAL and provide insights into leukaemogenesis.

Reference-free Structural Variant Detection in Microbiomes via Long-read Coassembly Graphs.

Bacterial genome dynamics are vital for understanding the mechanisms underlying microbial adaptation, growth, and their broader impact on host phenotype. Structural variants (SVs), genomic alterations of 10 base pairs or more, play a pivotal role in driving evolutionary processes and maintaining genomic heterogeneity within bacterial populations. While SV detection in isolate genomes is relatively straightforward, metagenomes present broader challenges due to absence of clear reference genomes and presence of mixed strains. In response, our proposed method rhea, forgoes reference genomes and metagenome-assembled genomes (MAGs) by encompassing a single metagenome coassembly graph constructed from all samples in a series. The log fold change in graph coverage between subsequent samples is then calculated to call SVs that are thriving or declining throughout the series. We show rhea to outperform existing methods for SV and horizontal gene transfer (HGT) detection in two simulated mock metagenomes, which is particularly noticeable as the simulated reads diverge from reference genomes and an increase in strain diversity is incorporated. We additionally demonstrate use cases for rhea on series metagenomic data of environmental and fermented food microbiomes to detect specific sequence alterations between subsequent time and temperature samples, suggesting host advantage. Our innovative approach leverages raw read patterns rather than references or MAGs to include all sequencing reads in analysis, and thus provide versatility in studying SVs across diverse and poorly characterized microbial communities for more comprehensive insights into microbial genome dynamics.

A graph-based pan-genome of Brassica oleracea provides new insights into its domestication and morphotype diversification.

The domestication of Brassica oleracea has resulted in diverse morphological types with distinct patterns of organ development. Here we report a graph-based pan-genome of B. oleracea constructed from high-quality genome assemblies of different morphotypes. The pan-genome harbors over 200 structural variant hotspot regions enriched in auxin- and flowering-related genes. Population genomic analyses revealed that early domestication of B. oleracea focused on leaf or stem development. Gene flows resulting from agricultural practices and variety improvement were detected among different morphotypes. Selective-sweep and pan-genome analyses identified an auxin-responsive small auxin up-regulated RNA gene and a CLAVATA3/ESR-RELATED family gene as crucial players in leaf-stem differentiation during the early stage of B. oleracea domestication and the BoKAN1 gene as instrumental in shaping the leafy heads of cabbage and Brussels sprouts. Our pan-genome and functional analyses further revealed that variations in the BoFLC2 gene play key roles in the divergence of vernalization and flowering characteristics among different morphotypes, and variations in the first intron of BoFLC3 are involved in fine-tuning the flowering process in cauliflower. This study provides a comprehensive understanding of the pan-genome of B. oleracea and sheds light on the domestication and differential organ development of this globally important crop species.

Ku80 is indispensable for repairing DNA double-strand breaks at highly methylated sites in human HCT116 cells.

DNA double-strand breaks (DSBs) are harmful to mammalian cells and a few of them can cause cell death. Accumulating DSBs in these cells to analyze their genomic distribution and their potential impact on chromatin structure is difficult. In this study, we used CRISPR to generate Ku80-/- human cells and arrested the cells in G1 phase to accumulate DSBs before conducting END-seq and Nanopore analysis. Our analysis revealed that DNA with high methylation level accumulates DSB hotspots in Ku80-/- human cells. Furthermore, we identified chromosome structural variants (SVs) using Nanopore sequencing and observed a higher number of SVs in Ku80-/- human cells. Based on our findings, we suggest that the high efficiency of Ku80 knockout in human HCT116 cells makes it a promising model for characterizing SVs in the context of 3D chromatin structure and studying the alternative-end joining (Alt-EJ) DSB repair pathway.

Whole-Genome Sequencing Analysis Reveals New Susceptibility Loci and Structural Variants Associated with Progressive Supranuclear Palsy.

Background: Progressive supranuclear palsy (PSP) is a rare neurodegenerative disease characterized by the accumulation of aggregated tau proteins in astrocytes, neurons, and oligodendrocytes. Previous genome-wide association studies for PSP were based on genotype array, therefore, were inadequate for the analysis of rare variants as well as larger mutations, such as small insertions/deletions (indels) and structural variants (SVs). Method: In this study, we performed whole genome sequencing (WGS) and conducted association analysis for single nucleotide variants (SNVs), indels, and SVs, in a cohort of 1,718 cases and 2,944 controls of European ancestry. Of the 1,718 PSP individuals, 1,441 were autopsy-confirmed and 277 were clinically diagnosed. Results: Our analysis of common SNVs and indels confirmed known genetic loci at MAPT, MOBP, STX6, SLCO1A2, DUSP10, and SP1, and further uncovered novel signals in APOE, FCHO1/MAP1S, KIF13A, TRIM24, TNXB, and ELOVL1. Notably, in contrast to Alzheimer's disease (AD), we observed the APOE ε2 allele to be the risk allele in PSP. Analysis of rare SNVs and indels identified significant association in ZNF592 and further gene network analysis identified a module of neuronal genes dysregulated in PSP. Moreover, seven common SVs associated with PSP were observed in the H1/H2 haplotype region (17q21.31) and other loci, including IGH, PCMT1, CYP2A13, and SMCP. In the H1/H2 haplotype region, there is a burden of rare deletions and duplications (P = 6.73×10-3) in PSP. Conclusions: Through WGS, we significantly enhanced our understanding of the genetic basis of PSP, providing new targets for exploring disease mechanisms and therapeutic interventions.

A graph clustering algorithm for detection and genotyping of structural variants from long reads.

BACKGROUND: Structural variants (SVs) are genomic polymorphisms defined by their length (>50 bp). The usual types of SVs are deletions, insertions, translocations, inversions, and copy number variants. SV detection and genotyping is fundamental given the role of SVs in phenomena such as phenotypic variation and evolutionary events. Thus, methods to identify SVs using long-read sequencing data have been recently developed. FINDINGS: We present an accurate and efficient algorithm to predict germline SVs from long-read sequencing data. The algorithm starts collecting evidence (signatures) of SVs from read alignments. Then, signatures are clustered based on a Euclidean graph with coordinates calculated from lengths and genomic positions. Clustering is performed by the DBSCAN algorithm, which provides the advantage of delimiting clusters with high resolution. Clusters are transformed into SVs and a Bayesian model allows to precisely genotype SVs based on their supporting evidence. This algorithm is integrated into the single sample variants detector of the Next Generation Sequencing Experience Platform, which facilitates the integration with other functionalities for genomics analysis. We performed multiple benchmark experiments, including simulation and real data, representing different genome profiles, sequencing technologies (PacBio HiFi, ONT), and read depths. CONCLUSION: The results show that our approach outperformed state-of-the-art tools on germline SV calling and genotyping, especially at low depths, and in error-prone repetitive regions. We believe this work significantly contributes to the development of bioinformatic strategies to maximize the use of long-read sequencing technologies.

Genome-wide association study between copy number variation and feeding behavior, feed efficiency, and growth traits in Nellore cattle.

BACKGROUND: Feeding costs represent the largest expenditures in beef production. Therefore, the animal efficiency in converting feed in high-quality protein for human consumption plays a major role in the environmental impact of the beef industry and in the beef producers' profitability. In this context, breeding animals for improved feed efficiency through genomic selection has been considered as a strategic practice in modern breeding programs around the world. Copy number variation (CNV) is a less-studied source of genetic variation that can contribute to phenotypic variability in complex traits. In this context, this study aimed to: (1) identify CNV and CNV regions (CNVRs) in the genome of Nellore cattle (Bos taurus indicus); (2) assess potential associations between the identified CNVR and weaning weight (W210), body weight measured at the time of selection (WSel), average daily gain (ADG), dry matter intake (DMI), residual feed intake (RFI), time spent at the feed bunk (TF), and frequency of visits to the feed bunk (FF); and, (3) perform functional enrichment analyses of the significant CNVR identified for each of the traits evaluated. RESULTS: A total of 3,161 CNVs and 561 CNVRs ranging from 4,973 bp to 3,215,394 bp were identified. The CNVRs covered up to 99,221,894 bp (3.99%) of the Nellore autosomal genome. Seventeen CNVR were significantly associated with dry matter intake and feeding frequency (number of daily visits to the feed bunk). The functional annotation of the associated CNVRs revealed important candidate genes related to metabolism that may be associated with the phenotypic expression of the evaluated traits. Furthermore, Gene Ontology (GO) analyses revealed 19 enrichment processes associated with FF. CONCLUSIONS: A total of 3,161 CNVs and 561 CNVRs were identified and characterized in a Nellore cattle population. Various CNVRs were significantly associated with DMI and FF, indicating that CNVs play an important role in key biological pathways and in the phenotypic expression of feeding behavior and growth traits in Nellore cattle.

The chromosome-level assembly of the wild diploid alfalfa genome provides insights into the full landscape of genomic variations between cultivated and wild alfalfa.

Alfalfa (Medicago sativa L.) is one of the most important forage legumes in the world, including autotetraploid (M. sativa ssp. sativa) and diploid alfalfa (M. sativa ssp. caerulea, progenitor of autotetraploid alfalfa). Here, we reported a high-quality genome of ZW0012 (diploid alfalfa, 769 Mb, contig N50 = 5.5 Mb), which was grouped into the Northern group in population structure analysis, suggesting that our genome assembly filled a major gap among the members of M. sativa complex. During polyploidization, large phenotypic differences occurred between diploids and tetraploids, and the genetic information underlying its massive phenotypic variations remains largely unexplored. Extensive structural variations (SVs) were identified between ZW0012 and XinJiangDaYe (an autotetraploid alfalfa with released genome). We identified 71 ZW0012-specific PAV genes and 1296 XinJiangDaYe-specific PAV genes, mainly involved in defence response, cell growth, and photosynthesis. We have verified the positive roles of MsNCR1 (a XinJiangDaYe-specific PAV gene) in nodulation using an Agrobacterium rhizobia-mediated transgenic method. We also demonstrated that MsSKIP23_1 and MsFBL23_1 (two XinJiangDaYe-specific PAV genes) regulated leaf size by transient overexpression and virus-induced gene silencing analysis. Our study provides a high-quality reference genome of an important diploid alfalfa germplasm and a valuable resource of variation landscape between diploid and autotetraploid, which will facilitate the functional gene discovery and molecular-based breeding for the cultivars in the future.

Monitoring Genomic Structural Rearrangements Resulting from Gene Editing.

The cytogenomics-based methodology of directional genomic hybridization (dGH) enables the detection and quantification of a more comprehensive spectrum of genomic structural variants than any other approach currently available, and importantly, does so on a single-cell basis. Thus, dGH is well-suited for testing and/or validating new advancements in CRISPR-Cas9 gene editing systems. In addition to aberrations detected by traditional cytogenetic approaches, the strand specificity of dGH facilitates detection of otherwise cryptic intra-chromosomal rearrangements, specifically small inversions. As such, dGH represents a powerful, high-resolution approach for the quantitative monitoring of potentially detrimental genomic structural rearrangements resulting from exposure to agents that induce DNA double-strand breaks (DSBs), including restriction endonucleases and ionizing radiations. For intentional genome editing strategies, it is critical that any undesired effects of DSBs induced either by the editing system itself or by mis-repair with other endogenous DSBs are recognized and minimized. In this paper, we discuss the application of dGH for assessing gene editing-associated structural variants and the potential heterogeneity of such rearrangements among cells within an edited population, highlighting its relevance to personalized medicine strategies.